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Advancing Reproducible
Science from Physical
Samples
IGSN and the iSamples Research
Coordination Network
Kerstin Lehnert
Megan Carter
IEDA (Interdisciplinary Earth Data Alliance), www.iedadata.org
IGSN e.V., www.igsn.org
Lamont-Doherty Earth Observatory, Columbia University
9/26/16
GSA2016:AdvancingReproducible
SciencefromPhysicalSamples:
IGSN&theiSamplesRCN
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Source: https://cos.io/top/
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GSA2016:AdvancingReproducibleSciencefromPhysical
Samples:IGSN&theiSamplesRCN
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Source: https://cos.io/top/
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GSA2016:AdvancingReproducibleSciencefromPhysical
Samples:IGSN&theiSamplesRCN
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Samples:IGSN&theiSamplesRCN
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M. McNutt, K. Lehnert, B. Hanson, B. A. Nosek, A. M. Ellison, J. L.
King; SCIENCE Policy Forum, 04 MAR 2016
“Access to data, samples, methods, and reagents used to conduct
research and analysis, as well as to the code used to analyze and
process data and samples, is a fundamental requirement for
transparency and reproducibility.”
9/26/16
GSA2016:AdvancingReproducibleSciencefromPhysical
Samples:IGSN&theiSamplesRCN
7
M. McNutt, K. Lehnert, B. Hanson, B. A. Nosek, A. M. Ellison, J. L.
King; SCIENCE Policy Forum, 04 MAR 2016
“Despite many efforts, there remains widespread disagreement
regarding data and sample availability and metadata, as well as
uneven sample deposition across the field sciences.”
iSamples: Rationale
• Improve discovery, access, sharing, analysis, and
curation of physical samples and the data
generated by their study as needed by the
science community
• Address requirements for reproducibility of
sample-based data across domains.
• Best practices for sample documentation, identification, and
citation.
• Culture that recognizes sample collection and curation as a
scholarly contribution (citation & credit).
• Policies regarding preservation and curation of physical objects
and need physical infrastructure.
8
9/26/16
GSA2016:AdvancingReproducibleSciencefromPhysical
Samples:IGSN&theiSamplesRCN
iSamples: An EarthCube RCN
http://renci.org/news/the-internet-of-samples-aims-to-break-down-research-barriers/
• Stakeholder Alignment Survey
• Early Career workshops
• Webinar series
• Two major community workshops
(UT Austin 2015, UNC/RENCI 2016)
• Joint activities & events with
related groups & projects (ESIP,
IGSN e.V., COPDESS, EarthCube RCNs &
BBs)
9/26/16
GSA2016:AdvancingReproducibleSciencefromPhysical
Samples:IGSN&theiSamplesRCN
9
iSamples Working Groups
• WG1: Identifiers & Metadata
• Develop recommendations for best practices regarding use of unique
sample identifiers, metadata, schema, and semantics
• WG2: Use Cases
• collect user stories that articulate practices in the life cycle of
samples for different users
• identify curatorial points of intervention
• develop policies and recommendations
• WG3: Engagement & Training
• Enhance communication of the benefits and leading practices of
documenting and sharing physical samples
• develop and disseminate Sample Management Training Modules
• WG4: Workflow Applications
• Requirements for tools to link local practices to standardized
protocols
9/26/16
GSA2016:AdvancingReproducibleSciencefromPhysical
Samples:IGSN&theiSamplesRCN
10
Use of Persistent Identifiers
9/26/16
GSA2016:AdvancingReproducibleSciencefromPhysical
Samples:IGSN&theiSamplesRCN
11
Background research
Cruise DOI
Samples
IGSN
Dataset publication
Dataset DOI
Funding
FundRef#
Article publication
Publication DOIORCID
Researchers
Use of Persistent Identifiers
9/26/16
GSA2016:AdvancingReproducibleSciencefromPhysical
Samples:IGSN&theiSamplesRCN
12
Background research
Cruise DOI
Samples
IGSN
Dataset publication
Dataset DOI
Funding
FundRef#
Article publication
Publication DOIORCID
Researchers
IGSN: International Geo Sample Number
• Globally unique and persistent identifier for physical samples
in the Earth Sciences
• guaranteed to be unique via a centralized control mechanism
operated by IGSN e.V.
• resolves to virtual sample representations (sample metadata
profiles) managed at federated IGSN Allocating Agents.
9/26/16
GSA2016:AdvancingReproducibleSciencefromPhysical
Samples:IGSN&theiSamplesRCN
13
9/26/16
GSA2016:AdvancingReproducibleSciencefromPhysical
Samples:IGSN&theiSamplesRCN
14
SESAR: 4,079,257
Geoscience
Australia:
1,804,990
CSIRO: 26,241
MARUM: 25,583
GFZ: 4,459
IGSN Status
Approx. 6 million
samples registered!
(April 2016)
GSA2016:AdvancingReproducibleSciencefromPhysical
Samples:IGSN&theiSamplesRCN
15
2005
2015
2015
2015 2015
9/26/16
IGSN Adoption: Publishers
COPDESS Statement of Commitment
9/26/16
GSA2016:AdvancingReproducibleSciencefromPhysical
Samples:IGSN&theiSamplesRCN
16
IGSN Adoption: Publishers
17
“… AGU Publications also strongly
encourages use of other identifiers in our
journal papers. International Geo Sample
Numbers (IGSNs) uniquely identify items,
such as a rock sample, a piece of coral, or a
vial of water taken from the natural
environment, and provide important,
consistent information about these
samples. Registering samples and including
the IGSN in papers helps secure provenance
information but most importantly connects
common samples across multiple studies in
the literature. IGSNs also will help you keep
track of your samples. These identifiers can
be reserved before a field season or
assigned afterward.”
Hanson, B. (2016), AGU opens its journals to author
identifiers, Eos, 97, doi:10.1029/2016EO043183.
Published on 7 January 2016. 9/26/16
GSA2016:AdvancingReproducibleSciencefromPhysical
Samples:IGSN&theiSamplesRCN
IGSN in
DataCite
9/26/16
GSA2016:AdvancingReproducibleSciencefromPhysical
Samples:IGSN&theiSamplesRCN
18
More IGSN News
• Consensus on standard IGSN metadata schema for describing
samples (“Birth Certificate”) at workshop in Fall 2015
• essential properties to describe a sample’s origin & classification
• published online at schema.igsn.org
• Prototype of Central IGSN Metadata Catalog developed
• harvests “birth certificate” metadata records from Allocating
Agents via the Open Archives Initiative Protocol for Metadata
Harvest (OAI-PMH)
• publishes metadata as a Linked Open Data graph for reuse by
Semantic Web clients
• GBIF interest, discussion started at International Data Week in
September 2016, workshop planned for Spring 2017
• More collaborations emerging: EZID, ORCID
9/26/16
GSA2016:AdvancingReproducibleSciencefromPhysical
Samples:IGSN&theiSamplesRCN
19
Much Left To Do …
• Develop & implement policies for access and sharing of
samples as part of reproducible research
• Create infrastructure for sample preservation and access
• Capacity?
• Business models?
• Governance?
• Certification of repositories?
• Software tools that support researchers and curators to
comply with best practices
• Further coordination & alignment between Geo & Bio
9/26/16
GSA2016:AdvancingReproducibleSciencefromPhysical
Samples:IGSN&theiSamplesRCN
20
Plans
• iSamples – IGSN workshop at
AGU Fall Meeting
• Sunday, Dec 11, 2016, 1pm
• iSamples workshop on ‘Access
& Preservation of Samples’
• Planned for Spring 2017
• IGSN – GBIF workshop planned
for Spring 2017 in Australia
9/26/16
GSA2016:AdvancingReproducibleSciencefromPhysical
Samples:IGSN&theiSamplesRCN
21

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Advancing Reproducible Science from Physical Samples: The IGSN and the iSamples RCN

  • 1. Advancing Reproducible Science from Physical Samples IGSN and the iSamples Research Coordination Network Kerstin Lehnert Megan Carter IEDA (Interdisciplinary Earth Data Alliance), www.iedadata.org IGSN e.V., www.igsn.org Lamont-Doherty Earth Observatory, Columbia University 9/26/16 GSA2016:AdvancingReproducible SciencefromPhysicalSamples: IGSN&theiSamplesRCN 1
  • 6. 9/26/16 GSA2016:AdvancingReproducibleSciencefromPhysical Samples:IGSN&theiSamplesRCN 6 M. McNutt, K. Lehnert, B. Hanson, B. A. Nosek, A. M. Ellison, J. L. King; SCIENCE Policy Forum, 04 MAR 2016 “Access to data, samples, methods, and reagents used to conduct research and analysis, as well as to the code used to analyze and process data and samples, is a fundamental requirement for transparency and reproducibility.”
  • 7. 9/26/16 GSA2016:AdvancingReproducibleSciencefromPhysical Samples:IGSN&theiSamplesRCN 7 M. McNutt, K. Lehnert, B. Hanson, B. A. Nosek, A. M. Ellison, J. L. King; SCIENCE Policy Forum, 04 MAR 2016 “Despite many efforts, there remains widespread disagreement regarding data and sample availability and metadata, as well as uneven sample deposition across the field sciences.”
  • 8. iSamples: Rationale • Improve discovery, access, sharing, analysis, and curation of physical samples and the data generated by their study as needed by the science community • Address requirements for reproducibility of sample-based data across domains. • Best practices for sample documentation, identification, and citation. • Culture that recognizes sample collection and curation as a scholarly contribution (citation & credit). • Policies regarding preservation and curation of physical objects and need physical infrastructure. 8 9/26/16 GSA2016:AdvancingReproducibleSciencefromPhysical Samples:IGSN&theiSamplesRCN
  • 9. iSamples: An EarthCube RCN http://renci.org/news/the-internet-of-samples-aims-to-break-down-research-barriers/ • Stakeholder Alignment Survey • Early Career workshops • Webinar series • Two major community workshops (UT Austin 2015, UNC/RENCI 2016) • Joint activities & events with related groups & projects (ESIP, IGSN e.V., COPDESS, EarthCube RCNs & BBs) 9/26/16 GSA2016:AdvancingReproducibleSciencefromPhysical Samples:IGSN&theiSamplesRCN 9
  • 10. iSamples Working Groups • WG1: Identifiers & Metadata • Develop recommendations for best practices regarding use of unique sample identifiers, metadata, schema, and semantics • WG2: Use Cases • collect user stories that articulate practices in the life cycle of samples for different users • identify curatorial points of intervention • develop policies and recommendations • WG3: Engagement & Training • Enhance communication of the benefits and leading practices of documenting and sharing physical samples • develop and disseminate Sample Management Training Modules • WG4: Workflow Applications • Requirements for tools to link local practices to standardized protocols 9/26/16 GSA2016:AdvancingReproducibleSciencefromPhysical Samples:IGSN&theiSamplesRCN 10
  • 11. Use of Persistent Identifiers 9/26/16 GSA2016:AdvancingReproducibleSciencefromPhysical Samples:IGSN&theiSamplesRCN 11 Background research Cruise DOI Samples IGSN Dataset publication Dataset DOI Funding FundRef# Article publication Publication DOIORCID Researchers
  • 12. Use of Persistent Identifiers 9/26/16 GSA2016:AdvancingReproducibleSciencefromPhysical Samples:IGSN&theiSamplesRCN 12 Background research Cruise DOI Samples IGSN Dataset publication Dataset DOI Funding FundRef# Article publication Publication DOIORCID Researchers
  • 13. IGSN: International Geo Sample Number • Globally unique and persistent identifier for physical samples in the Earth Sciences • guaranteed to be unique via a centralized control mechanism operated by IGSN e.V. • resolves to virtual sample representations (sample metadata profiles) managed at federated IGSN Allocating Agents. 9/26/16 GSA2016:AdvancingReproducibleSciencefromPhysical Samples:IGSN&theiSamplesRCN 13
  • 15. SESAR: 4,079,257 Geoscience Australia: 1,804,990 CSIRO: 26,241 MARUM: 25,583 GFZ: 4,459 IGSN Status Approx. 6 million samples registered! (April 2016) GSA2016:AdvancingReproducibleSciencefromPhysical Samples:IGSN&theiSamplesRCN 15 2005 2015 2015 2015 2015 9/26/16
  • 16. IGSN Adoption: Publishers COPDESS Statement of Commitment 9/26/16 GSA2016:AdvancingReproducibleSciencefromPhysical Samples:IGSN&theiSamplesRCN 16
  • 17. IGSN Adoption: Publishers 17 “… AGU Publications also strongly encourages use of other identifiers in our journal papers. International Geo Sample Numbers (IGSNs) uniquely identify items, such as a rock sample, a piece of coral, or a vial of water taken from the natural environment, and provide important, consistent information about these samples. Registering samples and including the IGSN in papers helps secure provenance information but most importantly connects common samples across multiple studies in the literature. IGSNs also will help you keep track of your samples. These identifiers can be reserved before a field season or assigned afterward.” Hanson, B. (2016), AGU opens its journals to author identifiers, Eos, 97, doi:10.1029/2016EO043183. Published on 7 January 2016. 9/26/16 GSA2016:AdvancingReproducibleSciencefromPhysical Samples:IGSN&theiSamplesRCN
  • 19. More IGSN News • Consensus on standard IGSN metadata schema for describing samples (“Birth Certificate”) at workshop in Fall 2015 • essential properties to describe a sample’s origin & classification • published online at schema.igsn.org • Prototype of Central IGSN Metadata Catalog developed • harvests “birth certificate” metadata records from Allocating Agents via the Open Archives Initiative Protocol for Metadata Harvest (OAI-PMH) • publishes metadata as a Linked Open Data graph for reuse by Semantic Web clients • GBIF interest, discussion started at International Data Week in September 2016, workshop planned for Spring 2017 • More collaborations emerging: EZID, ORCID 9/26/16 GSA2016:AdvancingReproducibleSciencefromPhysical Samples:IGSN&theiSamplesRCN 19
  • 20. Much Left To Do … • Develop & implement policies for access and sharing of samples as part of reproducible research • Create infrastructure for sample preservation and access • Capacity? • Business models? • Governance? • Certification of repositories? • Software tools that support researchers and curators to comply with best practices • Further coordination & alignment between Geo & Bio 9/26/16 GSA2016:AdvancingReproducibleSciencefromPhysical Samples:IGSN&theiSamplesRCN 20
  • 21. Plans • iSamples – IGSN workshop at AGU Fall Meeting • Sunday, Dec 11, 2016, 1pm • iSamples workshop on ‘Access & Preservation of Samples’ • Planned for Spring 2017 • IGSN – GBIF workshop planned for Spring 2017 in Australia 9/26/16 GSA2016:AdvancingReproducibleSciencefromPhysical Samples:IGSN&theiSamplesRCN 21

Notes de l'éditeur

  1. Sample are the products of research as well as research resources. As such they are part of the overall science ecosystem and included in discussions about Open Science and transparency in science. In the context of reproducible science, it is especially relevant to maintain the link between the observations made on samples, the data acquired on them, and the actual physical objects. This link is more often than not broken. . The link between data and the physical objects is relevant for other reasons as well. For example, collection and curation of samples requires expertise and resources and should receive credit. In the era of emerging digital data infrastructures we can solve the