I N T R O D U C T I O N T O

Research DataManagement

Adeline Grard - Service Central des Bibliothèques

Présentationin 2 times

BACKGROUND

= EXPERIENCES +

1

2

3

RDMBASICS

M I L

AIMS of RDM

Create, organize, make accessible, store,

and share research data of an institution.

DefinitionsDATA MANAGEMENT: "Data management is the practice of

organizing and maintaining data processes to meet ongoing

information lifecycle needs."

RESEARCH DATA: « the recorded factual material commonly

accepted in the scientific community as necessary to validate

research finding”

HETEROGENEOUS: size, type, flow,quality, documentation, renewable/unique

have different STAGES: from raw to

published

Researchdata in thehumanities

ALLEA about humanities: "In the humanities, we all use research

data, although we may not be aware of it (…) you are using it,

even if you don’t know it, and once you realise it, it will affect

your reaserach workflow forever."

Intuitively, the term “research data “ seems to be more at place

in natural of social science (survey data, experimental data).

However, research data apply to all materials that are

collected, generated or used during a research project, to

support research findings

3 main typesof data inhumanities

1. STATISTICAL DATA:

Most obvious thing that comes to mind, when we think about

data in the humanities.

= This is organized, numeric or ordinal information.

Some Examples

a. Census data of Indian population in the XVII

b. List of participants to an exhibition held by british consul in late XIX century

c. Registry of first catholic missionaries in South Asia.

3 main typesof data inhumanities

2. OBJECTS:

main type of data in humanities

= “all possible study objects used in the humanities, in both

physical and digital form.”

Example:

Image (2d, 3d),

(Digital or digitized) documents,

Sound and video recordings,

Images of physical objects,

Text generated through Optical Character Recognition of a scan, etc.

3 main typesof data inhumanities

3. METADATA:

Data about objects described above.

Example:

Contributors, title,publisher, place, date, number of pages of

manuscript

Archeological objects: description of the objects, GPS

coordinates, type of objects (nomenclature)

FAIR data principle

a guideline for RDM all around the world

F.A.I.R

FINDABLE: YOU CAN LOCATE IT (doi)

ACCESSIBLE: YOU CAN ACCESS IT (repository)

INTEROPARABLE: FOLLOW STANDARDS OF METADATA

REUSABLE: BY ANY RESEARCHER,

WITH PROPER DOCUMENTATION

P R O S & C O N S

12 REASONS TOJUMP INTO RDM

9 OBSTACLES ANDCONCERNS

Helps planning your research Increase use of data management best practicesGet access to data collected by othersShare your data with your fellow partner, scientific community, or society....But keep your sharing in control (legal, ethical)Get cited for your data (DOI)Visibility Transparency (reproducibility)Get more from your data (other researcher): better return on investmentStore and backup safelyMerge datasets and start new research projectsSometimes it's mandatory

RDM ADVANTAGES

12

Universities face many challenges with limited ressourcesAcademic inertiaGrowing but still limited pressure to comply from fundersComercial sponsorship restrictionsLegal and ethical restrictionsAcademic autonomy and liberty not to shareAdministrative loadExhaustive documentation/knowledge to make data reusableDesign RDM service to all - very different - institutes is a challenge

RDM OBSTACLES & CONCERS

9

CONTEXT URGE TO

IMPLEMENT RDM

I N T E R N A T I O N A L   R E S E A R C H   C O N T E X T

We live in a digital world

where data are central

Trust crisis in science -

reproducibility

Open access

Meet researchers needsResearch support to

reach excellence in research

In Belgium?

SODA (EOSC)

DMPonline

KULeuven

UGent

ULiège

ULB

R E S E A R C H D A T A M A N A G A M E N T I N U N I V E R S I T I E S

RDM and theResearch Life Cycle

A summary of main steps

R E S E A R C H L I F E C Y C L E

manageplan

save & secure

store & share

R E S E A R C H L I F E C Y C L E

managePLAN

save & secure

store & share

Funders expectations Search for existing data Ethics of data & data collection Write a DMP data management costs

R E S E A R C H L I F E C Y C L E

MANAGEplan

save & secure

store & share

Data quality standards Type of datas Metadatas Documentation of data Organizing and file naming

R E S E A R C H L I F E C Y C L E

manageplan

SAVE & SECURE

store & share

Back-up and security Store your data

R E S E A R C H L I F E C Y C L E

manageplan

save & secure

STORE & SHARE

Get citations for your data Publish your data Find a repository Make your data visible Write a data sharing agreement

R E S E A R C H D A T A M A N A G A M E N T I N U N I V E R S I T I E S

RDM servicesA summary of main steps

3 Pilars of a

RDM services

AIM: provide support to researchers throughout the research life cycle

P I L A R 1 : F O R M A T I O N

Reward bestpractices

Phd credits

Discuss their dataCV

Make it attractiveGuides

Webinars

Workshops

FAQ

Personnal meeting

Lessons

Support

Timing

Start PhdStart H2020 project

S E R V I C E S W O R K I N G

T O G E T H E R

PILAR 2:EXPERTISE

Library

Research

Administration

Informatics

RGPD delegate

Reseach Institutes

(local experts)

NEW ROLES

DATA COORDINATOR

DATA CURATOR

DATA STEWARDS/ CHAMPIONS

PILAR 3:INFRASTRUCTURE

WEBSITE

REPOSITORY

Storage servers or external solution

Tools (DMPonline)

EXAMPLE

OF RDM SERVICE

APPLIED TO PLANNIG STEP

R E S E A R C H L I F E C Y C L E

managePLAN

save & secure

store & share

FORMATION / INFORMATION Funders expectationsIntroduction to RDMSearch for existing dataEthics of data & data collectionWrite a DMPPlan data management costs

INFRASTRUCTURESitewebDMPonline

EXPERTISE ADMINISTRATION RGPD delegateLIBRARY

QUESTIONS

REMARKS

IDEAS

R E S E A R C H L I F E C Y C L E

MANAGEplan

save & secure

store & share

FORMATION / INFORMATION Data quality standardsType of datasMetadatasDocumentation of dataOrganizing and file namingBest practices of datamanagement

INFRASTRUCTURESiteweb

EXPERTISESMCSLOCAL DATA EXPERTSBIUL

R E S E A R C H L I F E C Y C L E

Content

manageplan

SAVE & SECURE

store & share

FORMATION / INFORMATION Back-up and securityStore your data

INFRASTRUCTURESitewebUCLouvain servers or other solutions

EXPERTISESGSIBIUL

R E S E A R C H L I F E C Y C L E

manageplan

save & secure

STORE & SHARE

EXPERTISEBIUL

INFRASTRUCTURESitewebDial.prDial.data

FORMATION / INFORMATION Get citations for your dataPublish your dataFind a repositoryMake your data visibleWrite a data sharing agreement

R E S E A R C H L I F E C Y C L E

manageplan

save & secure

STORE & SHARE

EXPERTISEBIUL

INFRASTRUCTURESitewebDial.prDial.data

FORMATION / INFORMATION Get citations for your dataPublish your dataFind a repositoryMake your data visibleWrite a data sharing agreement