This document discusses challenges around big data and the need for cross-domain interoperability in the Internet of Fair Data and Services (IFDS). It introduces the FAIR data principles which aim to make data findable, accessible, interoperable and reusable. The principles address metadata, identifiers, vocabularies and licensing. Adopting FAIR could reduce costs associated with data preparation and management. The IFDS builds on these principles to enable control and negotiation over digital resources across heterogeneous systems through an "hourglass" design. Communities are encouraged to define shared standards and services to improve interoperability according to FAIR.

1. TOWARDS CROSS-DOMAIN
INTEROPERATION IN THE INTERNET OF
FAIR DATA AND SERVICES
EEWC 2018 - LUXEMBOURG
Luiz Bonino
luiz.bonino@go-fair.org

2. THE BIG DATA/(DIGITAL) PROBLEM
The Data Tsunami

3. THE BIG DATA/(DIGITAL) PROBLEM
The Data Tsunami
Datarrheia

4. THE BIG DATA/(DIGITAL) PROBLEM
The Data Tsunami
Datarrheia
Standards

5. THE BIG DATA/(DIGITAL) PROBLEM
The Data Tsunami
Datarrheia
Standards
Needle Transport

6. THE BIG DATA/(DIGITAL) PROBLEM
The Data Tsunami
Datarrheia
Standards
Needle Transport
Do It Yourself Data

7. THE UNDERLYING PROBLEM
Fragmentation of…
• Data
• Models
• Software tools
• Platforms
• Regulations
• …

8. ENTERPRISE REALITY - HETEROGENEITY
Integrated Enterprise
Technologies
Providers
Platforms

9. ENTERPRISE REALITY – HETEROGENEITY - CHALLENGES
Integrated Enterprise
Technologies
Providers
Platforms
How can I get to know what is available?
Where to get?
How to get?
How to integrate?
How to streamline it (re)use?

10. ENTERPRISE REALITY – HETEROGENEITY – SOLUTION?
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11. ENTERPRISE REALITY – HETEROGENEITY – SOLUTION?
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12. ENTERPRISE REALITY – HETEROGENEITY – SOLUTION?
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13. ENTERPRISE REALITY – HETEROGENEITY – SOLUTION?
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14. ENTERPRISE REALITY – HETEROGENEITY – SOLUTION?
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15. WHAT IS FAIR?

16. FAIR 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

17. WHAT FAIR PRINCIPLES ARE NOT!
FAIR is not a standard
FAIR is not equal to ‘Open’ or ‘Free’
FAIR is not equal to RDF, Linked Data, or Semantic Web
FAIR is not assuming that only humans can find and re-use data
FAIR is not for humans only but for machines as well
Digital resources that are not FAIR are pretty ‘Re-useless’…..
Cloudy, increasingly FAIR; revisiting the FAIR Data guiding principles for the European Open Science Cloud DOI: 10.3233/ISU-170824
http://www.purl.org/fair/principles-explained

18. EC TAKES ACTION: THE EUROPEAN OPEN SCIENCE CLOUD
Europe acknowledged the
problem
Moved for a solution: EOSC
Data Stewardship (DS) for
better discovery
Internet of Data of FAIR Data &
Services
Training of 500.000 data
experts
Financing
€2B for initial phase EOSC
5% of research grants for DS
DS market $100B annually

19. THE EUROPEAN OPEN SCIENCE CLOUD: WHAT’S IN A NAME
European
Open
Science
Cloud

20. GO FAIR INITIATIVE: 2014 LEIDEN, THE NETHERLANDS

21. GO FAIR NOW A GLOBAL MOVEMENT
Let’s GO
FAIR
“We support appropriate efforts to promote open science and facilitate appropriate access
to publicly funded research results on findable, accessible, interoperable and reusable (FAIR)
principles.” (Statement 12)
http://europa.eu/rapid/press-release_STATEMENT-16-2967_en.htm

22. CURRENT STATUS EUROPE
3 Member States in the lead (NL, FR, DE)
7 additional Member States in the wings
GO FAIR International Office (funded by NL)
Main tasks:
International expansion
Coordination
Implementation Network support
Certification and training
6 Implementation Networks set up
Science Funders
Rare Diseases
Metabolomics
Training
Biodiversity (National History Museums)
OPEDAS (Other People’s Data and Services)

23. DEVELOPING IMPLEMENTATION NETWORKS

24. THE COST OF NOT GOING FAIR

25. DATA EXPERT EFFORT
Source: Data Science Report 2016, CrowdFlower, 2016: http://visit.crowdflower.com/rs/416-ZBE-142/images/CrowdFlower_DataScienceReport_2016.pdf

26. DATA EXPERT EFFORT
Source: Data Science Report 2016, CrowdFlower, 2016: http://visit.crowdflower.com/rs/416-ZBE-142/images/CrowdFlower_DataScienceReport_2016.pdf

27. BREAK DOWN DATA EXPERT EFFORT 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;
19% of the time
60% of the time
Ifyou have found and accessed the data

28. SOURCE: Study on the cost of not having FAIR research data
A PwC study for DG RTD of the European Commission
COST OF NOT HAVING FAIR DATA

29. COST OF NOT HAVING FAIR DATA

30. THE INTERNET OF FAIR DATA AND SERVICES

31. THE INTERNET
 The Internet solved the problem of the
interoperability of heterogeneous networks
 The hourglass design of the Internet system
enabled both interoperability and unparalleled
flexibility for extension

32. THE INTERNET OF FAIR DATA AND SERVICES
 The IFDS aims at solving the problem of
interoperability of heterogeneous data, services
and compute
 An hourglass design of the IFDS would enable
both interoperability and unparalleled flexibility
for extension

33. BUILDING BLOCKS
Data
Infra
Tools
Infra
Compute
Infra

34. THE INTERNET OF FAIR DATA AND SERVICES
Data
Tools Compute

35. IFDS
 Provide control over digital resources
 Who
 Where
 How
 Why
 From the “owner” side, clearly describe:
 Rights, conditions, requirements and access methods
 From the user side, clearly describe:
 Intentions and requirements
 Support (machine-based) negotiation

36. FIRST INITIATIVES OF THE IFDS
https://vimeo.com/215975839https://vimeo.com/143245835

37. WHAT COMMUNITIES LIKE ENTERPRISE ENGINEERING CAN DO TO BE
(MORE) FAIR AND WHAT IS IN THERE FOR THEM?

38. 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

39. 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. metadata 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 metadata;
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;
https://www.nature.com/articles/sdata201618

40. 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. metadata 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;
https://www.nature.com/articles/sdata201618

41. FAIR DATA PRINCIPLES – SUPPORT 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;
https://www.nature.com/articles/sdata201618

42. BENEFITS OF GOING FAIR
 Improve in intra- and inter-domain interoperability;
 Improve efficiency in dealing with digital resources;
 Join a global initiative;
 Availability of more FAIR digital resources;
 Decrease “time-to-market” integrated solutions;
 …

43. WHAT CAN COMMUNITIES DO?
 Metadata elements for commonly used digital resources. E.g. metadata
elements for EE models;
 Preferred reference conceptual models (vocabularies, schemas, ontologies,
etc., …);
 Define semantic models for commonly used resources (datasets, services, etc.)
 Offer community-specific services like vocabularies services, model
repositories, …;
 Mechanisms to connects models representing different enterprise
perspectives (and using differencing modeling languages)

44. Q&A – CONTACT INFO
Luiz Bonino
International Technology Coordinator – GO FAIR
Associate Professor BioSemantics – LUMC
E-mail: luiz.bonino@go-fair.org
Skype: luizolavobonino
Web: www.go-fair.org
LET’S GO FAIR?