Changes for page Data Curation

Last modified by abonard on 2025/06/03 10:55
From version 218.1
edited by lzehl
on 2024/05/06 09:51
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To version 216.1
edited by ingrreit
on 2023/09/27 17:04
Change comment: There is no comment for this version

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1 -XWiki.lzehl
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146 146  * [[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.
147 147  * [[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.
148 148  
149 -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.
149 +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.
150 150  
151 151  
152 152  ==== **4. Write a Data Descriptor** ====
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335 335  [[[[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]]
336 336  )))
337 337  
338 -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"]].
338 +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]].
339 339  
340 340  For feedback, requests, or contributions, please get in touch with the openMINDS development team via
341 341  
342 -* [[support@openmetadatainitiative.org>>mailto:mailto:support@openmetadatainitiative.org]]
343 -* [[GitHub Issues>>https://github.com/openMetadataInitiative/openMINDS/issues]] (for metadata schemas)
344 -* [[GitHub Issues>>https://github.com/openMetadataInitiative/openMINDS_instances/issues]] (for metadata instances)
345 -* [[openMINDS Community Forum>>https://neurostars.org/t/openminds-community-forum-virtual]]
342 +* the support-email: [[openminds@ebrains.eu>>path:mailto:openminds@ebrains.eu]]
343 +* the [[GitHub issue tracker>>url:https://github.com/HumanBrainProject/openMINDS/issues]]
344 +* the INCF NeuroStars [[openMINDS Community Forum>>url:https://neurostars.org/t/openminds-community-forum-virtual/20156]]
346 346  
347 347  ----
348 348  
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368 368  ==== **Add a tutorial or learning resource ** ====
369 369  
370 370  (% class="wikigeneratedid" id="H-LearningresourceA05Binformation5D" %)
371 -(% style="--darkreader-inline-color:#e8e6e3; color:#000000" %)//More information will follow//
370 +(% style="--darkreader-inline-color:#ffffff; color:#000000" %)//More information will follow//
372 372  
373 373  
374 374  ==== **Create a workflow** ====
375 375  
376 376  (% class="wikigeneratedid" id="H-Workflows5Binformation5D" %)
377 -(% style="--darkreader-inline-color:#e8e6e3; color:#000000" %)//More information will follow//
376 +(% style="--darkreader-inline-color:#ffffff; color:#000000" %)//More information will follow//
378 378  
379 379  ----
380 380  
381 381  == **EBRAINS commits to the FAIR principles** ==
382 382  
383 -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.
382 +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.
384 384  
385 385  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.
386 386  
387 -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]]. **
386 +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]].
388 388  
389 389  
390 390  ----
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430 430  
431 431  ----
432 432  
433 -== (% style="--darkreader-inline-color:#d2cec8; color:#1a202c; font-family:inherit; font-size:29px" %)**The curation team: meet the curators**(%%) ==
432 +== (% style="color:#1a202c; font-family:inherit; font-size:29px" %)**The curation team: meet the curators**(%%) ==
434 434  
435 435  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.
436 436  
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446 446  
447 447  (% class="small" %)Curation Scientist
448 448  Neuroscience (PhD)(%%)
449 -(% class="small" style="--darkreader-inline-color:#b0a99f; color:#4a5568" %)**Behavioral neuroscience and microscopy**
448 +(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)**Behavioral neuroscience and microscopy**
450 450  )))|(% style="width:303px" %)(((
451 451  [[image:Camilla.jpg||alt="My project.jpg" height="209" width="167"]]
452 452  
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455 455  (% class="small" %)Curation Scientist,
456 456  Phd Student
457 457  Neuroscience (M. Sc.)(%%)
458 -(% class="small" style="--darkreader-inline-color:#b0a99f; color:#4a5568" %)**Neuroanatomy and data integration**
457 +(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)**Neuroanatomy and data integration**
459 459  )))|(% style="width:303px" %)(((
460 460  [[image:My project (1).jpg||height="209" width="167"]]
461 461  
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464 464  (% class="small" %)Curation Scientist,
465 465  Phd Student
466 466  Neuroscience (M. Sc.)(%%)
467 -(% class="small" style="--darkreader-inline-color:#b0a99f; color:#4a5568" %)**Neuroanatomy and structural connectivity**
466 +(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)**Neuroanatomy and structural connectivity**
468 468  )))|(% style="width:303px" %)(((
469 469  [[image:My project1.jpg||height="209" width="167"]]
470 470  
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472 472  
473 473  (% class="small" %)Curation Scientist
474 474  Neurocognitive Psychology (M. Sc.)(%%)
475 -(% class="small" style="--darkreader-inline-color:#b0a99f; color:#4a5568" %)**Neuroimaging **
474 +(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)**Neuroimaging **
476 476  )))
477 477  
478 478  |(% style="width:303px" %)(((
... ... @@ -483,7 +483,7 @@
483 483  (% class="small" %)Curation Scientist,
484 484  Phd Student
485 485  Neuroscience (M. Sc.)(%%)
486 -(% class="small" style="--darkreader-inline-color:#b0a99f; color:#4a5568" %)**Neuroanatomy and brain atlases**
485 +(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)**Neuroanatomy and brain atlases**
487 487  )))| | |
488 488  
489 489  
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497 497  (% class="small" %)Curation Scientist,
498 498  Phd Student
499 499  Sensors and Cognitive Psychology (M. Sc.)(%%)
500 -(% class="small" style="--darkreader-inline-color:#b0a99f; color:#4a5568" %)**Human-Computer Interaction**
499 +(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)**Human-Computer Interaction**
501 501  )))|(% style="width:303px" %)(((
502 502  [[image:Lyuba.jpg||height="209" width="167"]]
503 503  
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505 505  
506 506  (% class="small" %)Knowledge Systems Engineer
507 507  Dr. rer. nat. (Systems Neuroscience)(%%)
508 -(% class="small" style="--darkreader-inline-color:#b0a99f; color:#4a5568" %)**Standard development, data & knowledge management, interdisciplinary communication, data analysis**
507 +(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)**Standard development, data & knowledge management, interdisciplinary communication, data analysis**
509 509  )))|(% style="width:303px" %) |(% style="width:303px" %)
510 510  
511 511  ----
Public

Data Curation