The Role of Ontology Engineering in Linked Data Publishing and Management: An Empirical Study

The Role of Ontology Engineering in Linked Data Publishing and Management: An Empirical Study

Markus Luczak-Rösch (University of Southampton, Southampton, UK), Elena Simperl (University of Southampton, Southampton, UK), Steffen Stadtmüller (Karlsruhe Institute of Technology, Karlsruhe, Germany) and Tobias Käfer (Karlsruhe Institute of Technology, Karlsruhe, Germany)
Copyright: © 2014 |Pages: 18
DOI: 10.4018/IJSWIS.2014070103

Abstract

In this article the authors evaluate the adoption and applicability of established ontology engineering results by the Linked Data providers' community. The evaluation relies on a combination of qualitative and quantitative methods; in particular, the authors conducted an analytical survey containing structured interviews with data publishers in order to give an account of the current ontology engineering practice in Linked Data provisioning, and compared and expanded our findings with statistics on ontology development and usage provided by the Billion Triple Challenges datasets from 2012 (using the vocab.cc platform) and from 2014 and other related tools. The findings of the evaluation allow data practitioners and ontologists to yield a better understanding of the conceptual part of the LOD Cloud; and form the basis for the definition of purposeful, empirically grounded guidelines and best practices for developing, managing and using ontologies in the new application scenarios that arise in the context of Linked Data.
Article Preview

Introduction

In the last years we have seen a continuous uptake of semantic technologies - most recently on the open Web, driven by the Linked Data movement, but in equal measure also in enterprise environments. The key distinct feature of semantic computing compared to other information management technologies is their use of Web standards - languages for knowledge representation, as well as protocols for exposing, accessing and exchanging this knowledge - to structure and formalize information in a way that enables computers to 'understand' complex concepts and situations in a similar way as humans do. Ontologies, defined as reusable models capturing the knowledge in a given domain, are one of the core building blocks of the semantic-technologies stack. In combination with components for semantic data management, reasoning, search, as well as annotation and description of digital artifacts, they can facilitate the development of sophisticated - and economically feasible - solutions to many prevailing problems in today's information management.

Complete Article List

Search this Journal:
Reset
Open Access Articles
Volume 15: 4 Issues (2019): Forthcoming, Available for Pre-Order
Volume 14: 4 Issues (2018)
Volume 13: 4 Issues (2017)
Volume 12: 4 Issues (2016)
Volume 11: 4 Issues (2015)
Volume 10: 4 Issues (2014)
Volume 9: 4 Issues (2013)
Volume 8: 4 Issues (2012)
Volume 7: 4 Issues (2011)
Volume 6: 4 Issues (2010)
Volume 5: 4 Issues (2009)
Volume 4: 4 Issues (2008)
Volume 3: 4 Issues (2007)
Volume 2: 4 Issues (2006)
Volume 1: 4 Issues (2005)
View Complete Journal Contents Listing