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Linked vocabulary recommendation tools for internet of things: A survey

Version 2 2024-06-05, 01:36
Version 1 2019-03-14, 12:56
journal contribution
posted on 2024-06-05, 01:36 authored by N Kolbe, S Kubler, J Robert, Y Le Traon, Arkady ZaslavskyArkady Zaslavsky
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.

History

Journal

ACM Computing Surveys

Volume

51

Article number

ARTN 127

Location

New York, N.Y.

ISSN

0360-0300

eISSN

1557-7341

Language

English

Publication classification

C1 Refereed article in a scholarly journal

Copyright notice

2019, Association for Computing Machinery

Issue

6

Publisher

ASSOC COMPUTING MACHINERY