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J Biomed Semantics ; 12(1): 15, 2021 08 09.
Artigo em Inglês | MEDLINE | ID: mdl-34372934


BACKGROUND: The ontology authoring step in ontology development involves having to make choices about what subject domain knowledge to include. This may concern sorting out ontological differences and making choices between conflicting axioms due to limitations in the logic or the subject domain semantics. Examples are dealing with different foundational ontologies in ontology alignment and OWL 2 DL's transitive object property versus a qualified cardinality constraint. Such conflicts have to be resolved somehow. However, only isolated and fragmented guidance for doing so is available, which therefore results in ad hoc decision-making that may not be the best choice or forgotten about later. RESULTS: This work aims to address this by taking steps towards a framework to deal with the various types of modeling conflicts through meaning negotiation and conflict resolution in a systematic way. It proposes an initial library of common conflicts, a conflict set, typical steps toward resolution, and the software availability and requirements needed for it. The approach was evaluated with an actual case of domain knowledge usage in the context of epizootic disease outbreak, being avian influenza, and running examples with COVID-19 ontologies. CONCLUSIONS: The evaluation demonstrated the potential and feasibility of a conflict resolution framework for ontologies.

Ontologias Biológicas/estatística & dados numéricos , Biologia Computacional/estatística & dados numéricos , Armazenamento e Recuperação da Informação/estatística & dados numéricos , Web Semântica , Semântica , Vocabulário Controlado , COVID-19/epidemiologia , COVID-19/prevenção & controle , COVID-19/virologia , Biologia Computacional/métodos , Bases de Dados Factuais/estatística & dados numéricos , Epidemias/prevenção & controle , Humanos , Armazenamento e Recuperação da Informação/métodos , Lógica , SARS-CoV-2/fisiologia
J Biomed Semantics ; 11(1): 4, 2020 06 23.
Artigo em Inglês | MEDLINE | ID: mdl-32576239


BACKGROUND: Most tutorial ontologies focus on illustrating one aspect of ontology development, notably language features and automated reasoners, but ignore ontology development factors, such as emergent modelling guidelines and ontological principles. Yet, novices replicate examples from the exercise they carry out. Not providing good examples holistically causes the propagation of sub-optimal ontology development, which may negatively affect the quality of a real domain ontology. RESULTS: We identified 22 requirements that a good tutorial ontology should satisfy regarding subject domain, logics and reasoning, and engineering aspects. We developed a set of ontologies about African Wildlife to serve as tutorial ontologies. A majority of the requirements have been met with the set of African Wildlife Ontology tutorial ontologies, which are introduced in this paper. The African Wildlife Ontology is mature and has been used yearly in an ontology engineering course or tutorial since 2010 and is included in a recent ontology engineering textbook with relevant examples and exercises. CONCLUSION: The African Wildlife Ontology provides a wide range of options concerning examples and exercises for ontology engineering well beyond illustrating just language features and automated reasoning. It assists in demonstrating tasks concerning ontology quality, such as alignment to a foundational ontology and satisfying competency questions, versioning, and multilingual ontologies.

Data Brief ; 29: 105098, 2020 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-31989008


This data article reports on a new set of 234 competency questions for ontology development and their formalisation into a set of 131 SPARQL-OWL queries. This is the largest set of competency questions with their linked queries to date, covering several ontologies of different type in different subject domains developed by different groups of question authors and ontology developers. The dataset is focused specifically on the ontology TBox (terminological part). The dataset may serve as a manually created gold standard for testing and benchmarking, research into competency questions and querying ontologies, and tool development. The data is available in Mendeley Data. Its analysis is presented in "Analysis of Ontology Competency Questions and their formalizations in SPARQL-OWL" [15].

J Biomed Inform ; 45(3): 482-94, 2012 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-22301196


Bio-ontology development is a resource-consuming task despite the many open source ontologies available for reuse. Various strategies and tools for bottom-up ontology development have been proposed from a computing angle, yet the most obvious one from a domain expert perspective is unexplored: the abundant diagrams in the sciences. To speed up and simplify bio-ontology development, we propose a detailed, micro-level, procedure, DiDOn, to formalise such semi-structured biological diagrams availing also of a foundational ontology for more precise and interoperable subject domain semantics. The approach is illustrated using Pathway Studio as case study.

Biologia Computacional/métodos , Algoritmos , Modelos Biológicos , Software