Semantic Data Governance for Regulatory Compliance

Across industry sectors, understanding, assessing and reporting for regulatory compliance is both a priority and a challenge for many organizations. Data-related laws, such as HIPAA, BASEL and GDPR, require an understanding of the sources, flows and destinations of data.
Based on W3C semantic standards and linked-data methodologies, TopBraid Enterprise Data Governance (TopBraid EDG) provides a solution that confirms the power of semantics to map data landscapes.
Using examples based on cases of use from the financial sector we will show how to consolidate, organize and manage metadata and relationships for compliance assessment.
We will demonstrate how TopBraid EDG addresses the problems in regulatory compliance by using Ontologies to:
•    manage the articles and structure of compliance requirements
•    provide a reasoning foundation for interpreting the meanings of regulations on data-in-context
•    describe data and how it flows through software executables in the business environment.
Key capabilities of the solution include: query and visualization to navigate data dependencies; and rules on the data to infer applicable regulatory obligations are
We will report on a data lineage methodology and best practices inspired by customer projects.  Finally, we will summarize how our experiences have revealed new opportunities using semantics to gain additional insights and governance.

Data-related laws, such as HIPAA, BASEL and GDPR, are complex documents that require considerable human understanding. Once that understanding exists there is a need to assess the implications on data at rest and data in motion in the enterprise.
Developing a shared understanding among multiple stakeholders of what is needed to fulfill regulatory compliance is a key problem.  It is essential to discover and describe how data, metadata, documents, other assets as well as people and processes map to regulatory obligations.
Highly-interrelated needs of people, processes and data, make graph-based knowledge representations and linked-data methodologies essential to meeting the challenges of regulatory compliance. By connecting all the related metadata, data, forms and other compliance collaterals, organizations can navigate complex data governance landscapes.
TopBraid Enterprise Data Governance (TopBraid EDG) is an agile data governance solution based on W3C semantic standards and linked-data technologies.  TopBraid EDG addresses the problems in regulatory compliance by using ontologies to manage the articles and structure of compliance requirements, to provide a reasoning foundation for interpreting the meanings of regulations on data-in-context, and to describe data and how it flows through software executables in the business environment. Key capabilities of the solution include: query and visualization to navigate data dependencies; and rules on the data to infer applicable regulatory obligations are
In practice, TopBraid EDG has been used to map applications and the data landscape in the financial domain. Using EDG, comprehensive lineage records have been created by loading information about thousands of applications and data flow dependencies. EDG also generates Avro schemas for the data lake from relational database structures.
Using examples from the financial sector we will show how to consolidate, organize and manage metadata and relationships for compliance assessment. We will demonstrate how TopBraid EDG addresses the problems in regulatory compliance by using Ontologies to:
•    manage the articles and structure of compliance requirements
•    provide a reasoning foundation for interpreting the meanings of regulations on data-in-context
•    describe data and how it flows through software executables in the business environment.
We will report on a data lineage methodology and best practices inspired by customer projects.  Finally, we will summarize how our experiences have revealed new opportunities using semantics to gain additional insights and governance.