SHARP: Harmonizing Galaxy and Taverna workflow provenance

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SHARP is a Linked Data approach for harmonizing cross-workflow provenance. In this demo, we demonstrate SHARP through a real-world omic experiment involving workflow traces generated by Taverna and Galaxy systems. SHARP starts by interlinking provenance traces generated by Galaxy and Taverna workflows and then harmonize the interlinked graphs thanks to OWL and PROV inference rules. The resulting provenance graph can be exploited for answering queries across Galaxy and Taverna workflow runs.

Science

SHARP: Harmonizing Galaxy and Taverna workﬂow
provenance
SeWeBMeDA’17 - Demonstration
Alban Gaignard1
, Khalid Belhajjame2
, Hala Skaf-Molli3
May 28, 2017
1
Nantes Academic Hospital, France
2
LAMSADE Paris-Dauphine University, France
3
LS2N - Nantes University, France

Multiple workﬂow engines
Taverna workﬂow
@research-lab
Galaxy workﬂow
@sequencing-facility
Variant eﬀect
prediction
VCF ﬁle
Exon ﬁltering
output
Merge
Alignment
sample
1.a.R1
sample
1.a.R2
Alignment
sample
1.b.R1
sample
1.b.R2
Alignment
sample
2.R1
sample
2.R2
Sort Sort
Variant calling
GRCh37
go to owl:sameAs
A. Gaignard, K. Belhajjame, H. Skaff Molli – SeWeBMeDA’17 1

SHARP approach
owl:sameAs
inferred
PROV
PROV
trace
PROV
trace
nanopub
PROV interlinking PROV harmonization PROV summarization
11 12 13
…
14
A. Gaignard, K. Belhajjame, H. Skaff Molli – SeWeBMeDA’17 5

Demonstration scenario
– Provenance capture
— Provenance interlinking
˜ Provenance harmonization
™ Provenance summarization (inﬂuence graphs,
nanopublications)
• https://github.com/albangaignard/galaxy-PROV
• https://github.com/albangaignard/sharp-prov-toolbox
A. Gaignard, K. Belhajjame, H. Skaff Molli – SeWeBMeDA’17 6

– Provenance capture
Taverna
Built-in when saving workﬂow execution results.
Galaxy
GALAXY-PROV tool + web interface:
• API key
• list Galaxy data processing histories
• generate PROV (turtle)
• visualize PROV (D3.js)
https://github.com/albangaignard/galaxy-PROV
A. Gaignard, K. Belhajjame, H. Skaff Molli – SeWeBMeDA’17 7

Galaxy workﬂow provenance capture demo
A. Gaignard, K. Belhajjame, H. Skaff Molli – SeWeBMeDA’17 7

— Provenance interlinking
1. SHA-512 ﬁngerprint of ﬁles
2. annotating PROV entities with SHA-512 digest
3. producing owl:sameAs → SPARQL CONSTRUCT-WHERE query
Command line tool
java -jar SharpProvToolbox/target/SHARP-1.0-SNAPSHOT-launcher.jar
-ri sample-data/control_mm9_chr15_Plekhh2-PigF_forward.fastq
sample-data/control_mm9_chr15_Plekhh2-PigF_reverse.fastq
sample-data/drugged_mm9_chr15_Plekhh2-PigF_forward.fastq
sample-data/drugged_mm9_chr15_Plekhh2-PigF_reverse.fastq
sample-data/unknown.fastq
A. Gaignard, K. Belhajjame, H. Skaff Molli – SeWeBMeDA’17 10

˜ Provenance harmonization
1. OWL entailments, Jena API
ReasonerRegistry.getOWLMiniReasoner()
2. PROV inferences (TGD), Jena rule engine
new GenericRuleReasoner(all prov rules)
3. Blank nodes removing (EGD)
Command line tool
java -jar SharpProvToolbox/target/SHARP-1.0-SNAPSHOT-launcher.jar
-i sample-data/taverna.prov.ttl
sample-data/galaxy.prov.ttl
sample-data/sameas.ttl
A. Gaignard, K. Belhajjame, H. Skaff Molli – SeWeBMeDA’17 12

™ Provenance summarization: inﬂuence graph
CONSTRUCT {
?x ?p ?y .
?x rdfs:label ?lx .
?y rdfs:label ?ly .
} WHERE {
?x ?p ?y .
FILTER (?p IN (prov:wasInfluencedBy)) .
?x rdfs:label ?lx .
?y rdfs:label ?ly .
}
+ HTML/D3.js code generation
Command line tool
java -jar SharpProvToolbox/target/SHARP-1.0-SNAPSHOT-launcher.jar
-i sample-data/taverna.prov.ttl
sample-data/galaxy.prov.ttl
sample-data/sameas.ttl
-s
A. Gaignard, K. Belhajjame, H. Skaff Molli – SeWeBMeDA’17 14

$™ Provenance summarization: nanopublication CONSTRUCT { GRAPH :assertion { ?ref_genome a sio:Genome . ?sample a sio:Sample ; sio:is-variant-of ?ref_genome ; sio:has-phenotype ?out . [...] } } WHERE { [...] ?out ( prov:wasInfluencedBy )+ ?sample . [...] } Command line tool java -jar SharpProvToolbox/target/SHARP-1.0-SNAPSHOT-launcher.jar -i sample-data/taverna.prov.ttl sample-data/galaxy.prov.ttl sample-data/sameas.ttl -sq sample-data/nanopub.query A. Gaignard, K. Belhajjame, H. Skaff Molli – SeWeBMeDA’17 16$

Questions ?
alban.gaignard@univ-nantes.fr
Acknowledgments

Backup slides
A. Gaignard, K. Belhajjame, H. Skaff Molli – SeWeBMeDA’17 19

PROV-O ontology
https://www.w3.org/TR/prov-o
A. Gaignard, K. Belhajjame, H. Skaff Molli – SeWeBMeDA’17 20

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GBSN - Microbiology (Unit 1)

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Theoretical predictions and observational data indicate a class of sub-Neptune exoplanets may have water-rich interiors covered by hydrogen-dominated atmospheres. Provided suitable climate conditions, such planets could host surface liquid oceans. Motivated by recent JWST observations of K2-18 b, we self-consistently model the photochemistry and potential detectability of biogenic sulfur gases in the atmospheres of temperate sub-Neptune waterworlds for the first time. On Earth today, organic sulfur compounds produced by marine biota are rapidly destroyed by photochemical processes before they can accumulate to significant levels. Domagal-Goldman et al. suggest that detectable biogenic sulfur signatures could emerge in Archean-like atmospheres with higher biological production or low UV flux. In this study, we explore biogenic sulfur across a wide range of biological fluxes and stellar UV environments. Critically, the main photochemical sinks are absent on the nightside of tidally locked planets. To address this, we further perform experiments with a 3D general circulation model and a 2D photochemical model (VULCAN 2D) to simulate the global distribution of biogenic gases to investigate their terminator concentrations as seen via transmission spectroscopy. Our models indicate that biogenic sulfur gases can rise to potentially detectable levels on hydrogen-rich water worlds, but only for enhanced global biosulfur flux (20 times modern Earth’s flux). We find that it is challenging to identify DMS at 3.4 μm where it strongly overlaps with CH4, whereas it is more plausible to detect DMS and companion byproducts, ethylene (C2H4) and ethane (C2H6), in the mid-infrared between 9 and 13 μm. Unified Astronomy Thesaurus concepts: Exoplanet atmospheres (487); Exoplanet

Biogenic Sulfur Gases as Biosignatures on Temperate Sub-Neptune Waterworlds

Sérgio Sacani

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SHARP: Harmonizing Galaxy and Taverna workflow provenance

1. SHARP: Harmonizing Galaxy and Taverna workﬂow provenance SeWeBMeDA’17 - Demonstration Alban Gaignard1 , Khalid Belhajjame2 , Hala Skaf-Molli3 May 28, 2017 1 Nantes Academic Hospital, France 2 LAMSADE Paris-Dauphine University, France 3 LS2N - Nantes University, France

2. Multiple workflow engines Taverna workflow @research-lab Galaxy workflow @sequencing-facility Variant effect prediction VCF file Exon filtering output Merge Alignment sample 1.a.R1 sample 1.a.R2 Alignment sample 1.b.R1 sample 1.b.R2 Alignment sample 2.R1 sample 2.R2 Sort Sort Variant calling GRCh37 go to owl:sameAs A. Gaignard, K. Belhajjame, H. Skaff Molli – SeWeBMeDA’17 1

6. SHARP approach owl:sameAs inferred PROV PROV trace PROV trace nanopub PROV interlinking PROV harmonization PROV summarization 11 12 13 … 14 A. Gaignard, K. Belhajjame, H. Skaff Molli – SeWeBMeDA’17 5

7. Demonstration scenario – Provenance capture — Provenance interlinking ˜ Provenance harmonization ™ Provenance summarization (inﬂuence graphs, nanopublications) • https://github.com/albangaignard/galaxy-PROV • https://github.com/albangaignard/sharp-prov-toolbox A. Gaignard, K. Belhajjame, H. Skaff Molli – SeWeBMeDA’17 6

8. – Provenance capture Taverna Built-in when saving workﬂow execution results. Galaxy GALAXY-PROV tool + web interface: • API key • list Galaxy data processing histories • generate PROV (turtle) • visualize PROV (D3.js) https://github.com/albangaignard/galaxy-PROV A. Gaignard, K. Belhajjame, H. Skaff Molli – SeWeBMeDA’17 7

9. Galaxy workﬂow provenance capture demo A. Gaignard, K. Belhajjame, H. Skaff Molli – SeWeBMeDA’17 7

10.

11.

12. — Provenance interlinking 1. SHA-512 ﬁngerprint of ﬁles 2. annotating PROV entities with SHA-512 digest 3. producing owl:sameAs → SPARQL CONSTRUCT-WHERE query Command line tool java -jar SharpProvToolbox/target/SHARP-1.0-SNAPSHOT-launcher.jar -ri sample-data/control_mm9_chr15_Plekhh2-PigF_forward.fastq sample-data/control_mm9_chr15_Plekhh2-PigF_reverse.fastq sample-data/drugged_mm9_chr15_Plekhh2-PigF_forward.fastq sample-data/drugged_mm9_chr15_Plekhh2-PigF_reverse.fastq sample-data/unknown.fastq A. Gaignard, K. Belhajjame, H. Skaff Molli – SeWeBMeDA’17 10

13.

14. ˜ Provenance harmonization 1. OWL entailments, Jena API ReasonerRegistry.getOWLMiniReasoner() 2. PROV inferences (TGD), Jena rule engine new GenericRuleReasoner(all prov rules) 3. Blank nodes removing (EGD) Command line tool java -jar SharpProvToolbox/target/SHARP-1.0-SNAPSHOT-launcher.jar -i sample-data/taverna.prov.ttl sample-data/galaxy.prov.ttl sample-data/sameas.ttl A. Gaignard, K. Belhajjame, H. Skaff Molli – SeWeBMeDA’17 12

15.

16. ™ Provenance summarization: inﬂuence graph CONSTRUCT { ?x ?p ?y . ?x rdfs:label ?lx . ?y rdfs:label ?ly . } WHERE { ?x ?p ?y . FILTER (?p IN (prov:wasInfluencedBy)) . ?x rdfs:label ?lx . ?y rdfs:label ?ly . } + HTML/D3.js code generation Command line tool java -jar SharpProvToolbox/target/SHARP-1.0-SNAPSHOT-launcher.jar -i sample-data/taverna.prov.ttl sample-data/galaxy.prov.ttl sample-data/sameas.ttl -s A. Gaignard, K. Belhajjame, H. Skaff Molli – SeWeBMeDA’17 14

17.

18. ™ Provenance summarization: nanopublication CONSTRUCT { GRAPH :assertion { ?ref_genome a sio:Genome . ?sample a sio:Sample ; sio:is-variant-of ?ref_genome ; sio:has-phenotype ?out . [...] } } WHERE { [...] ?out ( prov:wasInfluencedBy )+ ?sample . [...] } Command line tool java -jar SharpProvToolbox/target/SHARP-1.0-SNAPSHOT-launcher.jar -i sample-data/taverna.prov.ttl sample-data/galaxy.prov.ttl sample-data/sameas.ttl -sq sample-data/nanopub.query A. Gaignard, K. Belhajjame, H. Skaff Molli – SeWeBMeDA’17 16

19.

20.

21. Questions ? alban.gaignard@univ-nantes.fr Acknowledgments

22. Backup slides A. Gaignard, K. Belhajjame, H. Skaff Molli – SeWeBMeDA’17 19

23. PROV-O ontology https://www.w3.org/TR/prov-o A. Gaignard, K. Belhajjame, H. Skaff Molli – SeWeBMeDA’17 20

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