FAIRIFYING RESEARCH DATA ON YOUTH & ADOLESCENTS

Neha Moopen

Research Data Manager

2020-02-18 / OSCoffee

WHAT IS FAIR DATA?

This image was created by Scriberia for The Turing Way community and is used under a CC-BY licence. The image was obtained from https://zenodo.org/record/3332808.

SOME ADVANTAGES OF FAIR DATA...

Gaining maximum potential from data assets
Achieving maximum impact from research.
Increasing the visibility and citations of research
Improving the reproducibility and reliability of research
Attracting new partnerships with researchers, businesses, policy, and broader communities.
Enabling new research questions to be answered

See: https://www.uu.nl/en/research/research-data-management/guides/how-to-make-your-data-fair

HOWEVER...

Despite the benefits, the process of FAIRifying youth data can seem daunting.

Which data can be safely shared? With whom? Under which circumstances? 😥

So...

Dynamics of Youth & RDM Support have started a project to make it easier for youth researchers to make their data FAIR 🚀🙌

DYNAMICS OF YOUTH:

STRATEGIC THEME/ONDERZOEKSTHEMA

RDM SUPPORT

Websites: Dynamics of Youth & RDM Support

EXAMPLE OF FAIRIFICATION EFFORTS:

YOUTH COHORT STUDY

Website: YOUth cohort study

'TEST PROJECT' FOR FAIRIFICATION

FAIRifying all of DoY is a steep hill to climb! So we're focusing on one test project.

The aim is to adapt our experiences, materials/resources developed for the test project, to suit broader DoY-use.

We want to avoid reinventing the wheel as much as possible #reusability 😊

INTRODUCING...

...THE PROACTIVE COHORT STUDY!

...AND MEREL VAN DER VLIST TO TELL US MORE!

PROACTIVE: NEEDS & REQUIREMENTS

PROACTIVE: THE FAIRIFICATION PROCESS

1 DATA MANAGEMENT PLAN

Screenshot of PROactive's DMP written using the UMCU's template on DMPonline. The UU also has it's own template.

2 PROJECT DOCUMENTATION

Including, but not limited to:

•README

•Project Proposals & Ethical Review

•Project Administration

•Tools & Questionnaires

•Study Protocols & SOPs

•Data Management

•Research Outputs

•Reference Library

Screenshot of guidelines on setting up a Research Folder Structure at the UMCU. The UU doesn't have fixed guidelines, but RDM Support has recommendations on best practices!

3 GDPR COMPLIANCE

Data Protection Impact Assessment
Informed Consent Forms
Data Subjects Rights + how to account for it.
Adequate pseudonymization

image source: https://www.coreview.com/blog/alpin-gdpr-fines-list/

4 COHORT ADMINISTRATION SYSTEM

An alternative to not-very-secure Excel spreadsheets for participant administration/management?

Still being investigated! 🔎🔎

5 DATA CAPTURE SYSTEMS

The choice of data capture tools can make your data flow more efficient and ultimately, easier to FAIRify. For example, easier data exports (for eventual publication & sharing) and ensuring interoperability.

5 AUTOMATED DATA EXPORT & COMBINATION

Linked to the previous point, an efficient data flow = easier FAIRification. And while you're at it, reproducibility.

This (not complete, nor official) example goes from data collection to research and clinical care.

Castor & R: https://helpdesk.castoredc.com/article/420-using-the-castor-api-r-package-for-data-analysis
R Markdown magic: https://rmarkdown.rstudio.com/gallery.html

7 DATA STORAGE & BACKUP

This is where it really starts getting FAIR!

Websites: Archivematica & DataverseNL
The 'DRACO' team is busy setting up these systems for the UMCU. They'll be up and running soon!

At the UU, we have the options of Yoda & DataverseNL

8 METADATA & HARMONIZATION

There is an ongoing project, Connecting Data in Child Development (CD2), which aims to harmonize metadata across 6 longitudinal, youth cohort studies. As this project develops, we may start applying the same metadata scheme to PROactive and hopefully, across DoY as well. We'll likely use the DDI metadata standard.