Invited talk at the National Institute of Informatics (NII), Tokyo, July 2014

1. NII,Tokyo,July2014–PaoloMissier
The W3C PROV standard:
data model for the provenance of information,
and enabler for trustworthy publication
and exchange of open data
Paolo Missier, PhD
School of Computing Science
Newcastle University
Newcastle upon Tyne, UK
NII, Tokyo, July, 2014

2. NII,Tokyo,July2014–PaoloMissier
Motivation: generating and publishing genomics data
• Next Generation Sequencing at the forefront of genomics
• the number of DNA base pairs that can be sequenced per $ doubles every five
months (2010)
• In the UK, the cost of sequencing a single patient sample is currently just under
$1.5K and decreasing
• Genetic testing: from research method to clinical diagnostic tool
• Key technology: Whole-exome / Whole-genome processing
pipelines (WEP/WGP)
• Key problem: assessing the reliability of the results
Goal of data processing and interpretation:
to rapidly identify genetic mutations across the entire genome, which:
• Have known associations to genetic diseases
• Are unknown but potentially deleterious
Specifically important in the study of rare diseases

3. NII,Tokyo,July2014–PaoloMissier
Data publication and reuse in science/biology/genomics
Public, genome-wide gene expression data is potentially highly
reusable
Rung, Johan, and Alvis Brazma. “Reuse of Public Genome-Wide Gene Expression Data.”
Nature Reviews. Genetics 14, no. 2 (March 2013): 89–99. doi:10.1038/nrg3394.
But:
• Published data must be provably correct, trustworthy
Approximately half of the studies that use public gene expression data rely
solely on existing data without adding newly generated data, and half of
them use the public data in combination with new data.
Problem:
• A large WEP/ WES space, many experimental
configurations, many possible results

4. NII,Tokyo,July2014–PaoloMissier
Workflow for programming pipelines

5. NII,Tokyo,July2014–PaoloMissier
Multiple Workflow systems for implementing pipelines…
[1] Torri, Federica, Ivo D Dinov, Alen Zamanyan, Sam Hobel, Alex Genco, Petros Petrosyan, Andrew
P Clark, et al. “Next Generation Sequence Analysis and Computational Genomics Using
Graphical Pipeline Workflows.” Genes 3, no. 3 (August 30, 2012): 545–575.
doi:10.3390/genes3030545.
[2] Goecks, Jeremy, Anton Nekrutenko, and James Taylor. “Galaxy: A Comprehensive Approach for
Supporting Accessible, Reproducible, and Transparent Computational Research in the Life
Sciences.” Genome Biology 11, no. 8 (January 2010): R86. doi:10.1186/gb-2010-11-8-r86.
[3] Reid, Jeffrey, Andreq Carroll, Narayanan Veeraraghavan, and Mahmoud Dahdouli. “Launching Genomics
into the Cloud: Deployment of Mercury, a next Generation Sequence Analysis Pipeline.” BMC
Bioinformatics (2014).
Loni pipeline (UCLA, USA) [1]
Newcastle, UK [4]
Mercury [3]
Baylor College of Medicine,
Houston. Tx., USA)
[2]
[4] Watson, Paul, Hugo Hiden, and Simon Woodman. “E-Science Central for CARMEN:
Science as a Service.” Concurrency and Computation: Practice and Experience 22, no. 17
(2010): 2369–2380. doi:10.1002/cpe.1611.

6. NII,Tokyo,July2014–PaoloMissier
Multiple Pipeline configurations
Many tools to choose from, multiple ways to configure each tool
From: Pabinger, Stephan, Andreas Dander, Maria Fischer, Rene Snajder, Michael Sperk, Mirjana
Efremova, Birgit Krabichler, Michael R Speicher, Johannes Zschocke, and Zlatko Trajanoski. “A
Survey of Tools for Variant Analysis of next-Generation Genome Sequencing Data.” Briefings in
Bioinformatics (January 21, 2013): bbs086–. doi:10.1093/bib/bbs086.

7. NII,Tokyo,July2014–PaoloMissier
… and different configurations yield very different results
Outcomes are very sensitive to pipeline configuration
False positives, false negatives
The set of genetic mutations identified in one individual may vary
greatly depending on the tools used
Also: tools evolve over time  longitudinal variations over results

8. NII,Tokyo,July2014–PaoloMissier
The Cloud-e-Genome project
Goal 1:
provide mechanisms to rapidly and flexibly
create new WEP pipelines, and to deploy them
in a scalable way;
Goal 2:
provide clinicians with a tool for analysis
and interpretation of human variants
• 2 year pilot project
• Funded by UK’s National Institute for Health Research (NIHR)
through the Biomedical Research Council (BRC)
Challenge:
to deliver the benefits of WES/WGS technology to clinical practice
NGS data processing
Human variant
interpretation for
clinical diagnosis

9. NII,Tokyo,July2014–PaoloMissier
Implementing the pipeline using workflow technology

10. NII,Tokyo,July2014–PaoloMissier
Pipeline evolution
Pipeline:
set C = { c1 … cn } of components -- tool wrappers
Each ci has a configuration conf(ci) and a version v(ci)
…and why
• Technology / algorithm evolution
• Traditional GATK variant caller 
GATK haplotype caller
• Does the interface change?
• Do the operational assumptions
change?
Eg. GATK Variant Recalibrator
requires large input data. Not suitable for
targeted sequencing
What can change
1 – Tool version:
v(ci)  v’(ci)
2 - Tool replacement / add / remove:
ci  c’I
3 – Configuration parameters
conf(ci)  conf’(ci)
(*) S. Pabinger, A. Dander, M. Fischer, R. Snajder, M. Sperk, M. Efremova, B. Krabichler, M. R. Speicher, J.
Zschocke, and Z. Trajanoski, “A survey of tools for variant analysis of next-generation genome sequencing data.”
Briefings in bioinformatics, pp. bbs086–, Jan. 2013
Just for sequence alignment Pabinger et al. in their survey (*) list 17 aligners while
for variant annotation they refer to over 70 tools

11. NII,Tokyo,July2014–PaoloMissier
How do you know published results are sound?
Mechanisms for data dissemination exist
Data journals
Data repositories
Data structures: Research Objects
(from ResearchObject.org)
Bechhofer, Sean, Iain Buchan, David De Roure, Paolo Missier, J. Ainsworth, J. Bhagat, P.
Couch, et al. “Why Linked Data Is Not Enough for Scientists.” Future Generation Computer
Systems (2011). doi:doi:10.1016/j.future.2011.08.004.
… but they are not enough to meet two key requirements:
• Attribution of published data to its producers
• Verifiability and reproducibility of scientific results

12. NII,Tokyo,July2014–PaoloMissier
Role of provenance
Provenance refers to the sources of information, including entities
and processes, involving in producing or delivering an artifact (*)
Provenance is a description of how things came to be, and how
they came to be in the state they are in today (*)
• Provenance is evidence in support of clinical diagnosis
1. Why do these variants appear in the output list?
2. Why have you concluded they are disease-causing?
• Requires ability to trace variants through workflow execution
• Workflow managers provide this
“Why are these variants included in the results?”
“Why do these two results differ?”

13. NII,Tokyo,July2014–PaoloMissier
Why does provenance matter?
• To establish quality, relevance, trust
• To track information attribution through complex transformations
• To describe one’s experiment to others, for understanding / reuse
• To provide evidence in support of scientific claims
• To enable process analysis for debugging, improvement,
evolution

14. NII,Tokyo,July2014–PaoloMissier The W3C Working Group on Provenance:
timeline
1
4
W3C
Incubator group
on provenance
Chair: Yolanda Gil,
ISI, USC
W3C
working group
approved
Chairs:
Luc Moreau,
Paul Groth
2009-2010
Main output:
“Provenance XG Final Report”
http://www.w3.org/2005/Incubator/prov/XGR-prov/
- provides an overview of the various existing
approaches, vocabularies
- proposes the creation of a dedicated W3C Working
Group
April, 2011 April, 2013
Proposed
Recommendations
finalised
prov-dm: Data Model
prov-o: OWL ontology, RDF encoding
prov-n: prov notation
prov-constraints
...plus a number of non-prescriptive
Notes
http://www.w3.org/2011/prov/wiki/

15. NII,Tokyo,July2014–PaoloMissier PROV: scope and structure
1
5
source: http://www.w3.org/TR/prov-overview/
Recommendation
track

16. NII,Tokyo,July2014–PaoloMissier PROV Core Elements (graph depiction)
1
6
An entity is a physical, digital, conceptual, or other kind of thing with some fixed
aspects; entities may be real or imaginary.
An activity is something that occurs over a period of time and acts upon or with entities; it
may include consuming, processing, transforming, ..., using, or generating entities.
An agent is something that bears some form of responsibility for an activity taking place,
for the existence of an entity, or for another agent's activity.
Jump to alternate

17. NII,Tokyo,July2014–PaoloMissier Generation, Usage
1
7
Generation is the completion of production of a new entity by an activity. This entity did not
exist before generation and becomes available for usage after this generation.
Usage is the beginning of utilizing an entity by an activity. Before usage, the activity had
not begun to utilize this entity
PROV is based on a notion of instantaneous events, that mark transitions in the world
- generation, usage (and others)
Ordering constraints amongst events:
“generation of e must precede each of usages”
“a can only use / generate e after it has started and before it has ended”

18. NII,Tokyo,July2014–PaoloMissier Concepts and relations
1
8
Generation of “draft v1” expressed as relation:
wasGeneratedBy(“draft v1”, ...)
Usage of “draft v1” by “commenting” expressed as relation:
used(“commenting, “draft v1”,...)

19. NII,Tokyo,July2014–PaoloMissier PROV notation
1
9
document
prefix prov <http://www.w3.org/ns/prov#>
prefix ex <http://www.example.com/>
entity(ex:draftComments)
entity(ex:draftV1, [ ex:distr='internal', ex:status = "draft"])
entity(ex:paper1)
entity(ex:paper2)
activity(ex:commenting)
activity(ex:drafting)
wasGeneratedBy(ex:draftComments, ex:commenting, 2013-03-18T11:10:00)
used(ex:commenting, ex:draftV1, -)
wasGeneratedBy(ex:draftV1, ex:drafting, -)
used(ex:drafting, ex:paper1, -)
used(ex:drafting, ex:paper2, -)
endDocument

20. NII,Tokyo,July2014–PaoloMissier Same example — PROV-O notation (RDF/N3)
2
0
:draftComments a prov:Entity ;
:distr "internal"^^xsd:string ;
prov:wasGeneratedBy :commenting .
:commenting a prov:Activity ;
prov:used :draftV1 .
:draftV1 a prov:Entity ;
:distr "internal"^^xsd:string ;
:status "draft"^^xsd:string ;
:version "0.1"^^xsd:string ;
prov:wasGeneratedBy :drafting .
:drafting a prov:Activity ;
prov:used :paper1,
:paper2 .
:paper1 a prov:Entity,
"reference"^^xsd:string .
:paper2 a prov:Entity,
"reference"^^xsd:string .

21. NII,Tokyo,July2014–PaoloMissier Association, Attribution, Delegation: who did what?
2
1
An activity association is an assignment of responsibility to an agent for an activity,
indicating that the agent had a role in the activity.
Attribution is the ascribing of an entity to an agent.
entity(ex:draftComments, [ ex:distr='internal' ])
activity(ex:commenting)
agent(ex:Bob, [prov:type = "mainEditor"] )
agent(ex:Alice, [prov:type = "srEditor"])
wasAssociatedWith(ex:commenting, Bob, -, [prov:role = "editor"])
actedOnBehalfOf(Bob, Alice)
wasAttributedTo(ex:draftComments, ex:Bob)

22. NII,Tokyo,July2014–PaoloMissier Same example — PROV-O notation (RDF/N3)
2
2
:Alice a prov:Agent,
"ex:chiefEditor";
:firstName "Alice";
:lastName "Cooper".
:Bob a prov:Agent,
"ex:seniorEditor";
:firstName "Robert";
:lastName "Thompson"^;
prov:actedOnBehalfOf :Alice .
:draftComments prov:wasAttributedTo :Bob .
:drafting a prov:Activity ;
prov:wasAssociatedWith :Bob .

23. NII,Tokyo,July2014–PaoloMissier Association and Attribution
2
3
Q.: what is the relationship between attribution and association?
This is defined as an inference rule in the PROV-CONSTR document
entity(e)
agent(Ag)
activity(a)
wasAttributedTo(e, Ag)
wasGeneratedBy(e, a)
wasAssociatedWith(a, Ag)

24. NII,Tokyo,July2014–PaoloMissier Communication amongst activities
2
4
Communication is the exchange of some unspecified entity by two
activities, one activity using some entity generated by the other.
activity(ex:commenting)
activity(ex:drafting)
wasInformedBy(ex:commenting, ex:drafting)
:drafting a prov:Activity .
:commenting a prov:Activity ;
prov:wasInformedBy :drafting .

25. NII,Tokyo,July2014–PaoloMissier Communication, generation, usage
2
5
activity(ex:commenting)
activity(ex:drafting)
entity(e)
wasInformedBy(ex:commenting, ex:drafting)
wasGeneratedBy(e,ex:drafting)
used(ex:commenting, e)
Q.: what is the relationship between communication, generation, and usage?
This are inference rules 5 and 6 in the PROV-CONSTR document

26. NII,Tokyo,July2014–PaoloMissier Summary of the PROV Core model
2
6

27. NII,Tokyo,July2014–PaoloMissier Derivation amongst entities
2
7
A derivation is a transformation of an entity into another, an update of an entity
resulting in a new one, or the construction of a new entity based on a pre-existing
entity.
entity(ex:draftV1)
entity(ex:draftComments)
wasDerivedFrom(ex:draftComments, ex:draftV1)
Q.: what is the relationship between derivation, generation, and usage?
:draftComments a prov:Entity ;
prov:wasDerivedFrom :draftV1 .
:draftV1 a prov:Entity .

28. NII,Tokyo,July2014–PaoloMissier Relations may be given identifiers
2
8
entity(ex:draftComments)
entity(ex:draftV1)
activity(ex:commenting)
wasGeneratedBy(gen1; ex:draftComments, ex:commenting, -)
used(use1; ex:commenting, ex:draftV1, -)
gen1 denotes a generation event
use1 denotes a usage event
wasDerivedFrom(id; e2, e1, a, g2, u1, attrs)
General derivation relation:
Relation IDs make it possible to refer to relations in other relations

29. NII,Tokyo,July2014–PaoloMissier Rendering N-ary relations in PROV-O
2
9
RDF is for binary relations —- N-ary relations require reification
entity(ex:draftComments)
entity(ex:draftV1)
activity(ex:commenting)
wasGeneratedBy(gen1; ex:draftComments,
ex:commenting,
2013-03-18T10:00:01)
used(use1; ex:commenting, ex:draftV1, -)
:draftComments a prov:Entity ;
prov:qualifiedGeneration :gen1 .
:gen1 a prov:Generation ;
prov:activity :commenting;
prov:atTime “2013-03-18T10:00:01+09:00".
:commenting a prov:Activity ;
prov:qualifiedUsage :use1 .
:use1 a prov:Usage ;
:note "found comments useful";
prov:atTime "2013-03-21T10:00:01+09:00";
prov:entity :draftV1.

30. NII,Tokyo,July2014–PaoloMissier “Qualified relation” RDF pattern
3
0
:draftComments a prov:Entity ;
prov:qualifiedGeneration :gen1 .
:gen1 a prov:Generation ;
prov:activity :commenting;
prov:atTime “2013-03-18T10:00:01+09:00".
:commenting a prov:Activity ;
prov:qualifiedUsage :use1 .
:use1 a prov:Usage ;
:note "found comments useful";
prov:atTime "2013-03-21T10:00:01+09:00";
prov:entity :draftV1.

31. NII,Tokyo,July2014–PaoloMissier Plans — why was something done?
3
1
Most relation types have two arguments which are { Entity, Activity, Agent}
Derivation is one exception:
wasDerivedFrom(id; e2, e1, a, g2, u1, attrs)
Two other notable exceptions:
- Associations with a plan
- Delegation with an activity scope
wasAssociatedWith(id; a, ag, pl, attrs)
A plan is an entity that represents a set of actions or steps
intended by one or more agents to achieve some goal

32. NII,Tokyo,July2014–PaoloMissier Association with a plan
3
2
A plan plays a role in an association

33. NII,Tokyo,July2014–PaoloMissier Plans are typed entities
3
3
activity(ex:_aProgramExecution, [ex:execTime="22.5sec"])
agent(ex:_aJVM, [prov:type = “JVM-6.0”])
entity(ex:myCleverProgram,
[prov:type='prov:Plan', ex:label="Program 1"])
wasAssociatedWith(ex:_aProgramExecution, ex:_aJVM,
ex:myCleverProgram,
[prov:role="defaultRuntime",
ex:accessPath="webapp" ])
A plan is an entity having prov:type = “prov:plan”

34. NII,Tokyo,July2014–PaoloMissier Plan pattern as PROV-O
3
4
:_aProgramExecution a prov:Activity ;
:execTime "22.5sec;
prov:qualifiedAssociation [ a prov:Association ;
:accessPath "webapp";
prov:agent :_aJVM ;
prov:hadPlan :myCleverProgram ;
prov:hadRole "defaultRuntime"] .
:_aJVM a prov:Agent, “Java-6.0".
:myCleverProgram a prov:Entity, prov:Plan.
activity(ex:_aProgramExecution, [ex:execTime="22.5sec"])
agent(ex:_aJVM, [prov:type = “JVM-6.0”])
entity(ex:myCleverProgram,
[prov:type='prov:Plan', ex:label="Program 1"])
wasAssociatedWith(ex:_aProgramExecution, ex:_aJVM,
ex:myCleverProgram,
[prov:role="defaultRuntime",
ex:accessPath="webapp" ])

35. NII,Tokyo,July2014–PaoloMissier Plan pattern as PROV-O
3
5
:_aProgramExecution a prov:Activity ;
:execTime "22.5sec;
prov:qualifiedAssociation [ a prov:Association ;
:accessPath "webapp";
prov:agent :_aJVM ;
prov:hadPlan :myCleverProgram ;
prov:hadRole "defaultRuntime"] .
:_aJVM a prov:Agent, “Java-6.0".
:myCleverProgram a prov:Entity, prov:Plan.

36. NII,Tokyo,July2014–PaoloMissier Delegation within an activity scope
3
6

37. NII,Tokyo,July2014–PaoloMissier
Real-world artifacts vs provenance entities
3
7
ref: http://www.w3.org/2001/sw/wiki/PROV-FAQ#Examples_of_Provenance
“What do I know about the car I see in this Cambridge street today?”
•It was bought by Joe in 2011
•Joe drove it to Boston on March 16th,
2013. The car has now got 10,000 miles
on it
•Joe drove it to Cambridge on March
18th, 2013.
“Same” car, but different provenance at
each stage of its evolution
To Core
Elements

38. NII,Tokyo,July2014–PaoloMissier Alternate-specialization pattern
3
8
Two alternate entities present aspects of the same thing. These aspects may be the same or
different, and the alternate entities may or may not overlap in time.
An entity that is a specialization of another shares all aspects of the latter, and additionally
presents more specific aspects of the same thing as the latter.
...But, this is still that car!
Semantic notes:
1. Specialization implies alternate: IF specializationOf(e1,e2) THEN alternateOf(e1,e2).
2. Alternate is symmetric: IF alternateOf(e1,e2) THEN alternateOf(e2,e1)
3. Specialization is transitive: IF specializationOf(e1,e2) and specializationOf(e2,e3) THEN specializationOf(e1,e3).
To Core
Elements
differing in their
location
same owner,
added location

39. NII,Tokyo,July2014–PaoloMissier Reserved attributes and types
3
9
A small set of reserved attributes, with some usage restrictions

40. NII,Tokyo,July2014–PaoloMissier Bundles, provenance of provenance
4
0
A bundle is a named set of provenance descriptions, and is itself an entity,
so allowing provenance of provenance to be expressed.
bundle pm:bundle1
entity(ex:draftComments)
entity(ex:draftV1)
activity(ex:commenting)
wasGeneratedBy(ex:draftComments, ex:commenting,-)
used(ex:commenting, ex:draftV1, -)
endBundle
...
entity(pm:bundle1, [ prov:type='prov:Bundle' ])
wasGeneratedBy(pm:bundle1, -, 2013-03-20T10:30:00)
wasAttributedTo(pm:bundle1, ex:Bob)

41. NII,Tokyo,July2014–PaoloMissier Bundles in PROV-O
4
1
Bundle definition (an RDF named graph):
ex:bundle1 {
:draftComments a prov:Entity ;
:status “blah";
prov:wasGeneratedBy :commenting .
:commenting a prov:Activity ;
prov:used :draftV1 .
:draftV1 a prov:Entity .
}
Bundle usage:
ex:bundle1 a prov:Entity, "prov:Bundle";
prov:qualifiedGeneration [ a prov:Generation ;
prov:atTime “2013-03-20T10:30:00+09:00" ];
prov:wasAttributedTo :Bob .

42. NII,Tokyo,July2014–PaoloMissier Time, Events
4
2
wasStartedBy(id; a2, e, a1, t, attrs)
wasEndedBy(id; a2, e, a1, t, attrs)
Instead, the PROV data model is implicitly based on a notion of
instantaneous events, that mark transitions in the world (*)
(*) PROV-CONSTR http://www.w3.org/TR/prov-constraints/#events (non-normative)
Events:
- activity start, activity end,
- entity generation , entity usage, entity invalidation
- Provenance statements are combined by different systems
- An application may not be able to align the times involved to a single
global timeline
Therefore, PROV minimizes assumptions about time

43. NII,Tokyo,July2014–PaoloMissier From “scruffy” provenance to “valid” provenance
4
3
- Are all possible temporal partial ordering of events equally acceptable?
- How can we specify the set of all valid orderings?
More generally, how do we formally define what it means for a set of
provenance statements to be valid?
PROV defines a set of temporal constraints that ensure consistency
of a provenance graph

44. NII,Tokyo,July2014–PaoloMissier
Exploiting provenance: why do my results differ from yours?
Run pipeline version V1
V1  V2:
Replace BWA version
Modify Annovar configuration parameters
Variant list
VL1
Variant list
VL2Run pipeline version V2
??
Variant list
VL1
Variant list
VL2
DDIFF
(data differencing)
PDIFF
(provenance differencing)
Missier, Paolo, Simon Woodman, Hugo Hiden, and Paul Watson. “Provenance and Data Differencing
for Workflow Reproducibility Analysis.” Concurrency and Computation: Practice and Experience
(2013): doi:10.1002/cpe.3035.

45. NII,Tokyo,July2014–PaoloMissier
PDIFF - overview
WA
WB

46. NII,Tokyo,July2014–PaoloMissier
The corresponding provenance traces
d1
S0
S0'
w h
S3 S2
y z
S4
x
k
S1
d2
d1'
S0
k'h'
S3'
S2v2
w'
S3
S4
y' z'
x'
S5
d2
(i) Trace A (ii) Trace B
P0 P1
P0 P1
P0 P0 P1P1
S Sv2
d0 d0

47. NII,Tokyo,July2014–PaoloMissier
Delta graph computed by PDIFF
x, x
y, y z, z
w, w
k, k
S0 , S3
S0'
S3'
S1, S5
(service repl.)
S2, S2v2
(version change)
h, h
S0'
P0 branch of S4 P1 branch of S4
P0 branch of S2 P1 branch of S2
S,Sv2
(version change)
S0, S0
d1, d1
PDIFF helps determine the impact of
variations in the pipeline

48. NII,Tokyo,July2014–PaoloMissier
Provenance of Linked Open Data resources
Goal: to establish a LD-compliant association between an LD
resource and a description of its provenance
• Where does the provenance of a LD resource live?
• How can it be accessed?
Why?
1. to enable LD search and discovery
• By indexing data by its provenance
• Ex. “Find all resources for which Alice is an author which contain data derived
from dataset D”
1. To enable reasoning about quality/reliability of the LD resource
• Predicates and rules over provenance
• Ex. “if D has been derived from either {A,B,C} and Alice is one of the authors,
then score  X”

49. NII,Tokyo,July2014–PaoloMissier
Provenance of Linked Open Data resources: how
How: Three mechanisms:
1. Provenance Access and Query (PROV-AQ) – part of the W3C
PROV recommendation suite
1. Embedding provenance statements within the resource itself
• Eg the “Nanopublication” model
2. Packaging data + provenance as a Research Object

50. NII,Tokyo,July2014–PaoloMissier
1. Provenance pingback and query service
Image reproduced from:
De Nies, Tom, Robert Meusel, Kai Eckert, Dominique Ritze, and Anastasia Dimou. “A
Lightweight Provenance Pingback and Query Service for Web Publications.” In
Procs. IPAW 2014. Cologne, Germany: Springer, 2014.
Objective: to decouple publishing of content and of its provenance (as LOD)
Scenario:
• Publishers publish content resources, are not responsible for provenance
• Eg. Mendeley, ResearchGate, etc.
• Authors publish provenance, are not responsible for publishing content

51. NII,Tokyo,July2014–PaoloMissier
2. Provenance Embedding
The nanopublication model is an example of provenance embedding
within a published RDF document
From nanopub.org:
A nanopublication is the smallest unit of publishable information:
an assertion about anything that can be uniquely identified and
attributed to its author.
Individual nanopublications can be cited by others and tracked for
their impact on the community.

52. NII,Tokyo,July2014–PaoloMissier
Nanopublication: example
Assertion: an “association” between a gene and a genetic disorder.
The strength of this association is given by a statistical p-value.
See nanopub.org for details
{ : a nanopub:Nanopublication ;
nanopub:hasAssertion :NanoPub_1_Assertion ;
nanopub:hasProvenance :NanoPub_1_Provenance .
:NanoPub_1_Provenance nanopub:hasAttribution :NanoPub_1_Attribution ;
nanopub:hasSupporting :NanoPub_1_Supporting .
:NanoPub_1_Assertion a nanopub:Assertion .
:NanoPub_1_Provenance a nanopub:Provenance .
:NanoPub_1_Attribution a nanopub:Attribution .
:NanoPub_1_Supporting a nanopub:Supporting .
}
:NanoPub_1_Assertion {
:Association_1 a sio:statistical-association ;
sio:has-measurement-value :Association_1_p_value ; sio:refers-to ...
}
:NanoPub_1_Attribution {
:pav:authoredBy res_a, reS_b.
:NanoPub_1_Assertion pav:createdBy ...;
}
:NanoPub_1_Supporting { :Association_1
opm:wasDerivedFrom gene_disease_concept_profiles_1980_2010...;
opm:wasGeneratedBy gene_disease_concept_profiles_matching_1980_2010; .
}

53. NII,Tokyo,July2014–PaoloMissier
3. Research Objects for data and provenance packaging
Research Objects (ROs) are semantically rich aggregations of resources that
bring together data, methods and people in scientific investigations.
A Research Object is a combination of:
• Aggregation (reusing Object Reuse and Exchange [ORE])
• Annotation (reusing the Annotation Ontology [AO])
• RO ontologies
From the Wf4Ever EU project
See also:
Belhajjame K, Corcho O, Garijo D, Zhao J, Missier P, Newman DR, Palma R, Bechhofer S et al.:
Workflow-Centric Research Objects: A First Class Citizen in the Scholarly Discourse. In
proceedings of the ESWC2012 Workshop on the Future of Scholarly Communication in the
Semantic Web (SePublica2012), Heraklion, Greece, May 2012

54. NII,Tokyo,July2014–PaoloMissier
Links to resources cited in the talk
• The PROV Data Model (PROV-DM): www.w3.org/TR/prov-dm/
• A primer on PROV with a simple running example:
http://www.w3.org/TR/prov-primer/
• LD and PROV:
• Nanopublications: nanopub.org
• Research Objects: researchobject.org
• The Wf4Ever project: www.wf4ever-project.org
• PROV Access and Query conventions (PROV-AQ):
http://www.w3.org/TR/prov-aq/
• Visualising provenance using PROV-O-Viz: http://provoviz.org/
• PROV-O-Viz video:
• PROV-O-Viz IPAW’14 paper preprint:
http://dare.ubvu.vu.nl/handle/1871/51388
• Reference:
Hoekstra, Rinke, and Paul Groth. “PROV-O-Viz - Understanding the
Role of Activities in Provenance.” In Procs. IPAW 2014. Springer, 2014.

55. NII,Tokyo,July2014–PaoloMissier