Auto-filling the GDPR readiness checklist by querying the compliance graph. Underlying technologies are RDF/OWL/SPARQL for the creation and querying of the compliance graph.
Harshvardhan Pandit
2401d108cb
added GDPR readiness checklist HTML
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6 anni fa | |
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| demo | 6 anni fa | |
| sparql | 6 anni fa | |
| .gitignore | 6 anni fa | |
| LICENSE | 6 anni fa | |
| README.md | 6 anni fa | |
| inferred.owl | 6 anni fa | |
| remove_owl_data.py | 6 anni fa | |
| removed.ttl | 6 anni fa | |
| shoppingapp.owl | 6 anni fa |
README.md
GDPR-readiness-checklist-usecase
The Data Protection Commissioner of Ireland (DPC Ireland) has put forth a GDPR readiness checklist (GDPR-RC) [1] that consists of a spreadsheet meant to be filled to assess and help in GDPR readiness. This research aims to demonstrate how this information can be (semi-)automatically filled based on querying a compliance graph containing the required information. The research is primarily focused on provenance information (metadata), and uses the GDPR-RC as a demonstrative use-case of compliance-graph querying. Metadata is stored as RDF/OWL using the previously published GDPRov [2] and GDPRtEXT [3] vocabularies. Querying is done using SPARQL. The development environment for this work is primarily Protege, with the webapp using flask+rdflib.