This paper proposes a novel ontology, called SciOnt, for representing scientometric indicators. Scientometrics is the field that studies quantitative aspects of science and scientific phenomena. Scientometric indicators are used to evaluate scientific publications and research. However, many indicators and their diversity make them challenging to understand and use. SciOnt addresses this challenge by providing a formal and structured representation of scientometric indicator knowledge. It defines classes, relationships, and instances of these indicators. The ontology can be used for various purposes, including improving the analysis and comparison of scientometric indicators, facilitating the development of new and more efficient indicators, and enhancing the understanding and criticism of existing indicators. The paper details the methodology used to design SciOnt, including identifying and classifying scientometric indicators, constructing the ontology with Protégé software, and evaluating the ontology using expert feedback. Finally, the paper presents visualizations of the SciOnt ontology structure using different tools.

This paper proposes a novel ontology, called SciOnt, for representing scientometric indicators. Scientometrics is the field that studies the quantitative aspects of science and scientific phenomena. Scientometric indicators are used to evaluate scientific publications and research. However, many indicators and their diversity make them challenging to understand and use. SciOnt addresses this challenge by providing a formal and structured representation of scientometric indicator knowledge. It defines classes, relationships, and instances of these indicators. The ontology can be used for various purposes, including improving the analysis and comparison of scientometric indicators, facilitating the development of new and more efficient indicators, and enhancing the understanding and criticism of existing indicators. The paper details the methodology used to design SciOnt, including identifying and classifying scientometric indicators, determining competency questions, and constructing the ontology with Protégé 5.5 software. Finally, the paper evaluates the ontology and visualizes the SciOnt ontology structure using various plugins.