Rese a r c~ h D ata Management · 2020. 6. 23. · Adeline Grard - Service Central des...
Transcript of Rese a r c~ h D ata Management · 2020. 6. 23. · Adeline Grard - Service Central des...
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I N T R O D U C T I O N T O
Research DataManagement
Adeline Grard - Service Central des Bibliothèques
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Présentationin 2 times
BACKGROUND
= EXPERIENCES +
1
2
3
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RDMBASICS
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M I L
AIMS of RDM
Create, organize, make accessible, store,
and share research data of an institution.
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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
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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
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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.
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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.
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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)
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FAIR data principle
a guideline for RDM all around the world
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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
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P R O S & C O N S
12 REASONS TOJUMP INTO RDM
9 OBSTACLES ANDCONCERNS
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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
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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
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CONTEXT URGE TO
IMPLEMENT RDM
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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
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In Belgium?
SODA (EOSC)
DMPonline
KULeuven
UGent
ULiège
ULB
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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
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R E S E A R C H L I F E C Y C L E
manageplan
save & secure
store & share
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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
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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
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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
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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
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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
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3 Pilars of a
RDM services
AIM: provide support to researchers throughout the research life cycle
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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
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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
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PILAR 3:INFRASTRUCTURE
WEBSITE
REPOSITORY
Storage servers or external solution
Tools (DMPonline)
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EXAMPLE
OF RDM SERVICE
APPLIED TO PLANNIG STEP
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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
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QUESTIONS
REMARKS
IDEAS
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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
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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
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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
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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