EUROPEAN OPEN SCIENCE CLOUD & FAIR DATA

THE FORECAST FOR SAN DIEGO

PARTLY FAIR / PARTLY CLOUDY

November 3, 2016

The Data Tsunami

Datarrhoeia

Standards?

Needle Transport

Do It Yourself Data

THE BIG DATA PROBLEM

2

BUT WE ALL DID TRY, DIDN’T WE?

1992 Data Stewardship Plan

1997 Improved Data Stewardship Plan

SO…...............................

Most data do not TALK to each other

Data are lost and/or hard to find Inhibits fully effective health care, research & innovation

Research data malpractice (Life Science example):

Only 12% of NIH funded datasets are demonstrably deposited in recognized repositories: so over 200,000 ‘invisible’ public datasets can not be re-used effectively.

Approximately 50% of funded research not reproducible

Inhibits scaling of effective knowledge discovery

FAIR DATA PRINCIPLES: INVENTED IN THE NETHERLANDS

Leiden 2014

Initiated by

EVOLVED RAPIDLY INTO A GLOBAL MOVEMENT

Rapid acceptance and endorsement process

The conference

The Website

Research Data Alliance endorsement

DTL flagship project

FORCE11 international partner

Articles accepted in NATURE

NIH accepts FAIR compliance in Life Sciences Commons

DTL director Prof. Barend Mons Chair High Level Expert Group EC

The Personal Health Train Initiative started

EC announces European Open Science Cloud with FAIR as leading principle

World 2016

AND RECENTLY EVEN THE G20 WANTS 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

EC TAKES ACTION: THE EUROPEAN OPEN SCIENCE CLOUD

Europe acknowledged the problem

Moved for a solution: EOSC

Data stewardship for better discovery; mandatory!

Cost eligible for funding

Internet of Data based upon FAIR data principles

Training of 500.000 data experts

Financing

€6.7B for initial phase EOSC

EC + MS : €400 billion for research annually

@ 5% equals €20B for Data Stewardship

EOSC inspired by and based on Dutch FAIR initiative

FAIR ADOPTED BY USA (NIH) AS WELL

THE NIH The NIH Commons initiative

The Commons Data

Vouchers for mandatory

data stewardship

WHAT IS FAIR DATA?

Findable - (meta)data is uniquely and persistently identifiable.

Should have basic machine readable descriptive metadata.

Accessible - data is reachable and accessible by humans and

machines using standard formats and protocols.

Interoperable - (meta)data is machine readable and

annotated with resolvable vocabularies/ontologies.

Reusable - (meta)data is sufficiently well-described to allow

(semi)automated integration with other compatible data sources.

We want a large ecosystem of apps that use

FAIR Data

SO the FAIR solution between them must be THIN!

We want to support a wide range of source

providers

THE HOUR GLASS CONCEPT

http://www.nature.com/articles/sdata201618

THE FAIR GUIDING PRINCIPLES

THE FAIR DATA ECOSYSTEM

BENEFITS

Public data:

Improved sharing and re-use of research and personal health data

Improved results research and health data analytics

Improved involvement of citizen/patient (digital control of own data)

Improved economic benefits health care sector including prevention

Private data:

Interoperable with public domain data

Effective hypothesis validation

Improved decision support clinical development

Improved effectiveness discovery process

Leadership

San Diego can lead the implementation of the FAIR

Data Principles and beyond

Assets

San Diego Internet of Data

Open network of FAIR Data

Backbone infrastructure for both

OPPORTUNITIES SAN DIEGO

THE IMPLEMENTATION NODE APPROACH

SAN DIEGO

THE PERSONAL HEALTH TRAIN PROJECT

The Personal Health Train

Health data ‘stations’

Citizen ‘in control’

Public and Private sector

PHT video:

http://www.dtls.nl/fair-data/personal-health-train/

Thank you

albert.mons@dtls.nl

Questions?