Changes for page Data Curation

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

From 213.1 to 214.1 From 218.1 to 219.1

From version 214.1

edited by ingrreit
on 2023/09/27 16:22

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To version 218.1

edited by lzehl
on 2024/05/06 09:51

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  * [[Fairgraph>>https://fairgraph.readthedocs.io/en/stable/]]: This is the recommended software tool for programmatic interaction with the KG. It allows you to programmatically upload openMINDS compliant metadata into your KG space and interact with existing metadata.
  * [[KG Core Python SDK>>https://github.com/HumanBrainProject/kg-core-sdks]]: This python package gives you full freedom in interacting with he KG. It allows you to upload any JSON-LD with metadata into your private space. Note, for dataset publications in EBRAINS, the JSON-LD metadata files have to comply to openMINDS.
--Datasets published through the EBRAINS Knowledge Graph have to be registered using **openMINDS compliant metadata** delivered as JSON-LD files. See this summary table for an overview of [[the minimally required openMINDS properties for publishing>>https://drive.ebrains.eu/lib/47995dbc-f576-4008-a76c-eefbfd818529/file/ebrains-minimum-required-metadata.xlsx]] on EBRAINS.
++Datasets published through the EBRAINS Knowledge Graph have to be registered using **openMINDS compliant metadata** delivered as JSON-LD files. See this summary table for an overview of [[the minimally required openMINDS properties for publishing>>https://drive.ebrains.eu/f/3e226ad165054b35b456/||rel="noopener noreferrer" target="_blank"]] on EBRAINS.
  ==== **4. Write a Data Descriptor** ====
@@ -335,13 +335,14 @@
  [[[[image:https://github.com/HumanBrainProject/openMINDS/raw/main/img/light_openMINDS-logo.png||alt="openMINDS logo" height="87" width="164"]]>>https://github.com/HumanBrainProject/openMINDS]]
  )))
--openMINDS (open Metadata Initiative for Neuroscience Data Structures) is a community-driven, open-source metadata framework for graph database systems, such as the EBRAINS Knowledge Graph. It is composed of linked metadata models, libraries of serviceable metadata instances, and supportive tooling ([[openMINDS Python>>url:https://pypi.org/project/openMINDS/]], openMINDS Matlab). For exploring the openMINDS schemas, go to the [[HTML documentation>>url:https://humanbrainproject.github.io/openMINDS/]]. For a full overview of the framework, go to [[the openMINDS collab>>url:https://wiki.ebrains.eu/bin/view/Collabs/openminds/]] or the [[GitHub repository>>https://github.com/HumanBrainProject/openMINDS]].
++openMINDS is a community-driven, open-source metadata framework for linked data, as used in graph database systems, such as the EBRAINS Knowledge Graph. It is composed of multiple metadata models with interlinked schemas, libraries of serviceable metadata instances, and supportive tooling (e.g., [[openMINDS Python>>https://github.com/openMetadataInitiative/openMINDS_Python]] or [[openMINDS Matlab>>https://github.com/openMetadataInitiative/openMINDS_MATLAB]]). A full documentation (for users and contributors) of the openMINDS framework can be found on [[ReadTheDocs>>https://openminds-documentation.readthedocs.io||target="_blank"]].
  For feedback, requests, or contributions, please get in touch with the openMINDS development team via
--* the support-email: [[openminds@ebrains.eu>>path:mailto:openminds@ebrains.eu]]
--* the [[GitHub issue tracker>>url:https://github.com/HumanBrainProject/openMINDS/issues]]
--* the INCF NeuroStars [[openMINDS Community Forum>>url:https://neurostars.org/t/openminds-community-forum-virtual/20156]]
++* [[support@openmetadatainitiative.org>>mailto:mailto:support@openmetadatainitiative.org]]
++* [[GitHub Issues>>https://github.com/openMetadataInitiative/openMINDS/issues]] (for metadata schemas)
++* [[GitHub Issues>>https://github.com/openMetadataInitiative/openMINDS_instances/issues]] (for metadata instances)
++* [[openMINDS Community Forum>>https://neurostars.org/t/openminds-community-forum-virtual]]
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@@ -367,23 +367,23 @@
  ==== **Add a tutorial or learning resource ** ====
  (% class="wikigeneratedid" id="H-LearningresourceA05Binformation5D" %)
--(% style="--darkreader-inline-color:#ffffff; color:#000000" %)//More information will follow//
++(% style="--darkreader-inline-color:#e8e6e3; color:#000000" %)//More information will follow//
  ==== **Create a workflow** ====
  (% class="wikigeneratedid" id="H-Workflows5Binformation5D" %)
--(% style="--darkreader-inline-color:#ffffff; color:#000000" %)//More information will follow//
++(% style="--darkreader-inline-color:#e8e6e3; color:#000000" %)//More information will follow//
  ----
  == **EBRAINS commits to the FAIR principles** ==
--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.
++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 Findability, Accessibility, Interoperability, and Reusability of digital resources (data). 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.
  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: [[FAIR Assessment of EBRAINS datasets>>doc:.FAIR assessment of EBRAINS datasets.WebHome]]. The assessment follows the [[FAIRsFAIR Data Object Assessment Metrics>>https://zenodo.org/record/6461229||style="background-color: rgb(255, 255, 255);"]]:
++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); --darkreader-inline-bgcolor: #181a1b;"]]: see our **[[FAIR assessment of EBRAINS datasets>>doc:.FAIR assessment of EBRAINS datasets.WebHome]]. **
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@@ -396,7 +396,7 @@
--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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@@ -429,7 +429,7 @@
  ----
--== (% style="color:#1a202c; font-family:inherit; font-size:29px" %)**The curation team: meet the curators**(%%) ==
++== (% style="--darkreader-inline-color:#d2cec8; color:#1a202c; font-family:inherit; font-size:29px" %)**The curation team: meet the curators**(%%) ==
  The EBRAINS curators help researchers publish their research using the EBRAINS Research Infrastructure. A curator’s job is similar to the job of an editor of a scientific journal, checking the data is organized, understandable, accessible and sufficiently described.
@@ -445,7 +445,7 @@
  (% class="small" %)Curation Scientist
  Neuroscience (PhD)(%%)
--(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)**Behavioral neuroscience and microscopy**
++(% class="small" style="--darkreader-inline-color:#b0a99f; color:#4a5568" %)**Behavioral neuroscience and microscopy**
  )))|(% style="width:303px" %)(((
  [[image:Camilla.jpg||alt="My project.jpg" height="209" width="167"]]
@@ -454,7 +454,7 @@
  (% class="small" %)Curation Scientist,
  Phd Student
  Neuroscience (M. Sc.)(%%)
--(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)**Neuroanatomy and data integration**
++(% class="small" style="--darkreader-inline-color:#b0a99f; color:#4a5568" %)**Neuroanatomy and data integration**
  )))|(% style="width:303px" %)(((
  [[image:My project (1).jpg||height="209" width="167"]]
@@ -463,7 +463,7 @@
  (% class="small" %)Curation Scientist,
  Phd Student
  Neuroscience (M. Sc.)(%%)
--(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)**Neuroanatomy and structural connectivity**
++(% class="small" style="--darkreader-inline-color:#b0a99f; color:#4a5568" %)**Neuroanatomy and structural connectivity**
  )))|(% style="width:303px" %)(((
  [[image:My project1.jpg||height="209" width="167"]]
@@ -471,7 +471,7 @@
  (% class="small" %)Curation Scientist
  Neurocognitive Psychology (M. Sc.)(%%)
--(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)**Neuroimaging **
++(% class="small" style="--darkreader-inline-color:#b0a99f; color:#4a5568" %)**Neuroimaging **
  )))
  |(% style="width:303px" %)(((
@@ -482,7 +482,7 @@
  (% class="small" %)Curation Scientist,
  Phd Student
  Neuroscience (M. Sc.)(%%)
--(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)**Neuroanatomy and brain atlases**
++(% class="small" style="--darkreader-inline-color:#b0a99f; color:#4a5568" %)**Neuroanatomy and brain atlases**
  )))| | |
@@ -496,7 +496,7 @@
  (% class="small" %)Curation Scientist,
  Phd Student
  Sensors and Cognitive Psychology (M. Sc.)(%%)
--(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)**Human-Computer Interaction**
++(% class="small" style="--darkreader-inline-color:#b0a99f; color:#4a5568" %)**Human-Computer Interaction**
  )))|(% style="width:303px" %)(((
  [[image:Lyuba.jpg||height="209" width="167"]]
@@ -504,7 +504,7 @@
  (% class="small" %)Knowledge Systems Engineer
  Dr. rer. nat. (Systems Neuroscience)(%%)
--(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)**Standard development, data & knowledge management, interdisciplinary communication, data analysis**
++(% class="small" style="--darkreader-inline-color:#b0a99f; color:#4a5568" %)**Standard development, data & knowledge management, interdisciplinary communication, data analysis**
  )))|(% style="width:303px" %) |(% style="width:303px" %)
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