Conference paper Open Access

Exploring GDPR Compliance Over ProvenanceGraphs Using SHACL

Pandit, Harshvardhan J.


Citation Style Language JSON Export

{
  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.3246493", 
  "title": "Exploring GDPR Compliance Over ProvenanceGraphs Using SHACL", 
  "issued": {
    "date-parts": [
      [
        2018, 
        9, 
        5
      ]
    ]
  }, 
  "abstract": "<p>Semantic&nbsp; web&nbsp; technologies&nbsp; provide&nbsp; an&nbsp; open&nbsp; and&nbsp; adaptable framework for compliance regarding the General Data Protection Regulation&nbsp; (GDPR).&nbsp; Our&nbsp; previous&nbsp; work&nbsp; in&nbsp; this&nbsp; regard&nbsp; demonstrates&nbsp; the use of SPARQL for querying provenance of consent and personal data lifecycles&nbsp; for&nbsp; compliance.&nbsp; We&nbsp; extend&nbsp; this&nbsp; work&nbsp; through&nbsp; our&nbsp; model&nbsp; for evaluation of GDPR compliance using SHACL to validate the correctness and completeness of information. The model describes the creation of&nbsp; a&nbsp; compliance&nbsp; graph&nbsp; consisting&nbsp; of&nbsp; information&nbsp; required&nbsp; to&nbsp; document and&nbsp; demonstrate&nbsp; compliance&nbsp; linked&nbsp; to&nbsp; specific&nbsp; articles&nbsp; and&nbsp; obligations within the GDPR using the GDPRtEXT vocabulary.</p>", 
  "author": [
    {
      "family": "Pandit, Harshvardhan J."
    }
  ], 
  "id": "3246493", 
  "version": "preprint", 
  "type": "paper-conference", 
  "event": "Posters and Demos Track of the 14th International Conference on Semantic Systems (SEMANTiCS2018)"
}
11
11
views
downloads
All versions This version
Views 1114
Downloads 1111
Data volume 2.1 MB2.1 MB
Unique views 1112
Unique downloads 1111

Share

Cite as