Dataset Management Powered by Semantic Web Technologies

When developing data supply chains, more and more companies strive for compliance by design. This process aims to ensure that computer software meets business compliance rules and policies. Some examples of compliance questions that require an answer are On what legal grounds can we store and process the data?, Does the data need to be encrypted at rest?, How long can we keep the data? and Who shall be able to access the data?. To automate these decisions in the data supply chain, the software needs to retrieve required policies and rules to be able to take appropriate actions. Also, to be able to request for policies, the software needs to be aware of the data asset that it is currently processing; i.e., the data needs an asset identifier. Dun & Bradstreet is a leading global provider of business decisioning data and analytics for almost 200 years. In our Nordic data supply chain, we use Semantic Web technologies and knowledge graphs to govern which datasets are allowed to be processed. By assigning each dataset a unique identifier at the earliest stage in the data supply chain, any subsequent software decision point can retrieve the associated policies and take appropriate decisions. The information in the knowledge graph is governed and maintained by data owners and can be updated (when required) without changing any of the software in the data supply chain.