Faiz Currim

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Courses

Scholarly Contributions

Books

• Currim, F. A. (2004). Spatio-temporal set-based constraints in conceptual modeling: A theoretical framework and evaluation. The University of Arizona..
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  Doctoral Dissertation

Chapters

• Currim, F., & Ram, S. (2010). When entities are types: Effectively modeling type-instantiation relationships. In Advances in Conceptual Modeling--Applications and Challenges(pp 138--147). Springer.
• Currim, F., Neidig, N., Kampoowale, A., & Mhatre, G. (2010). The CARD system. In Conceptual Modeling--ER 2010(pp 433--437). Springer.
• Currim, F., & Ram, S. (2009). Survey of Cardinality Constraints in Snapshot and Temporal Semantic Data Models. In Systems Analysis and Design for Advanced Modeling Methods : Best Practices.

Journals/Publications

• Ram, S., Currim, F., & Srinivasan, K. (2023). A Human-in-the-loop Segmented Mixed-effects Modeling Method For Analyzing Wearables Data. ACM Transactions on Management Information Systems, 14(2). doi:10.1145/3564276
• Sriniva, K., Currim, F., Lindberg, C., Razjouyan, J., Gilligan, B., Lee, H., Canada, K., Goebel, N., Mehl, M., Lunden, M., Heerwagen, J., Najafi, B., Sternberg, E., Kampschroer, K., & Ram, S. (2023). Discovery of associative patterns between workplace sound level and physiological wellbeing using wearable devices and empirical Bayes modeling. NPJ Digital Medicine, 6(5). doi:10.21203/rs.3.rs-1386161/v1
• Emerson, K., Baldwin, E., Scott, T., Pidot, J. R., Lien, A., Currim, F., Bethard, S. J., Ram, S., Miller, M. L., & Lopez Hoffman, L. (2022). Toward NEPA Performance: A framework for assessing EIAs. Environmental Impacts Assessment Review.
• Li, Y., Currim, F. A., & Ram, S. (2022). Data Completeness and Complex Semantics in Conceptual Modeling: the need for a Disaggregation Construct. Journal of Data and Information Quality.
• Wang, Y., Currim, F., & Ram, S. (2022). Deep Learning of Spatiotemporal Patterns for Urban Mobility Prediction using Big Data. Information Systems Research.
• Bhattacharya, D., Currim, F. A., & Ram, S. (2021). Evaluating Distributed Computing Infrastructures: An Empirical Study Comparing Hadoop Deployments on Cloud and Local Systems. IEEE Transactions on Cloud Computing, 9(3), 1075 - 1088. doi:10.1109/TCC.2019.2902377
• Razjouyan, J., Lee, H., Gilligan, B., M., L. C., Nguyen, H., Canada, K., Sharafkhaneh, A., Srinivasan, K., Currim, F., Ram, S., Mehl, M., M., L. M., H., H. J., Kampschroer, K., Sternberg, E., & Najafi, B. (2020). Wellbuilt for Wellbeing: Controlling Relative Humidity in the Workplace Matters for Our Health. Indoor Air, 30(1), 167-179. doi:https://doi.org/10.1111/ina.12618
• Sternberg, E. M., Mehl, M. R., Ram, S., Currim, F., Srinivasan, K., Burton, A., Razjouyan, J., Lee, H., Gilligan, B., Lindberg, C., Nguyen, H., Canada, K., Sharafkhaneh, A., Goebel, N., Lunden, M., Bhangar, S., Heerwagen, J., Kampschroer, K., & Najafi, B. (2020). Wellbuilt for wellbeing: Controlling relative humidity in the workplace matters for our health. Indoor Air, 30(1), 167-179. doi:10.1111/ina.12618
• Lindberg, C. M., Srinivasan, K., Gilligan, B., Razjouyan, J., Lee, H., Najafi, B., Canada, K. J., Mehl, M. R., Currim, F., Ram, S., Lunden, M. M., Heerwagen, J. H., Kampschroer, K., & Sternberg, E. M. (2018). Effects of office workstation type on physical activity and stress. Occupational and Environmental Medicine, 75(10), 689--695.
• Srinivasan, K., Currim, F., & Ram, S. (2018). Predicting High Cost Patients at Point of Admission using Network Science. IEEE Journal of Biomedical and Health Informatics, 22(6), 1970-1977. doi:10.1109/JBHI.2017.2783049
• Currim, S., Ram, S., Durcikova, A., & Currim, F. (2014). Using a knowledge learning framework to predict errors in database design. Information Systems, 40, 11-31.
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  Abstract: Conceptual data modeling is a critical but difficult part of database development. Little research has attempted to find the underlying causes of the cognitive challenges or errors made during this stage. This paper describes a Modeling Expertise Framework (MEF) that uses modeler expertise to predict errors based on the revised Bloom's taxonomy (RBT). The utility of RBT is in providing a classification of cognitive processes that can be applied to knowledge activities such as conceptual modeling. We employ the MEF to map conceptual modeling tasks to different levels of cognitive complexity and classify current modeler expertise levels. An experimental exercise confirms our predictions of errors. Our work provides an understanding into why novices can handle entity classes and identifying binary relationships with some ease, but find other components like ternary relationships difficult. We discuss implications for data modeling training at a novice and intermediate level, which can be extended to other areas of Information Systems education and training. © 2013 Elsevier Ltd. All rights reserved.
• Hylock, R., & Currim, F. (2013). A maintenance centric approach to the view selection problem. Information Systems, 38(7), 971--987.
• 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.
• Currim, F., & Ram, S. (2012). Modeling spatial and temporal set-based constraints during conceptual database design. Information Systems Research, 23(1), 109--128.
• Jo, I., Jung, E., Currim, F., Jung, I. Y., & Yeom, H. Y. (2012). Safe and Efficient Privacy-policy Enforcement on Hadoop. Information Journal, 15(5), 1973--1984.
• Zhang, L., Currim, S., & Currim, F. (2011). Competitive Intelligence Task Analysis And Retrieval: An End-User Approach. Review of Business Information Systems (RBIS), 15(2), 15--24.
• Lu, D., Street, W. N., Currim, F., Hylock, R., & Delaney, C. (2009). A data modeling process for decomposing healthcare patient data sets. Online Journal of Nursing Informatics, 13(1).
• Currim, F., & Ram, S. (2008). Conceptually modeling windows and bounds for space and time in database constraints. Communications of the ACM, 51(11), 125--129.
• 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.
• 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.
• Timmermann, B. N., Wachter, G., Valcic, S., Hutchinson, B., Casler, C., Henzel, J., Ram, S., Currim, F., Manak, R., Franzblau, S., & others, . (1999). The Latin American ICBG: the first five years. Pharmaceutical Biology (Formerly International Journal of Pharmacognosy), 37(Supplement 1), 35--54.

Proceedings Publications

• Yang, Z., Ram, S., & Currim, F. (2020, Fall). What Makes an Online Suggestion A Good One for Online Health Communities. In Americas Conference on Information Systems (AMCIS).
• Dong, F., Currim, F., & Ram, S. (2019, Fall). Modeling Bike Sharing Systems and Predicting Station Demand Using Heterogeneous Data Sources. In Workshop on Information Technology and Systems (WITS).
• Yang, Z., Ram, S., & Currim, F. (2019, Fall). Suggestion Mining for Online Health Forums. In Workshop on Information Technology and Systems (WITS).
• Yang, Z., Ram, S., & Currim, F. (2018, Fall). Drug-Drug Interaction Mining and Interaction Terms Extraction using Deep Learning: A Word-level Attention Bi-Directional LSTM. In Workshop on Information Technology and Systems.
• Srinivasan, K., Currim, F., & Ram, S. (2017, December). Using Digital Health Wearable Devices to Understand the Relationship Between Sound levels and Wellbeing: A Segmented Mixed-effects Regression Approach. In 27th Workshop on Information Technology and Systems (WITS), Seoul, South Korea (WITS2017).
• Srinivasan, K., Currim, F., Ram, S., Lindberg, C., Sternberg, E. M., Skeath, P. R., Najafi, B., Razjouyan, J., Lee, H., Mehl, M. R., Herzl, D., Herzl, R., Lunden, M., Goebel, N., Andrews, S., Gilligan, B., Heerwagen, J., Kampschroer, K., & Canada, K. (2017, July, 2-5). A Regularization Approach for Identifying Cumulative Lagged Effects in Smart Health Applications. In 7th International Conference on Digital Health, London, 2017, 99-103.
• Ram, S., Dong, F., Currim, F. A., Wang, Y., Dantas, E., & Sabóia, L. A. (2016, September). SMARTBIKE: Policy making and decision support for Bike Share systems. In IEEE 2nd International Smart Cities Conference.
• Ram, S., Wang, Y., Currim, F., Dong, F., Dantas, E., & Sabóia, L. A. (2016, April, 11-15). SMARTBUS: A Web Application for Smart Urban Mobility and Transportation. In AW4city 2nd International Smart City Workshop, Proceedings of World Wide Web Conference, Montreal, 2016 (WWW 2016).
• Srinivasan, K., Currim, F., Ram, S., Lindberg, C., Sternberg, E. M., Skeath, P. R., Najafi, B., Razjouyan, J., Lee, H., Foe-Parker, C., Goebel, N., Herzl, R., Mehl, M. R., Gilligan, B., Heerwagen, J., Kampschroer, K., & Canada, K. (2016, April, 11-15). Feature importance and predictive modeling for multi-source healthcare data with missing values (Best Paper Award). In 6th International Conference on Digital Health, Proceedings of World Wide Web Conference, Montreal, 2016 (WWW 2016).
• Wang, Y., Currim, F., & Ram, S. (2016, December). Deep Learning for Bus Passenger Demand Prediction Using Big Data. In 26th Workshop on Information Technology and Systems (WITS), Dublin, Ireland (WITS2016).
• Wang, Y., Ram, S., Currim, F. A., Dantas, E., & Sabóia, L. A. (2016, September). A Big Data Approach for Smart Transportation Management on Bus Network ( Received Overall Conference Best Paper Award). In IEEE 2nd International Smart Cities Conference.
• Ram, S., Wang, Y., Currim, F., & Currim, S. (2015, December). Using Big Data for Predicting Freshmen Retention. In Proceedings of the International Conference on Information Systems - Exploring the Information Frontier, {ICIS} 2015, Fort Worth, Texas, USA, December 13-16, 2015.
• Wang, Y., Currim, F., Ram, S., & Currim, S. (2015, December). Class Imbalance Learning and Novel Feature Extraction Methods for Predicting Freshman Retention. In 25th Workshop on Information Technology and Systems (WITS), Dallas, TX (WITS2015).
• Currim, F., & Ram, S. (2010). When entities are types: effectively modeling type-instantiation relationships. In Third International Workshop on Active Conceptual Modeling of Learning, 138-147.
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  Type-instantiation relationships (TIRs) appear in many application domains including RFID-based inventory tracking, securities markets, health care, incident-response management, travel, advertising, and academia. For example an emergency response (type) is instantiated in the actual incident, or an advertisement (type) serves impressions on a website. This kind of relationship has received little attention in literature notwithstanding its ubiquity. Conventional modeling does not properly capture its underlying semantics. This can lead to data redundancy, denormalized relations and loss of knowledge about constraints during implementation. Our work formally defines and discusses the semantics of the type-instantiation relationship. We also present an analysis of how TIRs affect other relationships in a conceptual database schema, and the relational implications of our approach.
• Currim, S., Zhang, L., & Currim, F. (2010, Fall). Exploratory Competitive Intelligence through Task Complexity Analysis. In Fifth annual conference of Midwest Association for Information Systems (MWAIS).
• Currim, F., Jung, E., Xiao, X., & Jo, I. (2009). Privacy policy enforcement for health information data access. In Proceedings of the 1st ACM international workshop on Medical-grade wireless networks, 39--44.
• Currim, F., & Jung, E. (2008, Fall). Facilitating Seamless Data Movement with Appropriate Controls. In DIMACS/DyDAn Workshop on Internet Privacy.
• Currim, F., & Ram, S. (2008, Spring). RFID Tagging at the Aggregate level: Implications for Using Groupings. In SIGSAND 2008.
• Currim, S., & Currim, F. (2008, Spring). Database systems: Understanding the Effect of Organizational Knowledge Creation on Data Quality. In SIGSAND 2008.
• Hylock, R., Street, W. N., Lu, D., & Currim, F. (2008, Fall). NursingCareWare: warehousing for nursing care research and knowledge discovery. In Third INFORMS Workshop on Data Mining and Health Informatics, Washington, DC.
• Xiao, X., Jung, E., & Currim, F. (2008, Fall). Quips, MD: Query Information Privacy and Security, for Medical Data. In Workshop on Information Technology and Systems.
• Currim, F., & Ram, S. (2007, Fall). RFID Data: A case of and for types and instances. In Workshop on Information Technology and Systems.
• Currim, F., & Ram, S. (2006, Fall). Understanding the Concept of'Completeness' in Frameworks for Modeling Cardinality Constraints. In 16th Annual Workshop on Information Technolgies and Systems (WITS) Paper.
• Dyreson, C., Snodgrass, R. T., Currim, F., & Currim, S. (2006, Fall). Schema-mediated exchange of temporal XML data. In Conceptual Modeling-ER 2006, 212--227.
• 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.
• Currim, F., Currim, S., Dyreson, C., & Snodgrass, R. T. (2004, Spring). A Tale of Two Schemas: Creating a Temporal XML Schema from a Snapshot Schema with t-XSchema. In International Conference on Extending Database Technology, 348--365.
• Currim, F., Currim, S., Dyreson, C., & Snodgrass, R. T. (2004, Spring). A tale of two schemas: Creating a temporal XML schema from a snapshot schema with τXSchema. In Advances in Database Technology-EDBT 2004, 348--365.

Others

• Currim, F., Currim, S., Dyreson, C. E., Joshi, S., Snodgrass, R. T., Thomas, S. W., & Roeder, E. (2009, Fall). τXSchema: Support for data-and schema-versioned XML documents. http://timecenter.cs.aau.dk/TimeCenterPublications/TR-91.pdf
• Currim, F. A. (2004, Fall). Spatio-temporal set-based constraints in conceptual modeling: A theoretical framework and evaluation. Doctoral Dissertation.