Changes for page Data Curation

Last modified by abonard on 2025/06/03 10:55

From 212.1 to 213.1 From 216.1 to 217.1

From version 213.1

edited by ingrreit
on 2023/09/27 16:10

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To version 216.1

edited by ingrreit
on 2023/09/27 17:04

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@@ -379,11 +379,13 @@
  == **EBRAINS commits to the FAIR principles** ==
--Datasets, models and software shared via EBRAINS go through a streamlined curation process that ensures relevant annotation of the data using the [[openMINDS>>url:https://github.com/HumanBrainProject/openMINDS]] metadata framework and integration into the [[EBRAINS Knowledge Graph>>url:https://docs.kg.ebrains.eu/]] metadata management system. The research products are Findable and Accessible through the [[Knowledge Graph Search>>url:https://search.kg.ebrains.eu/?category=Dataset]] as dataset/model/software cards that display further information regarding the dataset's Interoperability and Reusability.
++In 2016, the 'FAIR Guiding Principles for the management and guardianship of scientific data'{{footnote}}Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016). https://doi.org/10.1038/sdata.2016.18 {{/footnote}} were introduced to the scientific community. The objective of the authors was to provide a set of general recommendations aimed at enhancing the Discoverability, Accessibility, Interoperability, and Reusability of digital resources. They emphasize the importance of making data more open, discoverable, and usable, ultimately facilitating collaboration and knowledge sharing within the scientific community. Today, the FAIR principles are widely recognized and adopted as best practices in data management and stewardship across scientific fields.
--To further specify how EBRAINS aligns with the FAIR principles, we have assessed the FAIRness of datasets shared in the EBRAINS Knowledge Graph following the [[FAIRsFAIR Data Object Assessment Metrics>>https://zenodo.org/record/6461229]]: Go to the [[FAIR Assessment of EBRAINS datasets>>doc:.FAIR assessment of EBRAINS datasets.WebHome]].
++In EBRAINS, all datasets, models and software shared go through a streamlined curation process that ensures relevant annotation of the data using the [[openMINDS>>url:https://github.com/HumanBrainProject/openMINDS]] metadata framework and integration into the [[EBRAINS Knowledge Graph>>url:https://docs.kg.ebrains.eu/]] metadata management system. The research products are Findable and Accessible through the [[Knowledge Graph Search>>url:https://search.kg.ebrains.eu/?category=Dataset]] as dataset/model/software cards that display further information regarding the dataset's Interoperability and Reusability.
++To further specify how EBRAINS aligns with the FAIR principles, we have assessed the FAIRness of datasets shared in the EBRAINS Knowledge Graph following the [[FAIRsFAIR Data Object Assessment Metrics>>https://zenodo.org/record/6461229||style="background-color: rgb(255, 255, 255);"]]: see our [[FAIR Assessment of EBRAINS datasets>>doc:.FAIR assessment of EBRAINS datasets.WebHome]].
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  == **General benefits of sharing data ** ==
@@ -394,7 +394,7 @@
--We support you to better follow the [[FAIR^^ ^^guiding principles>>https://www.nature.com/articles/sdata201618]] for data management and stewardship{{footnote}}Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016). https://doi.org/10.1038/sdata.2016.18 {{/footnote}}.  Publishing data, models or code via EBRAINS will provide you with a citeable [[DataCite DOI>>https://www.doi.org/the-identifier/resources/handbook/]] for your research product.
++We support you to better follow the [[FAIR^^ ^^guiding principles>>https://www.nature.com/articles/sdata201618]] for data management and stewardship. Publishing data, models or code via EBRAINS will provide you with a citeable [[DataCite DOI>>https://www.doi.org/the-identifier/resources/handbook/]] for your research product.
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