Paper Info
Title
Ontology and database schema: What's the difference?
Abstract
This paper analyzes the similarities and differences between an ontology (focused on meaning), and a database schema (focused on data). We address questions about purpose, representation, creation, usage and semantics of each. We distill out twenty-five features that characterize these two representational artifacts, the majority of which are relevant to both. Each has a strong semantic heritage using formal logic to build conceptual models of some subject matter. And while there are differences in 90% of the features, the differences are mostly historical, not technical. We identify pros and cons for each, and notice that there is usually no free lunch. The disadvantage that you think you are getting rid of may show up elsewhere in a different and unexpected way. We close by considering how ontology contributes to enterprise data integration. The emergence of using URIs as global identifiers (e.g. in OWL) dramatically enhances data integration as well as schema reuse and sharing. The primary focus on meaning helps ontology break through a lot of unnecessary complexity that exists in large traditional databases and greatly simplifies the process of integration. Ontology is providing a glimmer of light at the end of the tunnel for enterprise-wide data integration.
Year
DOI
Venue
2015
10.3233/AO-150158
APPLIED ONTOLOGY
Keywords
DocType
Volume
Ontology,schema,database schema,conceptual model,logical schema,physical schema,triple store,relational database,data integration
Journal
10
Issue
ISSN
Citations 
3-4
1570-5838
1
PageRank 
References 
Authors
0.35
7
1
Name
Order
Citations
PageRank
Michael Uschold142950.37