Reengineering and Extending the Agents in Grid Ontology

Szmeja, Paweł; Wasielewska, Katarzyna; Ganzha, Maria; Drozdowicz, Michal; Paprzycki, Marcin; Fidanova, Stefka; Lirkov, Ivan

doi:10.1007/978-3-662-43880-0_65

Cited by 5 publications

(4 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As mentioned above, all knowledge in the system is represented as an ontology, while communication protocols utilize messages with ontological content ( [4,6]). Typically, ontology is defined as a formal specification of shared conceptualization ( [10]).…”

Section: Ontology In the Aig Systemmentioning

confidence: 99%

“…Additionally, the domain of computational linear algebra was modeled as a proof-of-concept ontology. Detailed descriptions of developed ontologies can be found in [4,5,6].…”

Section: Ontology In the Aig Systemmentioning

confidence: 99%

“…• all information (knowledge, message content) in the system is ontologically represented and semantically processed (for detailed description of ontologies developed for the AiG project, see [4,5,6]).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Multicriteria analysis of ontologically represented information

Wasielewska¹,

Ganzha²,

Paprzycki³

et al. 2014

AIP Conference Proceedings

View full text Add to dashboard Cite

Our current work concerns the development of a decision support system for the software selection problem. The main idea is to utilize expert knowledge to help the user in selecting the best software / method / computational resource to solve a computational problem. Obviously, this involves multicriterial decision making and the key open question is: which method to choose. The context of the work is provided by the Agents in Grid (AiG) project, where the software selection (and thus multicriterial analysis) is to be realized when all information concerning the problem, the hardware and the software is ontologically represented. Initially, we have considered the Analytical Hierarchy Process (AHP), which is well suited for the hierarchical data structures (e.g. such that have been formulated in terms of ontologies). However, due to its well-known shortcomings, we have decided to extend our search for the multicriterial analysis method best suited for the problem in question. In this paper we report results of our search, which involved: (i) TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), (ii) PROMETHEE, and (iii) GRIP (Generalized Regression with Intensities of Preference). We also briefly argue why other methods have not been considered as valuable candidates.

show abstract

Section: Ontology In the Aig Systemmentioning

confidence: 99%

“…Additionally, the domain of computational linear algebra was modeled as a proof-of-concept ontology. Detailed descriptions of developed ontologies can be found in [4,5,6].…”

Section: Ontology In the Aig Systemmentioning

confidence: 99%

See 1 more Smart Citation

Multicriteria analysis of ontologically represented information

Wasielewska¹,

Ganzha²,

Paprzycki³

et al. 2014

AIP Conference Proceedings

View full text Add to dashboard Cite

show abstract

“…As of today, there do not seem to be any established, agreed upon, and widely used standards and methodologies for ontology evaluation. Instead, for years there have been examples of evaluations that were tailored to the specific ontology [8,9] or motivated by a specific, practical use case [7,10,11]. Lack of a commonly accepted evaluation methodology is one of problems negatively impacting potential reuse and adaptation of ontology-based solutions, as it was investigated for the enterprise domain [12].…”

Section: Introductionmentioning

confidence: 99%

Ontology Reuse: the Real Test of Ontological Design

Sowinski,

Wasielewska-Michniewska,

Ganzha

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

Reusing ontologies in practice is still very challenging, especially when multiple ontologies are involved. Moreover, despite recent advances, systematic ontology quality assurance remains a difficult problem. In this work, the quality of thirty biomedical ontologies, and the Computer Science Ontology, are investigated from the perspective of a practical use case. Special scrutiny is given to cross-ontology references, which are vital for combining ontologies. Diverse methods to detect the issues are proposed, including natural language processing and network analysis. Moreover, several suggestions for improving ontologies and their quality assurance processes are presented. It is argued that while the advancing automatic tools for ontology quality assurance are crucial for ontology improvement, they will not solve the problem entirely. It is ontology reuse that is the ultimate method for continuously verifying and improving ontology quality, as well as for guiding its future development. Many issues can be found and fixed only through practical and diverse ontology reuse scenarios.

show abstract