Abstract
Ontologies have emerged as a powerful tool for sharing knowledge, due to their ability to integrate them. A key challenge is the interoperability of data sources that do not have a common schema and that were collected, processed and analyzed under different methodologies. Data governance defines policies, organization and standards. Data governance focused on integration processes helps to define what is integrated, who does it and how it is integrated. The representation of this integration process implies that not only the elements involved in the integration of metadata and their data sets need to be represented, but also elements of coordination between people and knowledge domains need to be included. This paper shows the ontology that describes the data governance processes, the elements that make it up and their relationships. For its development, the methodology based on competency questions and definition of terms is used. The data governance ontology creates a context to support the interaction of different data sources. The ontology is instantiated by means of a case study for Data Governance in Mining Inspection for the Geology and Mining Service of the Chilean government.
This project was supported by the Mining Management of Sernageomin through the 0 Accidents project.
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Muñoz, A., Martí, L., Sanchez-Pi, N. (2021). Data Governance, a Knowledge Model Through Ontologies. In: Valencia-García, R., Bucaram-Leverone, M., Del Cioppo-Morstadt, J., Vera-Lucio, N., Jácome-Murillo, E. (eds) Technologies and Innovation. CITI 2021. Communications in Computer and Information Science, vol 1460. Springer, Cham. https://doi.org/10.1007/978-3-030-88262-4_2
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