This document discusses the FAIRDOM consortium's efforts to promote FAIR (Findable, Accessible, Interoperable, Reusable) principles for managing data, operations, and models from systems biology and systems medicine projects. It outlines challenges in asset management for multi-partner, multi-disciplinary projects using multiple formats and repositories. FAIRDOM provides pillars of support including community actions, platforms/tools, and a public project commons to help address these challenges and better enable sharing, reuse, and reproducibility of research assets according to FAIR principles.

1. FAIR Data, Operations and Model
management for Systems Biology
and Systems Medicine Projects
Prof Carole Goble
The FAIRDOM Consortium
carole.goble@manchester.ac.uk
http://fair-dom.org, http://fairdomhub.org
1st Conference of the European Association of Systems Medicine, 26-28 October 2016, Berlin

2. Asset Management and Sharing
• Access to public
funded research
• Reproducible results
• Value and cite all
research outcomes
• Sustained data
infrastructure

3. Findable
Accessible
Interoperable
Reusable
(Intelligible)
(Reproducible)
(Citable)
(Trackable)
https://www.force11.org/group/fairgroup/fairprinciples

4. Projects .... and Programmes....
funder and research project legacy
• Reuse
• Compliance
• Retention
• Dissemination
• Collaboration
• Reproducibility
• Resource & Skills
Limitations

5. Findable
Accessible
Interoperable
Reusable
Data
Operations
Models
Sponsors

6. FAIRDOM Association e.V. Partners
open innovation, not for profit
LifeGlimmer GmBH SB-ScienceManagement GmBH New Forest Ventures Ltd

7. FAIRDOM Pillars
Project Support
Community Actions
Platforms,Tools
Public Project Commons

8. Systems Approach…
people, assets, processes pragmatics
• Multiple, interrelated assets
• Multiple, dispersed repositories
• Multi-partner, -discipline projects
• Team science practices
• Experiment – Asset lifecycles
• Academic innovation drivers

9. Multiple, interrelated assets
structured formats, standards, ontologies context
Analytics &
Pipelines
Literature
SBML, CellML,
PharmML
Matlab, Mathematica
Fortran, R, Python
SOPS
Multiple omics:
genomics,
transcriptomics
proteomics,
metabolomics
fluxomics,
reactomics
Images
Reaction kinetics
Samples, Specimens, Strains
Human data
STANDARDS
versioning,
tracking:
provenance,
parameters,
citation
Operations
Data
SOPs
Models

10. FAIRData and Metadata Standards that
help to improve understanding and exchange….
Nicolas Le Novère, Babraham Institute, UK.

11. …researchers do not always use them....
Format MetadataMetadata Ontologies
*top three most popular
The evolution of standards and data management practices in systems biology
(2015). Stanford et al, Molecular Systems Biology, 11(12):851

12. … makes model reuse tricky…
Stanford et alThe evolution of standards and data management practices in systems biology,
Molecular Systems Biology (2015) 11: 851 DOI 10.15252/msb.20156053

13. Specialist Public Repositories
General archives
Multi Repository Repertoire
Access, Reuse
Local Data Stores
The evolution of standards and data management practices in systems biology (2015).
Stanford et al, Molecular Systems Biology, 11(12):851

14. sharing/publishing assets in public archives…
Data Models
*top three most popular
The evolution of standards and data management practices in systems biology
(2015). Stanford et al, Molecular Systems Biology, 11(12):851

15. Multi-partner, multi-disciplinary projects
where sharing and metadata collection isn’t second nature
Consortia
Grp
3
Grp
1
Grp
2

16. Multi-partner, multi-disciplinary projects
SOPs andYellow Pages top request…
What methods are been used to determine
enzyme activity?
What SOP was used for this sample?
Where is the validation data for this model?
Is there any group generating kinetic data?
Is this data available?
Track versions of my model
Whats the relationship between the data and
model?
Which data belong to
which publications?

17. Downstream assets discovery and sharing
Organisation Communication Dissemination
Navigate
through
assets
Reuse
later
Enable team
to reuse/
reproduce
Help others
find out
Reuse with
new partners
Tell more,
take credit
Standardised metadata practices
Assets

18. Find… own hard disk for storage…
The evolution of standards and data management practices in systems biology
(2015). Stanford et al, Molecular Systems Biology, 11(12):851

19. Samiul Hasan, GSK
Biocuration need in Pharma: Drivers from a Translational Bioinformatics
Perspective, Poster S16

20. The FAIR Project
Challenge
Track collection of data and metadata X X
Maintain experimental context X
Find and exchange assets X X
Long-term retain results beyond a project X X X
Share, disseminate and publish assets sensitively X X X
Consistently report for interpretation, interoperability
& comparison
X X
Promote standardised metadata practices. X X
Organise and link assets X X X
Reuse tools and community archives X
Integrate with other data stores and platforms X X
Support reproducible publications X X X X
Credit owners X X

21. FAIRDOM Pillars
Project Support
Community Actions
Platforms,Tools
Public Project Commons

22. Community, Knowledge Hub
http://www.fair-dom.org
Know-how,Guides,Templates,Workshops,Training,
Webinars, Standards and Policy Forums

23. Project Support
Processes, Practices, People…take time and persuasion
Community support
Specialprojectsupport
Specialprojectsupport
PALs
project
ambassadors
best practices,
forums, training
curation handholding
SBML model
technical curation

24. Asset Management Platforms
an ecosystem of resources
Front end
Web based rich interface
Catalogue and Commons
All about the metadata
Results repository
http://seek4science.org
Back end
Scaled LIMS and analytics
Auto-archiving
Instruments data repository
https://sis.id.ethz.ch/software/openbis.html

25. A community Commons….
self managed workspaces
Controlled sharing and
publishing

26. • Licenses
• Negotiated access
• Embargos
• Permission controls
• Staged sharing
• Private walled gardens
FAIR Play Practices
Using FAIRDOM my own
lab colleagues saw what I
was doing and called to
collaborate!
Jurgen Hannstra
Vrije Universiteit Amsterdam,
Netherlands

27. Investigation
Study Analysis
Data
Model
SOP(Assay)
….organised in an ISA
(Investigation, Study, Assay/Analysis) format.

28. Packaging
Retaining Context
Supporting Decision making

29. STUDY ASSAYINVESTIGATION
Experimental
assay
Modeling assay
Publication
[Maksim
Zakhartsev]

30. ... a “Research Object” Catalogue
metadata aggregated across repositories
retaining context to support decision making and reuse
Local Stores
External
Databases
Publishing services
Secure
Stores
Model
Resources

31. … with integrated tooling
metadata annotation against standards
model validation, comparison and simulation
SBML Model simulation
Model comparison
Model versioning
Reproducing simulations
[Jacky Snoep, Dagmar Waltemath, Martin Peters, Martin Scharm]

32. Retaining context, supporting decision making
Towards data harmonisation and indexing
[Susanna Sansone]

33. Stealthy Ramps for helping with Metadata Standards
Tooling for annotations and templates for different types of assay data
towards data harmonisation. Incentive by side effect.
Embed ontologies into
Excel templates
Excel spreadsheets enriched
with ontology annotations
Upload, extract metadata and register
http://www.rightfield.org.uk

34. Exchange and Publishing
Supplementary information
Annotation
file
Stoichiometric
matrix
SBML Stationary
fluxes
[Maxim Zakhartsev]

35. https://doi.org/10.15490/seek.1.investigation.56
Penkler et al (2015) FEBSJ 282:1481-1511.

36. Reproducible Exchange and Publishing
and better credit
Author List: Joe Bloggs; Jane Doe
Title: My Investigation
Date: September 2016
DOI: https://doi.org/10.15490/seek##
information travels with the data and models

37. FAIRDOM-SEEK local or public commons
*Troup, E.; Clark, I; Swain, P; Millar, AJ; Zielinski,T (2015) Practical evaluation of SEEK and openBIS for
biological data management in SynthSys http://hdl.handle.net/1842/12236
FAIRDOMHub.org
Vrije
Universiteit
Yellow Pages

38. IMOMESIC pathway
Integrating Modelling of Metabolism and Signalling towards an Application in Liver Cancer
https://fairdomhub.org/projects/24
[Ursula Klingmüller, Martin Böhm]

39. What about FAIR Systems Medicine?
OlafWolkenhauer et al, Enabling multiscale modeling in systems medicine, Genome Medicine 2014 6:21*
1. Samples
2. Access to sensitive data
3. Multi-models
*DOI: 10.1186/gm538, http://genomemedicine.com/content/6/3/21

40. Samples metadata framework
BBMRI, ELIXIR, Biosamples, FAIRDOM, UKCRCTissue Directory,
UK Synthetic Biology Centres
User defined sample models
Interlinking between sample types Sample type defines a
sharable standard
Tied to assay processes

41. FAIR Sensitive Data, certified repositories
walled gardens and registration flags for Catalogue
legal restrictions for sharing anonymised and non-anonymized data
Open
Data
Register metadata
Upload data
Register link
Register access method
Register metadata
Register access method
Local AAI service
Register metadata
Closed
Data
Closed
Data

42. Model Laissez-Faire
• Navigation between
• Single standards at 1 scale
• Multi-model hosting
Linking models….
• connecting (experimental/simulation) data to models
• connecting the single standards?
• interfacing between the different scales?

43. In summary…Pragmatic FAIR support
for projects people, assets, processes
• Multiple, interrelated assets
• Multiple, dispersed repositories
• Multi-partner, -discipline projects
• Multiple community tools
• Team science practices
• Experiment – Asset lifecycles
• Academic innovation drivers
meta
data
Standards-based
tools

44. Challenges to FAIR Asset Management
Free Puppies

45. FAIR Play microscopes -> data scopes,
sharing citizenship, incentives by side effects
PI leadership
Sticking to conventions
Local responsibility
Time and resource
Curation recognition
Trust
• Tribal trading behaviours
• Enclave sharing
• Not public donation
• Reciprocity & credit
Drivers …
• External dominate
• Personal productivity
affecting behavioural change
through libertarian paternalism
[Kristian Garza]

46. Jon OlavVik,
Norwegian University of Life Science
Maksim Zakhartsev
University Hohenheim, Stuttgart,
Germany
Alexey Kolodkin
Siberian Branch
Russian Academy of Sciences
Tomasz Zieliński,
SynthSys Centre
University Edinburgh, UK
Martin Peters, Martin Scharm
Systems Biology Bioinformatics
University of Rostock, Germany

47. 3rd Foundry meeting, Dec 1-2 2016
Frankfurt
Developers Foundry
Support developers of Systems Biology tools and platforms