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Journal Articles ACM Computing Surveys Year : 2019

Linked vocabulary recommendation tools for Internet of Things

Abstract

The Semantic Web emerged with the vision of eased integration of heterogeneous, distributed data on the Web. The approach fundamentally relies on the linkage between and reuse of previously published vocabularies to facilitate semantic interoperability. In recent years, the Semantic Web has been perceived as a potential enabling technology to overcome interoperability issues in the Internet of Things (IoT), especially for service discovery and composition. Despite the importance of making vocabulary terms discoverable and selecting the most suitable ones in forthcoming IoT applications, no state-of-the-art survey of tools achieving such recommendation tasks exists to date. This survey covers this gap by specifying an extensive evaluation framework and assessing linked vocabulary recommendation tools. Furthermore, we discuss challenges and opportunities of vocabulary recommendation and related tools in the context of emerging IoT ecosystems. Overall, 40 recommendation tools for linked vocabularies were evaluated, both empirically and experimentally. Some of the key findings include that (i) many tools neglect to thoroughly address both the curation of a vocabulary collection and effective selection mechanisms, (ii) modern information retrieval techniques are underrepresented, and (iii) the reviewed tools that emerged from Semantic Web use cases are not yet sufficiently extended to fit today’s IoT projects.
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Dates and versions

hal-02873991 , version 1 (18-06-2020)

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Niklas Kolbe, Sylvain Kubler, Jérémy Robert, Yves Le Traon, Arkady Zaslavsky. Linked vocabulary recommendation tools for Internet of Things. ACM Computing Surveys, 2019, 51 (6), pp.127. ⟨10.1145/3284316⟩. ⟨hal-02873991⟩
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