What is FAIR? 5 th International Summer School on Rare Disease and Orphan Drug Registries. Claudio Carta 1 and Marco Roos 2

Transcription

1 5 th International Summer School on Rare Disease and Orphan Drug Registries What is FAIR? Claudio Carta 1 and Marco Roos 2 1 National Centre for Rare Diseases Istituto Superiore di Sanità, Rome, Italy 2 Leiden University Medical Center, Leiden, The Netherlands Organised by Istituto Superiore di Sanità Rome (Italy), September 18-20,

2 FAIR : at first sight.. Findable Accessible Interoperable Reusable Organised by Istituto Superiore di Sanità Rome (Italy), September 18-20,

3 Scenario: is my paper in PubMed/Google FAIR? Can you give me more information? Can you share your raw data? Do you remember the abbreviation that stands for CK4 Do you remember all the abbreviations? The data is still readable by programs? Are computer readable? Organised by Istituto Superiore di Sanità Rome (Italy), September 18-20,

4 What about. papers of ? Can you share your raw data? 17 years ago 1990? Do you remember where raw data are? Are computer readable? Do you remember the abbreviation that stands for CK4 27 years ago You remember all the abbreviations? Can you give me more information? 1980? 37 years ago

5 Scenario Supplementary data

6 One of the Problems? Reusability Crisis Scientists losing data at a rapid rate Decline can mean 80% of data are unavailable after 20 years. Nature 19 December 2013

7 Sometimes.. it happens DATA

8 Another Problem? Data Overload

9 Some Example of Problems for the Research on Rare Diseases The EUCERD Recommendations call for international operability of registries and data bases in order for knowledge and data to be pooled and shared. Rare diseases suffer from fragmented knowledge, scattered expertise and patients, and research duplication. Interoperability on a global scale would enable data to be sufficiently pooled to reach sufficient statistically significant numbers for clinical research and public health purposes. Using international coding and nomenclature, minimum common data sets, and good practice guidelines would enhance interoperability and maximise the utility of registries and databases.

10 FAIR : not only a simple acronym Findable: F1. (meta)data are assigned a globally unique and persistent identifier; F2. data are described with rich metadata; F3. metadata clearly and explicitly include the identifier of the data it describes; F4. (meta)data are registered or indexed in a searchable resource; Interoperable: I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation. I2. (meta)data use vocabularies that follow FAIR principles; I3. (meta)data include qualified references to other (meta)data; Accessible: A1. (meta)data are retrievable by their identifier using a standardized communications protocol; A1.1 the protocol is open, free, and universally implementable; A1.2. the protocol allows for an authentication and authorization procedure, where necessary; A2. metadata are accessible, even when the data are no longer available; Reusable: R1. meta(data) are richly described with a plurality of accurate and relevant attributes; R1.1. (meta)data are released with a clear and accessible data usage license; R1.2. (meta)data are associated with detailed provenance; R1.3. (meta)data meet domain-relevant community standards;

11 FAIR Metrics Findable: F1. (meta)data are assigned a globally unique and persistent identifier; F2. data are described with rich metadata; F3. metadata clearly and explicitly include the identifier of the data it describes; F4. (meta)data are registered or indexed in a searchable resource; Interoperable: I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation. I2. (meta)data use vocabularies that follow FAIR principles; I3. (meta)data include qualified references to other (meta)data; YES/NO Extensible Don t Know Accessible: A1. (meta)data are retrievable by their identifier using a standardized communications protocol; A1.1 the protocol is open, free, and universally implementable; A1.2. the protocol allows for an authentication and authorization procedure, where necessary; A2. metadata are accessible, even when the data are no longer available; Reusable: R1. meta(data) are richly described with a plurality of accurate and relevant attributes; R1.1. (meta)data are released with a clear and accessible data usage license; R1.2. (meta)data are associated with detailed provenance; R1.3. (meta)data meet domain-relevant community standards;

12 What FAIR is not FAIR is not a standard FAIR is not equal to Semantic Web FAIR is not equal to Open or Free Data can be Open but not FAIR Data can be FAIR but not Open FAIR is not for humans only

13 This Sample Fake CSV/Excel File is FAIR?.anyway as in movies

14 This Sample Fake CSV/Excel File is FAIR?

15 This Sample Fake CSV/Excel File is FAIR?

16 Knowledge: associations implied by data Histone deacetylase 1 is a type of Protein Subject Predicate Object Q13547 NCIT_C25284 NCIT_C

17 Knowledge: associations implied by data

18 Knowledge: associations implied by data Patient X Has name CBBis6 Patient X Has sequence variant rs Patient X Has phenotype HP: foaf:name CBBis6"

19 Knowledge: associations implied by data Patient X Has phenotype HP:

20 FAIRification process Define semantic model Transform data records Define metadata Deploy FAIR data resource Query interface or user app Organised by Istituto Superiore di Sanità Rome (Italy), September 18-20,

21 FAIR Resources Catalog 1 Dataset 1 Distribution Catalog Catalog 2 Dataset 2 Distribution Catalog

22 FAIR Resources two independently FAIR* data sources, under control of the local data manager (e.g. HCP, patient organisation, patient) * Strictly speaking, the interoperability aspect mostly

23 FAIR Resources Data at each source is self-explaining through global standards that a computer program can understand

24 FAIR Resources Your neighbour's linkable data Their linkable data

25 FAIR Resources Share data or Ask data Share not all data Do not share data

26 Catalogue: Human & Machine readable <>rdf:type dcat:catalog; dct:title "Welcome to 5th International Summer School Rare Disease & Orphan Drug Registries"; dct:hasversion "1"; dct:publisher < dcat:themetaxonomy < < rdf:type foaf:organization; foaf:name "Claudio".

27 Dataset: Human & Machine readable <> rdf:type dcat:dataset; dct:title "Fake Sample Patients"; dct:hasversion "1"; dct:publisher < dcat:theme < < < < dct:ispartof < 4>. < rdf:type foaf:organization; foaf:name "Claudio".

28 Distribution: Human & Machine rdf: rdfs: dct: dcat: fdp: datacite: < <> rdf:type dcat:distribution.

29 FAIR Metadata Thanks to 29

30 What is FAIR data? Take home message FAIR is more of a simple acronym FAIR is for humans and computers FAIR do not means share FAIR is not trivial The way we implement FAIR is with ontologies Take care of the data means writing and executing FAIR data managment plans Get help from FAIR data specialists

31 5 th International Summer School Contact us on Rare Disease and Orphan Drug Registries Adopting FAIR principles Contact Us: Claudio Carta, Liaison/consultant. Summer School on Rare Diseases FAIR training, BYOD workshops, FAIRification in RD domain Annika Jacobsen, Roving FAIR data expert for rare diseases David van Enckevort, technical lead RD data linkage plan, link to RD software engineers Mascha Jansen, Coordinator FAIR data projects & BYODs for DTL/ELIXIR-NL Erik Schultes: FAIR data (awareness) training for Elixir: Brane Leskosek (and Celia van Gelder) Mark Thompson, FAIR software architect, link to FAIR engineering team Marco Roos, ELIXIR infrastructure for rare diseases, project lead RD data linkage plan Organised by Istituto Superiore di Sanità Rome (Italy), September 18-20,

32 Acknowledgments Annika Jacobsen, Rajaram Kaliyaperumal, Mark Thompson, David van Enckevort, Domenica Taruscio, Peter-Bram t Hoen, Marc Hanauer, Mascha Jansen, Luiz Bonino, Mark Wilkinson, Rachel Thompson, Erik Schultes,Barend Mons, rare disease patients and representatives Thanks for your attention