Paper Title
ONTO EVAL DATA VALUE FRAME WORK: EVALUATING ONTOLOGICAL DATA VALUE FOR SUPPORTING ONTOLOGY INTEGRATION

Abstract
In the realm of data governance, evaluating the value of datais a critical aspect that influences the success and integrity of data integrationprocesses. Traditionally, this evaluation has been conductedusing three primary models: market-based, economic, and dimensionalmodels. However, frameworks based on the dimensional model often lackformal validation, and there is a noticeable gap in tools that provide acomprehensive assessment of datasets and ontologies prior to integration.Moreover, while various tools and frameworks exist for evaluatingdata value of datasets, there is a significant lack of tools or frameworksspecifically designed to assess the data value of ontologies. Additionally,the literature reveals a clear absence of datasets specifically dedicated tothe evaluation of ontologies. Addressing these challenges, we propose the ”OntoEval Data Value Framework,” a novel framework designed for evaluatingthe data value of ontologies. Our approach leverages the OQuaREFramework to assess key data quality metrics such as clarity, interoperability,and extensibility, while also introducing new metrics like licensingand coherence/consistency, supported by custom algorithms developedfor this purpose. The application of this framework to a large-scale evaluationof 5,000 ontologies resulted in the creation of a comprehensivedataset that aggregates critical information about the evaluated ontologies.This formalized approach not only enhances the reliability of dataintegration but also fills a critical gap in the ontology evaluation landscape. Keywords - Data Value Evaluation, Ontology Evaluation, Data Management, Ontology Integration