Extending temporal databases to deal with telic/atelic medical data

Paolo Terenziani, Richard Thomas Snodgrass, Alessio Bottrighi, Mauro Torchio, Gianpaolo Molino

Research output: Contribution to journalArticle

14 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)113-126
Number of pages14
JournalArtificial Intelligence in Medicine
Volume39
Issue number2
DOIs
Publication statusPublished - Feb 2007

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Keywords

  • Data semantics
  • Relational data model
  • Telic/atelic clinical data
  • Temporal databases
  • TSQL2-like query language

ASJC Scopus subject areas

  • Artificial Intelligence
  • Medicine(all)

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