The Decision Provenance ontology
This ontology is for modelling decisions and thus the causes for actions or the use or generation of things. It allows for a better understanding of why something might have taken place, have been used or produced than the more generic PROV ontology, on which it is mainly based, does.
The specialised decision modelling elements of this ontology have been derived from the W3C Decisions and Decision-Making Incubator Group's Decision Ontology (DO) which can be found at https://github.com/nicholascar/decision-o. Many DO classes have been aligned with the PROV-O since it is widely recognised that analysing the elements of decisions post hoc is an exercise in provenance.
Unlike the original DO, this ontology cannot be used for normative scenarios: it is only capable of recording decisions that have already been made (so-called data-driven use in the DO). This is because PROV does not have a templating system which can indicate what should occur in future scenarios.
This ontology introduces only one new element for decision modelling over that which was present in the DO: an Agent which allows agency in decision making to be recorded.
NOTE: this ontology is now in Version 2.0 release however not all examples are updated to match the new version's modelling.
Namespace location:
- HTML: http://promsns.org/def/decprov
- RDF turtle: http://promsns.org/def/decprov.ttl
Local copies:
- HTML: decprov.html
- RDF Turtle: decprov.ttl
Figure 1: An Overview of the DecPROV classes and main relationships**
See MODELLING for a description of the choices made about classes in DecPROV, including why certain Decision Ontology classes were included, excluded or changed.
See EXAMPLES.
This ontology and all other content in this repository are licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) (local copy of deed: LICENSE).
Nicholas Car
Data Systems Architect
SURROUND Australia Pty Ltd
(formerly of Geoscience Australia & CSIRO)
nicholas.car@surroundaustralia.com
http://orcid.org/0000-0002-8742-7730