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FAIRDOM - FAIR Asset management and sharing experiences in Systems and Synthetic Biology

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FAIRDOM - FAIR Asset management and sharing experiences in Systems and Synthetic Biology

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Over the past 5 years we have seen a change in expectations for the management of all the outcomes of research – that is the “assets” of data, models, codes, SOPs and so forth. Don’t stop reading. Data management isn’t likely to win anyone a Nobel prize. But publications should be supported and accompanied by data, methods, procedures, etc. to assure reproducibility of results. Funding agencies expect data (and increasingly software) management retention and access plans as part of the proposal process for projects to be funded. Journals are raising their expectations of the availability of data and codes for pre- and post- publication. The multi-component, multi-disciplinary nature of Systems Biology demands the interlinking and exchange of assets and the systematic recording
of metadata for their interpretation.
The FAIR Guiding Principles for scientific data management and stewardship (http://www.nature.com/articles/sdata201618) has been an effective rallying-cry for EU and USA Research Infrastructures. FAIRDOM (Findable, Accessible, Interoperable, Reusable Data, Operations and Models) Initiative has 8 years of experience of asset sharing and data infrastructure ranging across European programmes (SysMO and EraSysAPP ERANets), national initiatives (de.NBI, German Virtual Liver Network, UK SynBio centres) and PI's labs. It aims to support Systems and Synthetic Biology researchers with data and model management, with an emphasis on standards smuggled in by stealth and sensitivity to asset sharing and credit anxiety.

This talk will use the FAIRDOM Initiative to discuss the FAIR management of data, SOPs, and models for Sys Bio, highlighting the challenges of and approaches to sharing, credit, citation and asset infrastructures in practice. I'll also highlight recent experiments in affecting sharing using behavioural interventions.

http://www.fair-dom.org

http://www.fairdomhub.org

http://www.seek4science.org

Presented at COMBINE 2016, Newcastle, 19 September.
http://co.mbine.org/events/COMBINE_2016

Over the past 5 years we have seen a change in expectations for the management of all the outcomes of research – that is the “assets” of data, models, codes, SOPs and so forth. Don’t stop reading. Data management isn’t likely to win anyone a Nobel prize. But publications should be supported and accompanied by data, methods, procedures, etc. to assure reproducibility of results. Funding agencies expect data (and increasingly software) management retention and access plans as part of the proposal process for projects to be funded. Journals are raising their expectations of the availability of data and codes for pre- and post- publication. The multi-component, multi-disciplinary nature of Systems Biology demands the interlinking and exchange of assets and the systematic recording
of metadata for their interpretation.
The FAIR Guiding Principles for scientific data management and stewardship (http://www.nature.com/articles/sdata201618) has been an effective rallying-cry for EU and USA Research Infrastructures. FAIRDOM (Findable, Accessible, Interoperable, Reusable Data, Operations and Models) Initiative has 8 years of experience of asset sharing and data infrastructure ranging across European programmes (SysMO and EraSysAPP ERANets), national initiatives (de.NBI, German Virtual Liver Network, UK SynBio centres) and PI's labs. It aims to support Systems and Synthetic Biology researchers with data and model management, with an emphasis on standards smuggled in by stealth and sensitivity to asset sharing and credit anxiety.

This talk will use the FAIRDOM Initiative to discuss the FAIR management of data, SOPs, and models for Sys Bio, highlighting the challenges of and approaches to sharing, credit, citation and asset infrastructures in practice. I'll also highlight recent experiments in affecting sharing using behavioural interventions.

http://www.fair-dom.org

http://www.fairdomhub.org

http://www.seek4science.org

Presented at COMBINE 2016, Newcastle, 19 September.
http://co.mbine.org/events/COMBINE_2016

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FAIRDOM - FAIR Asset management and sharing experiences in Systems and Synthetic Biology

  1. 1. FAIRDOM – FAIR Asset management and sharing experiences in Systems and Synthetic Biology Prof Carole Goble The FAIRDOM Consortium carole.goble@manchester.ac.uk http://fair-dom.org, http://fairdomhub.org COMBINE 2016, Newcastle, UK 19 September 2016
  2. 2. FAIR Findable Accessible Interoperable Reusable https://www.force11.org/group/fairgroup/fairprinciples Intelligible Reproducible Citable Track & Countable
  3. 3. Findable Accessible Interoperable Reusable Data Operations Models Systems and Synthetic Biology Projects
  4. 4. Sys Bio Projects .... 52006 11 projects 2015 12 projects
  5. 5. Stakeholders Stress… Sponsored to Support Projects: National level and ERANets Funders / Institutions • Capitalising on investments • Skills • Justification, Audit, Compliance • Showcase access Publishers • Reproducibility • New publishable assets • New services • Showcase access
  6. 6. Projects…. Researchers’ Productivity Rhetoric Multi-partner Distributed Dynamic membership Overlaps Sensitivities Collaboration Publication Showcasing Compliance Retention Home-grown resources Public resources Mixed Skills
  7. 7. Projects’ “PAP-PA” People, Assets, Processes -> Publishing,Analysis People Assets Processes
  8. 8. Projects’ People, Assets, Processes Organisation, Communication, Dissemination Simulation SOPs Data Models StandardsAnalytics Pipelines Samples Tracking Versioning Validation Articles Strains
  9. 9. Upstream, downstream assets discovery Organisation Communication Dissemination Helps navigation Reuse later Enable team to reuse/ reproduce Help others find out Reuse with new partners Tell more and take credit Collecting and tracking data/models Choosing what to keep Preparing what to share and when Most data/models won’t be shared • Wrong experimental method • Hidden parameter discovered • Faulty experiment Promote standardised metadata practices
  10. 10. FAIR Projects & Programmes 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?
  11. 11. FAIR Projects and Programmes Findable Exchange & find assets and people Citation Credit Accessible Share, disseminate and publish assets sensitively Gateway to third party tools, archives Store assets Package assets Track collection of data and metadata Consistent reporting for interpretation, interop & comparison Promote and support standardised metadata practices. Support reproducible publications Organise and link assets Maintain the experimental context Retain results beyond a project Reuse results, tools, archives Respect local solutions Standards! Standards!
  12. 12. FAIRDOM Initiative Project Support Community Actions Platforms,Tools Public Project Commons
  13. 13. FAIRDOM Community, Knowledge Hub http://www.fair-dom.org Know-how, Guides,Templates, Workshops,Training, Webinars, Standards and Policy Forums
  14. 14. Policy and International Initiatives
  15. 15. Surveys Stanford et alThe evolution of standards and data management practices in systems biology, Molecular Systems Biology (2015) 11: 851 DOI 10.15252/msb.20156053
  16. 16. Community Clubs http://www.fair-dom.org Samples Club with ELIXIR, BBMRI-ERIC, EBI… Rework and harmonise sample metadata framework bioschemas.org Developers Foundry Support developers of Systems Biology tools and platforms 3rd Foundry meeting Dec 1-2 2016, Frankfurt
  17. 17. FAIRDOM Platforms andTools FAIR Sharing Metadata Catalogue Project Commons Cross-repository gateway Tool gateway Results repository Web-based Local Storage Analytics Tracking LIMS, Auto-archiving In flight repositoryLocal-based
  18. 18. FAIRDOM Platform Installations *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 Local retention and In flight management, Private sharing Centres, large or national projects Local skills One stop showcase Programmes Post-project retention Supplementary materials
  19. 19. People and Project Commons FAIRDOMHub.org self-managed workspaces Sharing sensitivity
  20. 20. Investigation Study Analysis Data Model SOP(Assay)
  21. 21. Linking, “Packaging” & Citing Codes, Data, Models, SOPs, Samples, Strains, Articles, People, Projects…. Packaging
  22. 22. 25 Jon Olav Vik, Norwegian University of Life Science
  23. 23. 26 Programme Overarching research theme (The Digital Salmon) Project Research grant (DigiSal, GenoSysFat) Investigation A particular biological process, phenomenon or thing (typically corresponds to [plans for] one or more closely related papers) Study Experiment whose design reflects a specific biological research question Assay Standardized measurement or diagnostic experiment using a specific protocol (applied to material from a study) Jon Olav Vik, Norwegian University of Life Science
  24. 24. Visible, but details maybe inaccessible Visibility controls
  25. 25. STUDY ASSAYINVESTIGATION Experimental assay Modeling assay Publication Maksim Zakhartsev
  26. 26. Glucose Glycerol Ethanol Glycolysis PPP TCA CO2 Lactate Carbohydrates Nucleotides Kinases Pyrophosphotase RNA Electron transport Maintenance C1 metabolism Proteines NH4 transportSulfur metabolism Biomass Lipids Stoichiometric model 3 0 Stoichiometric model of Saccaromyces cerevisiae growing anaerobically at D=0.1 h¯¹ Compartments 1 Pathways 35 Transformers: 254 reactions 214 transports 33 polymerizati on 7 Compounds 253 balanced comp. 234
  27. 27. Supplementary information Annotation file SEEK Stoichiometric matrix SEEK SBML SEEK Stationary fluxes SEEK
  28. 28. ODE-based model 3 2 example = glc-permease  variables: Cex glc, Cglc, Cg6p parameters: Rmax, Kglc, KI-g6p, KII-g6p 0 500 1000 1500 0 2 4 6 glc-ex C i [mmol/L] 0 500 1000 1500 0 0.05 0.1 glc-in C i [mmol/L] 0 500 1000 1500 0 2 4 6 g6p C i [mmol/L] 0 500 1000 1500 0 1 2 3 f6p time [sec] C i [mmol/L]   0 ex glc pulseex pulsex glc glc Perm glc r dC FC D C C t r a C dt V     max .1 .1 6 6 .1 .1 6 .1 .1 6 .1 .1 max .1 .1 .1 1 1 1 1 1 1 1 perm influx efflux ex glc perm glc influx ex glc ex glc glc glc g p glc g p glcglc glc I g p glc II g p glc glc perm glc efflux glc glc glc glc r r r C R K r C C K C C C C CK K K K K K C R K r C C K K                       6 6 .1 6 .1 .1 6 .1 .1 1 ex glc g p glc g p ex glc glc I g p glc II g p glc C C C C C K K K K K            [Rizzi et al., 1997] DATA file Equations Simulations
  29. 29. https://dx.doi.org/10.11 11/febs.13237 https://doi.org/10.15490/seek.1.inves tigation.56 Model Publication Publishing and data citation reviewer Institutional Repository
  30. 30. FAIRDOM Catalogue, a web of resources drawing together across resources; reusing tools and repositories respect local project solutions, tool plugins Standards Personal Data Local Stores External Databases Publishing services Modelling tools SOPs BiVes Data tools
  31. 31. Specialist Public Repositories General archives Repository Repertoire Stanford et alThe evolution of standards and data management practices in systems biology, Molecular Systems Biology (2015) 11: 851 DOI 10.15252/msb.20156053 Local Data Stores
  32. 32. Laissez-Faire
  33. 33. openBIS metadata extraction data relationship/linking data processing minimal user input *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
  34. 34. Modelling standards based in browser validation and simulation Model comparison and versioning SBML Model simulation [Stellenbosch, Rostock]
  35. 35. http://seekdb.bionet.nsc.ru/ Alexey Kolodkin Siberian Branch RussianAcademy of Sciences
  36. 36. Reproducible model simulations in papers using COMBINE Archive & SED-ML [Jacky Snoep, DagmarWaltemath, Martin Peters ] Three tiered service store DOI citable supplementary files on FAIRDOMHub model and data curation reproducible clickable figures in papers using SED- ML
  37. 37. COMBINEArchives support Martin PetersTalkWednesday Morning
  38. 38. COMBINEArchives support Martin PetersTalkWednesday Morning
  39. 39. COMBINEArchives support Martin PetersTalkWednesday Morning
  40. 40. Standards-based Structured Description templates, register, harvest, index, search Metadata Catalogue Storage Registermetadata Uploaddata Registerlink Registeraccessmethod Closed Storage
  41. 41. Hooking together templates, register, harvest, index, search Just Enough Results Model Sample Spread sheets!! JBEI-ICE LabCollector LabArchives Jupyter Galaxy / Refinery in the works…. SPARQL endpoint release Focus – joining stuff up! - JSON read/write API - ISA-TAB output
  42. 42. Spreadsheet tooling for metadata templates and metadata harvesting
  43. 43. Data annotation with standards Embed ontologies into Excel templates Excel spreadsheets enriched with ontology annotations Upload, extract metadata and register in browser viewing + annotations
  44. 44. Model annotation – in schema
  45. 45. Model annotation – semanticSBML
  46. 46. Samples Club samples framework Sample type defines a sharable standard
  47. 47. Spotlight: Synthetic Biology SynBioChem Centre, UK
  48. 48. FAIRDOMWorkflows and Pathways
  49. 49. Project Support – Understanding Process Planning, Setups, Curation, Advice, Support Community support Specialprojectsupport Specialprojectsupport model technical curation with our JWS Online partners PALs project ambassadors co-design, tailoring, communication, requirements, review standard, best practices
  50. 50. More Projects and Centres User Meeting, Barcelona@ICSB 2016
  51. 51. Processes and People • 80% process, 20% tech • Structuring the ISA • PIs • Sticking to conventions and policies • Tension with standards take-up vs laissez faire • Time and resource • Local responsibility • Recognition • Institutional Repositories • Automagic
  52. 52. • Licenses • Negotiated access • Embargos • Permission controls • Staged sharing • Private walled gardens FAIR Play Using FAIRDOM my own lab colleagues saw what I was doing and called to collaborate! Jurgen Hannstra Vrije Universiteit Amsterdam, Netherlands
  53. 53. FAIR Play • Drivers – External dominate – Personal productivity • Trading behaviours – Tribal based – Modellers vs Experimentalists • “enclave” sharing – Rather than public donation • Reciprocity & credit – Citation affecting behavioural change through libertarian paternalism* *Garza et al Framing the Community Data System Interface, https://dx.doi.org/10.6084/m9.figshare.1300051.v5 Stanford et al The evolution of standards and data management practices in systems biology, Molecular Systems Biology (2015) 11: 851 DOI 10.15252/msb.20156053
  54. 54. FAIRDOMAssociation e.V.
  55. 55. Jon OlavVik, Norwegian University of Life Science Maksim Zakhartsev Plant Systems Biology University Hohenheim Stuttgart, Germany Alexey Kolodkin Siberian Branch Russian Academy of Sciences Tomasz Zieliński, SynthSys Centre University Edinburgh

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