Resumen de A framework for conceptual characterization of ontologies and its application in the cybersecurity domain
Beatriz Franco Martins Souza
Ontologies are computational artifacts with a wide range of applications. They represent knowledge as accurately as possible and provide humans with a framework for knowledge representation and clarification. Additionally, ontologies can be implemented and processed by adding semantics to data that needs to be exchanged between systems. In systems, data is the carrier of information and needs to comply with the FAIR Principles to fulfill its purpose. However, knowledge domains can be vast, complex, and sensitive, making interoperability challenging. Moreover, ontology design and development are not easy tasks; they must follow methodologies and standards and comply with a set of requirements. Indeed, ontologies have been used to provide data FAIRness due to their characteristics, applications, and semantic competencies.
With the growing need to interoperate data came the need to interoperate ontologies to guarantee the correct transmission and exchange of information. To meet the need to interoperate ontologies and at the same time conceptualize complex and vast domains, Ontology Networks emerged. Moreover, ontologies began to carry out conceptualizations, fragmenting knowledge in different ways depending on requirements, such as the ontology scope, purpose, whether it is processable or for human use, its context, and several other formal aspects, making Ontology Engineering also a complex domain. The problem is that in the Ontology Engineering Process, stakeholders take different perspectives of the conceptualizations, and this causes ontologies to have biases that are sometimes more ontological and sometimes more related to the domain. These problems result in ontologies that lack grounding and ontology implementations without a previous reference model.
We propose a (meta)ontology grounded over the Unified Foundational Ontology (UFO) and supported by well-known ontological classification standards, guides, and FAIR Principles to address this problem of lack of consensual conceptualization. The Ontology for Ontological Analysis (O4OA) considers ontological-related and domain-related perspectives, knowledge, characteristics, and commitment that are needed to facilitate the process of Ontological Analysis, including the analysis of ontologies composing an ontology network. Using O4OA we propose the Framework for Ontology Characterization (F4OC) to provide guidelines and best practices in the light of O4OA for stakeholders. The F4OC fosters a stable and uniform environment for ontological analysis, integrating stakeholder perspectives. Moreover, we applied O4OA and F4OC to several case studies in the Cybersecurity Domain, which is intricate, highly regulated, and sensitive to causing harm to people and organizations.
The main objective of this doctoral thesis is to provide a systematic and reproducible environment for ontology engineers and domain specialists responsible for ensuring ontologies developed according to the FAIR Principles. We aspire that O4OA and F4OC be valuable contributions to the conceptual modeling community as well as the additional outcomes for the cybersecurity community through the ontological analysis in our case studies.
