Presentation about the digital representation of physical samples in scientific publications, given at the European Geoscience Union meeting 2015 in the Splinter Meeting 1.36 "Digital Representation of Physical Samples in Scientific Publications".

1. Organized by the IGSN e.V. and
COPDESS (Coalition for Publishing Data in the Earth and Space Sciences)
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2.  Background & Rationale (Kerstin Lehnert)
 Physical Samples in the Digital Era
 The Coalition for Publishing Data in the Earth &
Space Sciences
 Persistent Unique Identification of Samples:
The IGSN (Jens Klump)
 Discussion
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3.  Samples are the source of observational data and
measurements across disciplines.
 Samples provide irreplaceable evidence of long-term
historical trends.
 Samples serve as standards or references.
 Samples record unique events in history and/or unique
opportunities to collect specimens (e.g. moon rocks).
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4. -8
-6
-4
-2
0
2
4
6
8
10
12
0.702 0.703 0.704 0.705 0.706 0.707 0.708
Hawaii
Iceland
Samoa
Society
Marquesas
Pitcairn-Gambier
Tristan
Cook-Austral
St. Helena
Fig. 15a
DMM
HIMU
EM-1
EM-2
Ice cores Sediment cores
Volcanic rocksSoil

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Reproducibility

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7. Arnold Workshop II: Reproducibility in Field
Sciences
AAAS Headquarters, Washington, DC
May 11/12, 2015
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Organizers:
Marcia McNutt (AAAS)
Brooks Hansen (AGU)
Clifford Duke (ESA)
Stuart Buck (LJAF)

8.  of samples
 of sample-based data
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Re-use

9.  Samples are often expensive to collect
(drilling, remote locations).
 Many samples are unique and irreplaceable.
 Re-analysis augments utility of existing data.
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10. • “Poor and uneven access and management of sample
collections”
• “Incomplete sample tracking and linking of samples to analyses
in the literature and databases”
• “Poor discoverability of existing samples”
EarthCube Domain End-user Workshop for Petrology & Geochemistry
at the National Museum of Natural History, Smithsonian Institution, March 2013

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LDEO Marine Core Repository

12.  Investigators
 Departments
 Institutions
3/26/2015 NDS ‘Internet of Sample’ 12
• Lack of resources: space, staff, tools
• Lack of policies
• Lack of leading practices & standards

13.  connect the physical samples with the digital data
 create “virtual representations” of samples online
(digitization of existing collections)
 ensure unique identification of samples so they can be
properly cited and located
 network catalogs and registries to allow discovery of
samples across distributed systems
 develop & implement best practices for consistent and
comprehensive documentation of samples
 preserve & curate the physical objects
 sustain storage facilities to curate actual physical objects;
 use IT to facilitate digital collection management.
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14

15.  Find the sample and contact its owner
 Find all publications that mention a specific
sample
 Find all data for that sample in easily usable,
electronic format
 Find other samples with similar properties
 geospatial
 temporal
 compositional
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16.  Online sample catalogs can dramatically improve
discovery and access of collections for broad
audiences.
 Software tools can support and streamline
collection management.
 Interoperability provides unprecedented
capabilities to
 Link data, samples, and publications
 Link all data acquired on a single sample & subsamples
 Integrate sample-based data with other data types
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17.  CODATA Task Group “Physical Samples in the Digital
Era”
 SciColl: Scientific Collections International
(Consortium)
 iSamples (Internet of Samples in the Earth Sciences)
 Funded EarthCube Research Coordination Network (RCN)
 advance access and re-use of physical samples through use
of innovative cyberinfrastructure
 DESC: Digital Environment for Sample Curation
 Shared cyberinfrastructure for sample collections &
repositories
 IGSN e.V.
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18. Coalition for Publishing Data in the Earth
& Space Sciences (www.copdess.org):
COPDESS Statement of Commitment:
“Promote use of other relevant community
permanent identifiers for samples (IGSN),
researchers (ORCID), and funders and grants
(FundRef).
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19. June 5, 2014 Deep Carbon Observatory Data Science Day 19

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EarthChem Portal shows 54 samples named ‘S1’

21. June 5, 2014 Deep Carbon Observatory Data Science Day 21
“The key measurement was the one backarc basalt
called "PPTUW”...
Subsequent efforts to confirm the observation ran into
problems. The apparently-same sample was variously
called PPTU, PPTUW/5, PPTUW-1, and TVZ19 in four
other papers. None of those papers gave its latitude
and longitude…!”
(J. Gill and E. Todd, personal communication 2013, related to IEDA data
rescue effort)
Names of dredge sample 3 of the Amphitrite
cruise
(PetDB database, www.petdb.org)

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0
5,000
10,000
15,000
20,000
25,000
30,000
2013 2014
Samples registered
0
20
40
60
80
100
2013 2014
Batches registered
As of Dec 31, 2014, SESAR has 373 users.
0
10
20
30
40
2013 2014
Accounts that registered

24.  Metadata standards for samples: how generic, how specific?
 At what granularity should samples be cited? (Credit to the
original collector)
 Can the IGSNs of an article be integrated into DOI metadata
(related identifier) so they become searchable? Should
samples be 'cited' in a distinct list?
 What protocols can be used to make IGSNs in articles
interactive? Can DOIs be used to resolve IGSNs?
 How can we reach authors and editors to encourage use of
IGSNs?
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