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.

Popularity-Driven Ontology Ranking Using Qualitative Features

“…Well known approaches include PageRank [22]; ontology-specific approaches consider qualitative metrics such as ontologies' popularity, availability, interlinkage to other ontologies, etc. [15]. Some ontology ranking models have been studied in [7].…”

“…Ontology ranking models have been integrated in tools that help users to find and select relevant ontologies according to their need, such as the previously mentioned LOV platform [32], TermPicker [28], and vocab.cc [30]. Such tools have been previously surveyed in the literature, as in [15]. Ontology reuse has been studied from more holistic viewpoints, such as methodological guidelines [11] and choosing ontologies from a set of candidates [14].…”

“…This section presents the selected ranking features that are considered to constitute our proposed model as well as our approach to derive relevance labels for ontologies of WoT application domains. The selection of ranking features is based on comprehensive studies in the literature on ontology ranking and quality [15,34]. We include all attributes identified in survey [15] except for subjective features and those that only concern term ranking, not ontology ranking.…”

“…The importance of ontology reuse is also increasing in Internet of Things (IoT) environments, in which the adoption of Semantic Web technologies has received great interest [2,4]. Emerging open innovation IoT ecosystems [15] aim for the seamless discovery, access and integration of heterogeneous, sensor-originated data through the Web, also referred to as the Web of Things (WoT). Efficient ontology reuse for the semantic annotation of data streams based on existing ontologies is thus a prerequisite to overcome this semantic interoperability challenge in the WoT [15].…”

“…Emerging open innovation IoT ecosystems [15] aim for the seamless discovery, access and integration of heterogeneous, sensor-originated data through the Web, also referred to as the Web of Things (WoT). Efficient ontology reuse for the semantic annotation of data streams based on existing ontologies is thus a prerequisite to overcome this semantic interoperability challenge in the WoT [15]. Moreover, it enables reasoning over data and establishing linkage to existing knowledge on the Web.…”