My presentation at Health-RI 2017 conference about the FAIR ecosystem that we have been developing for the last 3 years.

1. © GO FAIR 2017
FAIR DATA ECOSYSTEM
Health-RI Conference – December 8th, 2017
Luiz Bonino – luiz.bonino@go-fair.org

2. © GO FAIR 2017
FAIR DATA PRINCIPLES
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;
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;
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;
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;
https://www.nature.com/articles/sdata201618

3. © GO FAIR 2017
FAIRIFICATION WORKFLOW

4. © GO FAIR 2017
CURRENT SITUATION
Retrieve
non-FAIR
data
Analyse and
prepare
datasets
Combine with
other data
Query combined
data

5. © GO FAIR 2017
FAIRIFICATION WORKFLOW
Retrieve
non-FAIR
data
Download/locate file
Identify API call
Identify data access protocol

6. © GO FAIR 2017
FAIRIFICATION WORKFLOW
Retrieve
non-FAIR
data
Analyse and
prepare
datasets
Standard format (XML, RDF, relational DB API, VCF, DICOM, etc.)?
What is the content?
Column/field names?
Relations?
Data domain and range?
Understand the data
Data munging
…

7. © GO FAIR 2017
FAIRIFICATION WORKFLOW
Retrieve
non-FAIR
data
Define
semantic
model
What are the concepts involved?
Relations among concepts?
Existing vocabularies for the concepts and instances?
Analyse and
prepare
datasets
Interoperability
Reusability

8. © GO FAIR 2017
FAIRIFICATION WORKFLOW
Retrieve
non-FAIR
data
Define
semantic
model
Make
data
linkable
Apply the semantic model on the
original data to make it linkable
Analyse and
prepare
datasets
Interoperability
Reusability

9. © GO FAIR 2017
FAIRIFICATION WORKFLOW
Retrieve
non-FAIR
data
Define
semantic
model
Make
data
linkable
Assign
license
Who can access/reuse the data?
Under which conditions?
Analyse and
prepare
datasets
Accessibility
Reusability

10. © GO FAIR 2017
FAIRIFICATION WORKFLOW
Retrieve
non-FAIR
data
Define
semantic
model
Make
data
linkable
Assign
license
Define
metadata
Authors
Version
Distributions
Provenance
…
Analyse and
prepare
datasets
Findability
Accessibility
Interoperability
Reusability

11. © GO FAIR 2017
FAIRIFICATION WORKFLOW
Retrieve
non-FAIR
data
Define
semantic
model
Make
data
linkable
Assign
license
Define
metadata
Deploy
FAIR data
resource
How to make the data and me
tadata available in a FAIR way?
Analyse and
prepare
datasets
Findability
Accessibility
Interoperability
Reusability

12. © GO FAIR 2017
FAIRIFICATION WORKFLOW
Retrieve
non-FAIR
data
Define
semantic
model
Make
data
linkable
Assign
license
Define
metadata
Deploy
FAIR data
resource
Combine with
other FAIR data
Query combined
data
Analyse and
prepare
datasets

13. © GO FAIR 2017
FAIR DATA ECOSYSTEM

14. © GO FAIR 2017
FAIR DATA ECOSYSTEM
Create PublishPlan Find
011001
1
110010
1
100110
0
BYOD FAIR Hackathon
Training
Annotate
https://github.com/DTL-FAIRData

15. © GO FAIR 2017
FAIR DATA ECOSYSTEM
Create Publish AnnotateFind
0110011
1100101
1001100

16. © GO FAIR 2017
FAIR DATA ECOSYSTEM
Retrieve
non-FAIR
data
Analyse
datasets
Define
semantic
model
Make
data
linkable
Assign
license
Define
metadata
Deploy
FAIR data
resource
Combine with
other FAIR data
Query combined
data
011001
1
110010
1
100110
0
FAIR Hackathon
BYOD

17. © GO FAIR 2017
DTL FAIR ENGINEERING TEAM
Mark Thompson
LUMC
Kees Burger
DTL-P
Rajaram Kaliyaperumal
LUMC
Shamanou van Leeuwen
DTL-P
Nuno Nunes
DTL-P/U. Maastricht
Luiz Bonino
GO FAIR / LUMC
https://github.com/DTL-FAIRData

18. © GO FAIR 2017
DEMONSTRATIONS OUTSIDE
 End-to-end FAIRification process using the FAIR ecosystem
 Personal locker (based on the FAIR Data Point) integrated
with Castor’s myConsent
ODEX4all
FAIR-dICT

19. © GO FAIR 2017
Q&A – CONTACT INFO
Luiz Bonino
E-mail: luiz.bonino@go-fair.org
Skype: luizolavobonino
Web: www.go-fair.org