Delta: A Modular Ontology Evaluation System

Kondylakis, Haridimos; Nikolaos, Astyrakakis; Dimitra, Papatsaroucha; Anastasios, Koumarelis; Emmanouel, Kritikakis; Kyriakos, Kalkanis; Iraklis, Skepasianos; Stylianos, Klados; Papadakis, Nikos

doi:10.3390/info12080301

Cited by 8 publications

(3 citation statements)

References 31 publications

(32 reference statements)

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“…Semantic Web Ontology Language (OWL) and descriptive logic were the primary tools used to develop the forensic ontology in this research [69][70][71]. The choice of these tools was motivated by their ability to represent complex relationships in a machine-readable format while enabling sophisticated querying and formal reasoning [63,67,68,72,73]. OWL is a W3C standard language designed explicitly for ontology modeling and is widely supported by various ontology editors and reasoning engines [71].…”

Section: Methodsmentioning

confidence: 99%

Interoperability-Enhanced Knowledge Management in Law Enforcement: An Integrated Data-Driven Forensic Ontological Approach to Crime Scene Analysis

Spyropoulos,

Bratsas,

Makris

et al. 2023

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Nowadays, more and more sciences are involved in strengthening the work of law enforcement authorities. Scientific documentation is evidence highly respected by the courts in administering justice. As the involvement of science in solving crimes increases, so does human subjectivism, which often leads to wrong conclusions and, consequently, to bad judgments. From the above arises the need to create a single information system that will be fed with scientific evidence such as fingerprints, genetic material, digital data, forensic photographs, information from the forensic report, etc., and also investigative data such as information from witnesses’ statements, the apology of the accused, etc., from various crime scenes that will be able, through formal reasoning procedure, to conclude possible perpetrators. The present study examines a proposal for developing an information system that can be a basis for creating a forensic ontology—a semantic representation of the crime scene—through descriptive logic in the owl semantic language. The Interoperability-Enhanced information system to be developed could assist law enforcement authorities in solving crimes. At the same time, it would promote closer cooperation between academia, civil society, and state institutions by fostering a culture of engagement for the common good.

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Section: Methodsmentioning

confidence: 99%

Interoperability-Enhanced Knowledge Management in Law Enforcement: An Integrated Data-Driven Forensic Ontological Approach to Crime Scene Analysis

Spyropoulos,

Bratsas,

Makris

et al. 2023

Information

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“…As a result, many tools such as OntoQA [132], OOPS! [111], OntoMetrics [90], XD analyzer [30], ontologyAnalyzer [7,126] and Delta [86] have automated the measures of structural intrinsic characteristics. Thus, ontology developers can easily use these tools for the structural intrinsic evaluation of an ontology (see Table 13).…”

Section: Structural Intrinsic Characteristics (Ie Inherent Ontology Q...mentioning

confidence: 99%

A conceptual model for ontology quality assessment

Wilson

Goonetillake

Indika

et al. 2023

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With the continuous advancement of methods, tools, and techniques in ontology development, ontologies have emerged in various fields such as machine learning, robotics, biomedical informatics, agricultural informatics, crowdsourcing, database management, and the Internet of Things. Nevertheless, the nonexistence of a universally agreed methodology for specifying and evaluating the quality of an ontology hinders the success of ontology-based systems in such fields as the quality of each component is required for the overall quality of a system and in turn impacts the usability in use. Moreover, a number of anomalies in definitions of ontology quality concepts are visible, and in addition to that, the ontology quality assessment is limited only to a certain set of characteristics in practice even though some other significant characteristics have to be considered for the specified use-case. Thus, in this research, a comprehensive analysis was performed to uncover the existing contributions specifically on ontology quality models, characteristics, and the associated measures of these characteristics. Consequently, the characteristics identified through this review were classified with the associated aspects of the ontology evaluation space. Furthermore, the formalized definitions for each quality characteristic are provided through this study from the ontological perspective based on the accepted theories and standards. Additionally, a thorough analysis of the extent to which the existing works have covered the quality evaluation aspects is presented and the areas further to be investigated are outlined.

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“…The Equivalence Ratio metric expresses the relationship between the number of similar classes and the total number of classes within an ontology [123]. The metric is calculated by Eq.…”

Section: Equivalence Ratiomentioning

confidence: 99%

Application of ELECTRE algorithms in ontology selection.

Sooklall

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The field of artificial intelligence (AI) is expanding at a rapid pace. Ontology and the field of ontological engineering is an invaluable component of AI, as it provides AI the ability to capture and express complex knowledge and data in a form that encourages computation, inference, reasoning, and dissemination. Accordingly, the research and applications of ontology is becoming increasingly widespread in recent years. However, due to the complexity involved with ontological engineering, it is encouraged that users reuse existing ontologies as opposed to creating ontologies de novo. This in itself has a huge disadvantage as the task of selecting appropriate ontologies for reuse is complex as engineers and users may find it difficult to analyse and comprehend ontologies. It is therefore crucial that techniques and methods be developed in order to reduce the complexity of ontology selection for reuse. Essentially, ontology selection is a Multi-Criteria Decision-Making (MCDM) problem, as there are multiple ontologies to choose from whilst considering multiple criteria. However, there has been little usage of MCDM methods in solving the problem of selecting ontologies for reuse. Therefore, in order to tackle this problem, this study looks to a prominent branch of MCDM, known as the ELimination Et. Choix Traduisant la RÉalite (ELECTRE). ELECTRE is a family of decision-making algorithms that model and provide decision support for complex decisions comprising many alternatives with many characteristics or attributes. The ELECTRE algorithms are extremely powerful and they have been applied successfully in a myriad of domains, however, they have only been studied to a minimal degree with regards to ontology ranking and selection. In this study the ELECTRE algorithms were applied to aid in the selection of ontologies for reuse, particularly, three applications of ELECTRE were studied. The first application focused on ranking ontologies according to their complexity metrics. The ELECTRE I, II, III, and IV models were applied to rank a dataset of 200 ontologies from the BioPortal Repository, with 13 complexity metrics used as attributes. Secondly, the ELECTRE Tri model was applied to classify the 200 ontologies into three classes according to their complexity metrics. A preference-disaggregation approach was taken, and a genetic algorithm was designed to infer the thresholds and parameters for the ELECTRE Tri model. In the third application a novel ELECTRE model was developed, named ZPLTS-ELECTRE II, where the concept of Z-Probabilistic Linguistic Term Set (ZPLTS) was combined with the traditional ELECTRE II algorithm. The ZPLTS-ELECTRE II model enables multiple decision-makers to evaluate ontologies (group decision-making), as well as the ability to use natural language to provide their evaluations. The model was applied to rank 9 ontologies according to five complexity metrics and five qualitative usability metrics. The results of all three applications were analysed, compared, and contrasted, in order to understand the applicability and effectiveness of the ELECTRE algorithms for the task of selecting ontologies for reuse. These results constitute interesting perspectives and insights for the selection and reuse of ontologies.

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Delta: A Modular Ontology Evaluation System

Cited by 8 publications

References 31 publications

Interoperability-Enhanced Knowledge Management in Law Enforcement: An Integrated Data-Driven Forensic Ontological Approach to Crime Scene Analysis

Interoperability-Enhanced Knowledge Management in Law Enforcement: An Integrated Data-Driven Forensic Ontological Approach to Crime Scene Analysis

A conceptual model for ontology quality assessment

Application of ELECTRE algorithms in ontology selection.

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