Semantic Modelling of Organizational Knowledge as a Basis for Enterprise Data Governance 4.0 -- Application to a Unified Clinical Data Model

Author:

Miguel AP Oliveira, Stephane Manara, Bruno Molé, Thomas Muller, Aurélien Guillouche, Lysann Hesske, Bruce Jordan, Gilles Hubert, Chinmay Kulkarni, Pralipta Jagdev, Cedric R. Berger

Keyword:

Computer Science, Artificial Intelligence, Artificial Intelligence (cs.AI), Information Retrieval (cs.IR)

journal:

date:

2023-10-19 16:00:00

Abstract

Individuals and organizations cope with an always-growing data amount, heterogeneous in contents and formats. Prerequisites to get value out this data and minimise inherent risks related to multiple usages are adequate data management processes yielding data quality and control over its lifecycle. Common data governance frameworks relying on people and policies falls short of the overwhelming data complexity. Yet, harnessing this complexity is necessary to achieve high quality standards. The later will condition the outcome of any downstream data usage, including generative artificial intelligence trained on this data. In this paper, we report our concrete experience establishing a simple, cost-efficient framework, that enables metadata-driven, agile and (semi-)automated data governance (i.e. Data Governance 4.0). We explain how we implement and use this framework to integrate 25 years of clinical study data at enterprise scale, in a fully productive environment. The framework encompasses both methodologies and technologies leveraging semantic web principles. We built an knowledge graph describing data assets avatars in their business context including governance principles. Multiple ontologies articulated by an enterprise upper ontology enable key governance actions such as FAIRification, lifecycle management, definition of roles and responsibilities, lineage across transformations and provenance from source systems. This metadata model is a prerequisite to automatize data governance, make it fit-for-purpose to each use case and dynamically adapting it to business changes.

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