The document outlines the FAIR data principles, emphasizing the importance of making data Findable, Accessible, Interoperable, and Reusable through specific guidelines for metadata and data management. It details infrastructure requirements for implementing these principles, including protocols for data retrieval and description, licensing, and provenance. Additionally, it discusses a hackathon initiative aimed at creating solutions that align with FAIR data specifications.

1. AN ECOSYSTEM TO SUPPORT FAIR DATA
Luiz Olavo Bonino - luiz.bonino@dtls.nl
April 3rd 2017

2. 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;

3. FAIR DATA PRINCIPLES - METADATA
Findable:
F1. metadata 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. metadata 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. metadata use a formal, accessible, shared,
and broadly applicable language for
knowledge representation;
I2. metadata use vocabularies that follow FAIR
principles;
I3. metadata include qualified references to
other (meta)data;
Reusable:
R1. metadata are richly described with a
plurality of accurate and relevant attributes;
R1.1. metadata are released with a clear and
accessible data usage license;
R1.2. metadata are associated with detailed
provenance;
R1.3. metadata meet domain-relevant
community standards;

4. FAIR DATA PRINCIPLES - DATA
Findable:
F1. 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. 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. data use a formal, accessible, shared, and
broadly applicable language for knowledge
representation;
I2. data use vocabularies that follow FAIR
principles;
I3. data include qualified references to other
(meta)data;
Reusable:
R1. data are richly described with a plurality of
accurate and relevant attributes;
R1.1. data are released with a clear and
accessible data usage license;
R1.2. data are associated with detailed
provenance;
R1.3. data meet domain-relevant community
standards;

5. FAIR DATA PRINCIPLES - SUPPORTING INFRASTRUCTURE
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;

6. FAIR transformation FAIR transformation
Analysis transformation Analysis transformation

7. FAIR DATA ECOSYSTEM (DTL)
Create Publish AnnotateFind
011001
1
110010
1
100110
0
BYOD FAIR Hackathon

8. FAIR DATA ECOSYSTEM (DTL)
Create Publish AnnotateFind
011001
1
110010
1
100110
0
DataFAIRport
DTL

9. BRING YOUR OWN DATA - BYOD
■ Goals:
■ Learn how to make data linkable “hands-on” with experts
■ Create a “telling story” to demonstrate its use
■ Make FAIR Data at the source
■ Composition:
■ Data owners – specialists on given datasets
■ Data interoperability experts
■ Domain experts
Source: Marcos Roos

10. Domain Expert
Data Owner FAIR Data Expert
BYOD

11. BYOD

12. BYOD Planning
Preparation Execution Follow Up

13. BYOD Planning
Preparation
Identify Plan
Datasets
Attendees' profile
Output data access
Tentative dates
Tentative venue
Costs
Funds
Coordination
Set date
Invite attendees
Set venue
Catering
Lodging
Financial planning
Publicity
Working document
Preparatory calls
Data hosting
Software hosting
Documentation hosting

14. BYOD Planning
Execution
Day One
Introduction
SW, LD, Ontology intro
Use case intro
Workgroups division
Working sessions
WWW/TTTALA
Day Two
Progress report
Working sessions
Groups reports
WWW/TTTALA
Day Three
Data integration
Answer driving question
Explore data
Demo improvement
Final report
WWW/TTTALA

15. BYOD Planning
Follow-Up
D+15
Report difficulties
Clarifications
Next steps
D+45
Report difficulties
Clarifications
Next steps
Implementation
Expand FAIRification
Implement solution
Scale-up solution
Deploy

16. Based on OpenRefine

17. FAIR DATA PRINCIPLES - METADATA
Findable:
F1. metadata 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. metadata 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. metadata use a formal, accessible, shared,
and broadly applicable language for
knowledge representation;
I2. metadata use vocabularies that follow FAIR
principles;
I3. metadata include qualified references to
other (meta)data;
Reusable:
R1. metadata are richly described with a
plurality of accurate and relevant attributes;
R1.1. metadata are released with a clear and
accessible data usage license;
R1.2. metadata are associated with detailed
provenance;
R1.3. metadata meet domain-relevant
community standards;

18. FAIRIFICATION
FAIR Data Resource
submit generate
Generic
semantic
model

20. FAIRIFIER
■ Transform non-FAIR datasets into FAIR Data Resources
(dataset in FAIR format, license and metadata)
■ Data munging
■ Semantic modeling
■ License definition
■ Metadata definition and extraction
■ Data publication

21. FAIRIFIER

22. FAIRIFICATION PROCESS
■ Retrieve original data
■ Dataset identification and analysis
■ Definition of the semantic model
■ Data transformation
■ License assignment
■ Metadata definition
■ FAIR Data resource (data, metadata, license)
deployment

23. FAIRIFICATION
FAIR Data Resource
submit generate
Semantic
model

24. FAIRIFICATION - NEW DATASET TYPE
FAIR Data Resource
submit generate
FAIR Data
Model Registry
store
Semantic
Model &
Non-FAIR
- FAIR
mapping

25. FAIRIFICATION - RECURRING DATASET TYPE
FAIR Data Resource
submit generate
FAIR Data
Model Registry
query
Semantic
Model &
Non-FAIR
- FAIR
mapping
retrieve

27. FAIR DATA PRINCIPLES - DATA
Findable:
F1. 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. 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. data use a formal, accessible, shared, and
broadly applicable language for knowledge
representation;
I2. data use vocabularies that follow FAIR
principles;
I3. data include qualified references to other
(meta)data;
Reusable:
R1. data are richly described with a plurality of
accurate and relevant attributes;
R1.1. data are released with a clear and
accessible data usage license;
R1.2. data are associated with detailed
provenance;
R1.3. data meet domain-relevant community
standards;

29. FAIR Data Point metadata
Title
Responsible institution(s)
Contact
FAIR API version
License
…

30. FAIR Data Point metadata
Catalog metadata
Title
Theme taxonomy
Issued date
…
DCAT

31. FAIR Data Point metadata
Catalog 1 metadata
Dataset metadata
Title
Publisher
License
Theme(s)
Version
…
DCAT/HCLS

32. FAIR Data Point metadata
Catalog 1 metadata
Dataset 1 metadata
Distribution metadata
Title
Media type
Download/access URL
License
…
DCAT

33. FAIR Data Point metadata
Catalog metadata
Dataset metadata
Distribution
metadata
Data record metadata
Type
Domain
Range
…
RML

34. FAIR Data Point metadata
Catalog 2
metadata
Catalog 1 metadata
Dataset 1 metadata
Distribution
1.a
metadata
Data record
metadata
Distribution
1.b
metadata
Dataset 2 metadata
Distribution
2.a
metadata
Data record
metadata
Distribution
2.b
metadata
Dataset 3 metadata
Distribution
3.a
metadata
Data record
metadata

35. METADATA LAYERS
Data Repository (FDP)
(Dataset) Catalog(s)
Dataset
Distribution
Data Record

36. FAIR DATA PRINCIPLES - SUPPORTING INFRASTRUCTURE
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;

37. FAIR DATA POINT - GUI - FOR TECHIES

38. FAIR DATA POINT - GUI - FOR “NORMAL" PEOPLE
}
}
Repository
metadata
Catalog
metadata
summary

39. FAIR DATA POINT - GUI
}
}
Repository
metadata
Catalog
metadata
summary
}
Dataset/
distribution
metadata
summary
}Catalog
metadata

40. FAIR DATA POINT - GUI - DATASET

41. FAIR DATA POINT

42. EXISTING DATA REPOSITORIES

43. EXTENDING EXISTING DATA REPOSITORIES
+

44. FAIR HACKATHON - GOALS
■ Align solutions with FAIR Data Point specifications.
■ Metadata content
■ API
■ Data

45. FAIR HACKATHON OUTCOME
■ FAIR data model for solutions content;
■ Architecture of the required adjustments/extensions;
■ Technical specification of the adjustments/extensions;
■ Proof-of-concept of the adjusted solution;

46. FDP-COMPLIANT (BETA) SOLUTIONS
RDRF

47. FAIR transformation FAIR transformation
Analysis transformation Analysis transformation

48. 0110011
1100101
1001100
metadata
index
retrieves
metadata
search
interfaces
(GUI and API)

50. ■ Allow third-party annotation on existing knowledge
bases
■ Capture the provenance of the annotator and the
original statement
Open RDF
Knowledge AnnotatorORKA

51. DEMO: HTTP://DEV-VM.FAIR-DTLS.SURF-HOSTED.NL:8080/#/

52. DEMO: HTTP://DEV-VM.FAIR-DTLS.SURF-HOSTED.NL:8080/#/

53. DEMO: HTTP://DEV-VM.FAIR-DTLS.SURF-HOSTED.NL:8080/#/
ANNOTATIONS GO TO NANOPUB STORE

54. ■ A particular class of FAIR Data System to provide
support for data interoperability;
■ Supports publication and access to FAIR data.
■ Fosters an ecosystems of applications and services;
■ Federated architecture: different FAIRports (and other
FAIR Data Systems) are interconnectable;
■ Supports citations of datasets and data items;
■ Provides metrics for data usage and citation;

55. F A I
R

56. QUESTIONS?
Luiz Bonino
luiz.bonino@dtls.nl
www.dtls.nl

57. METADATA LAYERS
Data Repository (FDP)
(Dataset) Catalog(s)
Dataset
Distribution
Data Record
DCAT/HCLS
RML

58. METADATA LAYERS’ EXTENSIONS - VOCABULARIES
Data Repository (FDP)
(Dataset) Catalog(s)
Dataset
Distribution
Data Record

59. METADATA LAYERS’ EXTENSIONS - VOCABULARIES
DCAT
dcat:publisher
biosch:organization
"@context": "http://schema.org",
"@type": "NGO",
"address": {
"@type": "PostalAddress",
"addressLocality": "Utrecht, The Netherlands"
"postalCode": “3511 GC",
"streetAddress": “Catharijnesingel 54"
},
"email": “info(at)dtls.nl",
"@type": “Organization”,
“@type”: “not-for-profit”,
"name": “Dutch Techncentre for Life Sciences",
"telephone": "( 31) 85 30 30 711"

60. METADATA LAYERS’ EXTENSIONS - VOCABULARIES
dbpedia: biobank
edam: biobank

61. METADATA LAYERS’ EXTENSIONS - EXTENDED MODEL
Data Repository (FDP)
(Dataset) Catalog(s)
Dataset
Distribution
Data Record
DatA Tag Suite
(DATS)
PROV

62. DatA Tag Suite
(DATS)
Dataset
Publication
citations primaryPublications