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Changes for page Data Curation

Last modified by abonard on 2025/06/03 10:55
From version 210.1
edited by ingrreit
on 2023/07/04 16:18
Change comment: There is no comment for this version
To version 217.3
edited by eapapp
on 2024/01/17 17:05
Change comment: There is no comment for this version

Summary

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1 +Data Curation
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Content
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67 67  
68 68  The curation of data, models and software is different. Thus, below we explain the process for sharing for each research product separately.
69 69  
70 +**Before you get started, make sure you[[ sign up for a free EBRAINS account>>https://www.ebrains.eu/page/sign-up]]. This is needed to complete the data sharing process. **
70 70  
72 +
71 71  ----
72 72  
73 73  === Step by step - Data ===
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144 144  * [[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.
145 145  * [[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.
146 146  
147 -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/||rel=" noopener noreferrer" target="_blank"]] on EBRAINS.
148 148  
149 149  
150 150  ==== **4. Write a Data Descriptor** ====
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365 365  ==== **Add a tutorial or learning resource ** ====
366 366  
367 367  (% class="wikigeneratedid" id="H-LearningresourceA05Binformation5D" %)
368 -(% style="--darkreader-inline-color:#ffffff; color:#000000" %)//More information will follow//
370 +(% style="--darkreader-inline-color:#e8e6e3; color:#000000" %)//More information will follow//
369 369  
370 370  
371 371  ==== **Create a workflow** ====
372 372  
373 373  (% class="wikigeneratedid" id="H-Workflows5Binformation5D" %)
374 -(% style="--darkreader-inline-color:#ffffff; color:#000000" %)//More information will follow//
376 +(% style="--darkreader-inline-color:#e8e6e3; color:#000000" %)//More information will follow//
375 375  
376 376  ----
377 377  
380 +== **EBRAINS commits to the FAIR principles** ==
381 +
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 +
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 +
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]]. **
387 +
388 +
389 +----
390 +
378 378  == **General benefits of sharing data ** ==
379 379  
380 380  By sharing your data via EBRAINS, you gain access to the following benefits:
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383 383  
384 384  
385 385  
386 -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.
387 387  
388 388  ----
389 389  
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416 416  
417 417  ----
418 418  
419 -== (% 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**(%%) ==
420 420  
421 421  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.
422 422  
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432 432  
433 433  (% class="small" %)Curation Scientist
434 434  Neuroscience (PhD)(%%)
435 -(% 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**
436 436  )))|(% style="width:303px" %)(((
437 437  [[image:Camilla.jpg||alt="My project.jpg" height="209" width="167"]]
438 438  
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441 441  (% class="small" %)Curation Scientist,
442 442  Phd Student
443 443  Neuroscience (M. Sc.)(%%)
444 -(% 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**
445 445  )))|(% style="width:303px" %)(((
446 446  [[image:My project (1).jpg||height="209" width="167"]]
447 447  
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450 450  (% class="small" %)Curation Scientist,
451 451  Phd Student
452 452  Neuroscience (M. Sc.)(%%)
453 -(% 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**
454 454  )))|(% style="width:303px" %)(((
455 455  [[image:My project1.jpg||height="209" width="167"]]
456 456  
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458 458  
459 459  (% class="small" %)Curation Scientist
460 460  Neurocognitive Psychology (M. Sc.)(%%)
461 -(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)**Neuroimaging **
474 +(% class="small" style="--darkreader-inline-color:#b0a99f; color:#4a5568" %)**Neuroimaging **
462 462  )))
463 463  
464 464  |(% style="width:303px" %)(((
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469 469  (% class="small" %)Curation Scientist,
470 470  Phd Student
471 471  Neuroscience (M. Sc.)(%%)
472 -(% 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**
473 473  )))| | |
474 474  
475 475  
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483 483  (% class="small" %)Curation Scientist,
484 484  Phd Student
485 485  Sensors and Cognitive Psychology (M. Sc.)(%%)
486 -(% 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**
487 487  )))|(% style="width:303px" %)(((
488 488  [[image:Lyuba.jpg||height="209" width="167"]]
489 489  
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491 491  
492 492  (% class="small" %)Knowledge Systems Engineer
493 493  Dr. rer. nat. (Systems Neuroscience)(%%)
494 -(% 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**
495 495  )))|(% style="width:303px" %) |(% style="width:303px" %)
496 496  
497 497  ----
Public

Data Curation