Changes for page Data Curation

Last modified by abonard on 2025/06/03 10:55
From version 213.1
edited by ingrreit
on 2023/09/27 16:10
Change comment: There is no comment for this version
To version 217.2
edited by eapapp
on 2024/01/17 17:03
Change comment: Updated link to minimally required metadata file

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1 -XWiki.ingrreit
1 +XWiki.eapapp
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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/lib/47995dbc-f576-4008-a76c-eefbfd818529/file/ebrains-minimum-required-metadata.xlsx]] 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/f/3e226ad165054b35b456/]] on EBRAINS.
150 150  
151 151  
152 152  ==== **4. Write a Data Descriptor** ====
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367 367  ==== **Add a tutorial or learning resource ** ====
368 368  
369 369  (% class="wikigeneratedid" id="H-LearningresourceA05Binformation5D" %)
370 -(% style="--darkreader-inline-color:#ffffff; color:#000000" %)//More information will follow//
370 +(% style="--darkreader-inline-color:#e8e6e3; color:#000000" %)//More information will follow//
371 371  
372 372  
373 373  ==== **Create a workflow** ====
374 374  
375 375  (% class="wikigeneratedid" id="H-Workflows5Binformation5D" %)
376 -(% style="--darkreader-inline-color:#ffffff; color:#000000" %)//More information will follow//
376 +(% style="--darkreader-inline-color:#e8e6e3; color:#000000" %)//More information will follow//
377 377  
378 378  ----
379 379  
380 380  == **EBRAINS commits to the FAIR principles** ==
381 381  
382 -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.
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 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.
383 383  
384 -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]].
384 +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.
385 385  
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); --darkreader-inline-bgcolor: #181a1b;"]]: see our **[[FAIR assessment of EBRAINS datasets>>doc:.FAIR assessment of EBRAINS datasets.WebHome]]. **
386 386  
388 +
387 387  ----
388 388  
389 389  == **General benefits of sharing data ** ==
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394 394  
395 395  
396 396  
397 -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.
399 +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.
398 398  
399 399  ----
400 400  
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427 427  
428 428  ----
429 429  
430 -== (% style="color:#1a202c; font-family:inherit; font-size:29px" %)**The curation team: meet the curators**(%%) ==
432 +== (% style="--darkreader-inline-color:#d2cec8; color:#1a202c; font-family:inherit; font-size:29px" %)**The curation team: meet the curators**(%%) ==
431 431  
432 432  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.
433 433  
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443 443  
444 444  (% class="small" %)Curation Scientist
445 445  Neuroscience (PhD)(%%)
446 -(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)**Behavioral neuroscience and microscopy**
448 +(% class="small" style="--darkreader-inline-color:#b0a99f; color:#4a5568" %)**Behavioral neuroscience and microscopy**
447 447  )))|(% style="width:303px" %)(((
448 448  [[image:Camilla.jpg||alt="My project.jpg" height="209" width="167"]]
449 449  
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452 452  (% class="small" %)Curation Scientist,
453 453  Phd Student
454 454  Neuroscience (M. Sc.)(%%)
455 -(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)**Neuroanatomy and data integration**
457 +(% class="small" style="--darkreader-inline-color:#b0a99f; color:#4a5568" %)**Neuroanatomy and data integration**
456 456  )))|(% style="width:303px" %)(((
457 457  [[image:My project (1).jpg||height="209" width="167"]]
458 458  
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461 461  (% class="small" %)Curation Scientist,
462 462  Phd Student
463 463  Neuroscience (M. Sc.)(%%)
464 -(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)**Neuroanatomy and structural connectivity**
466 +(% class="small" style="--darkreader-inline-color:#b0a99f; color:#4a5568" %)**Neuroanatomy and structural connectivity**
465 465  )))|(% style="width:303px" %)(((
466 466  [[image:My project1.jpg||height="209" width="167"]]
467 467  
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469 469  
470 470  (% class="small" %)Curation Scientist
471 471  Neurocognitive Psychology (M. Sc.)(%%)
472 -(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)**Neuroimaging **
474 +(% class="small" style="--darkreader-inline-color:#b0a99f; color:#4a5568" %)**Neuroimaging **
473 473  )))
474 474  
475 475  |(% style="width:303px" %)(((
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480 480  (% class="small" %)Curation Scientist,
481 481  Phd Student
482 482  Neuroscience (M. Sc.)(%%)
483 -(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)**Neuroanatomy and brain atlases**
485 +(% class="small" style="--darkreader-inline-color:#b0a99f; color:#4a5568" %)**Neuroanatomy and brain atlases**
484 484  )))| | |
485 485  
486 486  
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494 494  (% class="small" %)Curation Scientist,
495 495  Phd Student
496 496  Sensors and Cognitive Psychology (M. Sc.)(%%)
497 -(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)**Human-Computer Interaction**
499 +(% class="small" style="--darkreader-inline-color:#b0a99f; color:#4a5568" %)**Human-Computer Interaction**
498 498  )))|(% style="width:303px" %)(((
499 499  [[image:Lyuba.jpg||height="209" width="167"]]
500 500  
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502 502  
503 503  (% class="small" %)Knowledge Systems Engineer
504 504  Dr. rer. nat. (Systems Neuroscience)(%%)
505 -(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)**Standard development, data & knowledge management, interdisciplinary communication, data analysis**
507 +(% class="small" style="--darkreader-inline-color:#b0a99f; color:#4a5568" %)**Standard development, data & knowledge management, interdisciplinary communication, data analysis**
506 506  )))|(% style="width:303px" %) |(% style="width:303px" %)
507 507  
508 508  ----
Public

Data Curation