Addressing the Challenges of Aggregational and Temporal Ontological Heterogeneity
Author(s)
Zhu, Hongwei
Madnick, Stuart E.
Date Issued
January 2006
Series/Report no.
Computer Science (CS)
Abstract
In this paper, we first identify semantic heterogeneities that, when not resolved, often cause serious data quality problems. We discuss the especially challenging problems of temporal and aggregational ontological heterogeneity, which concerns how complex entities and their relationships are aggregated and reinterpreted over time. Then we illustrate how the COntext INterchange (COIN) technology can be used to capture data semantics and reconcile semantic heterogeneities in a scalable manner, thereby improving data quality.
Subjects
Data Semantics
Semantic Heterogeneity
Aggregation
Temporal
Ontology
Context
Persistent DSpace Link
