Uncertainty modeling process for semantic technology

Rommel N Carvalho; Kathryn B Laskey; Paulo C. G. Da Costa

doi:10.7287/peerj.preprints.2045v1

Uncertainty modeling process for semantic technology

Rommel N Carvalho^1,2, Kathryn B Laskey ³, Paulo C. G. Da Costa³

1 Department of Research and Strategic Information, Office of the Comptroller General, Brazil's Office of the Comptroller General, Brasilia, DF, Brazil

2 Department of Computer Science, Universidade de Brasília, Brasília, DF, Brazil

3 Department of Systems Engineering and Operations Research, George Mason University, Fairfax, VA, United States

DOI: 10.7287/peerj.preprints.2045v1

Published: 2016-05-16
Accepted: 2016-05-16

Subject Areas: Artificial Intelligence, World Wide Web and Web Science, Software Engineering
Keywords: PR-OWL, MEBN, UP, methodology, UMP-ST, semantic web, Bayesian networks, uncertainty, modeling, semantic technology

Copyright: © 2016 Carvalho et al.
Licence: This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.

Cite this article: Carvalho RN, Laskey KB, Costa PCGD. 2016. Uncertainty modeling process for semantic technology. PeerJ Preprints 4:e2045v1 https://doi.org/10.7287/peerj.preprints.2045v1

Abstract

The ubiquity of uncertainty across application domains generates a need for principled support for uncertainty management in semantically aware systems. A probabilistic ontology provides constructs for representing uncertainty in domain ontologies. While the literature has been growing on formalisms for representing uncertainty in ontologies, there remains little guidance in the knowledge engineering literature for how to design probabilistic ontologies. To address the gap, this paper presents the Uncertainty Modeling Process for Semantic Technology (UMP-ST), a new methodology for modeling probabilistic ontologies. To explain how the methodology works and to verify that it can be applied to different scenarios, this paper describes step-by-step the construction of a proof-of-concept probabilistic ontology. The resulting domain model is intended to support identification of fraud in public procurements in Brazil. While the case study illustrates the development of a probabilistic ontology in the PR-OWL probabilistic ontology language, the methodology is applicable to any ontology formalism that properly integrates uncertainty with domain semantics.