OntoCheck: verifying ontology naming conventions and metadata completeness in Protégé 4

Abstract

BackgroundAlthough policy providers have outlined minimal metadata guidelines and naming conventions, ontologies of today still display inter- and intra-ontology heterogeneities in class labelling schemes and metadata completeness. This fact is at least partially due to missing or inappropriate tools. Software support can ease this situation and contribute to overall ontology consistency and quality by helping to enforce such conventions.ObjectiveWe provide a plugin for the Protégé Ontology editor to allow for easy checks on compliance towards ontology naming conventions and metadata completeness, as well as curation in case of found violations.ImplementationIn a requirement analysis, derived from a prior standardization approach carried out within the OBO Foundry, we investigate the needed capabilities for software tools to check, curate and maintain class naming conventions. A Protégé tab plugin was implemented accordingly using the Protégé 4.1 libraries. The plugin was tested on six different ontologies. Based on these test results, the plugin could be refined, also by the integration of new functionalities.ResultsThe new Protégé plugin, OntoCheck, allows for ontology tests to be carried out on OWL ontologies. In particular the OntoCheck plugin helps to clean up an ontology with regard to lexical heterogeneity, i.e. enforcing naming conventions and metadata completeness, meeting most of the requirements outlined for such a tool. Found test violations can be corrected to foster consistency in entity naming and meta-annotation within an artefact. Once specified, check constraints like name patterns can be stored and exchanged for later re-use. Here we describe a first version of the software, illustrate its capabilities and use within running ontology development efforts and briefly outline improvements resulting from its application. Further, we discuss OntoChecks capabilities in the context of related tools and highlight potential future expansions.ConclusionsThe OntoCheck plugin facilitates labelling error detection and curation, contributing to lexical quality assurance in OWL ontologies. Ultimately, we hope this Protégé extension will ease ontology alignments as well as lexical post-processing of annotated data and hence can increase overall secondary data usage by humans and computers.

Automated UMLS-Based Comparison of Medical Forms

“…Other studies focus on ontology editors [27] or ontology development in general [28] rather than comparing documentation forms. There are some publications regarding document clustering [29], [30], but these focus on clustering data, not metadata (data elements).…”

Formal Ontologies in Biomedical Knowledge Representation

“…The OWL API is a JAVA programming interface for manipulating OWL ontologies [48]. By now, a wide variety of tools and web infrastructure for ontology construction has been developed; including OntoFox [49], a tool for importing classes from existing ontologies and evaluation tools like the Ontology Pitfall Scanner OoOPS [50]; and OntoCheck, a tool for checking class labels for compliance with naming conventions [51].…”

ONTO-Analyst: um método extensível para a identificação e visualização de anomalias em ontologias

“…OntoCheck é um plug-in para o editor de ontologias Protégé que ajuda a limpar ontologias em relação às suas heterogeneidades lexicais. Isto é feito através da aplicação de convenções de nomenclaturas e integridade nos metadados (SCHOBER et al, 2012).…”

“…O limite desse trabalho, como todos os demais, é a impossibilidade de estender as identificações usando uma linguagem amplamente utilizada na comunidade da Web Semântica (como OWL, SPARQL ou SWRL). Outro ponto importante dessa comparação é que nenhum dos trabalhos relacionados possui visualização gráfica das anomalias encontras.Por último, quanto à limitação 6, os trabalhos relacionados de Poveda-Villalón (2016), Grimm e Wissmann (2011) eSchober et al (2012) são os únicos que possuem, parcialmente, verificações controladas em conjuntos representativos de ontologias. Em Poveda-Villalón (2016), os experimentos em ontologias foram realizados por usuários que submeteram ontologias para o sistema, não garantindo a replicabilidade dos resultados.…”

“…Em Poveda-Villalón (2016), os experimentos em ontologias foram realizados por usuários que submeteram ontologias para o sistema, não garantindo a replicabilidade dos resultados. EmSchober et al (2012) e Grimm e Wissmann (2011), apesar dos experimentos serem controlados e replicáveis, foram realizados, respectivamente, em apenas 6 e 12 ontologias escolhidas pelos autores dos trabalhos.…”