Susanna-Assunta Sansone is a data consultant and honorary academic editor who works on several projects related to making data FAIR (Findable, Accessible, Interoperable, Reusable). She is the associate director of Scientific Data, a peer-reviewed journal focused on publishing data descriptors to describe and provide access to scientifically valuable datasets. The goal of Scientific Data is to help promote open science and data reuse by publishing structured metadata and narratives about datasets alongside traditional research articles.

1. Data Consultant,
Honorary Academic Editor
Associate Director,
Principal Investigator
The rise of the data-centric !
research and publication enterprises!
Susanna-Assunta Sansone, PhD!
!
uk.linkedin.com/in/sasansone!
@biosharing!
@isatools!
@scientificdata!
!
'Managing Big Data - Setting the standards for analyzing and integrating big data’, Berlin, July 9-10, 2014
http://www.slideshare.net/SusannaSansone

2. • About myself!
o activities and interests!
• Be FAIR to your data!
o concept!
o my related projects!
• The Scientific Data exemplar!
o rationale!
o Data Descriptors!
Outline!

3. My areas of activity:!
• Data capture and curation!
• Data (nano)publication!
• Data provenance !
• Open, community ontologies
and standards!
• Semantic web!
• Software development!
• Training!
Communities I work with/for:! As part of:!
• UK, European and international
consortia!
• Pre-competitive informatics
public-private partnerships!
• Standardization initiatives!
with e.g.:!

4. Notes in Lab Books
(information for humans)
Spreadsheets andTables
( the compromise)
Facts as RDF statements
(information for machines)
Notes and narrative! Spreadsheets and tables! Linked data and nanopublications!
Enabling reproducible research and open science,
driving science and discoveries !
Increase the level of annotation at the source, tracking provenance and using community standards

5. https://projects.ac/blog/five-top-reasons-to-protect-your-data-and-practise-safe-science/
Credit to:

6. A great start, but not enough!
image by Greg Emmerich
http://discovery.urlibraries.org/
http://www.theguardian.com/higher-education-network/blog/2014/jun/26

7. Findable, Accessible, Interoperable, Reusable!
Worldwide movement for FAIR data

8. In all fairness, no much data is FAIR!

9. But it is not just about technology…!

10. The International Conference on Systems Biology (ICSB), 22-28 August, 2008 Susanna-Assunta
Sansone www.ebi.ac.uk/net-project
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0
…breath and depth of the content!
…is pivotal!

11. The International Conference on Systems Biology (ICSB), 22-28 August, 2008 Susanna-Assunta
Sansone www.ebi.ac.uk/net-project
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sample characteristic(s)!
experimental design!
experimental variable(s)!
technology(s)!
measurement(s)!
protocols(s)!
data file(s)!
......!

12. The International Conference on Systems Biology (ICSB), 22-28 August, 2008 Susanna-Assunta
Sansone www.ebi.ac.uk/net-project
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2
• make annotation explicit
and discoverable
• structure the descriptions for
consistency
• ensure/regulate access
• deposit and publish
• etc….
§ To make this dataset ‘FAIR’, one
must have standards, tools and
best practices to:
• report sufficient details
• capture all salient features of
the experimental workflow

13. A community mobilization to develop standards, e.g.:
§ Structural and operational differences
• organization types (open, close to members, society, WG etc.)
• standards development (how to formulate, conduct and maintain)
• adoption, uptake, outreach (link to journals, funders and commercial sector)
• funds (sponsors, memberships, grants, volunteering)
de jure de facto
grass-roots
groups
standard
organizations
Nanotechnology Working Group

14. A community mobilization to develop standards, e.g.:
§ Structural and operational differences
• organization types (open, close to members, society, WG etc.)
• standards development (how to formulate, conduct and maintain)
• adoption, uptake, outreach (link to journals, funders and commercial sector)
• funds (sponsors, memberships, grants, volunteering)
de jure de facto
grass-roots
groups
standard
organizations
Nanotechnology Working Group

15. Focus on reporting or content standards
Including minimum
information reporting
requirements, or
checklists to report the
same core, essential
information
Including controlled
vocabularies, taxonomies,
thesauri, ontologies etc. to
use the same word and
refer to the same ‘thing’
Including conceptual
model, conceptual
schema from which an
exchange format is derived
to allow data to flow from
one system to another
Community-developed, standards are pivotal to structure, enrich the
description and share datasets, facilitating understanding and reuse!

16. 16
Technologically-delineated
views of the world
!
Biologically-delineated
views of the world!
Generic features ( common core )!
- description of source biomaterial!
- experimental design components!
Arrays!
Scanning! Arrays &
Scanning!
Columns!
Gels!
MS! MS!
FTIR!
NMR!
Columns!
transcriptomics
proteomics
metabolomics
plant biology
epidemiology
microbiology
Fragmentation, duplications and gaps
To compare and integrate data we need interoperable standards

17. 17
Arrays!
Scanning! Arrays &
Scanning!
Columns!
Gels!
MS! MS!
FTIR!
NMR!
Columns!
transcriptomics
proteomics
metabolomics
Synergistic examples exist, but more are needed!

18. Growing number of reporting standards
+ 130
+ 150
+ 303
Source:BioPortal
Databases, !
annotation,!
curation !
tools !
implementing !
standards!
miame!
MIAPA!
MIRIAM!
MIQAS!
MIX!
MIGEN!
CIMR!
MIAPE!
MIASE!
MIQE!
MISFISHIE….!
REMARK!
CONSORT!
MAGE-Tab!
GCDML!
SRAxml!
SOFT!
FASTA!
DICOM!
MzML!
SBRML!
SEDML…!
GELML!
ISA-Tab!
CML!
MITAB!
AAO!
CHEBI!
OBI!
PATO! ENVO!
MOD!
BTO!
IDO…!
TEDDY!
PRO!
XAO!
DO
VO!
Source:BioSharing
Source:BioSharing

19. Navigating the sea of standards is not trivial!
The relationship among popular standard formats for pathway information!
BioPAX and PSI-MI are designed for data exchange to and from databases and pathway and
network data integration. SBML and CellML are designed to support mathematical simulations
of biological systems and SBGN represents pathway diagrams. !
CREDIT:
Demir, et al., The BioPAX
community standard for
pathway data sharing, 2010.

20. Which standards and database can we use/recommend
I work in the field of cell
migration research,
which one are
applicable to me?
I us cell migration in
translational research, are
there specific clinical
standards?

22. The International Conference on Systems Biology (ICSB), 22-28 August, 2008 Susanna-Assunta
Sansone www.ebi.ac.uk/net-project
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2

23. Registering and cataloging is just step one; the next one are:
• Develop assessment criteria for usability and popularity of standards
• Associate standards to data policies and databases
• Assemble journal and funder policies re data storage
• Make fully cross-searchable
• Intended goal: help stakeholders make informed decisions

25. General-purpose, configurable format,
designed to support:
• description of the experimental metadata,
making the annotation explicit and
discoverable
• provenance tracking
• use community standards, such as minimal
reporting guidelines and terminologies
• designed to be converted to - a growing
number of - other metadata formats, e.g.
used by EBI repositories
analysis !
method! script!
Data file or !
record in a
database!

27. The International Conference on Systems Biology (ICSB), 22-28 August, 2008 Susanna-Assunta
Sansone www.ebi.ac.uk/net-project
ISA powers data collection, curation resources and repositories, e.g.:

28. eTRIKS – european Translational Information
and Knowledge management Services
Consortium of academic (Imperial College, CNRS, Un
of Luxemburg) and pharmas (Janssen, Merck, AZ, Lilly,
Lundbeck, Pfizer, Roche, Sanofi, Bayer, GSK) building
a sustainable, open translational research informatics
platform
• Nature Publishing Group‘s Scientific Data
• BioMedCentral and BGI‘s GigaScience
• F1000 Research
• Oxford University Press
Susanna-Assunta Sansone, Philippe Rocca-Serra, Alejandra Gonzalez-Beltran, Eamonn Maguire, Milo Thurston;
Oxford alumni: Annapaola Santarsiero, Pavlos Georgiou + my previous team when at EBI (2001 – 2010)!

29. • About myself!
o activities and interests!
• Be FAIR to your data!
o concept!
o my related projects!
• The Scientific Data exemplar!
o rationale!
o Data Descriptors!
Outline!

30. FAIR data - roles and responsibilities
• Data has to become an integral part of
the scholarly communications!
• Responsibilities lie across several
stakeholder groups: researchers, data
centers, librarians, funding agencies and
publishers!
• But publishers occupy a “leverage point”
in this process!

31. Human Genome 2001
62 Pages, 150 Authors,
49 Figure, 27 tables
Encode Project 2012
30 papers,
3 Journals
Journal publishing - changing landscape !

32.
!
!
!
Launched on May 27th, 2014
A new online-only publication for descriptions of scientifically valuable datasets
in the life, environmental and biomedical sciences, but not limited to these!
Credit for sharing
your data
Focused on reuse
and reproducibility
Peer reviewed,
curated
Promoting Community
Data Repositories
Open Access
Supported by:!

33. !
!
!
Experimental metadata or!
structured component!
(in-house curated, machine-
readable formats)!
Article or !
narrative component!
(PDF and HTML)!
Data Descriptor: narrative and structure!

34. !
!
!
!
!
!
!
!
Scientific hypotheses:!
Synthesis!
Analysis!
Conclusions!
Methods and technical analyses supporting
the quality of the measurements:!
What did I do to generate the data?!
How was the data processed?!
Where is the data?!
Who did what when!
BEFORE: get your data to the community as soon as possible (see NPG pre-publication policy)
AT THE SAME TIME: publish your Data Descriptor(s) alongside research article(s)
AFTER: expand on your research articles, adding further information for reuse of the data
Relation with traditional articles - content and time!

35. Export to various formats
(ISA_tab, RDF, etc)
Linking between research papers, Data Descriptors, and data records
Making data discoverable
!
We currently recognize over
50 public data repositories!
!

36. Evaluation is not be based on the perceived impact or novelty of the findings!
• Experimental Rigour and Technical Data Quality!
o Were the data produced in a rigorous and methodologically sound manner?!
o Was the technical quality of the data supported convincingly with technical validation
experiments and statistical analyses of data quality or error, as needed?!
o Are the depth, coverage, size, and/or completeness of these data sufficient for the types of
applications or research questions outlined by the authors?!
• Completeness of the Description!
o Are the methods and any data-processing steps described in sufficient detail to allow others to
reproduce these steps?!
o Did the authors provide all the information needed for others to reuse this dataset or integrate it
with other data?!
o Is this Data Descriptor, in combination with any repository metadata, consistent with relevant
minimum information or reporting standards?!
• Integrity of the Data Files and Repository Record!
o Have you confirmed that the data files deposited by the authors are complete and match the
descriptions in the Data Descriptor?!
o Have these data files been deposited in the most appropriate available data repository?!
Peer review process focused on quality and reuse!

37. • Neuroscience, ecology, epidemiology, environmental science,
functional genomics, metabolomics, toxicology!
• New datasets and previously published data sets!
o a fuller, more in-depth look at the data processing steps,
supported by additional data files and code from each step!
o additional tutorial-like information for scientists interested in
reusing or integrating the data with their own!
• Datasets in figshare and domain specific databases!
• Code deposited in figshare and GitHub!
• Individual datasets, curated aggregation and citizen science!
• First dataset part of a collection !
• Academic and industry authors!
37
Current content is diverse – bimonthly releases !

38. • Do you run a data resource we should recognize?!
o See on our website the list of criteria databases should meet!!
• Are you interested in facilitating submission to us? !
o See our ISA-Tab specification on the website!
- you can implement and export in this format from your authoring/curation tool, or
from your database!!
• Do you want to submit Data Descriptor(s)?!
o Check suitability by sending a pre-submission enquire, we accept:!
- Submissions in the life, environmental and biomedical sciences; but not limited to!
- Experimental, observational and computational datasets!
- Individual datasets, curated aggregations, and collections!
- Unpublished data and follow-up, with additional information for wider reuse, e.g.:!
ü a fuller, more in-depth look at the data processing steps, supported by additional data
files and code from each step!
ü additional tutorial-like information for scientists interested in reusing or integrating the
data with their own!
Interested in collaborating and/or enable submission?!

39. Helping you publish, discover and reuse research data
Visit
nature.com/scientificdata
Email
scientificdata@nature.com
Tweet
@ScientificData
Supported by:!
Honorary Academic Editor
Susanna-Assunta Sansone, PhD
Managing Editor
Andrew L Hufton, PhD
Editorial Curator
Victoria Newman
Advisory Panel and Editorial Board
including senior researchers, funders,
librarians and curators