Improving the Domain Independence of Data Provenance Ontologies: A Demonstration Using Conceptual Graphs and the W7 Model

View Sample PDF

Author(s): Jun Liu (College of Business and Information Systems, Dakota State University, Madison, SD, USA)and Sudha Ram (Eller College of Management, University of Arizona, Tucson, AZ, USA)
Copyright: 2017
Volume: 28
Issue: 1
Pages: 20
Source title: Journal of Database Management (JDM)
Editor(s)-in-Chief: Keng Siau (City University of Hong Kong, Hong Kong SAR)
DOI: 10.4018/JDM.2017010104

Keywords: Data Mining and Databases / Databases / Information Science Reference / Library & Information Science

Purchase

View Improving the Domain Independence of Data Provenance Ontologies: A Demonstration Using Conceptual Graphs and the W7 Model on the publisher's website for pricing and purchasing information.

Abstract

Provenance is becoming increasingly important as more and more people are using data that they themselves did not generate. In the last decade, significant efforts have been directed toward developing generic, shared data provenance ontologies that support the interoperability of provenance across systems. An issue that is impeding the use of such provenance ontologies is that a generic provenance ontology, no matter how complete it is, is insufficient for capturing the diverse, complex provenance requirements in different domains. In this paper, the authors propose a novel approach to adapting and extending the W7 model, a well-known generic ontology of data provenance. Relying on various knowledge expansion mechanisms provided by the Conceptual Graph formalism, the authors' approach enables us to develop domain ontologies of provenance in a disciplined yet flexible way.

The IRMA Community

Research IRM

Improving the Domain Independence of Data Provenance Ontologies: A Demonstration Using Conceptual Graphs and the W7 Model

Purchase

Abstract

Related Content

IRMA Sponsors