@inproceedings{fdi:010090478,
  title = {{D}ata {FAIR}ification in a cross-institutional governance framework : recommendations from the {ANR}-{BRIDGE} project [poster]},
  author = {{A}venturier, {P}ascal and {A}laux, {M}. and {B}arthelemy, {C}. and {B}onnet, {P}. and {H}ugo, {C}atherine and {D}zal{\'e}, {E}. and {D}eboin, {M}.{C}. and {D}ecker, {L}uc and {D}esconnets, {J}ean-{C}hristophe and {D}oux, {G}. and {F}ortuno, {S}. and {M}ougin, {C}. and {P}erez, {J}{\'e}r{\^o}me and {S}abot, {F}ran{\c{c}}ois and {S}zabo, {D}.},
  editor = {},
  language = {{ENG}},
  abstract = {{C}ontext : {O}pen science is a priority for the {E}uropean {C}ommission, fostering research data management policies and infrastructures. {I}n {F}rance, the {S}econd {N}ational {P}lan for {O}pen {S}cience aims to ensure that open science becomes a common and shared practice, encouraged by the entire international ecosystem of higher education, research, and innovation. {I}n addition, the {F}rench {M}inistry of {R}esearch is building a national federated data repository : {R}echerche {D}ata {G}ouv, as part of its {O}pen {S}cience {P}lan. {O}bjectives {I}n this context, three {F}rench research organizations, each maintaining an institutional data repository based on {D}ataverse software, initiated the {BRIDGE} project funded by the {F}rench {N}ational {R}esearch {A}gency following a special {O}pen {S}cience call. {O}ne challenge is that {F}rench research is mainly organized into joint research units : within a same laboratory, project or publication datasets can be managed by different research organizations, necessitating choosing between several institutional and disciplinary data repositories that can cause data scattering. {T}hree priorities. {T}he goal of the {B}ridge project is to provide guidelines and harmonize research data policies and repository management in a reusable approach for other institutes or contexts, focusing on : 1. {A}nalyzing and improving institutional data governance policies 2. {P}roviding and endorsing common guidelines for data producers and managers 3. {C}hoosing {FAIR} vocabularies and developing {IT} tools to improve {FAIR}ness of repositories with some shared metadata schemas. {M}ain outputs : {D}efine and adopt common rules for all the project partners. {T}he {DMP} ({D}ata {M}anagement {P}lan) must be built in the light of these rules. {O}vercome some difficulties related to the practical implementation of data {FAIR}ication. {F}or example : bringing data into standard; define sharing conditions, common rules for harvesting metadata repositories . {A}lign with common ontologies and controlled vocabularies (data type, disciplinary fields, etc.) available via the semantic web.},
  keywords = {{FRANCE}},
  numero = {},
  pages = {1  multigr.},
  booktitle = {},
  year = {2022},
  DOI = {10.5281/zenodo.6652404},
  URL = {https://www.documentation.ird.fr/hor/fdi:010090478},
}