Provenance is information about entities, activities, and people involved in producing a piece of data or thing, which can be used to form assessments about its quality, reliability or trustworthiness. The PROV Family of Documents defines a model, corresponding serializations and other supporting defintions to enable the inter-operable interchange of provenance information in heterogeneous environments such as the Web. This document provides an overview this family of documents.

PROV Family of Documents

This document is part of the PROV family of documents, a set of documents defining various aspects that are necessary to achieve the vision of inter-operable interchange of provenance information in heterogeneous environments such as the Web. These documents are:


This document provides a non-normative overview of the PROV Family of Documents and provides a roadmap to using these these documents. Provenance is information about entities, activities, and people involved in producing a piece of data or thing, which can be used to form assessments about its quality, reliability or trustworthiness. The goal of PROV is to enable the wide publication and interchange of provenance on the Web and other information systems. PROV enables one to represent and interchange provenance information using widely available formats such as RDF and XML. In addition, it provides definitions for accessing provenance information, validating it, and mapping to Dublin Core.

Below is the organization of PROV. At its core is a conceptual data model, which defines a common vocabulary used to describe provenance. This is instantiated by various serializations. These serializations are what are used by implementations to interchange provenance. To help developers and users create valid provenance, a set of constraints are defined, which can be used to create provenance validators. Finally, to further support the interchange of provenance, additional definitions are provided for protocols to locate and access provenance, connect sets of provenance descriptions and define how to interoperate with the widely used Dublin Core vocabulary.

Organization of PROV

Document Roadmap

PROV consists of 10 documents (including this one). In order to use PROV, one need not be familiar with all of these documents. Indeed, PROV was specifically designed so that users and developers may get started quickly with basic usage and then incrementally progress to more advanced usage scenarios To help navigate PROV, each document is broadly classified as being intended for a specific audience.
  1. Users - this audience wants to understand PROV and use applications that support PROV.
  2. Developers - this audience wants to develop or build applications that create and consume provenance using PROV.
  3. Advanced - this audience aims to create validators, new PROV serializations, or other advanced provenance systems.
In the table below, we also denote the track that each document on whether it is intended to be a W3C Recommendation or a Working Group Note.
1UsersNotePROV-PRIMER is the entry point to PROV offering an introduction to the provenance model. This is where you should start and for many may be the only document needed.
2DevelopersRecPROV-O defines a light-weight OWL2 ontology for the provenance model. This is intended for the Linked Data and Semantic Web community.
3DevelopersNotePROV-XML defines an XML schema for the provenance model. This is intended for developers who need a native XML serialization of PROV
4AdvancedRecPROV-DM defines a conceptual data model for provenance including UML diagrams. PROV-O and PROV-XML are serializations of this conceptual model.
5AdvancedRecPROV-N defines a human-readable notation for provenance. This is used to define the conceptual model as well as PROV-CONSTRAINTS.
6 AdvancedRec PROV-CONSTRAINTS defines a set constraints that define a notion of valid provenance. It is specifically aimed at the implementors of validators.
7DevelopersNotePROV-AQ defines how to use Web-based mechanisms to locate and retrieve provenance information.
8DevelopersNotePROV-DC defines a mapping between Dublin Core and PROV.
9AdvancedNotePROV-LINKS Defines extensions to PROV to enable linking provenance information across containers for provenance

Additional Information

In addition, to these specifications, the PROV FAQ page addresses common questions as well as sets PROV in a broader context. This page is continually updated. Working group members have also given several tutorials about PROV including hands-on exercises, these may be a useful place to start. In addition, one can find a variety of blog posts and web pages on PROV - a short list can be found here. For a broader review of provenance that led to the creation of PROV, there are several reports produced by the W3C Provenance Incubator group including:
  1. An Overview of Provenance on the Web (slideshow - pdf)
  2. Requirements for Provenance on the Web
  3. State of the Art Report
Finally, the simplest way to use PROV is through one of the many applications that support it.


This document has been produced by the PROV Working Group, and its contents reflect extensive discussion within the Working Group as a whole.

Members of the PROV Working Group at the time of publication of this document were: Ilkay Altintas (Invited expert), Reza B'Far (Oracle Corporation), Khalid Belhajjame (University of Manchester), James Cheney (University of Edinburgh, School of Informatics), Sam Coppens (IBBT), David Corsar (University of Aberdeen, Computing Science), Stephen Cresswell (The National Archives), Tom De Nies (IBBT), Helena Deus (DERI Galway at the National University of Ireland, Galway, Ireland), Simon Dobson (Invited expert), Martin Doerr (Foundation for Research and Technology - Hellas(FORTH)), Kai Eckert (Invited expert), Jean-Pierre EVAIN (European Broadcasting Union, EBU-UER), James Frew (Invited expert), Irini Fundulaki (Foundation for Research and Technology - Hellas(FORTH)), Daniel Garijo (Universidad Politécnica de Madrid), Yolanda Gil (Invited expert), Ryan Golden (Oracle Corporation), Paul Groth (Vrije Universiteit), Olaf Hartig (Invited expert), David Hau (National Cancer Institute, NCI), Sandro Hawke (W3C/MIT), Jörn Hees (German Research Center for Artificial Intelligence (DFKI) Gmbh), Ivan Herman, (W3C/ERCIM), Ralph Hodgson (TopQuadrant), Hook Hua (Invited expert), Trung Dong Huynh (University of Southampton), Graham Klyne (University of Oxford), Michael Lang (Revelytix, Inc.), Timothy Lebo (Rensselaer Polytechnic Institute), James McCusker (Rensselaer Polytechnic Institute), Deborah McGuinness (Rensselaer Polytechnic Institute), Simon Miles (Invited expert), Paolo Missier (School of Computing Science, Newcastle university), Luc Moreau (University of Southampton), James Myers (Rensselaer Polytechnic Institute), Vinh Nguyen (Wright State University), Edoardo Pignotti (University of Aberdeen, Computing Science), Paulo da Silva Pinheiro (Rensselaer Polytechnic Institute), Carl Reed (Open Geospatial Consortium), Adam Retter (Invited Expert), Christine Runnegar (Invited expert), Satya Sahoo (Invited expert), David Schaengold (Revelytix, Inc.), Daniel Schutzer (FSTC, Financial Services Technology Consortium), Yogesh Simmhan (Invited expert), Stian Soiland-Reyes (University of Manchester), Eric Stephan (Pacific Northwest National Laboratory), Linda Stewart (The National Archives), Ed Summers (Library of Congress), Maria Theodoridou (Foundation for Research and Technology - Hellas(FORTH)), Ted Thibodeau (OpenLink Software Inc.), Curt Tilmes (National Aeronautics and Space Administration), Craig Trim (IBM Corporation), Stephan Zednik (Rensselaer Polytechnic Institute), Jun Zhao (University of Oxford), Yuting Zhao (University of Aberdeen, Computing Science).