FAIR in 15min - OpenConfOxford Dec 2017

Associate Professor, Associate DirectorSusanna-Assunta Sansone, PhD

@SusannaASansone

Oxford OpenCon Oxford, 1st Dec 2017

Consultant and Honorary Academic Editor

We need to do better science more efficiently

• Achieve research data transparency• Standards for annotation and interoperability

• Meet ethics and public expectations• Safe use of data

• Maximise the use of e-infrastructure• Secure, distributed and scalable

• Engage the innovation ecosystem• Academia, industry and government

• Invest in people, skills and methods

• Connect existing silo-ed disciplines

We need to do better science more efficiently

• Achieve research data transparency• Standards for annotation and interoperability

• Meet ethics and public expectations• Safe use of data

• Maximise the use of e-infrastructure• Secure, distributed and scalable

• Engage the innovation ecosystem• Academia, industry and government

• Invest in people, skills and methods

• Connect existing silo-ed disciplines

A set of principles, for those

wishing to enhance

the value of their

data holdings

Designed and endorsed by a diverse

set of stakeholders - representing

academia, industry, funding agencies,

and scholarly publishers.

https://www.force11.org/group/fairgroup/fairprinciples

These put emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individual

These put emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individual

Wider adoption by policies in UK and EU, e.g.

Wider adoption by many biomedical research infrastructure programmes in EU and USA, e.g.

Wider adoption by many biomedical research infrastructure programmes in EU and USA, e.g.

€19 million 2015 - 2019

Wider adoption by many biomedical research infrastructure programmes in EU and USA, e.g.

€19 million 2015 - 2019

€3.3 billion2014 - 2020

Wider adoption by many biomedical research infrastructure programmes in EU and USA, e.g.

€19 million 2015 - 2019 $95.5 million

2017 - 2020

€3.3 billion2014 - 2020

Big Life

Science Company

Yesterday Today Tomorrow

Yesterday Today TomorrowInnovation Model Innovation inside Searching for Innovation Heterogeneity of collaborations;

part of the wider ecosystem

IT Internal apps & data Struggling with change security and trust

Cloud, services

Data Mostly inside In and out Distributed

Portfolio Internally driven and owned Partially shared Shared portfolio

Credit to:

Big Life

Science Company

Proprietarycontentprovider

Publiccontentprovider

Academicgroup

Software vendor

CRO

Service provider

Regulatoryauthorities

The rise of public-private-partnerships

Defining FAIRness

Defining FAIRness

…..

Mapofthelandscape,monitoringdevelopmentandevolution ofdataandmetadatastandards,theiruse indatabases andthe

adoptionofbothindatapolicies

• Data has to become an integral part

of the scholarly communications

• Responsibilities lie across several

stakeholder groups: researchers,

data centers, librarians, funding

agencies and publishers

• But publishers occupy a “leverage

point” in this process

FAIR data - roles and responsibilities

• Incentive, credit for sharing- Big and small data- Unpublished data- Long tail of data- Curated aggregation

• Peer review of data• Value of data vs. analysis• Discoverability and reusability

- Complementing community databases

FAIR data – the value of data articles/journals

Let’s work together to foster a culture

in which FAIR science is the norm