Supporting Ontology Development Research Articles

A Personalized Ontology Recommendation System to Effectively Support Ontology Development by Reuse

The profusion of existing ontologies in different domains has made reusing ontologies a best practice when developing new ontologies. The ontology reuse process reduces the expensive cost of developing a new ontology, in terms of time and effort, and supports semantic interoperability. Existing ontology development tools do not assist in the recommendation of ontologies or their concepts to be reused. Also, existing ontology recommendation tools could suggest whole ontologies covering a set of input keywords without referring to which parts of them (e.g., concepts) can be reused. In this paper, we propose an effective ontology recommendation system that helps the user in the iterative development and reuse of ontologies. The system allows the user to provide explicit preferences about the new ontology, and iteratively guides the user to parts from existing ontologies which match his preferences for reuse. Finally, we developed a prototype of our ontology recommendation system and conducted a user-based evaluation to assess the effectiveness of our approach.

A Collaborative Framework Supporting Ontology Development Based on Agile and Scrum Model

Ontology describes concepts and relations in a specific domain-knowledge that are important for knowledge representation and knowledge sharing. In the past few years, several tools have been introduced for ontology modeling and editing. To design and develop an ontology is one of the challenge tasks and its challenges are quite similar to software development as it requires many collaborative activities from many stakeholders (e.g. domain experts, knowledge engineers, application users, etc.) through the development cycle. Most of the existing tools do not provide collaborative feature to support stakeholders to collaborate work more effectively. In addition, there are lacking of standard process adoption for ontology development task. Thus, in this work, we incorporated ontology development process into Scrum process as used for process standard in software engineering. Based on Scrum, we can perform standard agile development of ontology that can reduce the development cycle as well as it can be responding to any changes better and faster. To support this idea, we proposed a Scrum Ontology Development Framework, which is an online collaborative framework for agile ontology design and development. Each ontology development process based on Scrum model will be supported by different services in our framework, aiming to promote collaborative activities among different roles of stakeholders. In addition to services such as ontology visualized modeling and editing, we also provide three more important features such as 1) concept/relation misunderstanding diagnosis, 2) cross-domain concept detection and 3) concept classification. All these features allow stakeholders to share their understanding and collaboratively discuss to improve quality of domain ontologies through a community consensus.

Thematic issue of the Second combined Bio-ontologies and Phenotypes Workshop

This special issue covers selected papers from the 18th Bio-Ontologies Special Interest Group meeting and Phenotype Day, which took place at the Intelligent Systems for Molecular Biology (ISMB) conference in Dublin in 2015. The papers presented in this collection range from descriptions of software tools supporting ontology development and annotation of objects with ontology terms, to applications of text mining for structured relation extraction involving diseases and phenotypes, to detailed proposals for new ontologies and mapping of existing ontologies. Together, the papers consider a range of representational issues in bio-ontology development, and demonstrate the applicability of bio-ontologies to support biological and clinical knowledge-based decision making and analysis.The full set of papers in the Thematic Issue is available at http://www.biomedcentral.com/collections/sig.

Visualizing Information Science Knowledge by Modelling Domain Ontology (OIS)

Information Science (IS) is one of the areas that need a unified ontology model to facilitate information in order to access the heterogeneous data resources, and share a common understanding of the domain knowledge. The aim of the study is to develop a generic model of ontology that serves as a foundation of knowledge modelling for applications and aggregation with other ontologies. This study adopts the Methontology methodology to develop an Ontology of Information Science (OIS). To support ontology development, the virtual community of practice of Information science (Ontocop) was employed. The Ontology was coded using Protégé and the OWL web ontology language. The main achievement of the study is that a new model of Information Science Ontology (OIS) has been constructed, which is a generic model that contains only the key objects and associated attributes with their relationships. The model defines the 706 concept, which will be widely used in Information Science applications. The research reveals that OIS ontology is a model that meets the ontology quality criteria for the subject area. It is concluded that OIS ontology unifies information science knowledge, which is composed of Library, Computer, and Archival science, by creating a theoretical base that is useful for further practical systems. The OIS ontology can be reused as the basis for any domain development.

Visualizing Information Science Knowledge by Modelling Domain Ontology (OIS)

Information Science (IS) is one of the areas that need a unified ontology model to facilitate information in order to access the heterogeneous data resources, and share a common understanding of the domain knowledge. The aim of the study is to develop a generic model of ontology that serves as a foundation of knowledge modelling for applications and aggregation with other ontologies. This study adopts the Methontology methodology to develop an Ontology of Information Science (OIS). To support ontology development, the virtual community of practice of Information science (Ontocop) was employed. The Ontology was coded using Protégé and the OWL web ontology language. The main achievement of the study is that a new model of Information Science Ontology (OIS) has been constructed, which is a generic model that contains only the key objects and associated attributes with their relationships. The model defines the 706 concept, which will be widely used in Information Science applications. The research reveals that OIS ontology is a model that meets the ontology quality criteria for the subject area. It is concluded that OIS ontology unifies information science knowledge, which is composed of Library, Computer, and Archival science, by creating a theoretical base that is useful for further practical systems. The OIS ontology can be reused as the basis for any domain development.

Approaching the feasibility of SBVR as modeling language for ontology development: An exploratory experiment

Ontology development techniques still constitute an open research area despite its importance in semantic aware information systems. Until now, most methods have used UML in supporting ontology development process. Recent works propose the mapping of business rules expressions to ontology statements as a building technique by means of SBVR language. However, there is still no experimental research comparing such approaches.Aim of this work is to evaluate the feasibility of mapping business domain expressions to ontology statements. An exploratory experiment comparing performance of techniques based on UML and SBVR languages is presented. Comparison is rooted in the quality assessment of the ontologies developed by 10 equally sized groups randomly conformed by 30 undergraduate engineering students and applying such techniques.Developed ontologies largely outperform the minimally acceptable quality, according to the considered quality assessment framework. There is no statistical significant difference between the quality scores of the ontologies developed by means of UML and SBVR techniques, in any of the assessed quality dimensions.The feasibility of mapping business domain expressions to ontology statements is shown: ontologies developed by means of a SBVR based approach at least equate the quality of ontologies developed by using an UML based method. Results confirm previous research about the effectiveness of UML approaches for conceptualizing lightweight ontologies while stressing the potential of the SBVR language to express complex notions of a domain of interest. The potential of SBVR to OWL 2 mappings as an ontology development technique worthy of further study is highlighted.

Supporting ontology development with ODEd

Ontologies are becoming an important mechanism to build information systems. However, ontology construction is not a simple task. So, it is necessary to provide tools that support ontology development. This paper presents ODEd, an ontology editor that supports the definition of concepts, relations and properties, using graphic representations, besides promoting automatic inclusion of some classes of axioms and derivation of object infrastructures from ontologies. ODEd was built to support ontology development in ODE, a software engineering environment (SEE), so that ODE can be used as a domain-oriented SEE. Thus, ODEd aims to partially support an ontology-based domain engineering process.