Web Data Quality: Current State and New Challenges

Web Data Quality: Current State and New Challenges

Amrapali Zaveri (Institüt für Informatik, Universität Leipzig, Leipzig, Germany), Andrea Maurino (Department of Computer Science, University of Milano Bicocca, Milano, Italy) and Laure-Berti Equille (Qatar Computing Research Institute, Doha, Qatar)
Copyright: © 2014 |Pages: 6
DOI: 10.4018/ijswis.2014040101
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Abstract

The standardization and adoption of Semantic Web technologies has resulted in an unprecedented volume of data being published as Linked Data (LD). However, the “publish first, refine later” philosophy leads to various quality problems arising in the underlying data such as incompleteness, inconsistency and semantic ambiguities. In this article, we describe the current state of Data Quality in the Web of Data along with details of the three papers accepted for the International Journal on Semantic Web and Information Systems' (IJSWIS) Special Issue on Web Data Quality. Additionally, we identify new challenges that are specific to the Web of Data and provide insights into the current progress and future directions for each of those challenges.
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Summary Of Accepted Papers

The special issue received 24 papers that were reviewed by at least three anonymous and independent reviewers. After the first round of reviews, only five papers were invited to submit an improved version for further evaluation and, of those, only three papers (about 8% of the total number of submitted papers) were finally published.

The first article “OOPS! (Ontology Pitfall Scanner!): An On-line Tool for Ontology Evaluation” by María Poveda-Villalón, Asunción Gómez-Pérez and Mari Carmen Suárez-Figueroa from the Universidad Politecnica de Madrid in Spain, introduces the quality issues in the modeling phase of ontologies which represents an important component in the Web of Data since a large volume of data, annotated by means of ontologies, is shared on the Web.

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