The ProtégéLOV Plugin: Ontology Access and Reuse for Everyone

Garcia-Santa, Nuria; Atemezing, Ghislain Auguste; Villazón-Terrazas, Boris

doi:10.1007/978-3-319-25639-9_8

Cited by 8 publications

(5 citation statements)

References 6 publications

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“…In the Linked Open Dataspace, newer, collaborative efforts, such as Bio2RDF (Callahan et al , 2013), provide strict guidelines for the representation of concept identifiers while publishing data as RDF. ProtégéLov (Garcia-Santa et al , 2015) allows reuse of terms directly from the Linked Open Vocabularies repository using owl:equivalentClass and rdf:subClassOf axioms.…”

Section: Discussionmentioning

confidence: 99%

A systematic analysis of term reuse and term overlap across biomedical ontologies

Kamdar

Tudorache

Musen

2017

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Reusing ontologies and their terms is a principle and best practice that most ontology development methodologies strongly encourage. Reuse comes with the promise to support the semantic interoperability and to reduce engineering costs. In this paper, we present a descriptive study of the current extent of term reuse and overlap among biomedical ontologies. We use the corpus of biomedical ontologies stored in the BioPortal repository, and analyze different types of reuse and overlap constructs. While we find an approximate term overlap between 25-31%, the term reuse is only <9%, with most ontologies reusing fewer than 5% of their terms from a small set of popular ontologies. Clustering analysis shows that the terms reused by a common set of ontologies have >90% semantic similarity, hinting that ontology developers tend to reuse terms that are sibling or parent-child nodes. We validate this finding by analysing the logs generated from a Protégé plugin that enables developers to reuse terms from BioPortal. We find most reuse constructs were 2-level subtrees on the higher levels of the class hierarchy. We developed a Web application that visualizes reuse dependencies and overlap among ontologies, and that proposes similar terms from BioPortal for a term of interest. We also identified a set of error patterns that indicate that ontology developers did intend to reuse terms from other ontologies, but that they were using different and sometimes incorrect representations. Our results stipulate the need for semi-automated tools that augment term reuse in the ontology engineering process through personalized recommendations. KeywordsDescriptive Study; Ontologies; Biomedical Domain; Term Reuse; Term Overlap; Composite Mappings; Visualization Reuse in biomedical ontologiesThe biomedical research community has been one of the earliest adopters of ontologies to tackle the challenges of efficient knowledge organization, optimized information retrieval and effective annotation of datasets. Researchers have used ontologies for various purposes such as knowledge management, semantic search, data annotation, data integration, Author Manuscript Author ManuscriptAuthor ManuscriptAuthor Manuscript exchange, decision support and reasoning [1,2]. For example, i) the National Cancer Institute Thesaurus (NCIT) has been used as a reference terminology for cancer data [3], ii) the Gene Ontology (GO) has been ubiquitously used for enrichment analysis on gene sets obtained from microarray experiments [4], and iii) the Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) has been used for the electronic exchange of clinical health information [5].Over the years, ontology development has become a reuse-centric process [6,7]. All methodologies strongly encourage reuse while building new ontologies, be it at the level of an ontology, or at the level of individual terms [8,9]. In the literature, we may find two areas that benefit from reuse: i) ontology engineering, in which experts can reuse already existing ontology struct...

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Section: Discussionmentioning

confidence: 99%

A systematic analysis of term reuse and term overlap across biomedical ontologies

Kamdar

Tudorache

Musen

2017

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“…Reuse support [5] is also systematically sought by the maintainers of LOV [25], primarily at keyword relevance level; we are in contact with them and will seek to integrate our complementary approaches.…”

Section: Ontology Reuse Metrics and Methodsmentioning

confidence: 99%

Focused categorization power of ontologies: General framework and study on simple existential concept expressions

Svátek

Zamazal

Nguyen

et al. 2023

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When reusing existing ontologies for publishing a dataset in RDF (or developing a new ontology), preference may be given to those providing extensive subcategorization for important classes (denoted as focus classes). The subcategories may consist not only of named classes but also of compound class expressions. We define the notion of focused categorization power of a given ontology, with respect to a focus class and a concept expression language, as the (estimated) weighted count of the categories that can be built from the ontology’s signature, conform to the language, and are subsumed by the focus class. For the sake of tractable initial experiments we then formulate a restricted concept expression language based on existential restrictions, and heuristically map it to syntactic patterns over ontology axioms (so-called FCE patterns). The characteristics of the chosen concept expression language and associated FCE patterns are investigated using three different empirical sources derived from ontology collections: first, the concept expression pattern frequency in class definitions; second, the occurrence of FCE patterns in the Tbox of ontologies; and last, for class expressions generated from the Tbox of ontologies (through the FCE patterns); their ‘meaningfulness’ was assessed by different groups of users, yielding a ‘quality ordering’ of the concept expression patterns. The complementary analyses are then compared and summarized. To allow for further experimentation, a web-based prototype was also implemented, which covers the whole process of ontology reuse from keyword-based ontology search through the FCP computation to the selection of ontologies and their enrichment with new concepts built from compound expressions.

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“…This limitation could be overcome by improving ontology editors to encourage people to add labels and comments, an important feature for ontology matching tools. Recently, a beta version of ProtegeLOV 31 [47] has been released. It is an extension of a popular ontology editor which suggests preferred ontologies referenced in the LOV catalog when you are designing a new concept or a new property.…”

Section: B Use Case: Methodology Applied To Lov4iotmentioning

confidence: 99%

Building IoT-Based Applications for Smart Cities: How Can Ontology Catalogs Help?

Gyrard

Zimmermann

Sheth

2018

IEEE Internet Things J.

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The Internet of Things (IoT) plays an ever-increasing role in enabling Smart City applications. An ontology-based semantic approach can help improve interoperability between a variety of IoT-generated as well as complementary data needed to drive these applications. While multiple ontology catalogs exist, using them for IoT and smart city applications require significant amount of work. In this paper, we demonstrate how can ontology catalogs be more effectively used to design and develop smart city applications? We consider four ontology catalogs that are relevant for IoT and smart cities: READY4SmartCities, LOV, OpenSensingCity (OSC) and, LOV4IoT. To support semantic interoperability with the reuse of ontology-based smart city applications, we present a methodology to enrich ontology catalogs with those ontologies. Our methodology is generic enough to be applied to any other domains as is demonstrated by its adoption by OSC and LOV4IoT ontology catalogs. Researchers and developers have completed a survey based evaluation of the LOV4IoT catalog. The usefulness of ontology catalogs ascertained through this evaluation has encouraged their ongoing growth and maintenance. The quality of IoT and smart city ontologies have been evaluated to improve the ontology catalog quality. We also share the lessons learned regarding ontology best practices and provide suggestions for ontology improvements with a set of software tools.

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The ProtégéLOV Plugin: Ontology Access and Reuse for Everyone

Cited by 8 publications

References 6 publications

A systematic analysis of term reuse and term overlap across biomedical ontologies

A systematic analysis of term reuse and term overlap across biomedical ontologies

Focused categorization power of ontologies: General framework and study on simple existential concept expressions

Building IoT-Based Applications for Smart Cities: How Can Ontology Catalogs Help?

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