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FAIR, community standards and data FAIRification:
components and recipes
1st Annual Symposium of the Alan Turing Institute’s Knowledge Graphs IG, 17 June, 2022
Slides: https://www.slideshare.net/SusannaSansone
Group:
datareadiness.eng.ox.ac.uk
ORCiD: 0000-0001-5306-5690
Twitter: @SusannaASansone
Susanna-Assunta Sansone
Professor of Data Readiness;
Associate Director, Oxford e-Research Centre
Philippe Rocca-Serra
Associate Member of Faculty;
Group Coordinator, Oxford e-Research Centre
ORCiD: 0000-0001-9853-5668
Twitter: @Phil_at_OeRC
Outline
Discoveries are made using shared data and this requires data that are:
• Cited and stored to be discoverable
• Retrievable and structured in standard format(s)
• Richly described to be understandable
Rationale behind the FAIR Principles
https://www.forbes.com/sites/gilpress/2016/03/23/data-
preparation-most-time-consuming-least-enjoyable-data-science-
task-survey-says/#276a35e6f637
Data preparation accounts for about 80% of the work of data scientists
Use of data at scale by humans and machines
Globally unique and
persistent identifiers
Community defined
descriptive metadata
Community defined
terminologies
Detailed
provenance
Terms of access
Terms of
use
doi.org/10.2777/986252
www.gov.uk/government/publications/open-
research-data-task-force-final-report
www.turing.ac.uk/research/impact-
stories/changing-culture-data-science
www.fair-access.net.au
doi.org/10.1787/25186167 ark:/48223/pf0000374837
FAIR has aligned the broad community
around common guidelines
doi.org/10.7486/DRI.tq582c863
FAIR Principles:
a continuum of features, attributes and behaviours
Making FAIR a reality in the research ecosystem
doi.org/10.2777/1524
An intergovernmental organisation that brings
together life science resources
from across Europe, to coordinate them so that
they form a single infrastructure
ELIXIR - a sustainable infrastructure for
biological data
Food & Nutrition
+ Toxicology
#ELIXIR22
Some examples:
Projects and Communities, incl.: Global
initiatives,e.g
NEW: RDA Life Science Infrastructure IG with Australia BioCommons,
the US NIH Office of Data Science Strategy, and H3ABioNet in Africa.
IMI2 project guidelines for
open access to publications
and research data
Funders’
guidelines
ELIXIR Interoperability Platform:
FAIR Service Framework
IMI2 project guidelines for
open access to publications
and research data
Recommended by
European funders
ELIXIR FAIR Service Framework:
focus on two resources
(All disciplines)
(Life Science focused)
An informative and educational resource, and a service
FAIRsharing provides curated descriptions and relationship graphs of
standards, databases and policies in all disciplines
COMMUNITY STANDARDS
POLICIES
by funders, journals
and other organizations
DATABASES
including repositories
and knowledgebases
Identifiers
Terminologies Guidelines
Formats
Identifiers
Terminologies Guidelines
Formats
Conceptual model, conceptual
schema, exchange formats
to represent, contain and
move information
Controlled vocabularies,
thesauri, ontologies
to disambiguate terms
and enable semantic
relationships
Minimum information
reporting requirements,
or checklists
to report the same core,
essential information
Unambiguous, persistent and
context-independent schema
to identify data
and metadata elements
Standards to report metadata and data:
the pillars of FAIR
Identifiers
Terminologies Guidelines
Formats
Natural, engineering, humanities & social sciences
829
510
234
23
More than 1596 data and metadata standards
MIAME
MIRIAM
MIQAS
MIX
MIGEN
ARRIVE
…
MIAPE
MIASE
…
MISFISHIE
….
REMARK
CONSORT
SRAxml
SDTM FASTA
DICOM
OMOP
…
SBRML
SEDML
…
CDASH
ISA CML
MITAB
…
AAO
CHEBI
OBI
PATO ENVO
MOD
BTO
IDO
…
TEDDY
PRO
…
XAO
DO
…
VO EC number
URL PURL
LSID
Handle
ORCID
RRID
…
InChI
…
IVOA ID
…
DOI
Standard organizations, e.g.: Grass-roots groups, e.g.:
Life and biomedical sciences
Identifiers
Terminologies Guidelines
Formats
530
294
163
10
More than 900 data and metadata standards
Standard organizations, e.g.: Grass-roots groups, e.g.:
• Industry-level standards
• Mostly regulators-driven
• Participation is often regulated
• Standards are sold or licenced
• Formal development process, often
less flexible, could be lengthy
• Charges apply to advanced training
or programmatic access
• Mostly research-level standards
• Open to any interested party
• Volunteering efforts
• Standards are free for use
• Development process varies, more
flexible and adaptable to changes
• Minimal or little funds for carry out the
work, let alone provide training
Understanding their life cycle and landscape
Identifiers
Terminologies Guidelines
Formats
Standards: known pain points
DOI: 10.6084/m9.figshare.4055496.v1
Technical and social challenges, including:
• Fragmentation, harmonization and extensions
• Governance and ownership
• Indicators and evaluation methods
• Implementations, tools and services
• Synergies between basic and clinical/medical areas
• Credit and incentives for contributors
• Education, documentation and training
• Funding streams to support the ‘standard life cycle’
• Business models for sustainability
Guides consumers to discover, select and use these resources with confidence
Helps producers to make their resources more visible, more widely adopted and cited
Promoting the value of standards, their use in
repositories and adoption by policies
Total of
over 3639 resources
(June 2022)
repositories
standards
policies
Track the evolution of standards
URL:
https://committee.iso.org
/standard/68848.html
URL: fhttps://fairsharing.org/3533
Translational Medicine
Clinical Developments
URL: https://fairsharing.org/3519
(work in progress!)
A collaboration with their FAIR Implementation WG
Disclaimer: These profiles speak for a limited community and do not represent any company standards
Building and comparing
“FAIR profiles”
Clinical Developments
Disclaimer: These profiles speak for a limited community and do not represent any company standards
Snapshot of the semantic and
syntactic standards used
Findability
Sitemap.xml, JSON
Markup with Schema.org for
search indexes
DOI unique persistent
identifiers for each record
ORCID for author credit and
authentication
Accessibility
read/write REST API
read OAI-PMH
Interoperability
JSON markup
Standardized semantics
Cross-links to or import from
records in other registries
ROR for organizations (ongoing)
FundRef for funders (ongoing)
Reusability
CC BY 4.0 license
JSON export
The FAIRness of the FAIRsharing
Researchers Developers and
curators
Journal
publishers
Societies and
Alliances
Librarians and
Trainers
Funders
FAIRsharing: working with and for all stakeholders
Users, adopters and collaborators include:
https://fairsharing.org/communities
An endorsed output of the
FAIRsharing WG (since 2015):
A WG (since 2015) in:
A recommended resource in EOSC reports
Users from all stakeholder groups
Researchers Developers and curators Journal publishers
Societies and Alliances
Librarians and Trainers Funders
FAIRsharing: working with and for all stakeholders
https://eoscfuture-
grants.eu/node/262
https://fairsharing.org/community_curation
Soft launch with the first life science curators:
FAIRsharing: Community Curation Programme
Interested?
More at https://blog.fairsharing.org/?p=269
A 10,000 foot view of the EOSC Research Graph
“Open, participatory research graph where products of the
research life-cycle (e.g. scientific literature, research data,
project, software) are semantically linked to each other and carry
information about their access rights (i.e. if they are Open
Access, Restricted, Embargoed, or Closed) and the sources
from which they have been collected and where they are hosted”
URL: graph.openaire.eu
ELIXIR wants to make sure our data resources are
visible in this EOSC Research Graph
● Ensuring that ELIXIR resources and services, starting from databases,
knowledge bases and repositories are more discoverable in EOSC
○ Via the EOSC Research Graph by OpenAIRE
● Note that currently our understanding of this graph is limited
○ Still unclear of what the specific use cases are, how granular it will be etc.
This ELIXIR work is by:
Allyson Lister, FAIRsharing
Alasdair Gray, Bioschemas
and contributors
ELIXIR end goals:
feed proper info in the graph, and easily
FAIRsharing and Bioschemas as
information providers
● Provides rich descriptions of the databases, incl. content
types, access conditions, mantainers (ORCiD),
organizations (ROR) etc., also interlinked with standards
● And we already have descriptions of many/most ELIXIR
and EOSC-Life databases and standards
● Provides key metadata for discoverability of dataset content
● Many ELIXIR databases’ pages are already marked up
Prototyping the process - unfunded
Mapping
and
harvesting
We are mapping Bioschemas to
the Datacite schema (Enrico
Ottonello, Andreas Czerniak, Nick Juty,
Alasdair J. G. Gray)
We are mapping FAIRsharing model
and databases IDs to the openAIRE
model (Ramon Granell, Alessia Bardi,
Delphine Dauga, Allyson Lister)
OpenAIRE retrieves general
info from FAIRsharing and
follows the link to the
sitemap where it harvest the
Bioschemas mark-up
1. They register (or claim) their database, adding
(or vetting) additional descriptors, including:
- mantainers, as individuals and organizations
- publications
- data access conditions
- standards implemented
2. They specify the Bioschemas access points
1. ELIXIR members markup their database’s
pages, including links to:
- containing dataset
- publications
- equivalent resources in other sites
2. Create a sitemap
Bioschemas - database records: consolidation of
concepts
DOI: 10.25504/FAIRsharing.jwra3e
DOI: 10.25504/FAIRsharing.dt9z89
FAIRsharing - database as a whole: full descriptions
DOI: 10.25504/FAIRsharing.dt9z89
License
Maintainer(s)
Standard(s)
Database(s)
API
Life cycle
status
Overview information and status
FAIRsharing - database as a whole
DOI: 10.25504/FAIRsharing.dt9z89
Subject classification
Classification is powered by our
Subject Ontology of 436 terms
URL: fairsharing.org/browse/subject
URL: github.com/FAIRsharing/subject-ontology
FAIRsharing - database as a whole
DOI: 10.25504/FAIRsharing.dt9z89
Organizations and publications
FAIRsharing - database as a whole
DOI: 10.25504/FAIRsharing.dt9z89
Standards implemented and
related databases
FAIRsharing - database as a whole
DOI: 10.25504/FAIRsharing.dt9z89
Access points and conditions
FAIRsharing - database as a whole
These are profiles of the
organizations and their RIs, with
their data resources and standards
URL: fairsharing.org/graph/3513
FAIRsharing - building maps of resources
Collection URL: fairsharing.org/graph/3515;
each record has a DOI
Collection URL: fairsharing.org/graph/3513;
each record has a DOI
FAIRsharing - working with communities to create
subject-specific collection of resources
Stakeholder Advisors
● Amye Kenall, VP of Publishing and Product, Research Square
● Adam Leary, Oxford University Press
● Catriona MacCallum, Hindawi
● Dagmar Meyer, European Research Council, Executive Agency
● Dominic Fripp, JISC, UK
● Emma Ganley, Protocols.io
● Geraldine Clement-Stoneham, Medical Research Council
● Helena Cousijn, DataCite
● Iain Hrynaszkiewicz, PLoS
● Imma Subirats, FAO of the United Nations
● Kiera McNiece, Cambridge University Press
● Luiz Olavo Bonino, GO-FAIR
● Marina Soares E Silva and Sarah Callaghan, Elsevier
● Michael Ball, Biotechnology and Biological Sciences Research Council
● Mike Huerta, NIH National Library of Medicine
● Molly Cranston and Guillaume Wright, F1000Research
● Nick Everitt and Matthew Cannon, Taylor and Francis
● Scott Edmunds, GigaScience, Oxford University Press
● Simon Hodson, CODATA
● Theo Bloom, British Medical Journal
● Thomas Lemberger, EMBO Press
● Wei-Mun Chan, eLife
● Sowmya Swaminathan, Springer Nature
Current operational Team
● Allyson Lister, Content and Community Lead
● Milo Thurston, Technical Lead
● Ramon Granell, Data Enrichment & Quality Manager
● Delphine Dauga, Data Curator Manager
● Hiring in progress, Web Developer
● Dominique Batista, Research Software Engineer
● Philippe Rocca-Serra, Co-Founder
● Susanna-Assunta Sansone, PI and Founder
● and many collaborators and contributors!
Executive Advisors
● Varsha Khodiyar, Independent expert
● Chris Graf, Springer Nature
● David Carr, Independent expert
● Robert Hanisch, Director, NIST Office of Data & Informatics
● Peter McQuilton, FAIRsharing Founding Member, GSK
FAIR
Cookbook
A resource part of the
ELIXIR ecosystem,
but open to all!
https://faircookbook.elixir-europe.org
Motivations and ambitions
beyond the hype
Large body of generic FAIR
guidance
Motivations
Non-specific guidance for
the life sciences
Ambitions
Target specific situations to deliver a guide with
applied examples
Join academia and industry forces to make the
case for FAIR data management
Build capacity for high quality data
management in the private and public sectors
Lack of practical examples
of ‘how-to’ with different
data types and scenarios
FAIR-driven digital transformation by pharmas
● Biopharma R&D productivity can be improved
by implementing the FAIR Principles
● FAIR enables powerful new AI analytics to
access data for machine learning and prediction
● Requirements
○ financial, technical, training
● Challenges
○ change the culture, show business value,
achieve the ‘FAIR enough’ on an
The FAIR Cookbook
What is it?
An online, ‘live’ resource
for the life sciences
A collection of recipes
that cover the operation
steps of FAIR data
management
Who is it for?
Anyone who needs
practical assistance in
their FAIRification
journey or creates FAIR
guidance and
educational material
Who developed it?
Researchers and data
managers professionals
in the life sciences, from
academia and industry
Including ELIXIR members
https://faircookbook.elixir-europe.org
Learning objectives and who is the
Cookbook user?
Researchers,
Data Scientists,
Principal
Investigators
Data Managers,
Data Stewards,
Data Curators
Software
Developers,
Terminology
Managers
Policymakers,
Funders,
Trainers
Learn how to improve the FAIRness with
exemplar datasets
Understand the levels and indicators of
FAIRness
Discover open source technologies, tools
and services
Find out the required skills
Acknowledge the challenges
The Cookbook platform
open source community practices
Built using jupyter-book, following the practice used by
the Alan Turing Institute’ the Turing Way book, an open
source community-driven guide to reproducible, ethical,
inclusive and collaborative data science
Technology stack:
● github for version control and hosting
● Markdown the write-up
● HackMD markdown editor, integrated with github
● jupyter notebook for executable code
● binder for the web execution of jupyter notebook
distributed with a recipe
● mermaid javascript library for flowcharts, Gantt
charts and pie charts
https://the-turing-way.netlify.app/welcome
Current coordinators and editors
we are here to help
Content prioritisation
Identification of topics
Review of drafts
Call for contributions
Monthly book-dash
events
Pre-defined focus areas
Breakout on topics
Housekeeping
Technical platform
Website
Editorial Board Sections Board
The newly
developed
sections board
assists the
editorial board
Dominique Batista
Martin Cook
Contributors to date
Almost 100 life sciences professionals, researchers and data managers
FARIplus
partners
Industry
+
Academia
ELIXIR
Nodes
represented
● Over 70 recipes released
and more content
available
● Covering technical
processes with
FAIRification examples in
the life sciences:
○ Omics
○ pre-clinical
○ clinical areas
But not limited to it!
A resource for FAIR doers
Content type overview
Recipes focused on
each technical aspects,
and applicable to any
data type
Recipes specific to a
topic or data type
Content type overview
https://w3id.org/faircookbook/FCB004
https://w3id.org/faircookbook/FCB046
Exemplar chapter content
Interoperability
Content type overview
http://w3id.org/faircookbook/FCB044
http://w3id.org/faircookbook/FCB042
Content type overview
https://w3id.org/faircookbook/FCB050
https://w3id.org/faircookbook/FCB049
Anatomy of a recipe
components
Ingredients
An idea of tools/skills needed
Step by step process
Guidelines, process, description
Practical
elements, code
snippets
#Python3
#zooma-annotator-script.py
file
def
get_annotations(propertyType
, propertyValues, filters = ""): "
Examples
Conclusions
What should I read next?
Credit and citability
because your contribution matters!
CreDiT
attribution ontology
w3id.org/faircookbook/FCB006
The FAIRness of the Cookbook
Accessibility
HTTPS protocol
Interoperability
JSON-LD markup
Cross-links to objects in other
registries
From the ELIXIR ecosystem and beyond!
CreDiT attribution ontology
Reusability
CC BY 4.0 license for all
content
Findability
Sitemap.xml, JSON-LD
Markup with Schema.org,
Bioschemas
w3id.org unique persistent
identifiers for each recipe
ORCID for authors
The reusability chapter
https://w3id.org/faircookbook/FCB035
https://w3id.org/faircookbook/FCB035
https://doi.org/10.1016/j.xgen.2021.100028
Tagging recipes with
‘Dataset Maturity Indicators’
Maturity level and indicators
new available feature
https://fairplus.github.io/Data-Maturity
Provide insights into FAIR Maturity reached by
applying a specific recipe to improve a dataset
The Maturity chapter
Moving through maturity levels
What is missing?
Demonstrated benefits of FAIR for Reuse
• HPLC data fairification for AI: @Abbvie, Axel Wilbertz
• Image data annotation: @AZ, Alexander Buschle
• Integration of GWAS data: @BenevolentAI, Jia Li
• Biomap project: @UL, Irina Balaur, Soumyabrata Gosh
• Increasing number of (competing) semantic resources
• “Let 1000 flowers bloom” is nice but…
• Converging towards shared curation practice (precompetitive) and
efficient patterns
The challenge of interoperability: FAIR silos?
https://arxiv.org/pdf/2102.10062.pdf https://arxiv.org/pdf/2112.06567.pdf
Become part of a
community of FAIR experts!
1Identify a chapter and a topic
Findability Accessibility Interoperability Reusability
Infrastructure Applied examples Assessment
2 Choose a way of contributing and see our guidelines
Google Docs
HackMD
Git
Markdown cheat sheet
Get recipe template
Tips and tricks
Submit an
outline
3
You can
discuss it
with the
Editorial
Board
Start using the
FAIR Cookbook
Help us to help you,
this is a user-
oriented resource
Join a network
of FAIR experts
Share and broaden
your expertise,
joining our journey
Contribute
according to
your needs
Create and review,
or signpost gaps and
needs
Benefit from the
power of the
FAIR community
Become a recognised
expert, enlarge your
network
Recommend it
in your guidance
and training
material
For everyone
use it join it
adopted!
leverage it
The
roadmap,
your steps
Thanks to
Editorial Board
Section Editors
FAIRplus partners
All bookdashes’ participants
All authors
fairplus-cookbook@elixir-europe.org
faircookbook.elixir-europe.org
fairplus-project.eu This project has received funding from the Innovative Medicines Initiative Joint Undertaking under grant agreement No 802750. This Joint Undertaking receives
support from the European Union’s Horizon 2020 research and innovation programme and EFPIA Companies. This communication reflects the views of the
authors and neither IMI nor the European Union, EFPIA or any Associated Partners are liable for any use that may be made of the information contained herein.

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FAIR, community standards and data FAIRification: components and recipes

  • 1. FAIR, community standards and data FAIRification: components and recipes 1st Annual Symposium of the Alan Turing Institute’s Knowledge Graphs IG, 17 June, 2022 Slides: https://www.slideshare.net/SusannaSansone Group: datareadiness.eng.ox.ac.uk ORCiD: 0000-0001-5306-5690 Twitter: @SusannaASansone Susanna-Assunta Sansone Professor of Data Readiness; Associate Director, Oxford e-Research Centre Philippe Rocca-Serra Associate Member of Faculty; Group Coordinator, Oxford e-Research Centre ORCiD: 0000-0001-9853-5668 Twitter: @Phil_at_OeRC
  • 3. Discoveries are made using shared data and this requires data that are: • Cited and stored to be discoverable • Retrievable and structured in standard format(s) • Richly described to be understandable Rationale behind the FAIR Principles https://www.forbes.com/sites/gilpress/2016/03/23/data- preparation-most-time-consuming-least-enjoyable-data-science- task-survey-says/#276a35e6f637 Data preparation accounts for about 80% of the work of data scientists
  • 4. Use of data at scale by humans and machines Globally unique and persistent identifiers Community defined descriptive metadata Community defined terminologies Detailed provenance Terms of access Terms of use
  • 6. FAIR Principles: a continuum of features, attributes and behaviours
  • 7. Making FAIR a reality in the research ecosystem doi.org/10.2777/1524
  • 8. An intergovernmental organisation that brings together life science resources from across Europe, to coordinate them so that they form a single infrastructure
  • 9. ELIXIR - a sustainable infrastructure for biological data Food & Nutrition + Toxicology
  • 10. #ELIXIR22 Some examples: Projects and Communities, incl.: Global initiatives,e.g NEW: RDA Life Science Infrastructure IG with Australia BioCommons, the US NIH Office of Data Science Strategy, and H3ABioNet in Africa. IMI2 project guidelines for open access to publications and research data Funders’ guidelines ELIXIR Interoperability Platform: FAIR Service Framework
  • 11. IMI2 project guidelines for open access to publications and research data Recommended by European funders ELIXIR FAIR Service Framework: focus on two resources (All disciplines) (Life Science focused)
  • 12.
  • 13. An informative and educational resource, and a service FAIRsharing provides curated descriptions and relationship graphs of standards, databases and policies in all disciplines COMMUNITY STANDARDS POLICIES by funders, journals and other organizations DATABASES including repositories and knowledgebases Identifiers Terminologies Guidelines Formats
  • 14. Identifiers Terminologies Guidelines Formats Conceptual model, conceptual schema, exchange formats to represent, contain and move information Controlled vocabularies, thesauri, ontologies to disambiguate terms and enable semantic relationships Minimum information reporting requirements, or checklists to report the same core, essential information Unambiguous, persistent and context-independent schema to identify data and metadata elements Standards to report metadata and data: the pillars of FAIR
  • 15. Identifiers Terminologies Guidelines Formats Natural, engineering, humanities & social sciences 829 510 234 23 More than 1596 data and metadata standards
  • 16. MIAME MIRIAM MIQAS MIX MIGEN ARRIVE … MIAPE MIASE … MISFISHIE …. REMARK CONSORT SRAxml SDTM FASTA DICOM OMOP … SBRML SEDML … CDASH ISA CML MITAB … AAO CHEBI OBI PATO ENVO MOD BTO IDO … TEDDY PRO … XAO DO … VO EC number URL PURL LSID Handle ORCID RRID … InChI … IVOA ID … DOI Standard organizations, e.g.: Grass-roots groups, e.g.: Life and biomedical sciences Identifiers Terminologies Guidelines Formats 530 294 163 10 More than 900 data and metadata standards
  • 17. Standard organizations, e.g.: Grass-roots groups, e.g.: • Industry-level standards • Mostly regulators-driven • Participation is often regulated • Standards are sold or licenced • Formal development process, often less flexible, could be lengthy • Charges apply to advanced training or programmatic access • Mostly research-level standards • Open to any interested party • Volunteering efforts • Standards are free for use • Development process varies, more flexible and adaptable to changes • Minimal or little funds for carry out the work, let alone provide training Understanding their life cycle and landscape Identifiers Terminologies Guidelines Formats
  • 18. Standards: known pain points DOI: 10.6084/m9.figshare.4055496.v1 Technical and social challenges, including: • Fragmentation, harmonization and extensions • Governance and ownership • Indicators and evaluation methods • Implementations, tools and services • Synergies between basic and clinical/medical areas • Credit and incentives for contributors • Education, documentation and training • Funding streams to support the ‘standard life cycle’ • Business models for sustainability
  • 19.
  • 20. Guides consumers to discover, select and use these resources with confidence Helps producers to make their resources more visible, more widely adopted and cited Promoting the value of standards, their use in repositories and adoption by policies Total of over 3639 resources (June 2022) repositories standards policies
  • 21. Track the evolution of standards
  • 23. Translational Medicine Clinical Developments URL: https://fairsharing.org/3519 (work in progress!) A collaboration with their FAIR Implementation WG Disclaimer: These profiles speak for a limited community and do not represent any company standards Building and comparing “FAIR profiles”
  • 24. Clinical Developments Disclaimer: These profiles speak for a limited community and do not represent any company standards Snapshot of the semantic and syntactic standards used
  • 25. Findability Sitemap.xml, JSON Markup with Schema.org for search indexes DOI unique persistent identifiers for each record ORCID for author credit and authentication Accessibility read/write REST API read OAI-PMH Interoperability JSON markup Standardized semantics Cross-links to or import from records in other registries ROR for organizations (ongoing) FundRef for funders (ongoing) Reusability CC BY 4.0 license JSON export The FAIRness of the FAIRsharing
  • 26. Researchers Developers and curators Journal publishers Societies and Alliances Librarians and Trainers Funders FAIRsharing: working with and for all stakeholders
  • 27. Users, adopters and collaborators include: https://fairsharing.org/communities An endorsed output of the FAIRsharing WG (since 2015): A WG (since 2015) in: A recommended resource in EOSC reports Users from all stakeholder groups Researchers Developers and curators Journal publishers Societies and Alliances Librarians and Trainers Funders FAIRsharing: working with and for all stakeholders
  • 28. https://eoscfuture- grants.eu/node/262 https://fairsharing.org/community_curation Soft launch with the first life science curators: FAIRsharing: Community Curation Programme Interested? More at https://blog.fairsharing.org/?p=269
  • 29. A 10,000 foot view of the EOSC Research Graph “Open, participatory research graph where products of the research life-cycle (e.g. scientific literature, research data, project, software) are semantically linked to each other and carry information about their access rights (i.e. if they are Open Access, Restricted, Embargoed, or Closed) and the sources from which they have been collected and where they are hosted” URL: graph.openaire.eu
  • 30. ELIXIR wants to make sure our data resources are visible in this EOSC Research Graph ● Ensuring that ELIXIR resources and services, starting from databases, knowledge bases and repositories are more discoverable in EOSC ○ Via the EOSC Research Graph by OpenAIRE ● Note that currently our understanding of this graph is limited ○ Still unclear of what the specific use cases are, how granular it will be etc. This ELIXIR work is by: Allyson Lister, FAIRsharing Alasdair Gray, Bioschemas and contributors
  • 31. ELIXIR end goals: feed proper info in the graph, and easily
  • 32. FAIRsharing and Bioschemas as information providers ● Provides rich descriptions of the databases, incl. content types, access conditions, mantainers (ORCiD), organizations (ROR) etc., also interlinked with standards ● And we already have descriptions of many/most ELIXIR and EOSC-Life databases and standards ● Provides key metadata for discoverability of dataset content ● Many ELIXIR databases’ pages are already marked up
  • 33. Prototyping the process - unfunded Mapping and harvesting We are mapping Bioschemas to the Datacite schema (Enrico Ottonello, Andreas Czerniak, Nick Juty, Alasdair J. G. Gray) We are mapping FAIRsharing model and databases IDs to the openAIRE model (Ramon Granell, Alessia Bardi, Delphine Dauga, Allyson Lister) OpenAIRE retrieves general info from FAIRsharing and follows the link to the sitemap where it harvest the Bioschemas mark-up 1. They register (or claim) their database, adding (or vetting) additional descriptors, including: - mantainers, as individuals and organizations - publications - data access conditions - standards implemented 2. They specify the Bioschemas access points 1. ELIXIR members markup their database’s pages, including links to: - containing dataset - publications - equivalent resources in other sites 2. Create a sitemap
  • 34. Bioschemas - database records: consolidation of concepts
  • 37. DOI: 10.25504/FAIRsharing.dt9z89 Subject classification Classification is powered by our Subject Ontology of 436 terms URL: fairsharing.org/browse/subject URL: github.com/FAIRsharing/subject-ontology FAIRsharing - database as a whole
  • 38. DOI: 10.25504/FAIRsharing.dt9z89 Organizations and publications FAIRsharing - database as a whole
  • 39. DOI: 10.25504/FAIRsharing.dt9z89 Standards implemented and related databases FAIRsharing - database as a whole
  • 40. DOI: 10.25504/FAIRsharing.dt9z89 Access points and conditions FAIRsharing - database as a whole
  • 41. These are profiles of the organizations and their RIs, with their data resources and standards URL: fairsharing.org/graph/3513 FAIRsharing - building maps of resources
  • 42. Collection URL: fairsharing.org/graph/3515; each record has a DOI Collection URL: fairsharing.org/graph/3513; each record has a DOI FAIRsharing - working with communities to create subject-specific collection of resources
  • 43. Stakeholder Advisors ● Amye Kenall, VP of Publishing and Product, Research Square ● Adam Leary, Oxford University Press ● Catriona MacCallum, Hindawi ● Dagmar Meyer, European Research Council, Executive Agency ● Dominic Fripp, JISC, UK ● Emma Ganley, Protocols.io ● Geraldine Clement-Stoneham, Medical Research Council ● Helena Cousijn, DataCite ● Iain Hrynaszkiewicz, PLoS ● Imma Subirats, FAO of the United Nations ● Kiera McNiece, Cambridge University Press ● Luiz Olavo Bonino, GO-FAIR ● Marina Soares E Silva and Sarah Callaghan, Elsevier ● Michael Ball, Biotechnology and Biological Sciences Research Council ● Mike Huerta, NIH National Library of Medicine ● Molly Cranston and Guillaume Wright, F1000Research ● Nick Everitt and Matthew Cannon, Taylor and Francis ● Scott Edmunds, GigaScience, Oxford University Press ● Simon Hodson, CODATA ● Theo Bloom, British Medical Journal ● Thomas Lemberger, EMBO Press ● Wei-Mun Chan, eLife ● Sowmya Swaminathan, Springer Nature Current operational Team ● Allyson Lister, Content and Community Lead ● Milo Thurston, Technical Lead ● Ramon Granell, Data Enrichment & Quality Manager ● Delphine Dauga, Data Curator Manager ● Hiring in progress, Web Developer ● Dominique Batista, Research Software Engineer ● Philippe Rocca-Serra, Co-Founder ● Susanna-Assunta Sansone, PI and Founder ● and many collaborators and contributors! Executive Advisors ● Varsha Khodiyar, Independent expert ● Chris Graf, Springer Nature ● David Carr, Independent expert ● Robert Hanisch, Director, NIST Office of Data & Informatics ● Peter McQuilton, FAIRsharing Founding Member, GSK
  • 44.
  • 45. FAIR Cookbook A resource part of the ELIXIR ecosystem, but open to all! https://faircookbook.elixir-europe.org
  • 46. Motivations and ambitions beyond the hype Large body of generic FAIR guidance Motivations Non-specific guidance for the life sciences Ambitions Target specific situations to deliver a guide with applied examples Join academia and industry forces to make the case for FAIR data management Build capacity for high quality data management in the private and public sectors Lack of practical examples of ‘how-to’ with different data types and scenarios
  • 47. FAIR-driven digital transformation by pharmas ● Biopharma R&D productivity can be improved by implementing the FAIR Principles ● FAIR enables powerful new AI analytics to access data for machine learning and prediction ● Requirements ○ financial, technical, training ● Challenges ○ change the culture, show business value, achieve the ‘FAIR enough’ on an
  • 48. The FAIR Cookbook What is it? An online, ‘live’ resource for the life sciences A collection of recipes that cover the operation steps of FAIR data management Who is it for? Anyone who needs practical assistance in their FAIRification journey or creates FAIR guidance and educational material Who developed it? Researchers and data managers professionals in the life sciences, from academia and industry Including ELIXIR members https://faircookbook.elixir-europe.org
  • 49. Learning objectives and who is the Cookbook user? Researchers, Data Scientists, Principal Investigators Data Managers, Data Stewards, Data Curators Software Developers, Terminology Managers Policymakers, Funders, Trainers Learn how to improve the FAIRness with exemplar datasets Understand the levels and indicators of FAIRness Discover open source technologies, tools and services Find out the required skills Acknowledge the challenges
  • 50. The Cookbook platform open source community practices Built using jupyter-book, following the practice used by the Alan Turing Institute’ the Turing Way book, an open source community-driven guide to reproducible, ethical, inclusive and collaborative data science Technology stack: ● github for version control and hosting ● Markdown the write-up ● HackMD markdown editor, integrated with github ● jupyter notebook for executable code ● binder for the web execution of jupyter notebook distributed with a recipe ● mermaid javascript library for flowcharts, Gantt charts and pie charts https://the-turing-way.netlify.app/welcome
  • 51. Current coordinators and editors we are here to help Content prioritisation Identification of topics Review of drafts Call for contributions Monthly book-dash events Pre-defined focus areas Breakout on topics Housekeeping Technical platform Website Editorial Board Sections Board The newly developed sections board assists the editorial board Dominique Batista Martin Cook
  • 52. Contributors to date Almost 100 life sciences professionals, researchers and data managers FARIplus partners Industry + Academia ELIXIR Nodes represented
  • 53. ● Over 70 recipes released and more content available ● Covering technical processes with FAIRification examples in the life sciences: ○ Omics ○ pre-clinical ○ clinical areas But not limited to it! A resource for FAIR doers
  • 54. Content type overview Recipes focused on each technical aspects, and applicable to any data type Recipes specific to a topic or data type
  • 59. Anatomy of a recipe components Ingredients An idea of tools/skills needed Step by step process Guidelines, process, description Practical elements, code snippets #Python3 #zooma-annotator-script.py file def get_annotations(propertyType , propertyValues, filters = ""): " Examples Conclusions What should I read next?
  • 60. Credit and citability because your contribution matters! CreDiT attribution ontology w3id.org/faircookbook/FCB006
  • 61. The FAIRness of the Cookbook Accessibility HTTPS protocol Interoperability JSON-LD markup Cross-links to objects in other registries From the ELIXIR ecosystem and beyond! CreDiT attribution ontology Reusability CC BY 4.0 license for all content Findability Sitemap.xml, JSON-LD Markup with Schema.org, Bioschemas w3id.org unique persistent identifiers for each recipe ORCID for authors
  • 64. Tagging recipes with ‘Dataset Maturity Indicators’ Maturity level and indicators new available feature https://fairplus.github.io/Data-Maturity Provide insights into FAIR Maturity reached by applying a specific recipe to improve a dataset
  • 67. What is missing? Demonstrated benefits of FAIR for Reuse • HPLC data fairification for AI: @Abbvie, Axel Wilbertz • Image data annotation: @AZ, Alexander Buschle • Integration of GWAS data: @BenevolentAI, Jia Li • Biomap project: @UL, Irina Balaur, Soumyabrata Gosh
  • 68. • Increasing number of (competing) semantic resources • “Let 1000 flowers bloom” is nice but… • Converging towards shared curation practice (precompetitive) and efficient patterns The challenge of interoperability: FAIR silos? https://arxiv.org/pdf/2102.10062.pdf https://arxiv.org/pdf/2112.06567.pdf
  • 69. Become part of a community of FAIR experts! 1Identify a chapter and a topic Findability Accessibility Interoperability Reusability Infrastructure Applied examples Assessment 2 Choose a way of contributing and see our guidelines Google Docs HackMD Git Markdown cheat sheet Get recipe template Tips and tricks Submit an outline 3 You can discuss it with the Editorial Board
  • 70. Start using the FAIR Cookbook Help us to help you, this is a user- oriented resource Join a network of FAIR experts Share and broaden your expertise, joining our journey Contribute according to your needs Create and review, or signpost gaps and needs Benefit from the power of the FAIR community Become a recognised expert, enlarge your network Recommend it in your guidance and training material For everyone use it join it adopted! leverage it The roadmap, your steps
  • 71. Thanks to Editorial Board Section Editors FAIRplus partners All bookdashes’ participants All authors fairplus-cookbook@elixir-europe.org faircookbook.elixir-europe.org fairplus-project.eu This project has received funding from the Innovative Medicines Initiative Joint Undertaking under grant agreement No 802750. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA Companies. This communication reflects the views of the authors and neither IMI nor the European Union, EFPIA or any Associated Partners are liable for any use that may be made of the information contained herein.