crowd : A Visual Tool for Involving Stakeholders into Ontology Engineering Tasks
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crowd: A Visual Tool for Involving Stakeholders into Ontology Engineering Tasks Germán Braun1,2 · Christian Gimenez1 · Laura Cecchi1 · Pablo Fillottrani3,4 Received: 19 December 2019 / Accepted: 1 April 2020 © Gesellschaft für Informatik e.V. and Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract We present crowd, a web-based visual tool for ontology engineering tasks. Its aim is to involve ontology developers and domain experts into a collaborative comprehension and design of conceptual models, enhancing the communication between them and assessing their quality by fully integrating automatic reasoning in the tool. In this paper we briefly describe the initial requirements, architecture and user interface, and make an evaluation based on a use case and a comparison with related tools. Keywords Ontology engineering · Semantic web tools · Conceptual modelling
1 Introduction Involving knowledge engineers, domain experts and end users in the construction, maintenance, and use of ontologies requires a strong interaction between them and the models. Users manage diverse vocabularies and might have different interpretations about facts in the world being modelled. This requires to use a common language along with appropriate methodologies, manage effectively interactions and have a deep understanding of the tool for guiding and supporting this creative process.
* Germán Braun [email protected] Christian Gimenez [email protected] Laura Cecchi [email protected] Pablo Fillottrani [email protected] 1
Facultad de Informática, Universidad Nacional Nacional del Comahue, Neuquén, Argentina
2
Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires, Argentina
3
Departamento de Ciencias e Ingeniería de la Computacián, Universidad Nacional del Sur, Bahía Blanca, Argentina
4
Comisión de Investigaciones Científicas de la Provincia de Buenos Aires, Buenos Aires, Argentina
In spite of the fact that automated reasoning enabled tools provide vital support for ontology engineering by giving them the ability to detect errors and unexpected (non-) entailments [17, 24], they still suffer the lack of visualisation methods widely accepted by the Semantic Web community [14]. One of the reasons is that novel visualisation methods proposed are not fully integrated to logical-based reasoning tools. Another one is that methodologies and tools for ontology engineering appear to be fragmented across several tools and workarounds [8, 36]. Based on this motivation, we developed crowd1 with the following objectives: (i) define a suitable abstraction level (modelling language) for ontology engineering taking into account the involved actors and the underlying methodologies (ii) formalise how and to what extent the logical-based knowledge representation systems can be integrated with graphical languages in a tool. The first objective benefits from recent research related to characterisation of ontological levels, which ranges from foundational asp
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