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Instance Data Evaluation on the Semantic Web

Explore cutting-edge methods for evaluating semantic data on the web. This study delves into assessing the conformity of ontologies and instance data, uncovering logical inconsistencies, and detecting integrity issues. Gain insights into Semantic Web evaluation challenges and solutions.

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Instance Data Evaluation on the Semantic Web

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  1. Instance Data Evaluation on the Semantic Web Jiao Tao, Li Ding, Deborah L. McGuinness Tetherless World Constellation Rensselaer Polytechnic Institute Troy, NY, USA

  2. Data Evaluation on the SW: State of the Art • On the semantic web, instance data often accounts for orders of magnitude more data than ontology (Ding & Finin 2006). • However most data evaluation work (Rocha et al. 1998) focuses on ontology evaluation, i.e., checking whether the ontologies correctly describe the domain of interests. • There is very little, if any, work on evaluating the conformance between ontologies and instance data.

  3. Instance Data Evaluation on the Semantic Web Does D follow the semantic expectations in O ? 1. Create domain knowledge as ontologies O (semantic expectations) D O No syntax errors? Web 4. Publish D 3. Instantiate ontologies as instance data D O 2. Acquire ontologies Semantic expectation mismatches: (i) Logical inconsistencies (ii) Integrity issues

  4. Generic Evaluation Process (GEP) • Load instance data D • Is loading failing? • Parse instance data D • Is D syntactically correct? • Load referenced ontologies O = {O1,O2, …} • Is Oi reachable? where Oi defines the terms used by D. • Inspect logical inconsistencies in D • Is Oi logically consistent? • Merge all consistent referenced ontologies into O' • Are D+O’ logically consistent? • Inspect integrity issues in D • Compute DC = INF(D,O') which includes all triples in D and O', and all inferred sub-class/sub-property relations • Is there any integrity issue in D?

  5. IntegrityIssues • Unexpected Individual Type (UIT) Issue • rdfs:domain • rdfs:range • owl:allValuesFrom • Redundant Individual Type (RIT) Issue • Non-specific Individual Type (NSIT) Issue • Missing Property Value (MPV) Issue • owl:cardinality • owl:minCardinality • Excessive Property Value (EPV) Issue • owl:cardinality • owl:maxCardinality

  6. Example: MPV Make sure all instances of wine have a Maker

  7. SPARQL Solutions forIntegrity Issue Detection

  8. Implementation and Evaluation • Demo: TW OIE Service http://onto.rpi.edu/demo/oie/ • Comparative experiment results

  9. References • T. Berners-Lee, J. Hendler, and O. Lassila, The Semantic Web: A New Form of Web Content that Is Meaningful to Computers Will Unleash a Revolution of New Possibilities, Scientific American, pp. 34–43, 2001. • J. Davies, M. Lytras, and A. Sheth, Semantic-Web-Based Knowledge Management, IEEE Internet Computing, Vol. 11, No. 5, pp. 14-6, 2007. • L. Ding, and T. Finin, Characterizing the Semantic Web on the Web, ISWC, pp. 242-257, 2006. • R. A. Rocha, S. M. Huff, P. J. Haug, D. A. Evans, and B. E. Bray, Evaluation of a Semantic Data Model for Chest Radiology: Application of a New Methodology, Methods of Information in Medicine, Vol. 37, No.4-5, pp. 477-490, 1998. • D. L. McGuinness and P. Pinheiro da Silva. Explaining Answers from the Semantic Web: The Inference Web Approach. Journal of Web Semantics. Vol.1 No.4., pp 397-413, 2004.

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