Contextualizing heterogeneous data for integration and inference.

Zachary Pincus, Mark A. Musen

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Systems that attempt to integrate and analyze data from multiple data sources are greatly aided by the addition of specific semantic and metadata "context" that explicitly describes what a data value means. In this paper, we describe a systematic approach to constructing models of data and their context. Our approach provides a generic "template" for constructing such models. For each data source, a developer creates a customized model by filling in the tem-plate with predefined attributes and value. This approach facilitates model construction and provides consistent syntax and semantics among models created with the template. Systems that can process the template structure and attribute values can reason about any model so described. We used the template to create a detailed knowledge base for syndromic surveillance data integration and analysis. The knowledge base provided support for data integration, translation, and analysis methods.

Original languageEnglish
Pages (from-to)514-518
Number of pages5
JournalAMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
StatePublished - 2003

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