The General Data Protection Regulation (GDPR) poses enormous challenges on companies and organizations with respect to understanding, implementing, and maintaining the contained constraints. We report on how the ConRelMiner method can be used for untangling the GDPR. For this, the GDPR is filtered and grouped along the roles mentioned by the GDPR and the reduction of sentences to be read by analysts is shown. Moreover, the output of the ConRelMiner - a cluster graph with relations between the sentences - is displayed and interpreted. Overall the goal is to illustrate how the effort for implementing the GDPR can be reduced and a structured and meaningful representation of the relevant GDPR sentences can be found.
@cite_9: We investigate process mining for the declarative Dynamic Condition Response (DCR) graphs process modelling language. We contribute (a) a process mining algorithm for DCR graphs, (b) a proposal for a set of metrics quantifying output model quality, and (c) a preliminary example-based comparison with the Declare Maps Miner. The algorithm takes a contradiction-based approach, that is, we initially assume that all possible constraints hold, subsequently removing constraints as they are observed to be violated by traces in the input log.
Only few approaches target at digitalizing the GPDR such as @cite_9 : here the GDPR is formalized in terms of a declarative notion, the so called DCR graphs.