EasyOnto: A Collaborative Semiformal Ontology Development Platform

SWRL: Rule Acquisition Using Ontology

Scientific Journal of Riga Technical University Computer Sciences ◽

10.2478/v10143-010-0016-8 ◽

2009 ◽

Vol 40 (1) ◽

pp. 117-122 ◽

Cited By ~ 2

Author(s):

Darya Plinere ◽

Arkady Borisov

Keyword(s):

Knowledge Acquisition ◽

Main Issue ◽

Ontology Development ◽

Rule Based ◽

Development Platform ◽

Rule Acquisition ◽

Rule System ◽

Rule Based Systems

SWRL: Rule Acquisition Using Ontology Nowadays rule-based systems are very common. The use of ontology-based systems is becoming ever more popular, especially in addition to the rule-based one. The most widely used ontology development platform is Protégé. Protégé provides a knowledge acquisition tool, but still the main issue of the ontology-based rule system is rule acquisition. This paper presents an approach to using SWRL rules Tab, a plug-in to Protégé, for rule acquisition. SWRL rules Tab transforms conjunctive rules to Jess rules in IF…THEN form.

Download Full-text

OOPS! (OntOlogy Pitfall Scanner!)

International Journal on Semantic Web and Information Systems ◽

10.4018/ijswis.2014040102 ◽

2014 ◽

Vol 10 (2) ◽

pp. 7-34 ◽

Cited By ~ 69

Author(s):

María Poveda-Villalón ◽

Asunción Gómez-Pérez ◽

Mari Carmen Suárez-Figueroa

Keyword(s):

Empirical Analysis ◽

Description Logics ◽

Ontology Development ◽

Evaluation Tools ◽

Domain Experts ◽

Development Platform ◽

Ontology Evaluation ◽

Modeling Errors

This paper presents two contributions to the field of Ontology Evaluation. First, a live catalogue of pitfalls that extends previous works on modeling errors with new pitfalls resulting from an empirical analysis of over 693 ontologies. Such a catalogue classifies pitfalls according to the Structural, Functional and Usability-Profiling dimensions. For each pitfall, we incorporate the value of its importance level (critical, important and minor) and the number of ontologies where each pitfall has been detected. Second, OOPS! (OntOlogy Pitfall Scanner!), a tool for detecting pitfalls in ontologies and targeted at newcomers and domain experts unfamiliar with description logics and ontology implementation languages. The tool operates independently of any ontology development platform and is available online. The evaluation of the system is provided both through a survey of users' satisfaction and worldwide usage statistics. In addition, the system is also compared with existing ontology evaluation tools in terms of coverage of pitfalls detected.

Download Full-text

Sharing Ontologies and Rules Using Model Transformations

Handbook of Research on Emerging Rule-Based Languages and Technologies ◽

10.4018/978-1-60566-402-6.ch020 ◽

2010 ◽

pp. 471-492 ◽

Cited By ~ 1

Author(s):

Milan Milanovic ◽

Dragan Djuric ◽

Dragan Gasevic ◽

Vladan Devedzic

Keyword(s):

Semantic Web ◽

Ad Hoc ◽

General Rule ◽

Model Transformations ◽

Ontology Development ◽

Model Driven ◽

Development Platform ◽

Rule Languages ◽

Concrete Syntax ◽

Mapping Techniques

Web Ontology Language (OWL), Semantic Web Rule Language (SWRL) and Model-Driven Engineering (MDE) are technologies being developed in parallel, but by different communities. They have common points and issues and can be brought closer together. Many authors have so far stressed this problem and have proposed several solutions. The result of these efforts is the recent OMG’s initiative for defining an ontology development platform. However, the problem of transformation between Semantic Web ontology and rule languages and MDE-based languages has been solved using rather partial and ad hoc solutions, most often by XSLT. In this paper, we relations between the Semantic Web languages and MDE-compliant languages as separate technical spaces. In order to achieve a synergy between these technical spaces, we present ontology and rule languages in terms of MDE standards, recognize relations between the OWL and SWRL langauges and MDE-based ontology languages, and propose mapping techniques. In order to illustrate the approach, we use an MDE-defined architecture that includes the ontology and rule metamodels and ontology UML Profile. We also show how MDE techniques, such as model transformations, can be used to enable sharing rules and ontologies by using REWERSE Rule Markup Language (R2ML), a proposal for a general rule language. The main benefit of this approach is that it keeps the focus on the language concepts (i.e., languages’ abstract syntax - metamodels) rather than on technical issues caused by different concrete syntax. Yet, we also provide transformations that bridge between both languages’ concrete (XML) and abstract (MOF) syntax.

Download Full-text

An Infrastructure for Collaborative Ontology Development

10.3233/faia210375 ◽

2021 ◽

Author(s):

Dean Allemang ◽

Pawel Garbacz ◽

Przemysław Grądzki ◽

Elisa Kendall ◽

Robert Trypuz

Keyword(s):

Open Source ◽

Large Scale ◽

Version Control ◽

Ontology Development ◽

Financial Industry ◽

Development Platform ◽

Collaborative Software ◽

Ontology Design ◽

Collaborative Platform ◽

Collaborative Software Development

Collaborative development of a shared or standardized ontology presents unique issues in workflow, version control, testing, and quality control. These challenges are similar to challenges faced in large-scale collaborative software development. We have taken this idea as the basis of a collaborative ontology development platform based on familiar software tools, including Continuous Integration platforms, version control systems, testing platforms, and review workflows. We have implemented these using open-source versions of each of these tools, and packaged them into a full-service collaborative platform for collaborative ontology development. This platform has been used in the development of FIBO, the Financial Industry Business Ontology, an ongoing collaborative effort that has been developing and maintaining a set of ontologies for over a decade. The platform is open-source and is being used in other projects beyond FIBO. We hope to continue this trend and improve the state of practice of collaborative ontology design in many more industries.

Download Full-text

OOPS!

Innovations, Developments, and Applications of Semantic Web and Information Systems - Advances in Web Technologies and Engineering ◽

10.4018/978-1-5225-5042-6.ch005 ◽

2018 ◽

pp. 120-148

Author(s):

María Poveda-Villalón ◽

Asunción Gómez-Pérez ◽

Mari Carmen Suárez-Figueroa

Keyword(s):

Web Service ◽

Empirical Analysis ◽

Web Application ◽

Description Logics ◽

Ontology Development ◽

Evaluation Tools ◽

Domain Experts ◽

Development Platform ◽

Ontology Evaluation ◽

Modeling Errors

The first contribution of this paper consists on a live catalogue of pitfalls that extends previous works on modeling errors with pitfalls resulting from an empirical analysis of numerous ontologies. Such a catalogue classifies pitfalls according to the Structural, Functional and Usability-Profiling dimensions. For each pitfall, we include the value of its importance level (critical, important and minor). The second contribution is the description of OntOlogy Pitfall Scanner (OOPS!), a widely used tool for detecting pitfalls in ontologies and targeted at newcomers and domain experts unfamiliar with description logics and ontology implementation languages. The tool operates independently of any ontology development platform and is available through a web application and a web service. The evaluation of the system is provided both through a survey of users' satisfaction and worldwide usage statistics. In addition, the system is also compared with existing ontology evaluation tools in terms of coverage of pitfalls detected.

Download Full-text