Abstract

Data provenance refers to the relationships between data items, activities on those items, and agents. In 2013, W3C presented PROV-DM as a conceptual data model. The Open Provenance Model (OPM) is a precursor to the PROV-DM standard. Many applications have started using PROV and extending it for representing provenance across different domains. But we are still far from solving provenance-related issues. While provenance is widely considered important, designers lack guidelines for how to develop and incrementally improve provenance collection and use. This paper is an attempt to “read” such models using a new diagrammatic language called Flowthing Machines (FM). The aim with FM is to (i) shed some light on provenance and description and ontology, and (ii) make a contribution that might impact fundamental ideas in modeling of provenance.

Published in: International Conference on Information Society (i-Society 2018)

  • Date of Conference: 15-18 July 2018
  • DOI: 10.2053/iSociety.2018.0002
  • ISBN: 978-1-908320-92-6
  • Conference Location: Dublin, Ireland