Skip to main content
SpringerLink
Log in

An active database architecture for knowledge-based incremental abstraction of complex concepts from continuously arriving time-oriented raw data

  • Published:
Journal of Intelligent Information Systems Aims and scope Submit manuscript

Abstract

An effective solution to the tasks of continuous monitoring and aggregation querying of complex domain-meaningful concepts and patterns in environments featuring large continuously changing data sets is very important for many domains. Typical domains include: making financial decisions, integrating intelligence information from multiple sources, evaluating the effects of traffic controllers’ actions, detection of security threats in communication networks, planning and monitoring in robotics, and management of chronic patients in medical domains. In this paper, we present a general domain-independent method for an effective solution of these two tasks. Our method involves incremental creation of meaningful, interval-based abstractions, from raw, time-stamped data continuously arriving from multiple sources, which is supported by the accumulation and continuous validation of the created abstractions. We implemented our method in the Momentum system, which is an active knowledge-based time-oriented database—a temporal extension of the active-database concept that we propose for incremental application of knowledge to continuously arriving time-oriented data. We evaluated the Momentum system in a medical domain within a database of 1,000 patients monitored after bone-marrow transplantation, and a knowledge base of complex abstractions regarding more than 100 raw-data types and about 400 concept types derivable from them. Initial evaluations are highly encouraging with regards to the feasibility of the whole approach.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • ACT-NET (1996). The active database management system manifesto: A rulebase of ADBMS features. ACM SIGMOD Record, 25(3), 20–49 September.

    Google Scholar 

  • Beck (1999). Extreme programming explained: Embrace change (1st ed.). Addison-Wesley Pub. Co.

  • Boaz, D., Balaban, M., & Shahar, Y. (2003). A temporal-abstraction rule language for medical databases. Proceeding of the workshop on Intelligent Data Analysis in Medicine and Pharmacology (IDAMAP), Protaras, Cyprus.

  • Boaz, D., & Shahar, Y. (2005). A distributed temporal-abstraction mediation architecture for medical databases. Artificial Intelligence in Medicine, 34(1), 3–24.

    Article  Google Scholar 

  • Chakravarty, S., & Shahar, Y. (2000). CAPSUL: A constraint-based specification of repeating patterns in time-oriented data. Annals of Mathematics and Artificial Intelligence (AMAI), 30, 3–22.

    Article  MATH  Google Scholar 

  • Forgy, C. L. (1982). RETE: A fast algorithm for the many pattern/many object pattern match problem. Artificial Intelligence, 1982, 17–37.

    Article  Google Scholar 

  • Freeman, Hupfer, & Arnold (1999). JavaSpaces(TM) principles, patterns, and practice (1st ed.). Addison-Wesley Pub. Co.

  • Hightower, & Lesiecki (2001). Java tools for extreme programming: Mastering open source tools including ant, JUnit, and cactus (1st ed.). Wiley.

  • Kimball, R., & Ross, M. (2002). The data warehouse toolkit: The complete guide to dimensional modeling (2nd edn.). Wiley.

  • Nguyen, J. H., Shahar, Y., Tu, S. W., Das, A., & Musen, M. A. (1999). Integration of temporal reasoning and temporal-data maintenance into a reusable database mediator to answer abstract, time-oriented queries: The Tzolkin system. Journal of Intelligent Information Systems, 13(1/2), 121–145.

    Article  Google Scholar 

  • O’Connor, M. J., Grosso, W. E., Tu, S. W., & Musen, M. A. (2001). RASTA: A distributed temporal abstraction system to facilitate knowledge-driven monitoring of clinical databases. Proceedings of MEDINFO-2001, the Tenth World Congress on Medical Informatics (pp. 508–512). London, UK.

  • O’Connor, M. J., Tu, S. W., & Musen, M. A. (2002). The Chronus II temporal database mediator. Proceedings of the American Medical Informatics Association (AMIA) 2002 Annual Fall Symposium. San Antonio, Texas.

  • Paton, N. (Ed.) (1999). Active rules in database systems. Springer.

  • Shahar, Y. (1997). A framework for knowledge-based temporal abstraction. Artificial Intelligence, 90(1–2), 79–133.

    Article  MATH  Google Scholar 

  • Shahar, Y. (1998). Dynamic temporal interpretation contexts for temporal abstraction. Annals of Mathematics and Artificial Intelligence, 22(1–2), 159–192.

    Article  MATH  Google Scholar 

  • Shahar, Y., Chen, H., Stites, D. P., Basso, L. V., Kaizer, H., Wilson, D. M., et al. (1999). Semiautomated acquisition of clinical temporal-abstraction knowledge. Journal of the American Medical Informatics Association (JAMIA), 6, 494–511.

    Google Scholar 

  • Shahar, Y., Goren-Bar, D., Boaz, D., & Tahan, G. (2006). Distributed, intelligent, interactive visualization and exploration of time-oriented clinical data. Artificial Intelligence in Medicine 38(2), 115–135.

    Google Scholar 

  • Shahar, Y., & Molina, M. (1998). Knowledge-based spatiotemporal linear abstraction. Pattern Analysis and Applications, 1(2), 91–104.

    Article  MATH  Google Scholar 

  • Shahar, Y., & Musen, M. A. (1996). Knowledge-based temporal abstraction in clinical domains. Artificial Intelligence in Medicine, 8, 267–298.

    Article  Google Scholar 

  • Spokoiny, A., & Shahar, Y. (2003). Momentum—An active time-oriented database for intelligent abstraction, exploration and analysis of clinical data. Proceeding of the workshop on Intelligent Data Analysis in Medicine and Pharmacology—IDAMAP 2003, at 9th Conference on Artificial Intelligence in Medicine Europe—Europe (AIME) ‘03. Protaras, Cyprus.

  • Spokoiny, A., & Shahar, Y. (2004). A time-oriented active database approach for intelligent abstraction, monitoring and querying of clinical data from multiple sources. Proceedings of the 11th World Congress on Medical Informatics—MEDINFO-04. San Francisco, California, USA.

  • Spokoiny, A., & Shahar, Y. (in press). Incremental application of knowledge to continuously arriving time-oriented data. Journal of Intelligent Information Systems.

  • van Beek, P. (1991). Temporal query processing with indefinite information. Artificial Intelligence in Medicine, 3, 325–339.

    Article  Google Scholar 

  • Widom, J., & Ceri, S. (1996). Active database systems: Triggers and rules for advanced database processing. San Mateo, California: Morgan Kaufmann.

    Google Scholar 

  • Wiederhold, G. (1992). Mediators in the architecture of future information systems. IEEE Computer, 25, 38–50.

    Google Scholar 

  • Wiederhold, G., & Genesereth, M. (1997). The conceptual basis of mediation services. IEEE Expert, 12(5), 38–47.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Medical Informatics Research Center, Department of Information Systems Engineering, Ben-Gurion University, Beer Sheva, Israel

    Alex Spokoiny & Yuval Shahar

Authors
  1. Alex Spokoiny
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yuval Shahar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alex Spokoiny.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Spokoiny, A., Shahar, Y. An active database architecture for knowledge-based incremental abstraction of complex concepts from continuously arriving time-oriented raw data. J Intell Inf Syst 28, 199–231 (2007). https://doi.org/10.1007/s10844-006-0008-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10844-006-0008-x

Keywords

Search

Navigation