An Ontological-Based Model to Data Governance for Big Data

• Main Authors: Alfonso Castro, Victor A. Villagra, Paula Garcia, Diego Rivera, David Toledo
• Format: Article
• Language: English
• Published: IEEE 2021-01-01
• Series: IEEE Access
• Subjects: Big data; data governance; knowledge-based management; ontologies; reasoning; OWL
• Online Access: https://ieeexplore.ieee.org/document/9503381/

Nowadays, companies and official bodies are using the data as a principal asset to take strategic decisions. The advances in big data processing, storage and analysis techniques have allowed to manage the continuous increase in the volume of data. This increase in the volume of data together with its high variability and the large number of sources lead to a constant growing of the complexity of the data management environment. Data governance is the key for simplifying that complexity: it is the element that controls the decision making and responsibilities for all the processes related to data management. This paper discusses an approach to data governance based on ontological reasoning to reduce data management complexity. The proposed data governance system is built over an autonomous system based on distributed components. It implements semantic techniques and automatic ontology-based reasoning. The different components use a Shared Knowledge Plane to interact. Its fundamental piece is an ontology that represents all the data management processes included in data governance. A prototype of such a system has been implemented and tested for Telefonica’s global video service. The results obtained show the feasibility of using this type of technology to reduce the complexity of managing big data environments.