Skip to content

Category: Data governance

Policy-based Automated Compliance Checking

Under the GDPR requirements and privacy-by-design guidelines, access control for personal data should not be limited to a simple role-based scenario. For the processing to be compliant, additional attributes, such as the purpose of processing or legal basis, should be verified against an established data processing agreement or policy.

A Combined Rule-Based and Machine Learning Approach for Automated GDPR Compliance Checking

The General Data Protection Regulation (GDPR) requires data controllers to implement end-to-end compliance. Controllers must therefore ensure that the terms agreed with the data subject and their own obligations under GDPR are respected in the data flows from data subject to controllers, processors and sub-processors (i.e. data supply chain).

DMMM: Data Management Maturity Model

The assessment of the digital transformation progress is essential to understand and undertake in order to evaluate the level of maturity of data-driven companies in terms of data capabilities and to plan for improvement actions.

A Survey of Maturity Models in Data Management

Maturity models are helpful business tools that refine and develop how organizations conduct their businesses and benchmark their maturity status against a scale or with industry peers. They serve to prioritize the actions for improvement better and control the progress in reaching the target maturity stage.

Privacy Policy Classification with XLNet

The popularisation of privacy policies has become an attractive subject of research in recent years, notably after the General Data Protection Regulation came into force in the European Union. While

Towards Privacy Policy Conceptual Modeling

After GDPR enforcement in May 2018, the problem of implementing privacy by design and staying compliant with regulations has been more prominent than ever for businesses of all sizes, which