Rick Snodgrass

Interests

Research

Ergalics (the science of computing) and Databases (temporal databases, query language design, query optimization and evaluation, storage structures, database design)

Teaching

Database Design and Database Management Systems (DBMS), Object-Oriented Programming, Honors Pro-seminar

Courses

Scholarly Contributions

Books

• Currim, F., Currim, S., Dyreson, C. E., Joshi, S., Snodgrass, R. T., Thomas, S. W., & Roeder, E. (2009). $\tau$XSchema: Support for data-and schema-versioned XML documents. TimeCenter.
• Apers, P. M., Ceri, S., & Snodgrass, R. T. (2002). Best Papers of VLDB 2001. Springer-Verlag.
• Apers, P. M. (2001). Proceedings of the... International Conference on Very Large Data Bases. Morgan Kaufmann Pub.
• Slivinskas, G., Jensen, C. S., & Snodgrass, R. (2000). A Foundation for Conventional and Temporal Query Optimization. Aalborg Universitetsforlag Aalborg.
• Snodgrass, R. T. (2000). Developing time-oriented database applications in SQL. Morgan Kaufmann Publishers.
• Torp, K., Jensen, C. S., & Snodgrass, R. (1999). Modification of Now-Relative Databases. Aalborg Universitetsforlag.
• Tansel, A., Clifford, J., Gadia, S., Jajodia, S., Segev, A., & Snodgrass, R. T. (1998). Temporal Databases: Theory, Design, and Implementation. Benjamin/Cummings Publishing Company.
• Jensen, C., & Snodgrass, R. (1997). TimeCenter Prospectus. Aalborg Universitetsforlag.
• Zaniolo, C., Ceri, S., Faloutsos, C., Snodgrass, R. T., Subrahmanian, V. S., & Zicari, R. (1997). Advanced Database Systems. Morgan Kaufmann Publishers.
• B\"ohlen, M. H., Snodgrass, R. T., & Soo, M. D. (1996). Coalescing in temporal databases. Aalborg University, Institute for Electronic Systems, Department of Mathematics and Computer Science.
• Bair, J., Boehlen, M. H., Jensen, C. S., & Snodgrass, R. T. (1996). Notions of upward compatibility of temporal query languages. University of Aalborg, Institute for Electronic Systems, Department of Mathematics and Computer Science.
• Snodgrass, R., Boehlen, M., Jensen, C., & Steiner, A. (1996). Adding Valid Time to SQL/Temporal: ANSI Expert's Contribution.
• Snodgrass, R. T. (1995). Change Proposal for SQL/temporal Adding Valid Time. Aalborg University, Institute for Electronic Systems, Department of Mathematics and Computer Science.
• Snodgrass, R. T. (1995). The TSQL2 temporal query language. Springer Science \& Business Media.
• Snodgrass, R. T., B\"ohlen, M., & Jensen, C. (1995). Change Proposal for SQL. Aalborg Universitetscenter. Institut for Elektroniske Systemer.
• Snodgrass, R., & others, . (1995). The TSQL2 Query Language. The TSQL2 Language Design Committee, Kluwer Academic Publishers.
• Snodgrass, R., B\"ohlen, M., Jensen, C., & Steiner, A. (1995). Change Proposal for SQL/Temporal: Adding Valid Time-Part A. Aalborg Universitetsforlag.
• Computer Science, U., Dyreson, C. E., & Snodgrass, R. T. (1994). Temporal granularity and indeterminacy: Two sides of the same coin.
• Jensen, C. S., Hsu, S., Snodgrass, R. T., Jensen, C. S., Hsu, S., & Snodgrass, R. T. (1994). Valid-time Selection and Projection in TSQL2. University of Aalborg, Institute for Electronic Systems, Department of Mathematics and Computer Science.
• Pissinou, N., Snodgrass, R., & Elmasri, R. (1994). Towards an Infrastructure for Temporal Databases: Report of an International ARPA/NSF Workshop [held in Arlington, TX, 14-16.06. 1993]. University of Arizona. Department of Computer Science.
• Snodgrass, R. T., & Winslett, M. S. (1994). Proceedings of the 1994 ACM SIGMOD International Conference on Management of Data: SIGMOD'94, Minneapolis, Minnesota, May 24-27, 1994. Association for Computing Machinery.
• Snodgrass, R. T., Ahn, I., Ariav, G., Bayer, P., Clifford, J., Dyreson, C. E., Grandi, F., Hermosilla, L., Jensen, C. S., K\"afer, W., & others, . (1994). An Evaluation of TSQL2. Aalborg Universitetsforlag.
• Temporal Databases, I. W., & Snodgrass, R. (1993). Proceedings of the International Workshop on an Infrastructure for Temporal Databases: June 14-16, 1993. University of Arizona.
• Jensen, C. S., & Snodgrass, R. (1992). Proposal for a data model for the temporal structured query language. Univ. of Arizona.
• Snodgrass, R. (1992). An overview of the temporal query language TQuel. University of Arizona, Department of Computer Science.
• Soo, M. D., Snodgrass, R., & Dyreson, C. E. (1992). Architectural extensions to support multiple calendars. Univ. of Arizona.
• Jensen, C. S., & Snodgrass, R. (1991). Specialized temporal relations. University of Aalborg, Institute for Electronic Systems, Department of Mathematics and Computer Science.
• McKenzie, E., & Snodgrass, R. (1991). Supporting valid time in an historical relational algebra: Proofs and extensions. University of Arizona, Department of Computer Science.
• MacKenzie, E., McKenzie, E., & Snodgrass, R. (1989). An evaluation of algebras incorporating time. Department, Univ..
• McKenzie, E., & Snodgrass, R. (1987). Supporting valid time: An historical algebra. Defense Technical Information Center.
• Ogle, D., Schwan, K., & Snodgrass, R. (1987). The real-time collection and analysis of dynamic information in distributed and parallel systems. Computer and Information Science Research Center.

Chapters

• B\"ohlen, M. H., Jensen, C. S., & Snodgrass, R. T. (2009). Current Semantics. In Encyclopedia of Database Systems(pp 544--545). Springer US.
• B\"ohlen, M. H., Jensen, C. S., & Snodgrass, R. T. (2009). Temporal Compatibility. In Encyclopedia of Database Systems(pp 2936--2939). Springer US.
• B\"ohlen, M., Gamper, J., Jensen, C. S., & Snodgrass, R. T. (2009). SQL-Based Temporal Query Languages. In Encyclopedia of Database Systems(pp 2762--2768). Springer US.
• Dyreson, C. E., Jensen, C. S., & Snodgrass, R. (2009). Calendric System. In Encyclopedia of Database Systems(pp 305--305). Springer US.
• Dyreson, C. E., Jensen, C. S., & Snodgrass, R. T. (2009). Now in temporal databases. In Encyclopedia of database systems(pp 1920--1924). Springer US.
• Jensen, C. S. (2009). Lifespan. In Encyclopedia of Database Systems(pp 1612--1613). Springer US.
• Jensen, C. S., & Snodgrass, R. T. (2009). Time Instant. In Encyclopedia of Database Systems(pp 3112--3112). Springer US.
• Jensen, C. S., & Snodgrass, R. T. (2009). Transaction time. In Encyclopedia of Database Systems(pp 3162--3163). Springer US.
• Khatri, V., Snodgrass, R. T., & Terenziani, P. (2009). Atelic data. In Encyclopedia of Database Systems(pp 142--143). Springer US.
• Khatri, V., Snodgrass, R. T., & Terenziani, P. (2009). Telic distinction in temporal databases. In Encyclopedia of database systems(pp 2911--2914). Springer US.
• Snodgrass, R. T. (2009). Tsql2. In Encyclopedia of Database Systems(pp 3192--3197). Springer US.
• Zhang, D., Baclawski, K. P., & Tsotras, V. J. (2009). B+-Tree. In Encyclopedia of Database Systems(pp 197--200). Springer US.
• Dyreson, C., Snodgrass, R. T., Currim, F., & Currim, S. (2006). Schema-mediated exchange of temporal XML data. In Conceptual Modeling-ER 2006(pp 212--227). Springer Berlin Heidelberg.
• Terenziani, P., Snodgrass, R. T., Bottrighi, A., Torchio, M., & Molino, G. (2005). Extending temporal databases to deal with telic/atelic medical data. In Artificial Intelligence in Medicine(pp 58--66). Springer Berlin Heidelberg.
• Currim, F., Currim, S., Dyreson, C., & Snodgrass, R. T. (2004). A tale of two schemas: Creating a temporal XML schema from a snapshot schema with $\tau$xschema. In Advances in Database Technology-EDBT 2004(pp 348--365). Springer Berlin Heidelberg.
• Zhang, S., Dyreson, C., & Snodgrass, R. T. (2004). Schema-less, semantics-based change detection for XML documents. In Web Information Systems--WISE 2004(pp 279--290). Springer Berlin Heidelberg.
• Ram, S., Snodgrass, R. T., Khatri, V., & Hwang, Y. (2001). DISTIL: a design support environment for conceptual modeling of spatio-temporal requirements. In Conceptual Modeling—ER 2001(pp 70--83). Springer Berlin Heidelberg.
• Bettini, C., Dyreson, C. E., Evans, W. S., Snodgrass, R. T., & Wang, X. S. (1998). A glossary of time granularity concepts. In Temporal databases: Research and practice(pp 406--413). Springer Berlin Heidelberg.
• Jensen, C. S., Dyreson, C. E., B\"ohlen, M., Clifford, J., Elmasri, R., Gadia, S. K., Grandi, F., Hayes, P., Jajodia, S., K\"afer, W., & others, . (1998). The consensus glossary of temporal database concepts—february 1998 version. In Temporal Databases: Research and Practice(pp 367--405). Springer Berlin Heidelberg.
• Snodgrass, R. T., B\"ohlen, M. H., Jensen, C. S., & Steiner, A. (1998). Transitioning temporal support in TSQL2 to SQL3. In Temporal Databases: Research and Practice(pp 150--194). Springer Berlin Heidelberg.
• B\"ohlen, M. H., Chomicki, J., Snodgrass, R. T., & Toman, D. (1996). Querying TSQL2 databases with temporal logic. In Advances in Database Technology—EDBT'96(pp 325--341). Springer Berlin Heidelberg.
• B\"ohlen, M. H., Jensen, C. S., & Snodgrass, R. T. (1995). Evaluating the Completeness of TSQL2. In Recent Advances in Temporal Databases(pp 153--172). Springer London.
• Clifford, J., & Tuzhilin, A. (1995). PANEL The State-of-the-Art in Temporal Data Management: Perspectives from the Research and Financial Applications Communities. In Recent Advances in Temporal Databases(pp 356--357). Springer London.
• Clifford, J., Dyreson, C. E., Snodgrass, R. T., Isakowitz, T., & Jensen, C. S. (1995). Now. In The TSQL2 Temporal Query Language(pp 385--394). Springer US.
• Dyreson, C. E., & Snodgrass, R. T. (1995). A timestamp representation. In The TSQL2 Temporal Query Language(pp 475--499). Springer US.
• Dyreson, C. E., & Snodgrass, R. T. (1995). Temporal granularity. In The TSQL2 Temporal Query Language(pp 347--383). Springer US.
• Dyreson, C. E., & Snodgrass, R. T. (1995). Temporal indeterminacy. In The TSQL2 Temporal Query Language(pp 327--346). Springer US.
• Dyreson, C. E., & Snodgrass, R. T. (1995). The Baseline Clock. In The TSQL2 Temporal Query Language(pp 77--96). Springer US.
• Dyreson, C. E., Soo, M. D., & Snodgrass, R. T. (1995). The data model for time. In The TSQL2 Temporal Query Language(pp 97--101). Springer US.
• Hsu, S., Jensen, C. S., & Snodgrass, R. T. (1995). Valid-Time Selection and Projection. In The TSQL2 Temporal Query Language(pp 251--298). Springer US.
• Jensen, C. S., & Snodgrass, R. T. (1995). Semantics of time-varying attributes and their use for temporal database design. In OOER'95: Object-Oriented and Entity-Relationship Modeling(pp 366--377). Springer Berlin Heidelberg.
• Jensen, C. S., & Snodgrass, R. T. (1995). The Surrogate Data Type. In The TSQL2 Temporal Query Language(pp 153--156). Springer US.
• Jensen, C. S., Snodgrass, R. T., & Leung, T. C. (1995). Cursors. In The TSQL2 Temporal Query Language(pp 305--309). Springer US.
• Jensen, C. S., Snodgrass, R. T., & Soo, M. D. (1995). The tsql2 data model. In The TSQL2 temporal query language(pp 157--240). Springer US.
• Kline, N., Snodgrass, R. T., & Leung, T. C. (1995). Aggregates. In The TSQL2 Temporal Query Language(pp 395--425). Springer US.
• Leung, T. C., Jensen, C. S., & Snodgrass, R. T. (1995). Modification. In The TSQL2 Temporal Query Language(pp 299--303). Springer US.
• Roddick, J. F., & Snodgrass, R. T. (1995). Schema versioning. In The TSQL2 Temporal Query Language(pp 427--449). Springer US.
• Roddick, J. F., & Snodgrass, R. T. (1995). Transaction Time Support. In The TSQL2 Temporal Query Language(pp 319--325). Springer US.
• Snodgrass, R. T. (1995). Event Tables. In The TSQL2 Temporal Query Language(pp 311--318). Springer US.
• Snodgrass, R. T. (1995). Introduction to TSQL2. In The TSQL2 Temporal Query Language(pp 19--31). Springer US.
• Snodgrass, R. T. (1995). Language Syntax. In The TSQL2 Temporal Query Language(pp 549--549). Springer US.
• Snodgrass, R. T. (1995). Section 10 Additional Common Elements. In The TSQL2 Temporal Query Language(pp 605--606). Springer US.
• Snodgrass, R. T. (1995). Section 11 Schema Definition and Manipulation. In The TSQL2 Temporal Query Language(pp 607--616). Springer US.
• Snodgrass, R. T. (1995). Section 12 Module. In The TSQL2 Temporal Query Language(pp 617--620). Springer US.
• Snodgrass, R. T. (1995). Section 13 Data Manipulation. In The TSQL2 Temporal Query Language(pp 621--627). Springer US.
• Snodgrass, R. T. (1995). Section 21 Information Schema and Definition Schema. In The TSQL2 Temporal Query Language(pp 629--630). Springer US.
• Snodgrass, R. T. (1995). Section 22 Status Codes. In The TSQL2 Temporal Query Language(pp 631--631). Springer US.
• Snodgrass, R. T. (1995). Section 5 Lexical Elements. In The TSQL2 Temporal Query Language(pp 551--561). Springer US.
• Snodgrass, R. T. (1995). Section 6 Scalar Expressions. In The TSQL2 Temporal Query Language(pp 563--590). Springer US.
• Snodgrass, R. T. (1995). Section 7 Query Expressions. In The TSQL2 Temporal Query Language(pp 591--598). Springer US.
• Snodgrass, R. T. (1995). Section 8 Predicates. In The TSQL2 Temporal Query Language(pp 599--603). Springer US.
• Snodgrass, R. T. (1995). Tsql2 tutorial. In The TSQL2 Temporal Query Language(pp 33--47). Springer US.
• Snodgrass, R. T., & Kucera, H. (1995). Rationale for a temporal extension to sql. In The TSQL2 Temporal Query Language(pp 3--18). Springer US.
• Snodgrass, R. T., & Soo, M. D. (1995). Supporting Multiple Calendars. In The TSQL2 Temporal Query Language(pp 103--121). Springer US.
• Snodgrass, R. T., Jensen, C. S., & Grandi, F. (1995). Schema specification. In The TSQL2 Temporal Query Language(pp 241--243). Springer US.
• Snodgrass, R. T., Jensen, C. S., & Grandi, F. (1995). The From Clause. In The TSQL2 Temporal Query Language(pp 245--249). Springer US.
• Snodgrass, R. T., Jensen, C. S., Dyreson, C. E., K\"afer, W., Kline, N., & Roddick, J. F. (1995). A Second Example. In The TSQL2 Temporal Query Language(pp 49--73). Springer US.
• Soo, M. D., & Snodgrass, R. T. (1995). Temporal Data Types. In The TSQL2 Temporal Query Language(pp 123--152). Springer US.
• Soo, M. D., Jensen, C. S., & Snodgrass, R. T. (1995). An Architectural, Framework. In The TSQL2 Temporal Query Language(pp 465--473). Springer US.
• Soo, M. D., Jensen, C. S., & Snodgrass, R. T. (1995). An algebra for TSQL2. In The TSQL2 temporal query language(pp 505--546). Springer US.
• Soo, M. D., Kline, N., & Snodgrass, R. T. (1995). SQL-92 compatibility issues. In The TSQL2 Temporal Query Language(pp 501--504). Springer US.
• Snodgrass, R. T. (1992). Temporal databases. In Theories and methods of spatio-temporal reasoning in geographic space(pp 22--64). Springer Berlin Heidelberg.
• Snodgrass, R., & Shannon, K. (1986). Supporting flexible and efficient tool integration. In Advanced Programming Environments(pp 290--313). Springer Berlin Heidelberg.

Journals/Publications

• Matheson, T., Stubens, C., Wolf, N., Lee, C., Narayan, G., Saha, A., Scott, A., Soraisam, M., Bolton, A. S., Hauger, B., & others, . (2021). The ANTARES astronomical time-domain event broker. The Astronomical Journal, 161(3), 107.
• Snodgrass, R. T., Currim, S., & Suh, Y. (2021). Have query optimizers hit the wall?. The VLDB Journal, 1--20.
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  CORE A*
• Snodgrass, R. T., & Winslett, M. (2020). We need to automate the declaration of emphconflicts of interest. Commun. ACM, 63(10), 30--32.
• Narayan, G., Zaidi, T., Soraisam, M. D., Wang, Z., Lochner, M., Matheson, T., Saha, A., Yang, S., Zhao, Z., Kececioglu, J., Scheidegger, C., Snodgrass, R. T., Axelrod, T., Jenness, T., Maier, R. S., Ridgway, S. T., Seaman, R. L., Evans, E. M., Singh, N., , Taylor, C., et al. (2018). Machine-learning-based Brokers for Real-time Classification of the LSST Alert Stream. ASTROPHYSICAL JOURNAL SUPPLEMENT SERIES, 236(1).
• Currim, S., Snodgrass, R. T., Suh, Y., & Zhang, R. (2017). DBMS Metrology: Measuring Query Time. ACM TRANSACTIONS ON DATABASE SYSTEMS, 42(1).
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  CORE A*
• Snodgrass, R. T. (2017). Mixing computation with people: an interview with Marianne Winslett. ACM Ubiquity.
• Snodgrass, R. T. (2017). The changing culture of computer science: an interview with Marianne Winslett. ACM Ubiquity.
• Suh, Y., Snodgrass, R. T., & Currim, S. (2017). An empirical study of transaction throughput thrashing across multiple relational DBMSes. INFORMATION SYSTEMS, 66, 119-136.
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  This journal is ranked as A* in CORE
• Suh, Y., Snodgrass, R. T., Kececioglu, J. D., Downey, P. J., Maier, R. S., & Yi, C. (2017). EMP: execution time measurement protocol for compute-bound programs. SOFTWARE-PRACTICE & EXPERIENCE, 47(4), 559-597.
• Khatri, V., Ram, S., Snodgrass, R. T., & Terenziani, P. (2014). Capturing Telic/Atelic Temporal Data Semantics: Generalizing Conventional Conceptual Models. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 26(3), 528-548.
• Khatri, V., Ram, S., Snodgrass, R. T., & Terenziani, P. (2014). Capturing Telic/Atelic Temporal Data Semantics: Generalizing Conventional Conceptual Models. IEEE Transactions on Knowledge and Data Engineering, 26(3), 528-549.
• Khatri, V., Ram, S., Snodgrass, R. T., & Terenziani, P. (2014). Capturing telic/atelic temporal data semantics: Generalizing conventional conceptual models. IEEE Transactions on Knowledge and Data Engineering, 26(3), 528-548.
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  Abstract: Time provides context for all our experiences, cognition, and coordinated collective action. Prior research in linguistics, artificial intelligence, and temporal databases suggests the need to differentiate between temporal facts with goal-related semantics (i.e., telic) from those are intrinsically devoid of culmination (i.e., atelic). To differentiate between telic and atelic data semantics in conceptual database design, we propose an annotation-based temporal conceptual model that generalizes the semantics of a conventional conceptual model. Our temporal conceptual design approach involves: 1) capturing 'what' semantics using a conventional conceptual model; 2) employing annotations to differentiate between telic and atelic data semantics that help capture 'when' semantics; 3) specifying temporal constraints, specifically nonsequenced semantics, in the temporal data dictionary as metadata. Our proposed approach provides a mechanism to represent telic/atelic temporal semantics using temporal annotations. We also show how these semantics can be formally defined using constructs of the conventional conceptual model and axioms in first-order logic. Via what we refer to as the 'semantics of composition,' i.e., semantics implied by the interaction of annotations, we illustrate the logical consequences of representing telic/atelic data semantics during temporal conceptual design. © 2014 IEEE.
• Khatri, V., Ram, S., Snodgrass, R. T., & Terenziani, P. (2016). Capturing Telic-Atelic Temporal Data Semantics: Generalizing Conventional Conceptual Models. Transactions on Knowledge and Data Engineering, 26(3), 528-548.
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  This journal is ranked A in CORE
• Matheson, T., Saha, A., Snodgrass, R., & Kececioglu, J. (2014). ANTARES: A Prototype Transient Broker System. American Astronomical Meeting Abstracts, 223(343.02).
• Matheson, T., Saha, A., Snodgrass, R., & Kececioglu, J. (2014). ANTARES: The Arizona- NOAO Temporal Analysis and Response to Events System. Hot-Wiring the Transient Universe 3.
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  Eds: Wozniak, P | Graham, M | Mahabal, A
• Matheson, T., Saha, A., Snodgrass, R., & Kececioglu, J. (2014). ANTARES: The Arizona-NOAO Temporal Analysis and Response to Events System. Hot-Wiring the Transient Universe, 3.
• Saha, A., Matheson, T., Snodgrass, R., Kececioglu, J., Narayan, G., Seaman, R., Jenness, T., & Axelrod, T. (2014). ANTARES: A Prototype Transient Broker System. OBSERVATORY OPERATIONS: STRATEGIES, PROCESSES, AND SYSTEMS V, 9149.
• Snodgrass, R. (2014). The Science of Computer Science. ACM Ubiquity Symposium.
• Snodgrass, R., & Denning, P. (2014). Ubiquity symposium: The science of computer science: closing statement. Ubiquity, 2014(June), 2.
• Suh, Y., Snodgrass, R. T., & Zhang, R. (2014). AZDBLab: A Laboratory Information System for Large-Scale Empirical DBMS Studies. Proceedings of the VLDB Endowment, 7(13).
• Thomas, S. W., Snodgrass, R. T., & Zhang, R. (2014). Benchmark frameworks and tau Bench. SOFTWARE-PRACTICE & EXPERIENCE, 44(9), 1047-1075.
• Anselma, L., Terenziani, P., & Snodgrass, R. T. (2013). Valid-Time Indeterminacy in Temporal Relational Databases: Semantics and Representations. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 25(12), 2880-2894.
• Anselma, L., Terenziani, P., & Snodgrass, R. T. (2013). Valid-Time Indeterminacy in Temporal Relational Databases: Semantics and Representations. IEEE Transactions on Knowledge and Data Engineering, 24(12), 2880-2894.
• Anselma, L., Terenziani, P., & Snodgrass, R. T. (2013). Valid-time indeterminacy in temporal relational databases: Semantics and representations. IEEE Transactions on Knowledge and Data Engineering, 25(12), 2880-2894.
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  Abstract: Valid-time indeterminacy is "don't know when" indeterminacy, coping with cases in which one does not exactly know when a fact holds in the modeled reality. In this paper, we first propose a reference representation (data model and algebra) in which all possible temporal scenarios induced by valid-time indeterminacy can be extensionally modeled. We then specify a family of 16 more compact representational data models. We demonstrate their correctness with respect to the reference representation and analyze several properties, including their data expressiveness. Then, we compare these compact models along several relevant dimensions. Finally, we also extend the reference representation and a representative of compact representations to cope with probabilities. © 1989-2012 IEEE.
• Burgin, M., & Eberbach, E. (2013). Ubiquity symposium: Evolutionary computation and the processes of life: perspectives and reality of evolutionary computation: closing statement. Ubiquity, 2013(December), 5.
• Carlson, S. (2013). Ubiquity symposium: The science in computer science: how to talk about science: five essential insights. Ubiquity, 2013(March), 2.
• Pavlou, K. E., & Snodgrass, R. T. (2013). Generalizing Database Forensics. ACM TRANSACTIONS ON DATABASE SYSTEMS, 38(2).
• Pavlou, K. E., & Snodgrass, R. T. (2013). Generalizing database forensics. ACM Transactions on Database Systems, 38(2).
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  Abstract: In this article we present refinements on previously proposed approaches to forensic analysis of database tampering.We significantly generalize the basic structure of these algorithms to admit new characterizations of the "where" axis of the corruption diagram. Specifically, we introduce page-based partitioning as well as attribute-based partitioning along with their associated corruption diagrams. We compare the structure of all the forensic analysis algorithms and discuss the various design choices available with respect to forensic analysis. We characterize the forensic cost of the newly introduced algorithms, compare their forensic cost, and give our recommendations. We then introduce a comprehensive taxonomy of the types of possible corruption events, along with an associated forensic analysis protocol that consolidates all extant forensic algorithms and the corresponding type(s) of corruption events they detect. The result is a generalization of these algorithms and an overarching characterization of the process of database forensic analysis, thus providing a context within the overall operation of a DBMS for all existing forensic analysis algorithms. © ACM 2013.
• Riofrio, W. (2013). Ubiquity symposium: Evolutionary computation and the processes of life: information, biological, and evolutionary computing. Ubiquity, 2013(May), 2.
• Snodgrass, R. (2013). The science in computer science: broadening CS enrollments: an interview with Jan Cuny. ACM Ubiquity.
• Snodgrass, R. (2013). Ubiquity symposium: The science in computer science: broadening CS enrollments: an interview with Jan Cuny. Ubiquity, 2013(February), 1.
• Snodgrass, R. T. (2013). On experimental algorithmics: an interview with Catherine McGeoch and Bernard Moret. Ubiquity, 2013(December), 3.
• Thomas, S., Snodgrass, R., & Zhang, R. (2013). Benchmark frameworks and τBench. Software - Practice and Experience.
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  Abstract: Software engineering frameworks tame the complexity of large collections of classes by identifying structural invariants, regularizing interfaces, and increasing sharing across the collection. We wish to appropriate these benefits for families of closely related benchmarks, say for evaluating query engine implementation strategies. We introduce the notion of a benchmark framework, an ecosystem of benchmarks that are related in semantically rich ways and enabled by organizing principles. A benchmark framework is realized by iteratively changing one individual benchmark into another, say by modifying the data format, adding schema constraints, or instantiating a different workload. Paramount to our notion of benchmark frameworks are the ease of describing the differences between individual benchmarks and the utility of methods to validate the correctness of each benchmark component by exploiting the overarching ecosystem. As a detailed case study, we introduce τBench, a benchmark framework consisting of ten individual benchmarks, spanning XML, XQuery, XML Schema, and PSM, along with temporal extensions to each. The second case study examines the Mining Unstructured Data benchmark framework, and the third examines the potential benefits of rendering the TPC family as a benchmark framework. © 2013 John Wiley & Sons, Ltd.
• Browne, G., Khatri, V., Parsons, J., & Snodgrass, R. (2012). The Relationship Between User Requirements and Conceptual Models: Theory and an Empirical Investigation. Proceedings of the 2012 SIGSAND Symposium, 19.
• Currim, F. A., Currim, S. A., Dyreson, C. E., Snodgrass, R. T., Thomas, S. W., & Zhang, R. (2012). Adding Temporal Constraints to XML Schema. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 24(8), 1361-1377.
• Currim, F. A., Currim, S. A., Dyreson, C. E., Snodgrass, R. T., Thomas, S. W., & Zhang, R. (2012). Adding temporal constraints to XML schema. Knowledge and Data Engineering, IEEE Transactions on, 24(8), 1361--1377.
• Pavlou, K. E., & Snodgrass, R. T. (2012). DRAGOON: An Information Accountability System for High-Performance Databases. 2012 IEEE 28TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE), 1329-1332.
• Pavlou, K. E., & Snodgrass, R. T. (2012). DRAGOON: An information accountability system for high-performance databases. Proceedings - International Conference on Data Engineering, 1329-1332.
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  Abstract: Regulations and societal expectations have recently emphasized the need to mediate access to valuable databases, even access by insiders. Fraud occurs when a person, often an insider, tries to hide illegal activity. Companies would like to be assured that such tampering has not occurred, or if it does, that it will be quickly discovered and used to identify the perpetrator. At one end of the compliance spectrum lies the approach of restricting access to information and on the other that of information accountability. We focus on effecting information accountability of data stored in high-performance databases. The demonstrated work ensures appropriate use and thus end-to-end accountability of database information via a continuous assurance technology based on cryptographic hashing techniques. A prototype tamper detection and forensic analysis system named DRAGOON was designed and implemented to determine when tampering(s) occurred and what data were tampered with. DRAGOON is scalable, customizable, and intuitive. This work will show that information accountability is a viable alternative to information restriction for ensuring the correct storage, use, and maintenance of databases on extant DBMSes. © 2012 IEEE.
• Pavlou, K. E., & Snodgrass, R. T. (2012). Temporal implications of database information accountability. Proceedings - 2012 19th International Symposium on Temporal Representation and Reasoning, TIME 2012, 125-132.
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  Abstract: Information restriction controls access and renders records immutable; information accountability requires data transparency to easily and efficiently determine when a particular use is appropriate. Information accountability in the context of relational databases is associated with time in a surprising number of ways, as is summarized in this paper. Notarization and validation of a database exploit the temporal semantics of a transaction-time database. A corruption can be associated with multiple times. Forensic analysis determines the when: bounds on the corruption time, and the where: also specified in terms of time. These bounds are depicted in a two-dimensional corruption diagram, with both axes denoting time. The various kinds of corruption events are defined in terms of time. A parameter termed the regret interval has significant security and performance implications. This paper emphasizes the deep connections between time and the definition, detection, forensic analysis, and characterized extent of a database corruption within the context of information accountability. © 2012 IEEE.
• Snodgrass, R. T., Gao, D., Zhang, R., & Thomas, S. W. (2012). Temporal Support for Persistent Stored Modules. 2012 IEEE 28TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE), 114-125.
• Snodgrass, R. T., Gao, D., Zhang, R., & Thomas, S. W. (2012). Temporal support for persistent stored modules. Proceedings - International Conference on Data Engineering, 114-125.
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  Abstract: We show how to extend temporal support of SQL to the Turing-complete portion of SQL, that of persistent stored modules (PSM). Our approach requires minor new syntax beyond that already in SQL/Temporal to define and to invoke PSM routines, thereby extending the current, sequenced, and non-sequenced semantics of queries to PSM routines. Temporal upward compatibility (existing applications work as before when one or more tables are rendered temporal) is ensured. We provide a transformation that converts Temporal SQL/PSM to conventional SQL/PSM. To support sequenced evaluation of PSM routines, we define two different slicing approaches, maximal slicing and per-statement slicing. We compare these approaches empirically using a comprehensive benchmark and provide a heuristic for choosing between them. © 2012 IEEE.
• Zhang, R., Snodgrass, R. T., & Debray, S. (2012). Micro-Specialization in DBMSes. 2012 IEEE 28TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE), 690-701.
• Zhang, R., Snodgrass, R., & Debray, S. (2012). Micro-Specialization: A Self-Managed Ap- proach toImproving Query Performance. Proceedings of the ICDE Self-Managed Database Work-shop, 315-321.
• Morrison, C. T., & Snodgrass, R. T. (2011). Computer Science Can Use More Science. COMMUNICATIONS OF THE ACM, 54(6), 36-38.
• Morrison, C. T., & Snodgrass, R. T. (2011). Computer science can use more science. Communications of the ACM, 54(6), 36--38.
• Morrison, C. T., & Snodgrass, R. T. (2011). Viewpoint computer science can use more science. Communications of the ACM, 54(6), 36-38.
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  Abstract: Software developers should use empirical methods to analyze their designs to predict how working systems will behave. © 2011 ACM.
• Snodgrass, R. (2011). An Interview with Melanie Mitchell On Complexity. ACM Ubiquity.
• Snodgrass, R. (2011). On experimental algorithmics: an interview with Catherine McGeoch and Bernard Moret. ACM Ubiquity.
• Snodgrass, R. T. (2011). An interview with Melanie Mitchell: On complexity. Ubiquity, 2011(April), 2.
• Anselma, L., Terenziani, P., & Snodgrass, R. T. (2010). Valid-time indeterminacy in temporal relational databases: A family of data models. Proceedings - 17th International Symposium on Temporal Representation and Reasoning, TIME 2010, 139-145.
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  Abstract: Valid-time indeterminacy concerns not knowing exactly when a fact holds in the modeled reality. In this paper, we first propose a reference approach (data model and algebra) in which all possible temporal scenarios induced by valid-time indeterminacy can be extensionally modeled. We then specify a family of sixteen more compact representational data models. We demonstrate their correctness with respect to the reference approach and analyze several properties, including their data expressiveness and correctness with respect to the reference approach. Finally, we compare these compact models along several relevant dimensions. © 2010 IEEE.
• Pavlou, K. E., & Snodgrass, R. T. (2010). The Tiled Bitmap Forensic Analysis Algorithm. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 22(4), 590-601.
• Pavlou, K. E., & Snodgrass, R. T. (2010). The tiled bitmap forensic analysis algorithm. IEEE Transactions on Knowledge and Data Engineering, 22(4), 590-601.
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  Abstract: Tampering of a database can be detected through the use of cryptographically strong hash functions. Subsequently, applied forensic analysis algorithms can help determine when, what, and perhaps ultimately who and why. This paper presents a novel forensic analysis algorithm, the Tiled Bitmap Algorithm, which is more efficient than prior forensic analysis algorithms. It introduces the notion of a candidate set (all possible locations of detected tampering(s)) and provides a complete characterization of the candidate set and its cardinality. An optimal algorithm for computing the candidate set is also presented. Finally, the implementation of the Tiled Bitmap Algorithm is discussed, along with a comparison to other forensic algorithms in terms of space/time complexity and cost. An example of candidate set generation and proofs of the theorems and lemmata and of algorithm correctness can be found in the appendix, which can be found on the Computer Society Digital Library at http://doi.ieeecomputersociety.org/10.1109/TKDE.2009.121. © 2010 IEEE.
• Snodgrass, R. T. (2010). A Case Study of Temporal Data. Teradata Corporation.
• Snodgrass, R. T. (2010). Ergalics: A natural science of computation. University of Arizona.
• B\"ohlen, M. H., Jensen, C. S., & Snodgrass, R. T. (2009). Nonsequenced semantics. Encyclopedia of Database Systems, 1913--1915.
• McKenzie, E., & Snodgrass, R. (2009). Schema Evolution and the Relational Algebra. Journal of System and Software, 82(6), 947--962.
• Mitra, S., Winslett, M., Snodgrass, R. T., Yaduvanshi, S., & Ambokar, S. (2009). An Architecture for Regulatory Compliant Database Management. ICDE: 2009 IEEE 25TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING, VOLS 1-3, 162-173.
• Pavlou, K. E., & Snodgrass, R. T. (2008). Forensic Analysis of Database Tampering. ACM TRANSACTIONS ON DATABASE SYSTEMS, 33(4).
• Pavlou, K. E., & Snodgrass, R. T. (2008). Forensic analysis of database tampering. ACM Transactions on Database Systems, 33(4).
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  Abstract: Regulations and societal expectations have recently expressed the need to mediate access to valuable databases, even by insiders. One approach is tamper detection via cryptographic hashing. This article shows how to determine when the tampering occurred, what data was tampered with, and perhaps, ultimately, who did the tampering, via forensic analysis. We present four successively more sophisticated forensic analysis algorithms: the Monochromatic, RGBY, Tiled Bitmap, and a3D algorithms, and characterize their forensic cost under worst-case, best-case, and average-case assumptions on the distribution of corruption sites. A lower bound on forensic cost is derived, with RGBY and a3D being shown optimal for a large number of corruptions. We also provide validated cost formulæ for these algorithms and recommendations for the circumstances in which each algorithm is indicated. © 2008 ACM.
• Snodgrass, R. T., Dyreson, C., Currim, F., Currim, S., & Joshi, S. (2008). Validating quicksand: Temporal schema versioning in tau XSchema. DATA & KNOWLEDGE ENGINEERING, 65(2), 223-242.
• Snodgrass, R. T., Dyreson, C., Currim, F., Currim, S., & Joshi, S. (2008). Validating quicksand: Temporal schema versioning in τXSchema. Data and Knowledge Engineering, 65(2), 223-242.
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  Abstract: The W3C XML Schema recommendation defines the structure and data types for XML documents, but lacks explicit support for time-varying XML documents or for a time-varying schema. In previous work we introduced τXSchema, which is an infrastructure and suite of tools to support the creation and validation of time-varying documents, without requiring any changes to XML Schema. In this paper we extend τXSchema to support versioning of the schema itself. We introduce the concept of a bundle, which is an XML document that references a base (non-temporal) schema, temporal annotations describing how the document can change, and physical annotations describing where timestamps are placed. When the schema is versioned, the base schema and temporal and physical schemas can themselves be time-varying documents, each with their own (possibly versioned) schemas. We describe how the validator can be extended to validate documents in this seeming precarious situation of data that changes over time, while its schema and even its representation are also changing. © 2007 Elsevier B.V. All rights reserved.
• Dyreson, C., Snodgrass, R. T., Currim, F., Currim, S., & Joshi, S. (2007). Weaving temporal and reliability aspects into a schema tapestry. DATA & KNOWLEDGE ENGINEERING, 63(3), 752-773.
• Dyreson, C., Snodgrass, R. T., Currim, F., Currim, S., & Joshi, S. (2007). Weaving temporal and reliability aspects into a schema tapestry. Data \& Knowledge Engineering, 63(3), 752--773.
• Dyreson, C., Snodgrass, R. T., Currim, F., Currim, S., & Joshi, S. (2007). Weaving temporal and reliability aspects into a schema tapestry. Data and Knowledge Engineering, 63(3), 726-747.
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  Abstract: In aspect-oriented programming (AOP) a cross-cutting concern is implemented in an aspect. An aspect weaver blends code from the aspect into a program's code at programmer-specified cut points, yielding an aspect-enhanced program. In this paper, we apply some of the concepts from the AOP paradigm to data. Like code, data also has cross-cutting concerns such as versioning, security, privacy, and reliability. We propose modeling a cross-cutting data concern as a schema aspect. A schema aspect describes the structure of the metadata in the cross-cutting concern, identifies the types of data elements that can be wrapped with metadata, i.e., the cut points, and provides some simple constraints on the use of the metadata. Several schema aspects can be applied to a single data collection, though in this paper we focus on just two aspects: a reliability aspect and a temporal aspect. We show how to weave the schema for these two aspects together with the schema for the data into a single, unified schema that we call a schema tapestry. The tapestry guides the construction, interpretation, and validation of an aspect-enhanced data collection.
• Snodgrass, R. (2007). Frequently-asked questions about double-blind reviewing. ACM SIGMOD Record, 36(1), 60--62.
• Snodgrass, R. (2007). Frequently-asked questions about double-blind reviewing. SIGMOD Record, 36(1).
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  Abstract: Over the past few years, TODS has adopted many innovative policies: a call for short papers and directed surveys, a limit of one review per year per reviewer, a guaranteed turn-around time of five months, full implementation of the ACM Rights and Responsibilities policy, and reviewing statistics published on its web site. Most of these innovations were at the time unique to TODS; some other journals are now following up. These policies were somewhat controversial when first considered. What if the reviewer pool dried up given this promised limit? What if reviewers weren't responsive, causing the Editorial Board to violate its five-month guarantee? Over time, the community responded and everything worked out. These past policies were enacted to increase fairness and quality. The double-blind policy furthers both of these objectives. The expectation is that over time the database community will become accustomed to the process and benefits of double-blind reviewing, as has occurred in other scientific communities.
• Snodgrass, R. T. (2007). Editorial: Single- versus double-blind reviewing. ACM TRANSACTIONS ON DATABASE SYSTEMS, 32(1).
• Snodgrass, R. T. (2007). Editorial: Single- versus double-blind reviewing. ACM Transactions on Database Systems, 32(1).
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  Abstract: This editorial analyzes from a variety of perspectives the controversial issue of single-blind versus double-blind reviewing. In single-blind reviewing, the reviewer is unknown to the author, but the identity of the author is known to the reviewer. Double-blind reviewing is more symmetric: The identity of the author and the reviewer are not revealed to each other. We first examine the significant scholarly literature regarding blind reviewing. We then list six benefits claimed for double-blind reviewing and 21 possible costs. To compare these benefits and costs, we propose a double-blind policy for TODS that attempts to minimize the costs while retaining the core benefit of fairness that double-blind reviewing provides, and evaluate that policy against each of the listed benefits and costs. Following that is a general discussion considering several questions: What does this have to do with TODS, does bias exist in computer science, and what is the appropriate decision procedure We explore the knobs a policy design can manipulate to fine-tune a double-blind review policy. This editorial ends with a specific decision. © 2007 ACM.
• Snodgrass, R. T. (2007). Editorial: Single-versus double-blind reviewing. ACM Transactions on Database Systems (TODS), 32(1), 1.
• Snodgrass, R. T. (2007). Frequently-asked questions about double-blind reviewing. SIGMOD RECORD, 36(1), 60-62.
• Snodgrass, R. T. (2007). Towards a science of temporal Databases. TIME 2007: 14th International Symposium on Temporal Representation and Reasoning, Proceedings, 6-7.
• Snodgrass, R. T. (2007). Towards a science of temporal databases. Proceedings of the International Workshop on Temporal Representation and Reasoning, 6-7.
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  Abstract: Computer science has long been considered to emphasize three distinct perspectives: mathematics, science, and engineering. While the database field has some very strong mathematical and engineering work, the scientific perspective has been much less prominent. This keynote will elaborate the scientific perspective, apply it to research questions in temporal databases, and emphasize that this new way of thinking can yield new insights and deeper understanding. © 2007 IEEE.
• Terenziani, P., Snodgrass, R. T., Bottrighi, A., Torchio, M., & Molino, G. (2007). Extending temporal databases to deal with telic/atelic medical data. ARTIFICIAL INTELLIGENCE IN MEDICINE, 39(2), 113-126.
• Terenziani, P., Snodgrass, R. T., Bottrighi, A., Torchio, M., & Molino, G. (2007). Extending temporal databases to deal with telic/atelic medical data. Artificial Intelligence in Medicine, 39(2), 113--126.
• Terenziani, P., Snodgrass, R. T., Bottrighi, A., Torchio, M., & Molino, G. (2007). Extending temporal databases to deal with telic/atelic medical data. Artificial Intelligence in Medicine, 39(2), 113-126.
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  PMID: 17027241;Abstract: Objective: In this paper, we aim at defining a general-purpose data model and query language coping with both "telic" and "atelic" medical data. Background: In the area of Medical Informatics, there is an increasing realization that temporal information plays a crucial role, so that suitable database models and query languages are needed to store and support it. However, despite the wide range of approaches in the area, in this paper we show that a relevant class of medical data cannot be properly dealt with. Methodology: We first show that data models based on the "point-based" semantics, which is (implicitly or explicitly) assumed by the totality of temporal database approaches, have several limitations when dealing with "telic" data. We then propose a new model (based on the "interval-based" semantics) to cope with such data, and extend the query language accordingly. Results: We propose a new three-sorted model and a query language to properly deal with both "telic" and "atelic" medical data (as well as non-temporal data). Our query language is flexible, since it allows one to switch from "atelic" to "telic" data, and vice versa. Conclusion: In this paper, we demostrate the feasibilty of a database approach copying with both telic and atelic data as needed in several (medical) applications. © 2006 Elsevier B.V. All rights reserved.
• Terenziani, P., Snodgrass, R. T., Bottrighi, A., Torchio, M., & Molino, G. (2007). Extending temporal databases to deal with telic/atelic medical data. Artificial intelligence in medicine, 39(2), 113-26.
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  In this paper, we aim at defining a general-purpose data model and query language coping with both "telic" and "atelic" medical data.
• Urgun, B., Dyreson, C. E., Snodgrass, R. T., Miller, J. K., Kline, N., Soo, M. D., & Jensen, C. S. (2007). Integrating multiple calendars using $\tau$ ZAMAN. Software: Practice and Experience, 37(3), 267--308.
• Urgun, B., Dyreson, C. E., Snodgrass, R. T., Miller, J. K., Kline, N., Soo, M. D., & Jensen, C. S. (2007). Integrating multiple calendars using tau ZAMAN. SOFTWARE-PRACTICE & EXPERIENCE, 37(3), 267-308.
• Urgun, B., Dyreson, C. E., Snodgrass, R. T., Miller, J. K., Kline, N., Soo, M. D., & Jensen, C. S. (2007). Integrating multiple calendars using τZAMAN. Software - Practice and Experience, 37(3), 267-308.
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  Abstract: Programmers are increasingly interested in developing applications that can be used internationally. Part of the internationalization effort is the ability to engineer applications to use dates and times that conform to local calendars yet can inter-operate with dates and times in other calendars, for instance between the Gregorian and Islamic calendars. τZAMAN is a system that provides a natural language-and calendar-independent framework for integrating multiple calendars. τZAMAN performs 'runtime-binding' of calendars and language support. A running τZAMAN system dynamically loads calendars and language support tables from XML-formatted files. Loading a calendar integrates it with other, already loaded calendars, enabling users of τZAMAN to add, compare, and convert times between multiple calendars. τZAMAN also provides a flexible, calendar-independent framework for parsing temporal literals. Literals can be input and output in XML or plain text, using user-defined formats, and in different languages and character sets. Finally, τZAMAN is a client/server system, enabling shared access to calendar servers spread throughout the Web. This paper describes the architecture of τZAMAN and experimentally quantifies the cost of using a calendar server to translate and manipulate dates. Copyright © 2006 John Wiley & Sons, Ltd.
• \"Ozsu, T. (2007). SIGMOD Officers, Committees, and Awardees. SIGMOD Record, 36(3), 1.
• Dyreson, C., Snodgrass, R. T., Currim, F., & Currim, S. (2006). Schema-mediated exchange of temporal XML data. CONCEPTUAL MODELING - ER 2006, PROCEEDINGS, 4215, 212-227.
• Dyreson, C., Snodgrass, R. T., Currim, F., & Currim, S. (2006). Schema-mediated exchange of temporal XML data. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4215 LNCS, 212-227.
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  Abstract: When web servers publish data formatted in XML, only the current state of the data is (generally) published. But data evolves over time as it is updated. Capturing that evolution is vital to recovering past versions, tracking changes, and evaluating temporal queries. This paper presents a system to build a temporal data collection, which records the history of each published datum rather than just its current state. The key to exchanging temporal data is providing a temporal schema to mediate the interaction between the publisher and the reader. The schema describes how to construct a temporal data collection by "gluing" individual states into an integrated history. © Springer-Verlag Berlin Heidelberg 2006.
• Khatri, V., Ram, S., & Snodgrass, R. T. (2006). On augmenting database design-support environments to capture the geo-spatio-temporal data semantics. Information Systems, 31(2), 98--133.
• Khatri, V., Ram, S., & Snodgrass, R. T. (2006). On augmenting database design-support environments to capture the geo-spatio-temporal data semantics. Information Systems, 31(2), 98-133.
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  Abstract: A database design-support environment supports a data analyst in eliciting, articulating, specifying and validating data-related requirements. Extant design-support environments - based on conventional conceptual models - do not adequately support applications that need to organize data based on time (e.g., accounting, portfolio management, personnel management) and/or space (e.g., facility management, transportation, logistics). For geo-spatio-temporal applications, it is left to database designers to discover, design and implement - on an ad-hoc basis - the temporal and geospatial concepts that they need to represent the miniworld. To elicit the geo-spatio-temporal data semantics, we characterize guiding principles for augmenting the conventional conceptual database design approach, present our annotation-based approach, and illustrate how our proposed approach can be instantiated via a proof-of-concept prototype. Via a proof-of-concept database design-support environment, we exemplify our annotation-based approach, and show how segregating "what" from "when/where" via annotations satisfies ontologic- and cognition-based requirements, dovetails with existing database design methodologies, results in upward-compatible conceptual as well as XML schemas, and provides a straightforward mechanism to extend extant design-support environments. © 2004 Elsevier B.V. All rights reserved.
• Khatri, V., Ram, S., Snodgrass, R. T., & Vessey, I. (2006). Strong vs. Weak Approaches to Conceptual Design: The Case of, Temporal Data Semantics. Kelley School Bus., Bloomington, IN, TR, 147--1.
• Pavlou, K. E., & Snodgrass, R. T. (2006). The pre-images of bitwise AND functions in forensic analysis. History.
• Pavlou, K., & Snodgrass, R. T. (2006). Forensic analysis of database tampering. Proceedings of the ACM SIGMOD International Conference on Management of Data, 109-120.
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  Abstract: Mechanisms now exist that detect tampering of a database, through the use of cryptographically-strong hash functions. This paper addresses the next problem, that of determining who, when, and what, by providing a systematic means of performing forensic analysis after such tampering has been uncovered. We introduce a schematic representation termed a "corruption diagram" that aids in intrusion investigation. We use these diagrams to fully analyze the original proposal, that of a linked sequence of hash values. We examine the various kinds of intrusions that are possible, including retroactive, introactive, backdating, and postdating intrusions. We then introduce successively more sophisticated forensic analysis algorithms: the monochromatic, RGB, and polychromatic algorithms, and characterize the "forensic strength" of these algorithms. We show how forensic analysis can efficiently extract a good deal of information concerning a corruption event. Copyright 2006 ACM.
• Snodgrass, R. (2006). Single- Versus double-blind reviewing: An analysis of the literature. SIGMOD Record, 35(3), 8-21.
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  Abstract: A substantial scholarly literature regarding blind reviewing, which includes empirical studies for biomedicine, communication, computer science, economics, education, and many more are discussed. The arguments for double-blind reviewing are that it is fairer and it produces higher quality reviews. Peer review is the use of predetermined reviewers, in the case of program committees, or ad-hoc reviewers, in the case of reviewers for most journals, who individually read the submitted manuscript and prepare a written interview. The identity of the reviewer is not revealed to other reviewers in most of the journals. The important point is that the term single-blind reviewing applies only to hiding the identity of the reviewer from the author. An argument for double-blind reviewing is that it is fairer to authors and thus, indirectly to readers.
• Snodgrass, R. (2006). Single-versus double-blind reviewing: an analysis of the literature. ACM Sigmod Record, 35(3), 8--21.
• Snodgrass, R. T. (2006). Changes to the TODS editorial board.. SIGMOD record, 35(4), 77.
• Snodgrass, R. T. (2006). Single- versus double-blind reviewing: An analysis of the literature. SIGMOD RECORD, 35(3), 8-21.
• Snodgrass, R., & Jensen, C. (2006). Temporal Databases.
• Urgun, B., Dyreson, C. E., Snodgrass, R. T., Miller, J. K., Kline, N., Soo, M. D., & Jensen, C. S. (2006). Integrating Multiple Calendars using.
• Urgun, B., Dyreson, C. E., Snodgrass, R. T., Miller, J. K., Kline, N., Soo, M. D., & Jensen, C. S. (2006). Integrating Multiple Calendars.
• Abiteboul, S., Agrawal, R., Bernstein, P., Carey, M., Ceri, S., Croft, B., DeWitt, D., Franklin, M., Molina, H. G., Gawlick, D., Gray, J., Haas, L., Halevy, A., Hellerstein, J., Ioannidis, Y., Kersten, M., Pazzani, M., Lesk, M., Maier, D., , Naughton, J., et al. (2005). The lowell database research self-assessment. Communications of the ACM, 48(5), 111-118.
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  Abstract: The database research with focus on integration of text, data, code, fusion of information from heterogeneous data sources, and information privacy, conducted at Lowell, is discussed. The object-oriented (OO) and object-relational (OR) database management systems (DBMS) showed how text and other data types can be added to a DBMS. Several goals mentioned in the Lowell meeting included the proposal to reconsider DBMS architecture to handle new data types, approximate reasoning, and treating procedures and data as co-equal. It was found that information integration research would be well served by generating a test bed and collection of integration tasks.
• Abiteboul, S., Agrawal, R., Berstein, P., Carey, M., Ceri, S., Croft, B., DeWitt, D., Franklin, M., Garcia Molina, H., Gawlick, D., & others, . (2005). The Lowell Database Research Self-Assessment. CACM, 48(5), 111--118.
• Bernstein, P. A., Bertino, E., Heuer, A., Jensen, C. S., Meyer, H., \"Ozsu, M. T., Snodgrass, R. T., & Whang, K. (2005). An apples-to-apples comparison of two database journals. ACM SIGMOD Record, 34(4), 61--64.
• Bernstein, P. A., Bertino, E., Heuer, A., Jensen, C. S., Meyer, H., Özsu, M. T., Snodgrass, R. T., & Whang, K. (2005). An apples-to-apples comparison of two database journals. SIGMOD Record, 34(4), 61-64.
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  Abstract: This paper defines a collection of metrics on manuscript reviewing and presents historical data for ACM Transactions on Database Systems and The VLDB Journal.
• Bernstein, P. A., DeWitt, D., Heuer, A., Ives, Z., Jensen, C. S., Meyer, H., Özsu, M. T., Snodgrass, R. T., Whang, K., & Widom, J. (2005). Database publication practices. VLDB 2005 - Proceedings of 31st International Conference on Very Large Data Bases, 3, 1241-1245.
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  Abstract: There has been a growing interest in improving the publication processes for database research papers. This panel reports on recent changes in those processes and presents an initial cut at historical data for the VLDB Journal and ACM Transactions on Database Systems.
• Fernando, I., Snodgrass, R. T., & Moon, B. (2005). Spatiotemporal aggregate computation: A survey. IEEE Transactions on Knowledge and Data Engineering, 17(2), 271-286.
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  Abstract: Spatiotemporal databases are becoming increasingly more common. Typically, applications modeling spatiotemporal objects need to process vast amounts of data. In such cases, generating aggregate information from the data set is more useful than individually analyzing every entry. In this paper, we study the most relevant techniques for the evaluation of aggregate queries on spatial, temporal, and spatiotemporal data. We also present a model that reduces the evaluation of aggregate queries to the problem of selecting qualifying tuples and the grouping of these tuples into collections on which an aggregate function is to be applied. This model give us a framework that allows us to analyze and compare the different existing techniques for the evaluation of aggregate queries. At the same time, it allows us to identify opportunities for research on types of aggregate queries that have not been studied. © 2005 IEEE Published by the IEEE Computer Society.
• Gao, D., Jensen, C. S., Snodgrass, R. T., & Soo, M. D. (2005). Join operations in temporal databases. The VLDB Journal, 14(1), 2--29.
• Gao, D., Jensen, C. S., Snodgrass, R. T., & Soo, M. D. (2005). Join operations in temporal databases. VLDB Journal, 14(1), 2-29.
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  Abstract: Joins are arguably the most important relational operators. Poor implementations are tantamount to computing the Cartesian product of the input relations. In a temporal database, the problem is more acute for two reasons. First, conventional techniques are designed for the evaluation of joins with equality predicates rather than the inequality predicates prevalent in valid-time queries. Second, the presence of temporally varying data dramatically increases the size of a database. These factors indicate that specialized techniques are needed to efficiently evaluate temporal joins. We address this need for efficient join evaluation in temporal databases. Our purpose is twofold. We first survey all previously proposed temporal join operators. While many temporal join operators have been defined in previous work, this work has been done largely in isolation from competing proposals, with little, if any, comparison of the various operators. We then address evaluation algorithms, comparing the applicability of various algorithms to the temporal join operators and describing a performance study involving algorithms for one important operator, the temporal equijoin. Our focus, with respect to implementation, is on non-index-based join algorithms. Such algorithms do not rely on auxiliary access paths but may exploit sort orderings to achieve efficiency. © Springer-Verlag 2003.
• Lopez, I. V., Snodgrass, R. T., & Moon, B. (2005). Spatiotemporal aggregate computation: A survey. Knowledge and Data Engineering, IEEE Transactions on, 17(2), 271--286.
• Snodgrass, R. (2005). CMM and TODS. ACM SIGMOD Record, 34(3), 114--117.
• Snodgrass, R. (2005). Changes to the TODS editorial board. ACM SIGMOD Record, 34(4), 92--92.
• Snodgrass, R. T. (2005). ACM TODS associate editor manual. ACM, New York.
• Terenziani, P., Snodgrass, R. T., Bottrighi, A., Torchio, M., & Molino, G. (2005). Extending temporal databases to deal with telic/atelic medical data. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3581 LNAI, 58-66.
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  Abstract: In the area of Medical Informatics, there is an increasing realization that temporal information plays a crucial role, so that suitable database models and query languages are needed to store and support it. In this paper we show that current approaches developed within the database field have some limitations even from the point of view of the data model, so that an important class of temporal medical data cannot be properly represented. We propose a new three-sorted model and a query language that overcome such limitations. © Springer-Verlag Berlin Heidelberg 2005.
• Currim, F., Currim, S., Dyreson, C., & Snodgrass, R. T. (2004). A tale of two schemas: creating a temporal xml schema from a snapshot schema with τxschema. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2992, 348-365.
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  Abstract: The W3C XML Schema recommendation defines the structure and data types for XML documents. XML Schema lacks explicit support for time-varying XML documents. Users have to resort to ad hoc, non-standard mechanisms to create schemas for time-varying XML documents. This paper presents a data model and architecture, called τXSchema, for creating a temporal schema from a non-temporal (snapshot) schema, a temporal annotation, and a physical annotation. The annotations specify which portion(s) of an XML document can vary over time, how the document can change, and where timestamps should be placed. The advantage of using annotations to denote the time-varying aspects is that logical and physical data independence for temporal schemas can be achieved while remaining fully compatible with both existing XML Schema documents and the XML Schema recommendation. © Springer-Verlag 2004.
• Currim, F., Currim, S., Dyreson, C., & Snodgrass, R. T. (2004). Innovative Modelling Concepts for Spatial and Temporal Databases-A Tale of Two Schemas: Creating a Temporal XML Schema from a Snapshot Schema with t-XSchema. Lecture Notes in Computer Science, 2992, 348--365.
• Gao, D., Alvin, J., Moon, B., Snodgrass, R. T., Park, M., Huang, B. C., & Rodrigue, J. M. (2004). Main memory-based algorithms for efficient parallel aggregation for temporal databases. Distributed and Parallel Databases, 16(2), 123-163.
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  Abstract: The ability to model the temporal dimension is essential to many applications. Furthermore, the rate of increase in database size and stringency of response time requirements has out-paced advancements in processor and mass storage technology, leading to the need for parallel temporal database management systems. In this paper, we introduce a variety of parallel temporal aggregation algorithms for the shared-nothing architecture; these algorithms are based on the sequential aggregation tree algorithm. We are particularly interested in developing parallel algorithms that can maximally exploit available memory to quickly compute large-scale temporal aggregates without intermediate disk writes and reads. Via an empirical study, we found that the number of processing nodes, the partitioning of the data, the placement of results, and the degree of data reduction effected by the aggregation impacted the performance of the algorithms. For distributed result placement, we discovered that greedy time division merge was the obvious choice. For centralized results and high data reduction, pair-wise merge was preferred for a large number of processing nodes; for low data reduction, it only performed well up to 32 nodes. This led us to a centralized variant of greedy time division merge which was best for the remaining cases. We present a cost model that closely predicts the running time of greedy time division merge.
• Gao, D., Gendrano, J. A., Moon, B., Snodgrass, R. T., Park, M., Huang, B. C., & Rodrigue, J. M. (2004). Main memory-based algorithms for efficient parallel aggregation for temporal databases. Distributed and Parallel Databases, 16(2), 123--163.
• Khatri, V., Ram, S., & Snodgrass, R. T. (2004). Augmenting a conceptual model with geospatiotemporal annotations. IEEE Transactions on Knowledge and Data Engineering, 16(11), 1324-1338.
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  Abstract: While many real-world applications need to organize data based on space (e.g., geology, geomarketing, environmental modeling) and/or time (e.g., accounting, inventory management, personnel management), existing conventional conceptual models do not provide a straightforward mechanism to explicitly capture the associated spatial and temporal semantics. As a result, it is left to database designers to discover, design, and implement - on an ad hoc basis - the temporal and spatial concepts that they need. We propose an annotation-based approach that allows a database designer to focus first on nontemporal and nongeospatial aspects (i.e., "what") of the application and, subsequently, augment the conceptual schema with geospatiotemporal annotations (i.e., "when" and "where"). Via annotations, we enable a supplementary level of abstraction that succinctly encapsulates the geospatiotemporal data semantics and naturally extends the semantics of a conventional conceptual model. An overarching assumption in conceptual modeling has always been that expressiveness and formality need to be balanced with simplicity. We posit that our formally defined annotation-based approach is not only expressive, but also straightforward to understand and implement.
• Khatri, V., Ram, S., & Snodgrass, R. T. (2004). Augmenting a conceptual model with geospatiotemporal annotations. Knowledge and Data Engineering, IEEE Transactions on, 16(11), 1324--1338.
• Richard, K. T., & Snodgrass, T. (2004). odification Semantics in\% ow-) elative Databases.
• Snodgrass, R. (2004). TODS special issues. SIGMOD Record, 33(1), 5-6.
• Snodgrass, R. T. (2004). Changes to the ACM TODS Editorial Board.. SIGMOD Record, 33(4), 103.
• Snodgrass, R. T. (2004). TODS Special Issues.. SIGMOD Record, 33(1), 5--6.
• Snodgrass, R., & Brucks, M. (2004). Branding yourself. ACM SIGMOD Record, 33(2), 117--125.
• Snodgrass, R., & Brucks, M. (2004). Branding yourself. SIGMOD Record, 33(2), 117-125.
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  Abstract: The emergence of branding as a useful metaphor and new prespective to give insight into our choices of how and where to present our ideas is discussed. Brands help the consumer to organize their understanding of the commercial world, pass information to each other and to allocate their resources to meet their needs. The database research consumers effectively allocate their scarce time resources by relying on brands. Branding is used as a way of thinking about how to best communicate your ideas and insights to the consumers.
• Terenziani, P., & Snodgrass, R. T. (2004). Reconciling point-based and interval-based semantics in temporal relational databases: A treatment of the telic/atelic distinction. IEEE Transactions on Knowledge and Data Engineering, 16(5), 540-551.
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  Abstract: The analysis of the semantics of temporal data and queries plays a central role in the area of temporal databases. Although many different algebræ and models have been proposed, almost all of them are based on a point-based (snapshot) semantics for data. On the other hand, in the areas of linguistics, philosophy, and, recently, artificial Intelligence, an oft-debated Issue concerns the use of an Interval-based versus a point-based semantics. In this paper, we first show some problems Inherent in the adoption of a point-based semantics for data, then argue that these problems arise because there is no distinction drawn in the data between telic and atelic facts. We then Introduce a three-sorted temporal model and algebra including coercion functions for transforming relations of one sort into relations of the other at query time which properly copes with these issues.
• Terenziani, P., & Snodgrass, R. T. (2004). Reconciling point-based and interval-based semantics in temporal relational databases: A treatment of the telic/atelic distinction. Knowledge and Data Engineering, IEEE Transactions on, 16(5), 540--551.
• Torp, K., Jensen, C. S., & Snodgrass, R. T. (2004). Modification semantics in now-relative databases. Information Systems, 29(8), 653--683.
• Torp, K., Jensen, C. S., & Snodgrass, R. T. (2004). Modification semantics in now-relative databases. Information Systems, 29(8), 653-683.
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  Abstract: Most real-world databases record time-varying information. In such databases, the notion of "the current time," or NOW, occurs naturally and prominently. For example, when capturing the past states of a relation using begin and end time columns, tuples that are part of the current state have some past time as their begin time and NOW as their end time. While the semantics of such variable databases has been described in detail and is well understood, the modification of variable databases remains unexplored. This paper defines the semantics of modifications involving the variable NOW. More specifically, the problems with modifications in the presence of NOW are explored, illustrating that the main problems are with modifications of tuples that reach into the future. The paper defines the semantics of modifications - including insertions, deletions, and updates - of databases without NOW, with NOW, and with values of the type NOW+Δ, where Δ is a non-variable time duration. To accommodate these semantics, three new timestamp values are introduced. Finally, implementation is explored. We show how to represent the variable NOW with columns of standard SQL data types and give a mapping from SQL on NOW-relative data to standard SQL on these columns. The paper thereby completes the semantics, the querying, and the modification of now-relative databases. © 2003 Elsevier Ltd. All rights reserved.
• Urgun, B., Dyreson, C. E., Kline, N., Miller, J. K., Snodgrass, R. T., Soo, M. D., & Jensen, C. S. (2004). Integrating Multiple Calendars using Zaman.
• Zhang, S., Dyreson, C., & Snodgrass, R. T. (2004). Schema-less, semantics-based change detection for XML documents. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3306, 279-290.
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  Abstract: Schema-less change detection is the processes of comparing successive versions of an XML document or data collection to determine which portions are the same and which have changed, without using a schema. Change detection can be used to reduce space in an historical data collection and to support temporal queries. Most previous research has focused on detecting structural changes between document versions. But techniques that depend on structure break down when the structural change is significant. This paper develops an algorithm for detecting change based on the semantics, rather than on the structure, of a document. The algorithm is based on the observation that information that identifies an element is often conserved across changes to a document. The algorithm first isolates identifiers for elements. It then uses these identifiers to associate elements in successive versions. © Springer-Verlag 2004.
• Lee, Y. (2003). General Chair’s Message. Workshop Chair.
• Snodgrass, R. (2003). Developments at ACM TODS. SIGMOD Record, 32(4), 14-15.
• Snodgrass, R. (2003). Journal relevance. SIGMOD Record, 32(3), 11--15.
• Snodgrass, R. (2003). Journal relevance. SIGMOD Record, 32(3), 11-15.
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  Abstract: TODS is within just a few weeks of conferences in terms of turnaround time, about twice that of conferences for end-to-end time, and similar to top conferences in journal reference age and selectivity. Turnaround time is the interval between the submission, usually electronic, of a manuscript or a revision and the sending of the ediorial decision, almost entirely by electronic mail. End-to-end time is the interval between the original submission of a manuscript and the appearance in print of that manuscript. While it is certainly important to reference the most recent work, it is also important to reference related work done in the past, even long in the past.
• Snodgrass, R. T. (2003). ACM TODS in this Internet Age. SIGMOD Record, 32(1), 4--5.
• Snodgrass, R. T. (2003). Developments at ACM TODS.. SIGMOD Record, 32(4), 14--15.
• Snodgrass, R. T. (2003). TODS Reviewers.. SIGMOD Record, 32(2), 113--114.
• Apers, P., Ceri, S., & Snodgrass, R. (2002). VLDB Journal: Editorial. VLDB Journal, 11(3), 177-178.
• Khatri, V., Ram, S., Snodgrass, R. T., & O'Brien, G. M. (2002). Supporting user-defined granularities in a spatiotemporal conceptual model. Annals of Mathematics and Artificial Intelligence, 36(1-2), 195-232.
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  Abstract: Granularities are integral to spatial and temporal data. A large number of applications require storage of facts along with their temporal and spatial context, which needs to be expressed in terms of appropriate granularities. For many real-world applications, a single granularity in the database is insufficient. In order to support any type of spatial or temporal reasoning, the semantics related to granularities needs to be embedded in the database. Specifying granularities related to facts is an important part of conceptual database design because under-specifying the granularity can restrict an application, affect the relative ordering of events and impact the topological relationships. Closely related to granularities is indeterminacy, i.e., an occurrence time or location associated with a fact that is not known exactly. In this paper, we present an ontology for spatial granularities that is a natural analog of temporal granularities. We propose an upward-compatible, annotation-based spatiotemporal conceptual model that can comprehensively capture the semantics related to spatial and temporal granularities, and indeterminacy without requiring new spatiotemporal constructs. We specify the formal semantics of this spatiotemporal conceptual model via translation to a conventional conceptual model. To underscore the practical focus of our approach, we describe an on-going case study. We apply our approach to a hydrogeologic application at the United States Geologic Survey and demonstrate that our proposed granularity-based spatiotemporal conceptual model is straightforward to use and is comprehensive.
• Khatri, V., Ram, S., Snodgrass, R. T., & O'brien, G. M. (2002). Supporting user-defined granularities in a spatiotemporal conceptual model. Annals of Mathematics and Artificial Intelligence, 36(1-2), 195--232.
• Ross, K. A., Aho, A. V., & Ailamaki, A. (2002). Reminiscences on Influential Papers.. SIGMOD Record, 31(1), 107--108.
• Slivinskas, G., Jensen, C. S., & Snodgrass, R. T. (2002). Bringing order to query optimization. ACM SIGMOD Record, 31(2), 5--14.
• Slivinskas, G., Jensen, C. S., & Snodgrass, R. T. (2002). Bringing order to query optimization. SIGMOD Record, 31(2), 5-14.
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  Abstract: A variety of developments combine to highlight the need for respecting order when manipulating relations. For example, new functionality is being added to SQL to support OLAP-style querying in which order is frequently an important aspect. The set- or multiset-based frameworks for query optimization that are currently being taught to database students are increasingly inadequate. This paper presents a foundation for query optimization that extends existing frameworks to also capture ordering. A list-based relational algebra is provided along with three progressively stronger types of algebraic equivalences, concrete query transformation rules that obey the different equivalences, and a procedure for determining which types of transformation rules are applicable for optimizing a query. The exposition follows the style chosen by many textbooks, making it relatively easy to teach this material in continuation of the material covered in the textbooks, and to integrate this material into the textbooks.
• Snodgrass, R. T. (2002). Progress on ACM’s Becoming the Preferred Publisher. Communications of the ACM, 45(2), 97--98.
• Snodgrass, R. T. (2002). Rights and responsibilities in ACM publishing. Communications of the ACM, 45(2), 97--101.
• Snodgrass, R. T. (2002). Rights of TODS Readers, Authors and Reviewers. SIGMOD Record, 31(4), 5--9.
• Snodgrass, R. T. (2002). TODS Perceptions and Misconceptions. SIGMOD Record, 31(3), 6--8.
• Snodgrass, R. T. (2002). Why I like working in academia. SIGMOD Record, 31(1), 118-121.
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  Abstract: The personal experiences of Richard T. Snodgrass, a professor in the University of Arizona, in the field of academics are discussed. Richard holds a B.A. degree in Physics from Carleton College and M.S. and Ph.D degrees in Computer Science from Carnegie Mellon University. He is the Editor-in-Chief of the ACM Transactions on Database Systems. According to Richard, academics make less than equivalently trained counterparts in industry. Academic departments have a very flat management structure, organizational behavior jargon that translates into lots of committees.
• Snodgrass, R. T. (2002). Why i like working in academia. ACM SIGMOD Record, 31(1), 118--121.
• Wei, L. i., Gao, D., & Snodgrass, R. T. (2002). Skew handling techniques in sort-merge join. Proceedings of the ACM SIGMOD International Conference on Management of Data, 169-180.
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  Abstract: Joins are among the most frequently executed operations. Several fast join algorithms have been developed and extensively studied; these can be categorized as sort-merge, hash-based, and index-based algorithms. While all three types of algorithms exhibit excellent performance over most data, ameliorating the performance degradation in the presence of skew has been investigated only for hash-based algorithms. However, for sort-merge join, even a small amount of skew present in realistic data can result in a significant performance hit on a commercial DBMS. This paper examines the negative ramifications of skew in sort-merge join and proposes several refinements that deal effectively with data skew. Experiments show that some of these algorithms also impose virtually no penalty in the absence of data skew and are thus suitable for replacing existing sort-merge implementations. We also show how sort-merge band join performance is significantly enhanced with these refinements.
• Li, W., Gao, D., & Snodgrass, R. T. (2001). ATimecenter Technical Report.
• Li, W., Snodgrass, R. T., Deng, S., Gattu, V. K., & Kasthurirangan, A. (2001). Efficient sequenced temporal integrity checking. Proceedings - International Conference on Data Engineering, 131-140.
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  Abstract: Primary key and referential integrity are the most widely used integrity constraints in relational databases. Each has a sequenced analogue in temporal databases, in which the constraint must apply independently at every point in time. In this paper, we assume a stratum approach, which expresses the checking in conventional SQL, as triggers on period-stamped relations. We evaluate several novel approaches that exploit B+-tree indexes to enable efficient checking of sequenced primary key (SPK) and referential integrity (SRI) constraints. We start out with a brute force SPK algorithm, then adapt the Relational Intervaltree overlap algorithm. After that, we propose a new method, the Straight Traversal algorithm, which utilizes the B+-tree more directly to identify when multiple key values are present. Our evaluation, on two platforms, shows that Straight Traversal algorithm approaches the performance of built-in nontemporal primary key and referential integrity checking, with constant time per tuple.
• Slivinskas, G., Jensen, C. S., & Snodgrass, R. T. (2001). A foundation for conventional and temporal query optimization addressing duplicates and ordering. IEEE Transactions on Knowledge and Data Engineering, 13(1), 21-49.
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  Abstract: Most real-world databases contain substantial amounts of time-referenced, or temporal, data. Recent advances in temporal query languages show that such database applications may benefit substantially from built-in temporal support in the DBMS. To achieve this, temporal query representation, optimization, and processing mechanisms must be provided. This paper presents a foundation for query optimization that integrates conventional and temporal query optimization and is suitable for both conventional DBMS architectures and ones where the temporal support is obtained via a layer on top of a conventional DBMS. This foundation captures duplicates and ordering for all queries, as well as coalescing for temporal queries, thus generalizing all existing approaches known to the authors. It includes a temporally extended relational algebra to which SQL and temporal SQL queries may be mapped, six types of algebraic equivalences, concrete query transformation rules that obey different equivalences, a procedure for determining which types of transformation rules are applicable for optimizing a query, and a query plan enumeration algorithm. The presented approach partitions the work required by the database implementor to develop a provably correct query optimizer into four stages: The database implementor has to 1) specify operations formally, 2) design and prove correct appropriate transformation rules that satisfy any of the six equivalence types, 3) augment the mechanism that determines when the different types of rules are applicable to ensure that the enumeration algorithm applies the rules correctly, and 4) ensure that the mapping generates a correct initial query plan.
• Slivinskas, G., Jensen, C. S., & Snodgrass, R. T. (2001). A foundation for conventional and temporal query optimization addressing duplicates and ordering. Knowledge and Data Engineering, IEEE Transactions on, 13(1), 21--49.
• Slivinskas, G., Jensen, C. S., & Snodgrass, R. T. (2001). Adaptable query optimization and evaluation in temporal middleware. Proceedings of the ACM SIGMOD International Conference on Management of Data, 127-138.
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  Abstract: Time-referenced data are pervasive in most real-world databases. Recent advances in temporal query languages show that such database applications may benefit substantially from built-in temporal support in the DBMS. To achieve this, temporal query optimization and evaluation mechanisms must be provided, either within the DBMS proper or as a source level translation from temporal queries to conventional SQL. This paper proposes a new approach: using a middleware component on top of a conventional DBMS. This component accepts temporal SQL statements and produces a corresponding query plan consisting of algebraic as well as regular SQL parts. The algebraic parts are processed by the middleware, while the SQL parts are processed by the DBMS. The middleware uses performance feedback from the DBMS to adapt its partitioning of subsequent queries into middleware and DBMS parts. The paper describes the architecture and implementation of the temporal middleware component, termed TANGO, which is based on the Volcan o extensible query optimizer and the XXL query processing library. Experiments with the system demonstrate the utility of the middleware's internal processing capability and its cost-based mechanism for apportioning the processing between the middleware and the underlying DBMS.
• Slivinskas, G., Jensen, C. S., & Snodgrass, R. T. (2001). Adaptable query optimization and evaluation in temporal middleware. SIGMOD Record (ACM Special Interest Group on Management of Data), 30(2), 127-138.
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  Abstract: Time-referenced data are pervasive in most real-world databases. Recent advances in temporal query languages show that such database applications may benefit substantially from built-in temporal support in the DBMS. To achieve this, temporal query optimization and evaluation mechanisms must be provided, either within the DBMS proper or as a source level translation from temporal queries to conventional SQL. This paper proposes a new approach: using a middleware component on top of a conventional DBMS. This component accepts temporal SQL statements and produces a corresponding query plan consisting of algebraic as well as regular SQL parts. The algebraic parts are processed by the middleware, while the SQL parts are processed by the DBMS. The middleware uses performance feedback from the DBMS to adapt its partitioning of subsequent queries into middleware and DBMS parts. The paper describes the architecture and implementation of the temporal middleware component, termed TANGO, which is based on the Volcano extensible query optimizer and the XXL query processing library. Experiments with the system demonstrate the utility of the middleware's internal processing capability and its cost-based mechanism for apportioning the processing between the middleware and the underlying DBMS.
• Slivinskas, G., Jensen, C., & Snodgrass, R. (2001). SPECIAL SECTION: 16TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING-A Foundation for Conventional and Temporal Query Optimization Addressing Duplicates and Ordering. IEEE Transactions on Knowledge and Data Engineering, 13(1), 21--49.
• Snodgrass, R. T. (2001). ACM Transactions on Database Systems: Editorial. ACM Transactions on Database Systems, 26(3), 261-263.
• Snodgrass, R. T. (2001). Accessibility of the Database Literature. SIGMOD Record, 30(3), 7--10.
• Terenziani, P., & Snodgrass, R. T. (2001). Reconciling Point-based and Interval-based Semantics in Temporal Relational. History.
• B\"ohlen, M. H., Jensen, C. S., & Snodgrass, R. T. (2000). Temporal statement modifiers. ACM Transactions on Database Systems (TODS), 25(4), 407--456.
• Böhlen, M. H., Jensen, C. S., & Snodgrass, R. T. (2000). Temporal Statement Modifiers. ACM Transactions on Database Systems, 25(4), 407-456.
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  Abstract: A wide range of database applications manage time-varying data. Many temporal query languages have been proposed, each one the result of many carefully made yet subtly interacting design decisions. In this article we advocate a different approach to articulating a set of requirements, or desiderata, that directly imply the syntactic structure and core semantics of a temporal extension of an (arbitrary) nontemporal query language. These desiderata facilitate transitioning applications from a nontemporal query language and data model, which has received only scant attention thus far. The paper then introduces the notion of statement modifiers that provide a means of systematically adding temporal support to an existing query language. Statement modifiers apply to all query language statements, for example, queries, cursor definitions, integrity constraints assertions, views, and data manipulation statements. We also provide a way to systematically add temporal support to an existing implementation. The result is a temporal query language syntax, semantics, and implementation that derives from first principles. We exemplify this approach by extending SQL-92 with statement modifiers. This extended language, termed ATSQL, is formally defined via a denotational-semantics-style mapping of temporal statements to expressions using a combination of temporal and conventional relational algebraic operators.
• Ceri, S., Kalinichenko, L. A., Kitsuregawa, M., Lu, H., Oezsoyoglu, Z. M., Snodgrass, R. T., & Vianu, V. (2000). sIGMOD sister societies. SIGMOD Record, 29(1), 4--15.
• Dyreson, C. E., Evans, W. S., Lin, H., & Snodgrass, R. T. (2000). Efficiently supporting temporal granularities. IEEE Transactions on Knowledge and Data Engineering, 12(4), 568-587.
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  Abstract: Granularity is an integral feature of temporal data. For instance, a person's age is commonly given to the granularity of years and the time of their next airline flight to the granularity of minutes. A granularity creates a discrete image, in terms of granules, of a (possibly continuous) time-line. We present a formal model for granularity in temporal operations that is integrated with temporal indeterminacy, or "don't know when" information. We also minimally extend the syntax and semantics of SQL-92 to support mixed granularities. This support rests on two operations, scale and cast, that move times between granularities, e.g., from days to months. We demonstrate that our solution is practical by showing how granularities can be specified in a modular fashion, and by outlining a time- and space-efficient implementation. The implementation uses several optimization strategies to mitigate the expense of accommodating multiple granularities. © 2000 IEEE.
• Dyreson, C. E., Evans, W. S., Lin, H., & Snodgrass, R. T. (2000). Efficiently supporting temporal granularities. Knowledge and Data Engineering, IEEE Transactions on, 12(4), 568--587.
• Slivinskas, G., Jensen, C. S., & Snodgrass, R. T. (2000). Query plans for conventional and temporal queries involving duplicates and ordering. Proceedings - International Conference on Data Engineering, 547-558.
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  Abstract: Most real-world database applications contain a substantial portion of time-referenced, or temporal, data. Recent advances in temporal query languages show that such database applications could benefit substantially from built-in temporal support in the DBMS. To achieve this, temporal query representation, optimization, and processing mechanisms must be provided. This paper presents a general, algebraic foundation for query optimization that integrates conventional and temporal query optimization and is suitable for providing temporal support both via a stand-alone temporal DBMS and via a layer on top of a conventional DBMS. By capturing duplicate removal and retention and order preservation for all queries, as well as coalescing for temporal queries, this foundation formalizes and generalizes existing approaches.
• Snodgrass, R. T. (2000). Chair's Message. SIGMOD Record, 29(1), 3.
• Snodgrass, R. T. (2000). SIGMOD Program Review. SIGMOD Record, 29(4), 5--10.
• Torp, K., Jensen, C. S., & Snodgrass, R. T. (2000). Effective timestamping in databases. The VLDB Journal—The International Journal on Very Large Data Bases, 8(3-4), 267--288.
• Torp, K., Jensen, C. S., & Snodgrass, R. T. (2000). Effective timestamping in databases. VLDB Journal, 8(3-4), 267-288.
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  Abstract: Many existing database applications place various timestamps on their data, rendering temporal values such as dates and times prevalent in database tables. During the past two decades, several dozen temporal data models have appeared, all with timestamps being integral components. The models have used timestamps for encoding two specific temporal aspects of database facts, namely transaction time, when the facts are current in the database, and valid time, when the facts are true in the modeled reality. However, with few exceptions, the assignment of timestamp values has been considered only in the context of individual modification statements. This paper takes the next logical step: It considers the use of timestamping for capturing transaction and valid time in the context of transactions. The paper initially identifies and analyzes several problems with straightforward timestamping, then proceeds to propose a variety of techniques aimed at solving these problems. Timestamping the results of a transaction with the commit time of the transaction is a promising approach. The paper studies how this timestamping may be done using a spectrum of techniques. While many database facts are valid until now, the current time, this value is absent from the existing temporal types. Techniques that address this problem using different substitute values are presented. Using a stratum architecture, the performance of the different proposed techniques are studied. Although querying and modifying time-varying data is accompanied by a number of subtle problems, we present a comprehensive approach that provides application programmers with simple, consistent, and efficient support for modifying bitemporal databases in the context of user transactions.
• Alvin, J., Huang, B. C., Rodrigue, J. M., Moon, B., & Snodgrass, R. T. (1999). Parallel algorithms for computing temporal aggregates. Proceedings - International Conference on Data Engineering, 418-427.
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  Abstract: The ability to model the temporal dimension is essential to many applications. Furthermore, the rate of increase in database size and response time requirements has outpaced advancements in processor and mass storage technology, leading to the need for parallel temporal database management systems. In this paper, we introduce a variety of parallel temporal aggregation algorithms for a shared-nothing architecture based on the sequential Aggregation Tree algorithm. Via an empirical study, we found that the number of processing nodes, the partitioning of the data, the placement of results, and the degree of data reduction effected by the aggregation impacted the performance of the algorithms. For distributed results placement, we discovered that Time Division Merge was the obvious choice. For centralized results and high data reduction, Pairwise Merge was preferred regardless of the number of processing nodes, but for low data reduction, it only performed well up to 32 nodes. This led us to a centralized variant of Time Division Merge which was best for larger configurations having low data reduction.
• Carey, M. J., Seligman, L. J., Pirahesh, H., Hamilton, J., Cherniavsky, J., Zemankova, M., Neimat, M., Ubell, M., Durdik, P., Hawthorn, P., & others, . (1999). NSF workshop on industrial/academic cooperation in database systems. SIGMOD Record, 28(1), 115--130.
• Jensen, C. S., & Snodgrass, R. T. (1999). Temporal data management. IEEE Transactions on Knowledge and Data Engineering, 11(1), 36-44.
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  Abstract: A wide range of database applications manage time-varying information. Existing database technology currently provides little support for managing such data. The research area of temporal databases has made important contributions in characterizing the semantics of such information and in providing expressive and efficient means to model, store, and query temporal data. This paper introduces the reader to temporal data management, surveys state-of-the-art solutions to challenging aspects of temporal data management, and points to research directions.
• Jensen, C. S., & Snodgrass, R. T. (1999). Temporal data management. Knowledge and Data Engineering, IEEE Transactions on, 11(1), 36--44.
• Kline, N., Li, J., Snodgrass, R., & others, . (1999). Specifying multiple calendars, calendric systems, and field tables and functions in TimeADT.
• Moon, B., Alvin, J., Gendrano, J. A., Park, M., Snodgrass, R. T., Huang, B. C., Rodrigue, J. M., & others, . (1999). Parallel Aggregation for Temporal Databases.
• Snodgrass, R. T. (1999). Chair's Message. SIGMOD Record, 28(1), 3.
• Snodgrass, R. T., Abiteboul, S., Cluet, S., Franklin, M. J., Lohman, G. M., Lomet, D. B., Oezsoyoglu, G., Ramakrishnan, R., Ross, K. A., Sellis, T. K., & others, . (1999). Reminiscences on influential papers. SIGMOD Record, 28(1), 110--114.
• Dyreson, C. E., & Snodgrass, R. T. (1998). Supporting Valid-Time Indeterminacy. ACM Transactions on Database Systems, 23(1), 1-57.
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  Abstract: In valid-time indeterminacy it is known that an event stored in a database did in fact occur, but it is not known exactly when. In this paper we extend the SQL data model and query language to support valid-time indeterminacy. We represent the occurrence time of an event with a set of possible instants, delimiting when the event might have occurred, and a probability distribution over that set. We also describe query language constructs to retrieve information in the presence of indeterminacy. These constructs enable users to specify their credibility in the underlying data and their plausibility in the relationships among that data. A denotational semantics for SQL's select statement with optional credibility and plausibility constructs is given. We show that this semantics is reliable, in that it never produces incorrect information, is maximal, in that if it were extended to be more informative, the results may not be reliable, and reduces to the previous semantics when there is no indeterminacy. Although the extended data model and query language provide needed modeling capabilities, these extensions appear initially to carry a significant execution cost. A contribution of this paper is to demonstrate that our approach is useful and practical. An efficient representation of valid-time indeterminacy and efficient query processing algorithms are provided. The cost of support for indeterminacy is empirically measured, and is shown to be modest. Finally, we show that the approach is general, by applying it to the temporal query language constructs being proposed for SQL3.
• Dyreson, C. E., & Snodgrass, R. T. (1998). Supporting valid-time indeterminacy. ACM Transactions on Database Systems (TODS), 23(1), 1--57.
• Richard, K. T., & Snodgrass, T. (1998). Stratum Approaches to Temporal DBMS Implementation. IDEAS... International Database Engineering and Applications Symposium: Proceedings..., 4.
• Snodgrass, R. (1998). Reminiscences in influential papers. ACM SIGMOD Record, 27(1), 54--57.
• Snodgrass, R. T. (1998). Managing Temporal Data A Five-Part Series. Database programming and design, TimeCenter technical report.
• Snodgrass, R. T. (1998). Of duplicates and septuplets. Database Programming \& Design, 11(6), 46--49.
• Snodgrass, R. T. (1998). Querying valid-time state tables. Database Programming \& Design, 11(7), 60--65.
• Snodgrass, R. T. (1998). Temporal support in standard SQL. Database Programming \& Design, 11(10), 44--48.
• Snodgrass, R. T., Jensen, C. S., Bohlen, M. H., Busatto, R., Dyreson, C. E., Gregersen, H., Pfoser, D., Torp, K., Ram, S., Datta, A., & others, . (1998). Copyright c 1998RichardT. Snodgrass. Allrightsreserved..
• Torp, K., Jensen, C., & Snodgrass, R. (1998). Supporting Temporal Data Management Applications via Stratum Approaches. Supporting Temporal Data Management Applications via Stratum Approaches, 4--13.
• Tsotras, V. J., Jensen, C. S., & Snodgrass, R. T. (1998). An Extensible Notation for Spatiotemporal Index Queries. SIGMOD Record (ACM Special Interest Group on Management of Data), 27(1), 47-53.
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  Abstract: Temporal, spatial and spatiotemporal queries are inherently multidimensional, combining predicates on explicit attributes with predicates on time dimension(s) and spatial dimension(s). Much confusion has prevailed in the literature on access methods because no consistent notation exists for referring to such queries. As a contribution towards eliminating this problem, we propose a new and simple notation for spatiotemporal queries. The notation aims to address the selection-based spatiotemporal queries commonly studied in the literature of access methods. The notation is extensible and can be applied to more general multidimensional, selection-based queries.
• Tsotras, V. J., Jensen, C. S., & Snodgrass, R. T. (1998). An extensible notation for spatiotemporal index queries. ACM Sigmod Record, 27(1), 47--53.
• Bair, J., Böhlen, M. H., Jensen, C. S., & Snodgrass, R. J. (1997). Notions of upward compatibility of temporal query languages. Wirtschaftsinformatik, 39(1), 25-34+105.
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  Abstract: Migrating applications from conventional to temporal database management technology has received scant mention in the research literature. This paper formally defines three increasingly restrictive notions of upward compatibility which capture properties of a temporal SQL with respect to conventional SQL that, when satisfied, provide for a smooth migration of legacy applications to a temporal system. The notions of upward compatibility dictate the seman- tics of conventional SQL statements and constrain the semantics of extensions to these statements. The paper evaluates the seven extant temporal extensions to SQL, all of which are shown to complicate migration through design decisions that violate one or more of these notions. We then outline how SQL-92 can be systematically extended to become a temporal query language that satisfies all three notions.
• Busatto, R., Bohlen, M. H., Gregersen, H., Busatto, R., Jensen, C. S., Gregersen, H., Torp, K., Jensen, C. S., Datta, A., Torp, K., Lin, H., Datta, A., Snodgrass, R. T., Lin, H., Dyreson, C. E., Snodgrass, R. T., Dyreson, C. E., Soo, M. D., Soo, M. D., , Steiner, A., et al. (1997). Layered Implementation of Temporal DBMSs| Concepts and Techniques.
• Clifford, J., Dyreson, C., Isakowitz, T., Jensen, C. S., & Snodgrass, R. T. (1997). On the Semantics of now in Temporal Databases. ACM Transactions on Database System, 22(2), 215--254.
• Clifford, J., Dyreson, C., Isakowitz, T., Jensen, C. S., & Snodgrass, R. T. (1997). On the semantics of “now” in databases. ACM Transactions on Database Systems (TODS), 22(2), 171--214.
• Dyreson, C., & Snodgrass, R. T. (1997). The TSQL2 Baseline Clock.
• Jensen, C. S., Snodgrass, R. T., Bohlen, M. H., Busatto, R., Gregersen, H., Torp, K., Datta, A., Ram, S., Dyreson, C. E., Nam, K. W., & others, . (1997). served..
• Jensen, C., & Snodgrass, R. (1997). Tutorial G: Temporal Databases. Tutorial G: Temporal Databases.
• Snodgrass, R. T. (1997). A Second Addendum to Valid-and Transaction-time Proposals. Change, 3, 97--011.
• Snodgrass, R. T. (1997). Chair's Message. SIGMOD Record, 26(4), 3.
• Snodgrass, R. T., Bohlen, M. H., Jensen, C. S., Steiner, A., Busatto, R., Gregersen, H., Torp, K., Datta, A., Dyreson, C. E., Nam, K. W., & others, . (1997). andAndreasSteiner. Allrightsreserved..
• Torp, K., Snodgrass, R., & Jensen, C. S. (1997). Correct and Efficient Timestamping of Temporal Data. History.
• Tsotras, V. J., Jensen, C. S., & Snodgrass, R. T. (1997). A notation for spatiotemporal queries. History.
• Wijsen, J., Meersman, R., Jensen, C. S., Michael, H., Gregersen, H., Torp, K., Snodgrass, R. T., Datta, A., Ram, S., Dyreson, C. E., & others, . (1997). VrijeUniversiteitBrussel. Allrightsreserved..
• Böhlen, M. H., Chomicki, J., Snodgrass, R. T., & Toman, D. (1996). Querying TSQL2 databases with temporal logic. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1057 LNCS, 325-341.
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  Abstract: We establish an exact correspondence between temporal logic and a subset of TSQL2, a consensus temporal extension of SQL-92. The translation from temporal logic to TSQL2 developed here enables a user to write high-level queries which can be evaluated against a space-efficient representation of the database. The reverse translation, also provided, makes it possible to characterize the expressive power of TSQL2. We demonstrate that temporal logic is equal in expressive power to a syntactically defined subset of TSQL2.
• Clifford, J., Dyreson, C., Isakowitz, T., Jensen, C. S., & Snodgrass, R. T. (1996). On the Semantics of \" Now\" in Databases.
• Dyreson, C., & Sloane, A. M. (1996). NORTH QUEENSLAND.
• Jensen, C. S., & Snodgrass, R. T. (1996). Semantics of time-varying information. Information Systems, 21(4), 311--352.
• Jensen, C. S., Snodgrass, R. T., & Soo, M. D. (1996). Extending existing dependency theory to temporal databases. IEEE Transactions on Knowledge and Data Engineering, 8(4), 563-582.
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  Abstract: Normal forms play a central role in the design of relational databases. Several normal forms for temporal relational databases have been proposed. These definitions are particular to specific temporal data models, which are numerous and incompatible. This paper attempts to rectify this situation. We define a consistent framework of temporal equivalents of the important conventional database design concepts: functional dependencies, primary keys, and third and Boyce-Codd normal forms. This framework is enabled by making a clear distinction between the logical concept of a temporal relation and its physical representation. As a result, the role played by temporal normal forms during temporal database design closely parallels that of normal forms during conventional database design. These new normal forms apply equally well to all temporal data models that have timeslice operators, including those employing tuple timestamping, backlogs, and attribute value timestamping. As a basis for our research, we conduct a thorough examination of existing proposals for temporal dependencies, keys, and normal forms. To demonstrate the generality of our approach, we outline how normal forms and dependency theory can also be applied to spatial and spatiotemporal databases. ©1996 IEEE.
• Jensen, C. S., Snodgrass, R. T., & Soo, M. D. (1996). Extending existing dependency theory to temporal databases. Knowledge and Data Engineering, IEEE Transactions on, 8(4), 563--582.
• Silberschatz, A., Zdonik, S., Blakeley, J., Buneman, P., Dayal, U., Imielinski, T., Jajodia, S., Korth, H., Lohman, G., Lomet, D., Maier, D., Manola, F., Ozsu, T., Ramakrishnan, R., Ramamritham, K., Schek, H., Silberschatz, A., Snodgrass, R., Ullman, J., , Widom, J., et al. (1996). Strategic directions in database systems - Breaking out of the box. ACM Computing Surveys, 28(4), 764-778.
• Snodgrass, R. T. (1996). A Road Map of Additions to SQL/Temporal. ANSI, Feb.
• Snodgrass, R. T. (1996). INTERNATIONAL ORGANIZATION FOR STANDARDIZATION ORGANISATION INTERNATIONALE DE NORMALISATION.
• Snodgrass, R. T. (1996). INTERNATIONAL ORGANIZATION FOR STANDARDIZATION.
• Snodgrass, R. T. (1996). ISO IEC JTC1 SC21 WG3 DBL MCI-143.
• Snodgrass, R. T. (1996). Road Map Queries in the US and UK Proposals.
• Snodgrass, R. T. (1996). Subject: SQL Temporal Status: Change Proposal Title: Adding Valid Time to SQL Temporal Source: ANSI Expert's Contribution.
• Snodgrass, R. T. (1996). The inefficiency of misalignment. ACM Comput. Surv., 28(4es), article--89.
• Snodgrass, R. T., B\"ohlen, M. H., Jensen, C. S., & Steiner, A. (1996). Adding transaction time to SQL/Temporal. ISO-ANSI SQL/Temporal Change Proposal, ANSI X3H2-96-152r ISO/IEC JTC1/SC21/WG3 DBL, 1101, 143.
• Snodgrass, R. T., B\"ohlen, M. H., Jensen, C. S., & Steiner, A. (1996). Adding valid time to SQL/temporal. ANSI X3H2-96-501r2, ISO/IEC JTC, 1.
• Clifford, J., Jensen, C., Snodgrass, R., & Bohlen, M. (1995). The state-of-the-art in temporal data management: Perspectives from the research and financial applications communities.
• Dyreson, C., Snodgrass, R., & Freiman, M. (1995). Efficiently supporting temporal granularities in a DBMS.
• Jensen, C. S., Michael, H., B\"ohlen, M. H., Snodgrass, R. T., Jensen, C. S., Jensen, C. S., Snodgrass, R. T., & Snodgrass, R. T. (1995). Evaluating and Enhancing the Completeness of TSQL2.
• Kline, N., & Snodgrass, R. T. (1995). Computing temporal aggregates. Proceedings - International Conference on Data Engineering, 222-231.
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  Abstract: Aggregate computation, such as selecting the minimum attribute value of a relation, is expensive, especially in a temporal database. We describe the basic techniques behind computing aggregates in conventional databases and show that these techniques are not efficient when applied to temporal databases. We examine the problem of computing constant intervals (intervals of time for which the aggregate value is constant) used for temporal grouping. We introduce two new algorithms for computing temporal aggregates: the aggregation tree and the k-ordered aggregation tree. An empirical comparison demonstrates that the choice of algorithm depends in part on the amount of memory available, the number of tuples in the underlying relation, and the degree to which the tuples are ordered. This study shows that the simplest strategy is to first sort the underlying relation, then apply the k-ordered aggregation tree algorithm with k = 1.
• Ozsoyoglu, G., & Snodgrass, R. T. (1995). Guest Editors' Introduction to Special Section On Temporal and Real-Time Databases. IEEE Transactions on Knowledge and Data Engineering, 7(4), 511--512.
• Ozsoyoglu, G., & Snodgrass, R. T. (1995). Temporal and real-time databases: A survey. Knowledge and Data Engineering, IEEE Transactions on, 7(4), 513--532.
• Ozsoyoglu, G., & Snodgrass, R. T. (1995). Temporal and real-time databases: a survey. IEEE Transactions on Knowledge and Data Engineering, 7(4), 513-532.
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  Abstract: A temporal database contains time-varying data. In a real-time database transactions have deadlines or timing constraints. In this paper we review the substantial research in these two previously separate areas. First we characterize the time domain; then we investigate temporal and real-time data models. We evaluate temporal and real-time query languages along several dimensions. We examine temporal and real-time DBMS implementation. Finally, we summarize major research accomplishments to date and list several unanswered research questions.
• Segev, A., Jensen, C. S., & Snodgrass, R. T. (1995). Report on the 1995 international workshop on temporal databases. SIGMOD record, 24(4), 46--52.
• Al-Taha, K. K., Snodgrass, R. T., & Soo, M. D. (1994). Bibliography on spatiotemporal databases. International Journal of Geographical Information Systems, 8(1), 95--103.
• Dyreson, C. E., & Snodgrass, R. T. (1994). Efficient timestamp input and output. Software - Practice and Experience, 24(1), 89-109.
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  Abstract: In this paper we provide efficient algorithms for converting between timestamp values that signify some number of seconds from an arbitrary origin, and character strings specifying Gregorian dates, such as `January 1, 1993'. We give several algorithms that explore a range of time and space trade-offs. Unlike previous algorithms, those discussed here have a constant time cost over a greatly extended range of timestamp values. These algorithms are especially useful in operating systems and in database management systems.
• Dyreson, C. E., & Snodgrass, R. T. (1994). Efficient timestamp input and output. Software: Practice and Experience, 24(1), 89--109.
• Jensen, C. S., & Snodgrass, R. (1994). Temporal specialization and generalization. IEEE Transactions on Knowledge and Data Engineering, 6(6), 954-974.
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  Abstract: A standard relation has two dimensions: attributes and tuples. A temporal relation contains two additional orthogonal time dimensions, namely, valid time and transaction time. Valid time records when facts are true in the modeled reality, and transaction time records when facts are stored in the temporal relation. Although, in general, there are no restrictions between the valid time and transaction time associated with each fact, in many practical applications, the valid and transaction times exhibit more or less restricted interrelationships that define several types of specialized temporal relations. Five different areas where a variety of types of specialized temporal relations are present, are examined.
• Jensen, C. S., & Snodgrass, R. (1994). Temporal specialization and generalization. Knowledge and Data Engineering, IEEE Transactions on, 6(6), 954--974.
• Jensen, C. S., Clifford, J., Elmasri, R., Gagia, S. K., Hayes, P., Jajodia, S., Dyreson, C., Grandi, F., Kafer, W., Kline, N., & others, . (1994). A Consensus Glossary of Temporal Database Concepts. SIGMOD Record, 23(1).
• Jensen, C. S., Soo, M. D., & Snodgrass, R. T. (1994). Unifying temporal data models via a conceptual model. Information Systems, 19(7), 513--547.
• Jensen, C. S., Soo, M. D., & Snodgrass, R. T. (1994). Unifying temporal data models via a conceptual model. Information Systems, 19(7), 513-547.
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  Abstract: To add time support to the relational model, both first normal form (1NF) and non-1NF data models have been proposed. Each has associated advantages and disadvantages. For example, remaining within 1NF when time support is added may introduce data redundancy. On the other hand, well-established storage organization and query evaluation techniques require atomic attribute values, and are thus intended for 1NF models; utilizing a non-1NF model may degrade performance. This paper describes a new temporal data model designed with the single purpose of capturing the time-dependent semantics of data. Here, tuples of bitemporal relations are stamped with sets of two-dimensional chronons in transaction-time/valid-time space. We use the notion of snapshot equivalence to map temporal relation instances and temporal operators of one existing model to equivalent instances and operators of another. We examine five previously proposed schemes for representing bitemporal data: two are tuple-timestamped 1NF representations, one is a Backlog relation composed of 1NF timestamped change requests, and two are non-1NF attribute value-timestamped representations. The mappings between these models are possible using mappings to and from the new conceptual model. The framework of well-behaved mappings between models, with the new conceptual model at the center, illustrates how it is possible to use different models for display and storage purposes in a temporal database system. Some models provide rich structure and are useful for display of temporal data, while other models provide regular structure useful for storing temporal data. The equivalence mappings effectively move the distinction between the investigated data models from a semantic basis to a display-related or a physical, performance-relevant basis, thereby allowing the exploitation of different data models by using each for the task(s) for which they are best suited. © 1994.
• Pissinou, N., Snodgrass, R. T., Elmasri, R., Mumick, I. S., \"Ozsu, T., Pernici, B., Segev, A., Theodoulidis, B., & Dayal, U. (1994). Towards an infrastructure for temporal databases: report of an invitational ARPA/NSF workshop. ACM Sigmod Record, 23(1), 35--51.
• Pissinou, N., Snodgrass, R., Elmasri, R., Mumick, I., Tamer, M., & Ozsu, B. (1994). Technical Report List.
• Snodgrass, R. T. (1994). Overview of the Special Section on Temporal Database Infrastructure. SIGMOD Record, 23(1), 34.
• Snodgrass, R. T., & Winslett, M. (1994). ACM SIGMOD Record Volume 23 Issue 2.
• Snodgrass, R. T., Ahn, I., Ariav, G., Batory, D. S., Clifford, J., Dyreson, C. E., Elmasri, R., Grandi, F., Jensen, C. S., K\"afer, W., & others, . (1994). TSQL2 language specification. Sigmod Record, 23(1), 65--86.
• Snodgrass, R. T., Ahn, I., Ariav, G., Batory, D., Clifford, J., Dyreson, C. E., Elmasri, R., Grandi, F., Jensen, C. S., K\"afer, W., & others, . (1994). Announcement—the temporal query language TSQL2 final language definition. ACM SIGMOD Record, 23(3), 34.
• Soo, M. D., Snodgrass, R. T., & Jensen, C. S. (1994). Efficient evaluation of the valid-time natural join. Proceedings - International Conference on Data Engineering, 282-292.
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  Abstract: Joins are arguably the most important relational operators. Poor implementations are tantamount to computing the Cartesian product of the input relations. In a temporal database, the problem is more acute for two reasons. First, conventional techniques are designed for the optimization of joins with equality predicates, rather than the inequality predicates prevalent in valid-time queries. Second, the presence of temporally-varying data dramatically increases the size of the database. These factors require new techniques to efficiently evaluate valid-time joins. We address this need for efficient join evaluation in databases supporting valid-time. A new temporal-join algorithm based on tuple partitioning is introduced. This algorithm avoids the quadratic cost of nested-loop evaluation methods; it also avoids sorting. Performance comparisons between the partition-based algorithm and other evaluation methods are provided. While we focus on the important valid-time natural join, the techniques presented are also applicable to other valid-time joins.
• Al-Taha, K. K., Snodgrass, R. T., & Soo, M. D. (1993). Bibliography on spatiotemporal databases. ACM Sigmod Record, 22(1), 59--67.
• Dyreson, C. E., & Snodgrass, R. T. (1993). Timestamp semantics and representation. Information Systems, 18(3), 143--166.
• Dyreson, C. E., & Snodgrass, R. T. (1993). Timestamp semantics and representation. Information Systems, 18(3), 143-166.
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  Abstract: Many database management systems and operating systems provide support for time values. At the physical level time values are known as timestamps. A timestamp has a physical realization and a temporal interpretation. The physical realization is a pattern of bits while the temporal interpretation is the meaning of each bit pattern, that is, the time each pattern represents. All previous proposals defined timestamps in terms of seconds. However, as we show, there are at least seven definitions of this fundamental time unit. We propose a more precise temporal interpretation, the time-line clock, that constructs a time-line by using different well-defined clocks in different periods. We also propose timestamp formats for events, intervals and spans. These formats can represent all of time to the granularity of a second, and all of recorded history to a finer granularity of a microsecond. Our proposed formats were designed to be more space and time efficient than existing representations. We compare our formats with those used in common operating systems and database management systems. © 1993.
• Dyreson, C. E., & Snodgrass, R. T. (1993). Valid-time indeterminacy. Proceedings - International Conference on Data Engineering, 335-343.
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  Abstract: In valid-time indeterminacy, it is known that an event stored in a temporal database did in fact occur, but it is not known exactly when the event occurred. We present an extension of the tuple-timestamped temporal data model, called the possible chronons data model, to support valid-time indeterminacy. In the possible chronons data model, each event is represented with a set of possible chronons, delimiting when the event might have occurred, and a probability distribution over that set. We extend the TQuel query language with constructs that specify the user's credibility in the underlying valid-time data and the user's plausibility in the relationships among that data. We outline a formal tuple calculus semantics, and show that this semantics reduces to the determinate semantics on determinate data.
• Hsu, S. H., & Snodgrass, R. (1993). Optimal block size for set-valued attributes. Information Processing Letters, 45(3), 153-158.
• Hsu, S. H., & Snodgrass, R. (1993). Optimal block size for set-valued attributes. Information processing letters, 45(3), 153--158.
• Jensen, C. S., & Snodgrass, R. (1993). Three proposals for a third-generation temporal data model. Proceedings, International Workshop on an lnfrasrrucrure for Temporal Databases.
• Jensen, C. S., Soo, M. D., & Snodgrass, R. T. (1993). Unification of temporal data models. Proceedings - International Conference on Data Engineering, 262-270.
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  Abstract: To add time support to the relational model, both first normal form (1NF) and non-1NF approaches have been proposed. Each has associated difficulties. Remaining within 1NF when time support is added may introduce data redundancy. The non-1NF models may not be capable of directly using existing relational storage structures or query evaluation strategies. This paper describes a new, conceptual temporal data model that better captures the time-dependent semantics of the data while permitting multiple data models at the representation level. This conceptual model effectively moves the distinction between the various existing data models from a semantic basis to a physical, performance-relevant basis. We define a conceptual notion of a bitemporal relation where tuples are stamped with sets of two-dimensional chronons in transaction-time/valid-time space. We introduce a tuple-timestamped 1NF representation to exemplify how the conceptual bitemporal data model is related, by means of snapshot equivalence, with representational models. We then consider querying within the two-level framework. We first define an algebra at the conceptual level. We proceed to map this algebra to the sample representational model in such a way that new operators compute equivalent results for different representations of the same conceptual bitemporal relation. This demonstrates that the representational model is faithful to the semantics of the conceptual data model, with many choices available that may be exploited to improve performance.
• Ogle, D. M., Schwan, K., & Snodgrass, R. (1993). Application-dependent dynamic monitoring of distributed and parallel systems. IEEE Transactions on Parallel and Distributed Systems, 4(7), 762-778.
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  Abstract: Achieving high performance for parallel or distributed programs often requires substantial amounts of information about the programs themselves, about the systems on which they are executing, and about specific program runs. The monitoring system presented in this paper collects, analyzes, and makes application-dependent monitoring information available to the programmer and to the executing program. The system may be used for off-line program analysis, for on-line debugging, and for making on-line, dynamic changes to parallel or distributed programs to enhance their performance. We employ a high-level, uniform data model for the representation of program information and monitoring data. We show how this model may be used for the specification of program views and attributes for monitoring, and we demonstrate how such specifications can be translated into efficient, program-specific monitoring code that uses alternative mechanisms for the distributed analysis and collection to be performed for the specified views. The model's utility has been demonstrated on a wide variety of parallel machines, including several kinds of multiprocessors and a local area network.
• Ogle, D. M., Schwan, K., & Snodgrass, R. (1993). Application-dependent dynamic monitoring of distributed and parallel systems. Parallel and Distributed Systems, IEEE Transactions on, 4(7), 762--778.
• Snodgrass, R. T., Gomez, S., & LE McKenzie, J. (1993). Aggregates in the temporal query language TQuel. Knowledge and Data Engineering, IEEE Transactions on, 5(5), 826--842.
• Snodgrass, R. T., Gomez, S., & McKenzie Jr., L. (1993). Aggregates in the temporary query language TQuel. IEEE Transactions on Knowledge and Data Engineering, 5(5), 826-842.
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  Abstract: This paper defines new constructs to support aggregation in the temporal query language TQuel and presents their formal semantics in the tuple relational calculus. A formal semantics for Quel aggregates is defined in the process. Multiple aggregates; aggregates appearing in the where, when, and valid clauses; nested aggregation; and instantaneous, cumulative, moving window, and unique variants are supported. These aggregates provide a rich set of statistical functions that range over time, while requiring minimal additions to TQuel and its semantics. We show how the aggregates may be supported in an historical algebra, both in a batch and in an incremental fashion, demonstrating that implementation is straightforward and efficient.
• Soo, M., & Snodgrass, R. (1993). Multiple calendar support for conventional database management systems. Proc. Int. Workshop on an Infrastructure for Temporal Databases.
• Soo, M., & Snodgrass, R. (1993). Overview of MultiCal. The MultiCal Project.
• Dyreson, C. E., & Snodgrass, R. T. (1992). Historical indeterminacy.
• Hsu, S., Jensen, C., & Snodgrass, R. (1992). Valid-time projection in TSQL2. TempIS Document.
• Jensen, C. S., & Snodgrass, R. T. (1992). Temporal specialization. Proceedings - International Conference on Data Engineering, 594-603.
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  Abstract: The authors explore a variety of temporal relations with specialized relationships between transaction and valid time. An example is a retroactive temporal event relation, where the event must have occurred before it was stored, i.e., the valid time-stamp is restricted to be less than the transaction time-stamp. The authors discuss many useful restrictions, defining a large number of specialized types of temporal relations, and indicate some of their applications. A detailed taxonomy of specialized temporal relations is presented. This taxonomy may be used during database design to specify the particular time semantics of temporal relations.
• Jensen, C. S., Clifford, J., Gadia, S. K., Segev, A., & Snodgrass, R. T. (1992). A glossary of temporal database concepts. ACM Sigmod Record, 21(3), 35--43.
• Snodgrass, R., & GRANDI, F. (1992). Schema specification in TSQL2. TSQL2 Commentary TSQL2 language design committee.
• Soo, M., & Snodgrass, R. (1992). Mixed calendar query language support for temporal constants. The MultiCal Project, Release, 1.
• McKenzie Jr, L. E., & Snodgrass, R. T. (1991). Evaluation of relational algebras incorporating the time dimension in databases. ACM Computing Surveys (CSUR), 23(4), 501--543.
• Snodgrass, R., & Shannon, K. (1991). Semantic Clustering. Fourth Int’l Workshop on Persistent Object Sys.
• McKenzie, E., & Snodgrass, R. (1990). Schema evolution and the relational algebra. Information Systems, 15(2), 207--232.
• McKenzie, E., & Snodgrass, R. (1990). Schema evolution and the relational algebra. Information Systems, 15(2), 207-232.
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  Abstract: In this paper we discuss extensions to the conventional relational algebra to support both aspects of transaction time, evolution of a database's contents and evolution of a database's schema. We define a relation's schema to be the relation's temporal signature, a function mapping the relation's attribute names onto their value domains and class, indicating the extent of support for time. We also introduce commands to change a relation, now defined as a triple consisting of a sequence of classes, a sequence of signatures, and a sequence of states. A semantic type of system is required to identify semantically incorrect expressions and to enforce consistency constraints among a relation's class, signature and state following update. We show that these extensions are applicable, without change, to historical algebras that support valid time, yielding an algebraic language for the query and update of temporal databases. The additions preserve the useful properties of the conventional algebra. © 1990.
• Snodgrass, R. (1990). Temporal databases status and research directions. ACM Sigmod Record, 19(4), 83--89.
• Snodgrass, R. (1990). Temporal databases: status and research directions. SIGMOD Record (ACM Special Interest Group on Management of Data), 19(4), 83-89.
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  Abstract: The author begins with a chronology, touching briefly on all work that he am aware of in this area. He discusses in some detail what he considers to be the ten most important papers and events in terms of their impact on the discipline of temporal databases. His goal is to characterize the evolution of this field, as an introduction to the approximately 350 papers specifically relating time to databases that have appeared thus far. He then identifies and discusses areas where more work is needed.
• Snodgrass, R., & Shannon, K. (1990). Fine grained data management to achieve evolution resilience in a software development environment. ACM SIGSOFT Software Engineering Notes, 15(6), 144--156.
• Ahn, I., & Snodgrass, R. (1989). Performance analysis of temporal queries. Information Sciences, 49(1), 103--146.
• Ahn, I., & Snodgrass, R. (1989). Performance analysis of temporal queries. Information Sciences, 49(1-3), 103-146.
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  Abstract: Temporal databases maintaining history data on line extend conventional databases with capabilities for historical queries and rollback operations. To analyze the performance of temporal queries on databases using various access methods, we propose a model that takes a temporal query and a database schema as input, and outputs the estimated I/O cost for the query on that database. The model consists of four transformations through a series of formal expressions characterizing all phases of query processing. We validate the model by comparing the I/O cost estimated from the model with the actual cost measured from a prototype temporal DBMS. Since conventional databases are a subset of temporal databases, the model can also be used to analyze the performance of conventional databases. © 1989.
• Jensen, C. S., & Snodgrass, R. (1989). THE UNIVERSITY OF AALBORG.
• Shannon, K., & Snodgrass, R. (1989). Mapping the Interface Description Language type model into C. IEEE Transactions on Software Engineering, 15(11), 1333-1346.
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  Abstract: The Interface Description Language (IDL) is a notation for describing the characteristics of data structures passed among collections of cooperating processes in a programming environment. The authors discuss a mapping from IDL to C data structures and macro definitions that supports the full language and is type safe and run-time efficient, but is not particularly compile-time efficient nor easy to use. They then propose that the mapping be performed in a preprocessor, thereby achieving efficiency and ease of use as well.
• Shannon, K., & Snodgrass, R. (1989). Mapping the Interface Description Language type model into C. Software Engineering, IEEE Transactions on, 15(11), 1333--1346.
• Snodgrass, R. (1989). The interface description language: definition and use.
• Ahn, I., & Snodgrass, R. (1988). Partitioned storage for temporal databases. Information Systems, 13(4), 369--391.
• Ahn, I., & Snodgrass, R. (1988). Partitioned storage for temporal databases. Information Systems, 13(4), 369-391.
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  Abstract: Efficiently maintaining history data on line together with current data is difficult. This paper discusses one promising approach, the temporally partitioned store. The current store contains current data and possibly some history data, whil the history store holds the rest of the data. The two stores can utilize different storage formats, and even different storage media, depending on the individual data characteristics. We discuss various issues on the temporally partitioned store, investigate several formats for the history store, and evaluate their performance on a set of sample queries. © 1988.
• Hoffman, D., & Snodgrass, R. (1988). Trace specifications: Methodology and models. Software Engineering, IEEE Transactions on, 14(9), 1243--1252.
• Hoffman, D., & Snodgrass, R. (1988). Trace specifications: Methodology and models.. IEEE Transactions on Software Engineering, 14(9), 1243-1252.
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  Abstract: The authors summarize the trace specification language and present the trace specification methodology: a set of heuristics designed to make the reading and writing of complex specifications manageable. Also described is a technique for constructing formal, executable models from specifications written using the methodology. These models are useful as proofs of specification consistency and as executable prototypes. Fully worked examples of the methodology and the model building techniques are included.
• Snodgrass, R. (1988). A relational approach to monitoring complex systems. ACM Transactions on Computer Systems (TOCS), 6(2), 157--195.
• Snodgrass, R. (1988). RELATIONAL APPROACH TO MONITORING COMPLEX SYSTEMS.. ACM Transactions on Computer Systems, 6(2), 157-196.
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  Abstract: Traditional monitoring techniques are inadequate when monitoring complex systems such as multiprocessors or distributed systems. A new approach is described in which a historical database forms the conceptual basis for the information processed by the monitor. This approach permits advances in specifying the low-level data collection, specifying the analysis of the collected data, performing the analysis, and displaying the results. Two prototype implementations demonstrate the feasibility of the approach.
• McKenzie, E., & Snodgrass, R. (1987). Supporting Valid Time: An Historical Algebra TR87-008 August 1987.
• Snodgrass, R. (1987). Supporting Valid Time: A11 Historical Algebra i.
• Snodgrass, R. (1987). TEMPORAL QUERY LANGUAGE TQUEL.. ACM Transactions on Database Systems, 12(2), 247-298.
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  Abstract: Recently, attention has been focused on temporal databases, representing an enterprise over time. We have developed a new language, TQuel, to query a temporal database. TQuel was designed to be a minimal extension, both syntactically and semantically, of Quel, the query language in the Ingres relational database management system. This paper discusses the language informally, then provides a tuple relational calculus semantics for the TQuel statements that differ from their Quel counterparts, including the modification statements. The three additional temporal constructs defined in TQuel are shown to be direct semantic analogues of Quel's where clause and target list. We also discuss reducibility of the semantics to Quel's semantics when applied to a static database. TQuel is compared with ten other query languages supporting time.
• Snodgrass, R. (1987). The temporal query language TQuel. ACM Transactions on Database Systems (TODS), 12(2), 247--298.
• Snodgrass, R. T. (1987). Displaying IDL instances. ACM SIGPlan Notices, 22(11), 10--17.
• Warren, W. B., Kickenson, J., & Snodgrass, R. T. (1987). A tutorial introduction to using IDL. ACM SIGPlan Notices, 22(11), 18--34.
• Snodgrass, R. (1986). Announcement of the IDL toolkit. ACM SIGSOFT Software Engineering Notes, 11(1), 111.
• Snodgrass, R. T. (1986). Research Concerning Time in Databases - Project Summaries. SIGMOD Record, 15(4), 19--39.
• Snodgrass, R., & Ahn, I. (1985). TAXONOMY OF TIME IN DATABASES.. Array, 236-246.
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  Abstract: The need for supporting time varying information in databases has been recognized for quite some time. Many authors have proposed numerous schemes to satisfy this need by incorporating one or two time attributes in the database. Unfortunately, there has been confusion concerning the terminology and definition of these time attributes. This paper proposes a new taxonomy of three times for use in databases, one that is more cleanly defined, that may be conceptualized in a pictorial fashion, and that defines several kinds of databases differentiated by their ability to represent temporal information. The paper argues that future database management systems should support all three times to fully capture time varying behavior.
• Segall, Z., Singh, A., Snodgrass, R. T., Jones, A. K., & Siewiorek, D. P. (1983). An integrated instrumentation environment for multiprocessors. Computers, IEEE Transactions on, 100(1), 4--14.
• Segall, Z., Singh, A., Snodgrass, R. T., Jones, A. K., & Siewiorek, D. P. (1983). INTEGRATED INSTRUMENTATION ENVIRONMENT FOR MULTIPROCESSORS.. IEEE Transactions on Computers, C-32(1), 4-14.
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  Abstract: The concept of an integrated instrumentation environment (IIE) for multiprocesor is introduced. The primary objective of such an environment is to assist the user in the proces of experimentation. The emphasis in an IIE is on experiment management (including stimulus generation, monitoring, data collection and analysis), rather than on techniques for program development as in conventional programming environments. An experiment schema is introduced as an appropriate structuring concept for experiment management purposes. Schema instances capture the results of an experiment for later analysis. An example is developed in some detail to demonstrate the potential benefits of such an approach.
• Snodgrass, R. (1983). An object-oriented command language. Software Engineering, IEEE Transactions on, 1--8.
• Snodgrass, R. (1983). OBJECT-ORIENTED COMMAND LANGUAGE.. IEEE Transactions on Software Engineering, SE-9(1), 1-8.
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  Abstract: A description is given of Cola, an object-oriented command language for Hydra; Hydra is a capability-based operating system that runs on C. mmp, a tightly coupled multiprocessor. The two primary aspects of Cola, that it is a command language for Hydra, and that it is based on the object paradigm, are examined. Cola was designed to effect a correspondence between capabilities in Hydra and objects that are supported by the language. Cola is based on Smalltalk in that it uses message-passing as a control structure to allow syntactic freedom in the expression of commands to the system. Cola objects are arranged in a hierarchy, and the message-passing mechanism was designed to exploit this structure by automatically forwarding an unanswered message up the hierarchy. Two ramifications of this mechanism, automatic inheritance and shadowing, are discussed.
• SEGALL, Z., SINGH, A., SNODGRASS, R., JONES, A., & SIEWIOREK, D. (1982). Real time status monitoring for distributed systems[Final Report, Jan. 1981- Aug. 1982].
• Snodgrass, R. (1980). SOPHISTICATED MICROCOMPUTER USER INTERFACE.. SIGSMALL Newsletter (ACM Special Interest Group on Small Computing Systems and Applications), 6(2), 97-107.
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  Abstract: The design and implementation of a menu-oriented interface for personal computers is discussed. Factors pertaining to the cognitive limitations of users are examined and their impact on the design of the system is described. The major attributes of the system are (1) all communication between the operator and the computer is through menus or forms (which are analogus to hard copy documents); (2) extensive help is available at all times; (3) the interface can adapt to the experience of the user; (4) the display processing time is short; and (5) an external data format exists that completely defines the interface. The various components of the interface are discussed in detail, followed by a discussion of the implementation.

Proceedings Publications

• Saha, A., Wang, Z., Matheson, T., Narayan, G., Snodgrass, R., Kececioglu, J., Scheidegger, C., Axelrod, T., Jenness, T., Ridgway, S., Seaman, R., Taylor, C., Toeniskoetter, J., Welch, E., Yang, S., & Zaidi, T. (2016, May). ANTARES: Progress towards building a 'Broker' of time-domain alerts. In OBSERVATORY OPERATIONS: STRATEGIES, PROCESSES, AND SYSTEMS VI, 9910.
• Dempsey, J., Snodgrass, R. T., Kishi, I., & Titcomb, A. L. (2015, March). The Emerging Role of Self-Perception in Student Intentions. In ACM Conference on Computer Science Education (SIGCSE).
• Dempsey, J., Snodgrass, R. T., Kishi, I., & Titcomb, A. L. (2015, March). The Emerging Role of Self-Perception in Student Intentions. In Proceedings of the ACM Conference on Computer Science Education (SIGCSE), 6.
• Snodgrass, R. T. (2015, March). The Emerging Role of Self-Perception in Student Intentions. In ACM Conference on Computer Science Education (SIGCSE).
• Saha, A., Matheson, T., Snodgrass, R., Kececioglu, J., Narayan, G., Seaman, R., Jenness, T., & Axelrod, T. (2014). ANTARES: a prototype transient broker system. In SPIE Astronomical Telescopes+ Instrumentation, 914908--914908.
• Currim, S., Snodgrass, R. T., Suh, Y., Zhang, R., Johnson, M. W., & Cheng, Y. i. (2013, January). DBMS metrology: Measuring query time. In Proceedings of the ACM SIGMOD International Conference on Management of Data, 421-432.
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  Abstract: It is surprisingly hard to obtain accurate and precise measurements of the time spent executing a query. We review relevant process and overall measures obtainable from the Linux kernel and introduce a structural causal model relating these measures. A thorough correlational analysis provides strong support for this model. Using this model, we developed a timing protocol, which (1) performs sanity checks to ensure validity of the data, (2) drops some query executions via clearly motivated predicates, (3) drops some entire queries at a cardinality, again via clearly motivated predicates, (4) for those that remain, for each computes a single measured time by a carefully justified formula over the underlying measures of the remaining query executions, and (5) performs post-analysis sanity checks. The resulting query time measurement procedure, termed the Tucson Protocol, applies to proprietary and open-source DBMSes. Copyright © 2013 ACM.
• Pavlou, K. E., & Snodgrass, R. T. (2012, January). Achieving database information accountability in the cloud. In Proceedings - 2012 IEEE 28th International Conference on Data Engineering Workshops, ICDEW 2012, 147-150.
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  Abstract: Regulations and societal expectations have recently emphasized the need to mediate access to valuable databases. Fraud occurs when a person (mostly an insider) tampers illegally with a database. Data owners would like to be assured that such tampering has not occurred, or if it does, that it will be quickly discovered. The problem is exacerbated with data stored in cloud databases such as Amazon's Relational Database Service (RDS) or Microsoft's SQL Azure Database. In our previous work we have shown that information accountability across the enterprise is a viable alternative to information restriction for ensuring the correct storage, use, and maintenance of databases on extant DBMSes. We have developed a prototype audit system (DRAGOON) that employs cryptographic hashing techniques to support accountability in high-performance databases. Cloud databases present a new set of problems that make extending DRAGOON challenging. In this paper we discuss these problems and show how the DRAGOON architecture can be refined to provide a more practical and feasible information accountability solution for data stored in the cloud. © 2012 IEEE.
• Zhang, R., Debray, S., & Snodgrass, R. T. (2012). Micro-specialization: dynamic code specialization of database management systems. In Proceedings of the Tenth International Symposium on Code Generation and Optimization, 63--73.
• Zhang, R., Snodgrass, R. T., & Debray, S. (2012). Application of Micro-Specialization to Query Evaluation Operators. In Data Engineering Workshops (ICDEW), 2012 IEEE 28th International Conference on, 315--321.
• Zhang, R., Snodgrass, R. T., & Debray, S. (2012). Micro-Specialization in DBMSes. In Data Engineering (ICDE), 2012 IEEE 28th International Conference on, 690--701.
• Mitra, S., Winslett, M., Snodgrass, R. T., Yaduvanshi, S., & Ambokar, S. (2009). An architecture for regulatory compliant database management. In Data Engineering, 2009. ICDE'09. IEEE 25th International Conference on, 162--173.
• Snodgrass, R. T. (2007). Towards a Science of Temporal Databases.. In TIME, 6--7.
• Dyreson, C., Snodgrass, R. T., Currim, F., Currim, S., & Joshi, S. (2006). Validating Quicksand: Schema Versioning in tauXSchema. In Data Engineering Workshops, 2006. Proceedings. 22nd International Conference on, 82--82.
• Bernstein, P. A., DeWitt, D., Heuer, A., Ives, Z., Jensen, C. S., Meyer, H., \"Ozsu, M. T., Snodgrass, R. T., Whang, K., & Widom, J. (2005). Database publication practices. In Proceedings of the 31st international conference on Very large data bases, 1241--1245.
• Lomet, D., Snodgrass, R. T., & Jensen, C. S. (2005). Using the lock manager to choose timestamps. In Database Engineering and Application Symposium, 2005. IDEAS 2005. 9th International, 357--368.
• Snodgrass, R. T., Yao, S. S., & Collberg, C. (2004). Tamper detection in audit logs. In Proceedings of the Thirtieth international conference on Very large data bases-Volume 30, 504--515.
• Gao, D., & Snodgrass, R. T. (2003). Temporal slicing in the evaluation of XML queries. In Proceedings of the 29th international conference on Very large data bases-Volume 29, 632--643.
• Dunn, J., Davey, S., Descour, A., & Snodgrass, R. T. (2002). Sequenced subset operators: definition and implementation. In Data Engineering, 2002. Proceedings. 18th International Conference on, 81--92.
• Li, W., Gao, D., & Snodgrass, R. T. (2002). Skew handling techniques in sort-merge join. In Proceedings of the 2002 ACM SIGMOD international conference on Management of data, 169--180.
• Li, W., Snodgrass, R. T., Deng, S., Gattu, V. K., & Kasthurirangan, A. (2001). Efficient sequenced integrity constraint checking. In Proceedings of the 17th International Conference on Data Engineering, 131--140.
• Li, W., Snodgrass, R. T., Deng, S., Gattu, V. K., & Kasthurirangan, A. (2001). Efficient sequenced temporal integrity checking. In Data Engineering, 2001. Proceedings. 17th International Conference on, 131--140.
• Slivinskas, G., Jensen, C. S., & Snodgrass, R. T. (2001). Adaptable query optimization and evaluation in temporal middleware. In ACM SIGMOD Record, 30, 127--138.
• Gendrano, J. A., Huang, B. C., Rodrigue, J. M., Moon, B., & Snodgrass, R. T. (1999). Parallel algorithms for computing temporal aggregates. In Data Engineering, 1999. Proceedings., 15th International Conference on, 418--427.
• Torp, K., Jensen, C. S., & Snodgrass, R. T. (1999). Modification semantics in now-relative databases. In International Journal of Information Systems.
• Torp, K., Jensen, C. S., & Snodgrass, R. T. (1998). Stratum approaches to temporal DBMS implementation. In Database Engineering and Applications Symposium, 1998. Proceedings. IDEAS'98. International, 4--13.
• Isakowitz, T., Clifford, J., Dyreson, C., Jensen, C. S., & Snodgrass, R. T. (1997). On the Semantics of" Now" in Databases. In ACM Transactions on Database Systems.
• Kline, N., & Snodgrass, R. T. (1995). Computing temporal aggregates. In Data Engineering, 1995. Proceedings of the Eleventh International Conference on, 222--231.
• Snodgrass, R. (1995). Temporal object-oriented databases: a critical comparison. In Modern Database Systems, 386--408.
• Snodgrass, R. T., Clifford, J., Dayal, U., & Segev, A. (1995). Panel: Whither TSQL3?. In Proceedings of the International Workshop on Temporal Databases: Recent Advances in Temporal Databases, 355.
• Soo, M. D., Snodgrass, R. T., & Jensen, C. S. (1994). Efficient evaluation of the valid-time natural join. In Data Engineering, 1994. Proceedings. 10th International Conference, 282--292.
• Dyreson, C. E., & Snodgrass, R. T. (1993). Valid-time indeterminacy. In Data Engineering, 1993. Proceedings. Ninth International Conference on, 335--343.
• Jensen, C. S., Soo, M. D., & Snodgrass, R. T. (1993). Unification of temporal data models. In Data Engineering, 1993. Proceedings. Ninth International Conference on, 262--271.
• Jensen, C. S., & Snodgrass, R. T. (1992). Temporal specialization. In Data Engineering, 1992. Proceedings. Eighth International Conference on, 594--603.
• Shannon, K., & Snodgrass, R. T. (1990). Semantic Clustering.. In POS, 389--402.
• McKenzie, E., & Snodgrass, R. (1987). Extending the relational algebra to support transaction time. In ACM SIGMOD Record, 16, 467--478.
• Ahn, I., & Snodgrass, R. (1986). Performance evaluation of a temporal database management system. In ACM SIGMOD Record, 15, 96--107.
• Snodgrass, R. T. (1986). Temporal databases. In IEEE computer.
• Snodgrass, R., & Ahn, I. (1985). A taxonomy of time databases. In ACM Sigmod Record, 14, 236--246.
• Snodgrass, R. (1984). Monitoring in a software development environment: A relational approach. In ACM SIGPLAN Notices, 19, 124--131.
• Snodgrass, R. (1980). A sophisticated microcomputer user interface. In Proceedings of the 3rd ACM SIGSMALL symposium and the first SIGPC symposium on Small systems, 97--107.

Poster Presentations

• Suh, Y., Snodgrass, R., & Zhang, R. (2014, September). AZDBLab: A Laboratory Information System for a Large-Scale Empirical Study. VLDB’14 Demos.

Others

• Zhang, R., Snodgrass, R. T., & Debray, S. K. (2017, Feb). Methods of Microspecialization in Database Management Systems. United States Patent and Trademark Office.
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  U.S. Patent No. 9,576,002.
• Debray, S. K., Snodgrass, R. T., & Zhang, R. (2014). METHODS OF MICRO-SPECIALIZATION IN DATABASE MANAGEMENT SYSTEMS.
• Pavlou, K., & Snodgrass, R. (2012, May). The DRAGOON Project.
• Snodgrass, R., Johnson, M., Suh, Y., & Zhang, R. (2012, June). The Arizona Database Lab (AZDBLAB).
• Snodgrass, R., Kvochki, A., Patki, T., & Shrestha, A. (2014, June). A Laboratory for Computer Science (LOCUS).
• Thomas, S., Snodgrass, R., & Zhang, R. (2012, December). ? BE NCH.
• Chen, W. C. (2011). Ion channel profiles in murine spiral ganglion neurons: characterization of two-pore-domain potassium channels, voltage-gated calcium channels, and calcium-activated potassium channels.
• Jensen, C. S., & Snodgrass, R. T. (2008). Temporal Database Entries for the Springer Encyclopedia of Database Systems.
• Snodgrass, R. T. (2005). ERIC PAUL ROEDER.
• Gao, D., & Snodgrass, R. T. (2003). Syntax, Semantics, and Query Evaluation in the XQuery Temporal XML Query Language.
• Apers, P., Ceri, S., & Snodgrass, R. (2002). Special issue: Best papers of VLDB 2001.
• Snodgrass, R. (2002). Reminiscences on influential papers.
• Snodgrass, R. T., & Bair, J. (2002). Method and apparatus for changing temporal database information.
• Snodgrass, R., Jensen, C., Slivinskas, G., & Torp, K. (2002). Adaptable query optimization and evaluation in temporal middleware.
• Bair, J., & Snodgrass, R. T. (2001). Method and apparatus for producing sequenced queries.
• Snodgrass, R. T., & Bair, J. (2001). Method and apparatus for changing temporal database.
• Jensen, C. S., & Snodgrass, R. T. (2000). Temporally Enhanced Database Design..
• Bair, J., & Snodgrass, R. T. (1999). Method and apparatus for producing sequenced queries.
• Snodgrass, R. T. (1997). Response to MAD-220.
• Snodgrass, R. T. (1996). Addendum to Valid-and Transaction-time Proposals,".
• Snodgrass, R. T. (1993). An Overview of TQuel..
• Jones, A. (1988). REOCCURRENCE OF THE PACIFIC SEAHORSE, HIPPOCAMPUS-INGENS, IN SAN-DIEGO BAY.
• McKenzie, E., & Snodgrass, R. (1988). Scheme Evolution and the Relationship Algebra. Revision.
• Stam, R. B., & Snodgrass, R. T. (1988). A Bibliography on Temporal Databases.
• Ahn, I., & Snodgrass, R. (1987). The TempIS Project: Performance Analysis of Temporal Queries.
• McKenzie, E., & Snodgrass, R. (1987). An evaluation of historical algebras.
• Snodgrass, R. (1987). The TEMPIS Project: Current Status.
• Snodgrass, R., Gomez, S., & McKenize, E. (1987). Aggregates in the temporal query language TQuel.
• Segall, Z., Singh, A., Snodgrass, R., Jones, A. K., & Siewiorek, D. P. (1982). Real Time Status Monitoring for Distributed Systems..
• Snodgrass, R. (1982). Monitoring Distributed Systems: A Relational Approach..