dans.knaw.nlDANS is an institute of KNAW and NWO

FAIR data in trustworthy repositories

EOSC Symposium 2019

Social & Cultural Data - taking the Users’ Perspective

Ilona von Stein - DANS

@DANSKNAW @FAIRsFAIR_EU

28 Nov 2019, Budapest

Outline

• FAIR data principles

• Data repositories

• FAIR-enabling data repositories

• FAIR data assessment: levels

• Conclusion and discussion

© Marjan Grootveld

DANS is about keeping data FAIR

Institute of

Dutch Academy

and Research

Funding

Organisation

(KNAW & NWO)

since 2005

First predecessor

dates back to

1964 (Steinmetz

Foundation),

Historical Data

Archive 1989

Mission:

promote and

provide

permanent

access to digital

research

resources

Core issue in research

Trust is a central element

The data re-user wants to know:

• Where do these data come from?

• How were they collected?

• What has happened with themalong the way?

The data producer wants to know:

• How can I be sure that “they” interpret and use my data in the right way?

Illustration by Jørgen Stamp

digitalbevaring.dk CC BY 2.5 Denmark

FAIR Guiding Principles

CREATING DATA

PROCESSING DATA

ANALYSING DATA

PRESERVING DATA

GIVING ACCESS TO

DATA

RE-USING DATA

Simplified research data life cycle based on: https://www.ukdataservice.ac.uk/manage-data/lifecycle

Managing and documenting data through all stages helps to build trust.

http://www.nature.com/articles/sdata201618www.force11.org/group/fairgroup/fairprinciples

Everybody loves FAIR!

Everybody wants to be FAIR, ▪ but what does that mean? ▪ how to put the principles into practice?▪ and how to measure FAIRness?

Images by kenwoodpress.com, Good Ware by flaticon.com, freebeesupply.com, openlibrary.org

FAIRytale?

“Research data will not become nor stay FAIR by magic. We need skilled people, transparent processes, interoperable technologies and

collaboration to build, operate and maintain research data infrastructures.”

Mari Kleemola, Finnish Social Science Data Archive/CoreTrustSeal Board, Secretary

https://tietoarkistoblogi.blogspot.com/2018/11/being-trustworthy-and-fair.html

Icon by Freepik from flaticon.com

FAIR digital object / FAIR ecosystem

A model for FAIR Digital Objects The components of a FAIR Ecosystem

Turning FAIR data into reality, Final report and Action Plan from the European Commission Expert Group on FAIR Data

Data repositories

A data repository [is a virtual place that] preserves, manages and provides access to many types of digital materials in a variety of formats*

• Institutional (institution or department)• Discipline specific (research fields or subjects)• Generic

Each may have specific requirements concerning e.g.

• data reuse • file format and data structure• types of metadata that can be used

Icon: https://icon-library.net/icon/data-repository-icon-5.html CCO Public Domain License

* CoreTrustSeal glossary (coretrustseal.org), taken from the CASRAI dictionary (https://dictionary.casrai.org)

Now, to the users perspective ☺

Image by freepik.com

Why would they care about:

• FAIR data

• Data repositories

• FAIR-aligned data repositories

and

about the certification of all that?

Why to use a data repository?

Illustration: Ainsley Seago CC BY

• It makes life easier for researchers

• It builds scientific integrity and trust

• Your data remain:• accessible • understandable • reusable

Repositories make and keep your data FAIR

How do repositories make data FAIR?

For example:

• by providing persistent unique identifiers• long-term findability, sustainable citations,

appropriate academic credit

• by supporting findability through a public catalogue• effective data discovery is key to data sharing

• by supporting you to add a usage license for the data• clear terms and conditions that meet legal requirements

• by implementing and promoting metadata standards• interoperability

See also “Top 10 FAIR Data & Software Things”. Zenodo. http://doi.org/10.5281/zenodo.3409968

Illustrations: Jørgen Stamp: Digitalbevaring (CC-BY from http://digitalbevaring.dk/digital-bevaring/)

How do repositories keep data FAIR?

They provide the long-term stewardship of FAIR digital objects, including curation activities, to ensure that the data remains FAIR over time

• Support for data producers (e.g. on file formats)

• Support for data users (e.g. on citation)

See also Mokrane & Recker, 2019. CoreTrustSeal-certified repositories. Enabling Finadable, Accessible, Interoperable and Reusable (FAIR) data. https://ipres2019.org/static/pdf/iPres2019_paper_74.pdf

Image: https://datasupport.researchdata.nl

How to find your ultimate repository? (1)

General steps for finding a repository are:• Use, if possible, a certified repository

• Use a disciplinary repository if there is one

• alternatively, use the institutional repository, if you have onewhere the data will also be preserved for the long term

For giving (i.e. archiving, sharing) and taking (i.e. reusing) data

Image: https://www.inlinepolicy.com/blog/can-data-sharing-survive-the-new-data-protection-regime

How to find your ultimate repository? (2)

• re3data.org

• Global registry of research data repositories

• Funded by the German Research Foundation (DFG)

• Filtered search and browse options

Select a trustworthy repository

✓ Certified repositories are assessed against a set of guidelines to evaluate their trustworthiness

✓ A certified repository typically provides severalservices that ensure the FAIRness of your dataset.

✓ A few certification frameworks exist that can be used to assess the quality of a repository

✓ CoreTrustSeal is in common use for this

Worldwide network of core certified repositories

FAIR data assessment: levels

DATA REPOSITORY

F4. (meta)data are registered or

indexed in a searchable resource

+ TECHNOLOGIES

+ PROCEDURES

+ EXPERTISE

+ PEOPLE

(META)DATA

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

Assessment work in FAIRsFAIR

Focus on:

• Evaluation and certification of repositories that enable FAIR data

• Assessment of FAIR data within a repository

The FAIRsFAIR-project aimsto supply practical solutionsfor the use of FAIR data principles

Duration:March 2019 – Feb 20222

Budget: €10 milion

22 partners from 8 member states

www.fairsfair.eu@FAIRsFAIR_EU

Evaluation and certification of repositories

• Support the FAIR alignment of certification schemes for data repositories, building on existing frameworks such as CoreTrustSeal

• Call for repositories involvement – in depth FAIR-aligned certification support - to expand the European network of trustworthy repositories enabling FAIR

• Provide an improved registry for finding and selecting relevant trustworthy repositories

Assessment of data FAIRness

• Two use-cases:

- Manual FAIR self-assessment tool for researchers - prior to depositing

- Automatic assessment tool for data repositories – existing datasets

• This will be tested through a number of pilots

Takeaway messages

• Trust is a central element in data sharing and data reuse

• FAIR-aligned repositories enhance the accessibility, understandability and reusability of data over time

• FAIR data assessment can be done at different levels and must include infrastructure

• Certified repositories keep FAIR data FAIR

Icon by Freepik from flaticon.com

dans.knaw.nlDANS is an institute of KNAW and NWO

Thanks for your attention!

ilona.von.stein@dans.knaw.nl

@DANSKNAW @FAIRsFAIR_EU

dans.knaw.nl/en

Acknowledgements: Marjan Grootveld, Ingrid Dillo,

Mustapha Mokrane (DANS)