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Results of Questionnaire W3C PROV Vocabulary Extension Survey

The results of this questionnaire are available to anybody. In addition, answers are sent to the following email address: zednis@rpi.edu

This questionnaire was open from 2012-01-11 to 2013-03-30.

13 answers have been received.

Jump to results for question:

  1. Vocabulary Extension Information
  2. Contact Information
  3. PROV Encodings Supported
  4. Feature Coverage
  5. Provenance Exchange

1. Vocabulary Extension Information

Please provide the name and url of the vocabulary, ontology or other extension to PROV.

Details

Responder NameURLDescription
Irene Celino Human Computation ontology swa.cefriel.it/ontologies/hc The Human Computation Ontology is the specification of the entities and relations occurring in a Human Computation campaign that employs human contributors in solving a set of tasks. The Human Computation ontology is mapped to the Provenance Ontology (PROVO) to describe the results of a Human Computation approach in terms of their 'provenance', i.e. their origin within the tasks solved by human workers.
Stian Soiland-Reyes tavernaprov http://ns.taverna.org.uk/2012/tavernaprov/ Vocabulary for Taverna specific workflow run provenance. See 'Taverna'
implementation registration and https://github.com/wf4ever/taverna-prov/

Also extends the wfprov vocabulary (see separate registration) - this survey shows only particular extensions beyond wfprov. The extensions in this vocabulary proide a way to talk about value byte sizes, checksums and errors occurring in workflow runs.
Daniel Garijo The Open Provenance Model for Workflows (OPMW) http://www.opmw.org/ OPMW is an ontology for describing workflows based on the Open Provenance Model. OPMW allows the publication of workflow execution traces as well as the more abstract reusable workflows that were originally used. Since the publication of the PROV-O standard, OPMW also extends the W3C recommendation.
Palma Raul roevo http://purl.org/wf4ever/roevo roevo enables the representation of the different stages of the ROs lifecycle, their dependencies, as well as the corresponding versions of ROs and their aggregated resources, with the associated changes in these resources. Built on top of RO model within Wf4Ever project (http://www.wf4ever-project.org/).
Khalid Belhajjame wfprov http://purl.org/wf4ever/wfprov# The wfprov ontology is part of the Wf4Ever
(http://wf4ever.github.com/ro/) ontologies, which are used for
specifying research objects. The Wfprov provide the terms that are
necessary for describing the provenance of workflow execution traces,
under namespace http://purl.org/wf4ever/wfprov#.
Daniel Garijo P-plan http://purl.org/net/p-plan The Ontology for Provenance and Plans (P-Plan) is an extension of the PROV-O ontology created to represent the plans that guided the execution of scientific processes. P-Plan describes how the plans are composed and their correspondence to provenance records that describe the execution itself.
Jun Zhao Jun Zhao http://purl.org/net/provenance/ns The Provenance Vocabulary provides classes and properties for describing provenance of Web data. The vocabulary focuses on two main use cases: 1.) It enables consumers of Web data to describe provenance of data retrieved from the Web and of data derived from such Web data. 2.) It enables providers of Web data to publish provenance-related metadata about their data.
Satya Sahoo Systems molecular biology provenance ontology (SysPro) http://physiomimi.case.edu/sempod/index.php/Main_Page The Systems molecular biology provenance ontology (SysPro) is used in the Semantic Proteomics Dashboard (SemPoD) to enable researchers at the Case Center for Proteomics and Bioinformatics (CPB) to query proteomics data across projects and allow integration with legacy data. SysPro models provenance metadata together with domain information, also called semantic provenance, to support multiple query functionalities in an intuitive query interface. The SysPro ontology extends the PROV-ontology (PROV-O) and re-uses terms from existing proteomics standards, such as the minimum information required for reporting a molecular interaction experiment (MIMIx), and the minimum information about a proteomics experiment (MIAPE).

Further information at: http://physiomimi.case.edu/sempod/index.php/Main_Page
Yanfeng Shu Yanfeng Shu http://www.csiro.au/sensorweb/seff/SEFF.owl The ontology was designed to model provenance in the workflow for streamflow forecasting in the South Esk river catchment in Tasmania, Australia.
Kerry Taylor ISO_19115_Lineage http://www.w3.org/2001/sw/wiki/images/a/a1/Lineage.owl This is an OWL 2 DL extension of PROV-O that models part of the ISO 19115 UML metadata standard; in particular the concepts relating to lineage. The modelling covers the standard classes prefixed by LI_ ("lineage") and LE_("lineage extended") and provides placeholders for the other classes referenced by them. The intention of this ontology is to enable ISO lineage records (typically presented in XML) to be re-presented according to this ontology and therefore supporting interoperability with other PROV-O provenance records. The design has treated PROV-O as an upper ontology extended with the ISO 1195 concepts, faithfully carrying through the names and structure of the ISO 19115. As a result the design may well differ from both a direct translation of the UML to OWL and also from a fresh attempt to model the ISO 19115 content in PROV-O.
Stian Soiland-Reyes PAV Provenance, Authoring and Versioning http://purl.org/pav/2.1/ PAV is a lightweight ontology for tracking Provenance, Authoring and Versioning. PAV specializes the W3C provenance ontology PROV-O in order to describe authorship, curation and digital creation of online resources.

PAV supplies terms for distinguishing between the different roles of the agents contributing content in current web based systems: contributors, authors, curators and digital artifact creators. The ontology also provides terms for tracking provenance of digital entities that are published on the web and then accessed, transformed and consumed.
Ali Mufajjul cProv http://orangelabs.com/cprov# cProv is an extended vocabulary (Prov) for the cloud based services. It defines additional subset nodes, edges and properties in order to provide a greater expressive capability required for the complex cloud domain.
Timothy Lebo PML 3.0 https://github.com/timrdf/pml PROV-O extension to include concepts from Proof Markup Language 2.0.

2. Contact Information

Details

Responder NameEmail
Irene Celino Irene Celino irene.celino@gmail.com
Stian Soiland-Reyes Stian Soiland-Reyes soiland-reyes@cs.manchester.ac.uk
Daniel Garijo Daniel Garijo dgarijo@fi.upm.es
Palma Raul Raul Palma rpalma@man.poznan.pl
Khalid Belhajjame Khalid Belhajjame Khalid.Belhajjame@cs.man.ac.uk
Daniel Garijo Daniel Garijo dgarijo@fi.upm.es
Jun Zhao Jun Zhao/Olaf Hartig jun.zhao@zoo.ox.ac.uk / ohartig@uwaterloo.ca
Satya Sahoo Catherine Jayapandian, Satya Sahoo sempodcwru@googlegroups.com
Yanfeng Shu Yanfeng Shu yanfeng.shu@csiro.au
Kerry Taylor Kerry Taylor Kerry.Taylor@csiro.au
Stian Soiland-Reyes Stian Soiland-Reyes soiland-reyes@cs.manchester.ac.uk
Ali Mufajjul Mufajjul Ali mufajjul.ali@orange.com
Timothy Lebo Timothy Lebo lebot@rpi.edu

3. PROV Encodings Supported

summary | by responder | by choice

Choose all that apply

Summary

ChoiceAll responders
Results
PROV-O 12
PROV-N 1
PROV-XML 1

Skip to view by choice.

View by responder

Details

Responder PROV Encodings SupportedPlease list any additional supported encodings (e.g. PROV-JSON, PROV-CSV, etc.) in the free-text area below
Irene Celino
  • PROV-O
Stian Soiland-Reyes
  • PROV-O
Daniel Garijo
  • PROV-O
Palma Raul
  • PROV-O
Khalid Belhajjame
  • PROV-O
Daniel Garijo
  • PROV-O
Jun Zhao
  • PROV-O
Satya Sahoo
  • PROV-O
 None
Yanfeng Shu
  • PROV-O
Kerry Taylor
  • PROV-O
 none
Stian Soiland-Reyes
  • PROV-O
Ali Mufajjul
  • PROV-N
  • PROV-XML
Timothy Lebo
  • PROV-O

View by choice

ChoiceResponders
PROV-O
  • Irene Celino
  • Stian Soiland-Reyes
  • Daniel Garijo
  • Palma Raul
  • Khalid Belhajjame
  • Daniel Garijo
  • Jun Zhao
  • Satya Sahoo
  • Yanfeng Shu
  • Kerry Taylor
  • Stian Soiland-Reyes
  • Timothy Lebo
PROV-N
  • Ali Mufajjul
PROV-XML
  • Ali Mufajjul

4. Feature Coverage

Indicate covered features by selecting one of the following below:

  • 1) I Don't Know
  • 2) Used Directly
  • 3) Extended

Summary

ChoiceAll responders
123No opinion
Entity 12 1
Activity 12 1
Agent 3 7 3
Generation 5 6 2
Usage 5 6 2
Communication 1 2 10
Derivation 1 4 8
Attribution 2 5 6
Association 4 5 4
Delegation 2 1 10
Start 4 9
End 4 1 8
Invalidation 1 1 11
Revision 1 1 2 9
Quotation 1 2 10
PrimarySource 1 2 10
Person 2 3 8
Organization 1 2 10
SoftwareAgent 2 1 4 6
Plan 2 7 4
Influence 4 2 7
Bundle 1 2 10
Specialization 2 11
Alternate 2 11
Collection 1 12
EmptyCollection 1 12
Membership 1 12
Identifier 1 12
Attributes 2 11
Label 1 12
Location 1 3 2 7
Role 1 4 8
Type 1 12
Value 3 10

Averages:

Choices All responders:
Value
Entity3.00
Activity3.00
Agent2.70
Generation2.55
Usage2.55
Communication2.67
Derivation2.80
Attribution2.71
Association2.56
Delegation2.33
Start2.00
End2.20
Invalidation2.50
Revision2.25
Quotation1.67
PrimarySource1.67
Person1.60
Organization1.67
SoftwareAgent2.29
Plan2.78
Influence2.33
Bundle2.67
Specialization2.00
Alternate2.00
Collection2.00
EmptyCollection1.00
Membership2.00
Identifier1.00
Attributes2.00
Label2.00
Location 2.17
Role2.80
Type2.00
Value2.00

Details

Responder EntityActivityAgentGenerationUsageCommunicationDerivationAttributionAssociationDelegationStartEndInvalidationRevisionQuotationPrimarySourcePersonOrganizationSoftwareAgentPlanInfluenceBundleSpecializationAlternateCollectionEmptyCollectionMembershipIdentifierAttributesLabelLocation RoleTypeValueRationale
Irene Celino 3 3 3 3 3 3 3 3 3 No opinion No opinion No opinion No opinion No opinion No opinion No opinion 1 No opinion 1 No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion 1 No opinion No opinion No opinion
Stian Soiland-Reyes 3 3 No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion 3 3 No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion 2 No opinion No opinion 3 No opinion No opinion It's difficult to say how a vocabulary is 'using' another term when doing an owl import. Above I've highlighted terms that this vocabulary extends, even though those are extending the wfprov vocabulary (which extends PROV-O), but I have not marked terms that are used or extended in wfprov. The implementation using this vocabulary will use many of the PROV-O terms natively, but this is not expressed by this vocabulary registration. (See registration for Taverna)
Daniel Garijo 3 3 2 2 2 No opinion No opinion 2 2 No opinion No opinion No opinion No opinion No opinion No opinion 2 No opinion No opinion No opinion 3 2 3 No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion 2 No opinion No opinion 2
Palma Raul 3 3 2 3 3 No opinion 2 3 2 No opinion 2 2 No opinion 2 2 2 No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion
Khalid Belhajjame 3 3 3 3 3 No opinion No opinion No opinion 3 No opinion 2 2 No opinion No opinion No opinion No opinion No opinion No opinion 3 3 No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion 3 No opinion No opinion
Daniel Garijo 3 3 No opinion 2 2 No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion 3 2 3 No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion See http://www.opmw.org/model/p-plan/
Jun Zhao 3 3 3 3 3 No opinion No opinion No opinion 3 3 No opinion 3 No opinion 3 No opinion No opinion No opinion No opinion No opinion 3 No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion - For those terms that are not used or extended we chose the default “No opinion”
- For those terms that are both extended and directly used, we chose the former.
Satya Sahoo 3 3 3 2 2 No opinion No opinion No opinion No opinion No opinion 2 2 No opinion No opinion No opinion No opinion 2 No opinion 2 2 No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion 2 3 No opinion No opinion Though many molecular system biology research centers now have significant infrastructure in terms of instrumentation to acquire ‘omics datasets, most of these datasets end up in study-specific data silos. SemPoD, using SysPro, enables cross-linking datasets across ‘omics and clinical studies as part of the translational research roadmap, facilitates integration with legacy data, and allows seamless query across different types of data.

SysPro captures the experimental conditions or provenance, for example sample type, instrumentation, sample preparation, and statistical measures, to facilitate integration, filtering, and query research data in the Case CPB.
Yanfeng Shu 3 3 3 2 2 2 No opinion 2 2 2 No opinion No opinion No opinion No opinion No opinion No opinion 2 2 3 No opinion 2 No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion 3 No opinion No opinion No opinion only data products, steps, and people or organisations involved were captured as provenance, but not detailed usage, generation, or other influence information.
Kerry Taylor 3 3 3 2 3 No opinion No opinion No opinion 2 No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion 3 No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion These were the features we needed to map the intension of the ISO lineage model
Stian Soiland-Reyes No opinion No opinion No opinion No opinion No opinion No opinion 3 3 No opinion No opinion No opinion No opinion No opinion 3 No opinion No opinion No opinion No opinion No opinion No opinion 3 No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion No opinion All PAV properties are going from the same resource, a prov:Entity equivalent, going to either an Entity or Agent equivalent. There are no activities detailed in PAV.

No classes are defined in PAV, so the Entity/Agent "use" is only indirectly through the use of subproperties of PROV properties prov:wasAttributedTo, prov:wasDerivedFrom, prov:wasRevisionOf and prov:wasInfluencedBy.
Ali Mufajjul 3 3 2 3 2 3 3 3 3 2 2 2 2 1 1 1 1 1 1 2 2 2 2 2 2 1 2 1 2 2 2 2 2 2 These were needed to express the complex relationships and dependencies that exists in cloud-based services.
Timothy Lebo 3 3 3 3 3 No opinion 3 3 3 No opinion No opinion No opinion 3 No opinion 2 No opinion 2 2 3 3 3 No opinion 2 2 No opinion No opinion No opinion No opinion No opinion No opinion 3 3 No opinion 2

5. Provenance Exchange

Is this vocabulary extension generated or consumed by an implementation, which one(s)?

Details

Responder Provenance Exchange
Irene Celino Yes, this is used by the Urbanopoly application to record what users do to solve their human computation tasks and the system to aggregate their answers. The resulting data are published as linked data at http://swa.cefriel.it/linkeddata.
Stian Soiland-Reyes Taverna
Daniel Garijo The Wings provenance generator is the responsible for the creation of data from this vocabulary. The data is available in a sparql endpoint: http://wwww.opmw.org/sparql, and it is consumed by a couple of visualizers for showing their results (I don't have the URLs now).
Palma Raul roevo API (http://www.wf4ever-project.org/wiki/display/docs/RO+evolution+API)
RODL (http://sandbox.wf4ever-project.org/rodl/)
Wf-RO transformation service (http://sandbox.wf4ever-project.org/wf-ro; documentation:http://www.wf4ever-project.org/wiki/display/docs/Wf-RO+transformation+service )
ro-manager (https://github.com/wf4ever/ro-manager)
Khalid Belhajjame wfprov is used by Taverna-PROV (https://github.com/wf4ever/taverna-prov), a Taverna plugin for the Taverna Workbench and Taverna Command Line, which allows exporting the provenance traces of a workflow run.
Daniel Garijo This vocabulary is compatible with the OPMW representation.
Jun Zhao Information expressed using the Provenance Vocabulary can be generated by the plug-ins to the D2RServer (http://www4.wiwiss.fu-berlin.de/bizer/d2r-server/), Triplify (http://triplify.org/), and Pubby (http://www4.wiwiss.fu-berlin.de/pubby/).
Satya Sahoo SemPoD application
Yanfeng Shu yes. It was consumed by a provenance management system. The provenance traces can be accessed by https://github.com/provbench/CSIRO-PROV
Kerry Taylor not at present but is planned
Stian Soiland-Reyes Used by:
* Wf4Ever Research Objects model v0.2 (to be released at http://purl.org/wf4ever/model)
* Domeo annotation framework (http://www.annotationframework.org/)
* Annotation Ontology (http://code.google.com/p/annotation-ontology/)
* AlzSWAN (http://hypothesis.alzforum.org/)
* Nanopublications guidelines (http://www.nanopub.org/guidelines/current)
* Elsevier Satellite format (http://dcpapers.dublincore.org/pubs/article/download/3636/1862 )
Ali Mufajjul The vocabulary extension was generated, and it is to be consumed by an implementation.
Timothy Lebo csv2rdf4lod-automation

More details on responses

  • Timothy Lebo: last responded on 13, February 2013 at 15:45 (UTC)

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