Changes for page Data Curation

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From version 214.1
edited by ingrreit
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To version 193.1
edited by ingrreit
on 2023/06/14 09:00
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1 -Data Curation
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1 -Collabs.WebHome
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17 17  {{/html}}
18 18  
19 19  
20 -(% class="wikigeneratedid" id="HPublishingneurosciencedata2CmodelsandsoftwareviaEBRAINS" %)
21 -(% style="font-size:2em" %)**Publishing neuroscience data, models and software via EBRAINS**
20 +== Publishing neuroscience data, models and software via EBRAINS ==
22 22  
22 +
23 23  (% class="wikigeneratedid" %)
24 24  The aim of this collab is to provide you with detailed information about publishing data, simulations, computational models, and software via EBRAINS. If you want a quick overview of the sharing process, see [[https:~~/~~/ebrains.eu/service/share-data>>https://ebrains.eu/service/share-data]].
25 25  
... ... @@ -67,9 +67,7 @@
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. **
71 71  
72 -
73 73  ----
74 74  
75 75  === Step by step - Data ===
... ... @@ -85,6 +85,8 @@
85 85  //to share data on EBRAINS: //
86 86  // //
87 87  [[[[image:image-20230324171114-2.png||height="150" width="106"]]>>https://drive.ebrains.eu/f/dfd374b9b43a458192e9/]]
86 +
87 +
88 88  )))
89 89  
90 90  
... ... @@ -106,20 +106,10 @@
106 106  
107 107  ==== **2. Upload data ** ====
108 108  
109 -(% class="box floatinginfobox" id="share-data-infographic" %)
110 -(((
111 -(% style="text-align:center" %)
112 -//Download our infographic//
113 -//with guidelines
114 -on data organization: //
115 115  
116 -(% style="text-align:center" %)
117 -[[[[image:image-20230621121014-1.png||height="150" width="106"]]>>https://drive.ebrains.eu/lib/f5cf4964-f095-49bd-8c34-e4ffda05a497/file/ebrains-infographic-data-organisation.pdf/]]
118 -)))
119 -
120 120  (% style="margin-right:10px" %)[[image:https://lh5.googleusercontent.com/sieKO-kW8O18iPaUyonwyo4UfHBmtc2E9BDnjbx52j6J_uGmm-OzGAo7sloMk3sYwKa6QW3hYQsOA9N4H7uGQpca088Wrk0Nurpt_J3B0-NSbcaPNdZIh21otQcG6jnAxLGiKoEvkTyaDGTMk3fu7me8mQ=s2048||height="94px;" width="94px;"]](%%)**Ensure data is structured consistently prior to upload. **
121 121  
122 -We look for organized data, not organized according to our standard. This is to support the broadest degree of sharing possible. We do however require that the data is organized in a consistent and precise manner. Please see our// //[[guidelines on data organization>>https://drive.ebrains.eu/smart-link/25299f04-c4e5-4028-8f5f-3b8208f9a532/]] for further guidance.
112 +We look for organized data, not organized according to our standard. This is to support the broadest degree of sharing possible. We do however require that the data is organized in a consistent and precise manner. Please see our// //[[collection of guidelines on data organization>>https://drive.ebrains.eu/smart-link/25299f04-c4e5-4028-8f5f-3b8208f9a532/]] for further guidance.
123 123  
124 124  (% style="margin-right:10px" %)[[image:https://lh5.googleusercontent.com/EWtYwfVlbeC-jqPasgmzidqc50GrkKIEgwXeUeql8aaMHIukmFdWEy0nufVWWATbxDDK3XwwZEDmASrbpCsBk1u0HpAd8x4ZgAMsMPRcWyrb9etlV6FgKE_QN2e6SqKxHE0rzkR8uI1rRW_5z21TFGYVnw=s2048||height="91px;" width="91px;"]](%%)**Upload data to EBRAINS Storage, either using a drag-and-drop solution (opt. 1) or an interactive python script (opt. 2).**
125 125  
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167 167  (% class="box floatinginfobox" id="data-descriptor-infographic" %)
168 168  (((
169 169  (% style="text-align:center" %)
170 -//Download our infographic
171 -about the EBRAINS Data//
172 -//Descriptor//
160 +//Download our infographic: //
161 +//The EBRAINS Data//
162 +//Descriptor at a glance//
173 173  // //
174 174  [[[[image:image-20230324171109-1.png||height="150" width="106"]]>>https://drive.ebrains.eu/f/c1ccb78be52e4bdba7cf/]]
165 +
175 175  )))
176 176  
177 177  ==== **5. Preview and publish** ====
... ... @@ -182,96 +182,49 @@
182 182  Once a Curator has assembled the dataset in the EBRAINS Knowledge Graph, combining the data, metadata and data descriptor, the data provider will receive a private URL for previewing the dataset prior to release. We need an official approval from the data custodian{{footnote}}The Data Custodian is responsible for the content and quality of the Data and metadata, and is the person to be contacted by EBRAINS CS in case of any misconduct related to the Data. It is the obligation of a Data Custodian to keep EBRAINS informed about changes in the contact information of the authors of the Datasets provided by them ([[EBRAINS Data Provision Protocol - version 1.1>>https://strapi-prod.sos-ch-dk-2.exo.io/EBRAINS_Data_Provision_Protocol_dfe0dcb104.pdf]]).{{/footnote}} to release the dataset. Once released, a [[DataCite DOI>>https://datacite.org/]] will be generated for the dataset. If the identical data collection has received a DOI elsewhere, we recommend re-using the already issued DOI.
183 183  
184 184  
185 -
186 -
187 187  ----
188 188  
189 -=== Step by Step - Models ===
178 +==== ====
190 190  
180 +==== **Sharing human subject data** ====
191 191  
192 -==== 1. Start early ====
182 +(% class="box floatinginfobox" %)
183 +(((
184 +**Human subject data that can be shared on EBRAINS:**
185 +// //
186 +// - Post-mortem data//
187 +// - Aggregated data//
188 +// - Strongly pseudonymized or de-identified subject data//
189 +// with a legal basis for sharing (e.g. Informed Consent)//
190 +// //
193 193  
194 -It is not necessary to wait until you are ready to publish to register your model with EBRAINS.
192 +(% class="small" %)
193 +//If you have human data that does not qualify as any of the above,//
194 +//please [[get in touch>>https://www.ebrains.eu/contact/]] and we will clarify the available options.//
195 +)))
195 195  
196 -By registering a model early in your project, you can take advantage of EBRAINS tools
197 -to keep track of simulations and to share them with your collaborators.
198 198  
199 -==== 2. Create/choose a Collab workspace ====
198 +Human subject data shared on EBRAINS must comply with [[GDPR >>https://gdpr-info.eu/]]and [[EU directives>>https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A32010L0063]]. The information we need to assess this is collected via our [[Ethics and Regulatory Compliance Survey>>https://nettskjema.no/a/224765]].
200 200  
201 -We use EBRAINS Collaboratory "collab" workspaces to help manage the model curation process.
200 +Post-mortem and aggregated human data can be shared openly, given direct identifiers in the metadata are removed. Strongly pseudonymized and de-identified data can be shared via the Human Data Gateway (HDG).
202 202  
203 -In particular, we use collab membership (the "Team") to control who can view or edit your model metadata prior to publication.
202 +The Human Data Gateway (HDG) was introduced in February 2021 as a response to the needs of multiple data providers who are bringing human subject data to EBRAINS. HDG covers the sharing of strongly pseudonymized or de-identified data, a limited range human subject data without direct identifiers and with very few indirect identifiers.
204 204  
205 -It is up to you whether you create a new collab for each model, or reuse an existing collab
206 -(it is no problem to have multiple models associated with a single collab).
204 +The HDG adds an an authentication layer on top of the data. This means that **data users **must request access to the data (via their EBRAINS account) and will receive access provided they actively accept the [[EBRAINS Access Policy>>https://ebrains.eu/terms#access-policy]], the [[EBRAINS General Terms of Use>>https://ebrains.eu/terms#general-terms-of-use]], and the [[EBRAINS Data Use Agreement>>https://ebrains.eu/terms#data-use-agreement]]. The account holder also have to accept that information about their request and access to specific data under HDG is being tracked and stored. **Data owners** must be aware that sharing under the HDG affects the legal responsibilities for the data. They must agree to joint control of the data (see the [[Data Provision Protocol v1>>url:https://strapi-prod.sos-ch-dk-2.exo.io/EBRAINS_Data_Provision_Protocol_dfe0dcb104.pdf]], section 1.4 - 1.5) and the Data Protection Officers of the responsible institutions must have accepted that the data can be shared under HDG.
207 207  
208 -Collabs are also useful for storing simulation results, adding documentation for your model,
209 -and/or providing tutorials in Jupyter notebooks.
206 +The HDG is an extension of the existing services and does not replace the future EBRAINS Service for sensitive data (planned for 2024) which is outside the domain of the current EBRAINS Data and Knowledge services.
210 210  
211 -==== 3. Upload code ====
212 212  
213 -We recommend storing model code and/or configuration files in an online Git repository, for example on GitHub.
214 -This repository should be public when you publish the model, but a private repository can be used for model development.
209 +----
215 215  
216 -Alternatively, you can upload code to the Collab Drive or Bucket storage.
211 +=== Step by Step - Models ===
217 217  
218 -==== 4.Submit metadata ====
219 219  
220 -We recommend submitting metadata using the Model Catalog app, installed in your collab.
214 +~1. Request curation using the [[Curation request form>>https://nettskjema.no/a/277393#/]]. You will be contacted by a curator with more information.
221 221  
222 -To install it:
223 223  
224 -1. click the "+ Create" button
225 -1. in the "Create Page" form, add a title, such as "Model Catalog", and select "Community App", then click "Create"
226 -1. scroll down until you find the "Model Catalog" app, click "Select", then "Save & View"
217 +//Additional information will be added soon.//
227 227  
228 -You will then see a table of all the models and validation tests associated with this collab.
229 -If this is your first time using the app, the table will probably be empty.
230 -To add your model, click "+", fill in the form, then click "Add model".
231 -
232 -As development of your model proceeds, you can easily register new versions of the code,
233 -and new parameterizations, by clicking "Add new version".
234 -
235 -If you prefer not to use the app, you can instead fill in the [[Curation request form>>https://nettskjema.no/a/277393#/]].,
236 -and you will be contacted by e-mail with further instructions.
237 -
238 -==== 5. Provide a reference dataset ====
239 -
240 -Once you're ready to publish your model entry in the EBRAINS Knowledge Graph,
241 -we encourage you to provide a dataset containing the simulation results produced by your model,
242 -following the process under "Step by step - Data" above.
243 -
244 -These reference data will be linked to the model, and will be helpful to anyone trying to
245 -reuse your model.
246 -
247 -We will soon introduce a "Reproducible" badge for all models that include a reference dataset,
248 -and whose simulation results can be reproduced by an EBRAINS curator.
249 -
250 -==== 6. Request publication, preview and publish ====
251 -
252 -Until you request your model entry to be published in the EBRAINS Knowledge Graph,
253 -only members of the collab will be able to view the model entry, in the Model Catalog app
254 -or using the Model Validation Python client.
255 -
256 -After publication, the model will appear in the [[EBRAINS public search results>>https://search.kg.ebrains.eu/?category=Model||rel="noopener noreferrer" target="_blank"]], and will receive a DOI.
257 -
258 -To request publication, [[contact EBRAINS support>>https://ebrains.eu/support||rel="noopener noreferrer" target="_blank"]], providing the collab name and the model name or ID.
259 -
260 -
261 -Curators will then perform a number of checks:
262 -
263 -1. Does the model description provide sufficient context to understand the purpose and use of the model?
264 -1. Does the code repository contain a licence file, explaining the conditions for reusing the code?
265 -1. Does the model have a clearly defined version identifier (e.g. v1.0)? For models in a Git repository, the version identifier should match the name of a tag or release.
266 -
267 -The curators will also take a snapshot of your model code.
268 -
269 -* For models in public Git repositories, we archive a copy of the repository in [[Software Heritage>>https://www.softwareheritage.org/||rel="noopener noreferrer" target="_blank"]].
270 -* For models in a collab Bucket or Drive, we make a read-only copy of the code in a public container in the EBRAINS repository.
271 -
272 -Once this is done, you will be invited to review a preview of how the model entry will appear in the KG Search,
273 -and will have the opportunity to request modifications prior to approval and publication.
274 -
275 275  ----
276 276  
277 277  === Step by Step - Software ===
... ... @@ -298,41 +298,14 @@
298 298  
299 299  ----
300 300  
301 -=== Sharing human subject data ===
302 -
303 -(% class="box floatinginfobox" %)
304 -(((
305 -**Human subject data that can be shared on EBRAINS:**
306 -// //
307 -// - Post-mortem data//
308 -// - Aggregated data//
309 -// - Strongly pseudonymized or de-identified subject data//
310 -// with a legal basis for sharing (e.g. Informed Consent)//
311 -// //
312 -
313 -(% class="small" %)
314 -//If you have human data that does not qualify as any of the above,//
315 -//please [[get in touch>>https://www.ebrains.eu/contact/]] and we will clarify the available options.//
316 -)))
317 -
318 -
319 -Human subject data shared on EBRAINS must comply with [[GDPR >>https://gdpr-info.eu/]]and [[EU directives>>https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A32010L0063]]. The information we need to assess this is collected via our [[Ethics and Regulatory Compliance Survey>>https://nettskjema.no/a/224765]].
320 -
321 -Post-mortem and aggregated human data can be shared openly, given direct identifiers in the metadata are removed. Strongly pseudonymized and de-identified data can be shared via the Human Data Gateway (HDG).
322 -
323 -The Human Data Gateway (HDG) was introduced in February 2021 as a response to the needs of multiple data providers who are bringing human subject data to EBRAINS. HDG covers the sharing of strongly pseudonymized or de-identified data, a limited range human subject data without direct identifiers and with very few indirect identifiers.
324 -
325 -The HDG adds an an authentication layer on top of the data. This means that **data users **must request access to the data (via their EBRAINS account) and will receive access provided they actively accept the [[EBRAINS Access Policy>>https://ebrains.eu/terms#access-policy]], the [[EBRAINS General Terms of Use>>https://ebrains.eu/terms#general-terms-of-use]], and the [[EBRAINS Data Use Agreement>>https://ebrains.eu/terms#data-use-agreement]]. The account holder also have to accept that information about their request and access to specific data under HDG is being tracked and stored. **Data owners** must be aware that sharing under the HDG affects the legal responsibilities for the data. They must agree to joint control of the data (see the [[Data Provision Protocol v1>>url:https://strapi-prod.sos-ch-dk-2.exo.io/EBRAINS_Data_Provision_Protocol_dfe0dcb104.pdf]], section 1.4 - 1.5) and the Data Protection Officers of the responsible institutions must have accepted that the data can be shared under HDG.
326 -
327 -The HDG is an extension of the existing services and does not replace the future EBRAINS Service for sensitive data (planned for 2024) which is outside the domain of the current EBRAINS Data and Knowledge services.
328 -
329 -----
330 -
331 331  == **The openMINDS metadata framework** ==
332 332  
333 333  (% class="box floatinginfobox" %)
334 334  (((
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]]
250 +
251 +(% style="text-align: center;" %)
252 +//openMINDS GitHub//
336 336  )))
337 337  
338 338  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]].
... ... @@ -345,98 +345,14 @@
345 345  
346 346  ----
347 347  
348 -== **Add practical value to your shared data, model or software** ==
265 +== **The curation team: meet the curators** ==
349 349  
350 -
351 -=== **Showcase shared data, models or software in other services** ===
352 -
353 -Below is a list of additional services that data, models or software shared via EBRAINS can benefit from. EBRAINS is continuously looking to increase the number of interoperable services.
354 -
355 -
356 -|(% colspan="2" %)**Viewer for 2D images**
357 -|[[image:MIO_screenshot.PNG]]|Integrate image data with //the Mio viewer//: EBRAINS Multi-Image OpenSeadragon viewer provides an intuitive way of navigating high-resolution 2D image series. It has browser-based classic pan and zoom capabilities. A collection can be displayed as a filmstrip (Filmstrip Mode) or as a table (Collection Mode) with adjustable number of row and columns. See [[Mio viewer links available for this dataset>>https://search.kg.ebrains.eu/?category=Dataset&q=nr2f1#9677359c-73fa-4425-b8fa-3de794e9017a]] as an example. MioViewer user manual is found [[here>>https://multi-image-osd.readthedocs.io/en/latest/index.html]].
358 -|(% colspan="2" %)**Viewer for sequential atlas-registered 2D images with annotation options**
359 -|[[image:LZ_screenshot.PNG]]|Integrate atlas-registered 2D image data with //the LocaliZoom viewer//: The EBRAINS LocaliZoom serial section viewer displays series of registered 2D section images with atlas overlay, allowing the users to zoom into high-resolution images and have information about the brain regions. See the [[LocaliZoom links available for this dataset>>https://doi.org/10.25493/T686-7BX]] as an example. LocaliZoom user manual is found [[here>>https://localizoom.readthedocs.io/en/latest/index.html]].
360 -|(% colspan="2" %)**Interactive 3D atlas viewer with options for data visualization**
361 -|[[image:3Datlas_screenshot.PNG]]|Upload your data to the //Siibra-explorer//: The siibra-explorer is used for visualizing volumetric brain data in all the brain atlases provided by EBRAINS (Human, Monkey, Rat and Mouse). The siibra-explorer viewer uses siibra-api to enable navigation of brain region hierarchies, maps in different coordinate spaces, and linked regional data features. Furthermore, it is connected with the siibra toolsuite providing several analytical workflows. To learn more about how to register your data to atlases, read about the [[Atlas services on ebrains.eu>>https://ebrains.eu/services/atlases#Integratedatatoanatlas]].
362 -|(% colspan="2" %)**Use your research product in an interactive publication**
363 -|[[image:LivePaper_screenshot.PNG]]|Add your data, models or software to a// Live paper. //Read more about [[Live papers on ebrains.eu>>https://www.ebrains.eu/data/live-papers/live-papers]].
364 -
365 -----
366 -
367 -==== **Add a tutorial or learning resource ** ====
368 -
369 -(% class="wikigeneratedid" id="H-LearningresourceA05Binformation5D" %)
370 -(% style="--darkreader-inline-color:#ffffff; color:#000000" %)//More information will follow//
371 -
372 -
373 -==== **Create a workflow** ====
374 -
375 -(% class="wikigeneratedid" id="H-Workflows5Binformation5D" %)
376 -(% style="--darkreader-inline-color:#ffffff; color:#000000" %)//More information will follow//
377 -
378 -----
379 -
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 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.
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: [[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);"]]:
387 -
388 -
389 -----
390 -
391 -== **General benefits of sharing data ** ==
392 -
393 -By sharing your data via EBRAINS, you gain access to the following benefits:
394 -
395 -[[image:image-20230324170841-3.png]]
396 -
397 -
398 -
399 -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.
400 -
401 -----
402 -
403 -== **Frequently asked questions ** ==
404 -
405 ->Is the curation process time consuming and difficult?
406 -
407 -No, if communication is on a regular basis, we are able to finish curation within two weeks. Publishing your data naturally takes some effort but we will support you as much as possible.
408 -
409 ->Is sharing my data also beneficial for me or only for others?
410 -
411 -When you publish your data via EBRAINS, we provide comprehensive data management support and safe long term storage - all free of charge. Additionally, your data can be cited, just like a scientific journal article. Sharing your data may even lead to new funding opportunities. Many funders specifically support projects that are part of the “Open Science” initiative.
412 -
413 ->Can my data be too insignificant to share?
414 -
415 -No, there is no such thing as insignificant data. Data that is considered insignificant for a given topic, may have great significance for another. By making “insignificant” data publicly available, other researchers may find something interesting that was off-topic for your own purposes.
416 -
417 ->Can my data be easily misused if I share it?
418 -
419 -No, your data will be covered by a Creative Commons license of your choice. There are a variety of licenses available, enabling you to prevent use for specific purposes, e.g. commercial use.
420 -
421 ->Can I share my data before my paper is published?
422 -
423 -Yes, if you do not want to share your data before publishing the results in an article, you can publish your dataset with an embargo status. This will make it possible to find information about the data without making the data itself available, and give you a citeable DOI.
424 -
425 ->Can I lose my competitive edge if I share my data before I publish the associated paper?
426 -
427 -No, publishing your data does not mean that others can use it however they want. Use of your data will require citation, and by choosing an appropriate Creative Commons licence you decide what others are allowed to do with it. If you still feel worried, you can publish your data under embargo, and in this way delay the date of data release, but still make it possible for others to find the information about the data.
428 -
429 -
430 -----
431 -
432 -== (% style="color:#1a202c; font-family:inherit; font-size:29px" %)**The curation team: meet the curators**(%%) ==
433 -
434 434  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.
435 435  
436 436  The curators in EBRAINS are located in Oslo, Jülich, Trier and Paris. 
437 437  
438 438  
439 -**Located in Norway**
272 +**Located in Norway:**
440 440  
441 441  |(% style="width:303px" %)(((
442 442  [[image:My project2.jpg||height="209" width="167"]]
... ... @@ -486,7 +486,7 @@
486 486  )))| | |
487 487  
488 488  
489 -\\**Located in Germany**
322 +\\**Located in Germany:**
490 490  
491 491  |(% style="width:303px" %)(((
492 492  [[image:My project (2).jpg||height="209" width="167"]]
... ... @@ -497,36 +497,111 @@
497 497  Phd Student
498 498  Sensors and Cognitive Psychology (M. Sc.)(%%)
499 499  (% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)**Human-Computer Interaction**
500 -)))|(% style="width:303px" %)(((
501 -[[image:Lyuba.jpg||height="209" width="167"]]
333 +)))|(% style="width:328px" %)(((
334 +
502 502  
336 +
337 +
338 +
339 +
340 +
341 +
342 +
503 503  **Lyuba Zehl**
504 504  
505 505  (% class="small" %)Knowledge Systems Engineer
506 506  Dr. rer. nat. (Systems Neuroscience)(%%)
507 507  (% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)**Standard development, data & knowledge management, interdisciplinary communication, data analysis**
508 -)))|(% style="width:303px" %) |(% style="width:303px" %)
348 +)))|(% style="width:321px" %) |(% style="width:324px" %)
509 509  
510 510  ----
511 511  
352 +== **Add practical value to your shared data, model or software** ==
512 512  
513 513  
514 514  ----
515 515  
516 -== Contact ==
357 +=== **Showcase shared data, models or software in other services** ===
517 517  
518 -[[curation-support@ebrains.eu>>mailto:curation-support@ebrains.eu]]
359 +Below is a list of additional services that data, models or software shared via EBRAINS can benefit from. EBRAINS is continuously looking to increase the number of interoperable services.
519 519  
361 +
362 +|(% colspan="2" %)**Viewer for 2D images**
363 +|[[image:MIO_screenshot.PNG]]|Integrate image data with //the Mio viewer//: EBRAINS Multi-Image OpenSeadragon viewer provides an intuitive way of navigating high-resolution 2D image series. It has browser-based classic pan and zoom capabilities. A collection can be displayed as a filmstrip (Filmstrip Mode) or as a table (Collection Mode) with adjustable number of row and columns. See [[Mio viewer links available for this dataset>>https://search.kg.ebrains.eu/?category=Dataset&q=nr2f1#9677359c-73fa-4425-b8fa-3de794e9017a]] as an example. MioViewer user manual is found [[here>>https://multi-image-osd.readthedocs.io/en/latest/index.html]].
364 +|(% colspan="2" %)**Viewer for sequential atlas-registered 2D images with annotation options**
365 +|[[image:LZ_screenshot.PNG]]|Integrate atlas-registered 2D image data with //the LocaliZoom viewer//: The EBRAINS LocaliZoom serial section viewer displays series of registered 2D section images with atlas overlay, allowing the users to zoom into high-resolution images and have information about the brain regions. See the [[LocaliZoom links available for this dataset>>https://doi.org/10.25493/T686-7BX]] as an example. LocaliZoom user manual is found [[here>>https://localizoom.readthedocs.io/en/latest/index.html]].
366 +|(% colspan="2" %)**Interactive 3D atlas viewer with options for data visualization**
367 +|[[image:3Datlas_screenshot.PNG]]|Upload your data to the //Siibra-explorer//: The siibra-explorer is used for visualizing volumetric brain data in all the brain atlases provided by EBRAINS (Human, Monkey, Rat and Mouse). The siibra-explorer viewer uses siibra-api to enable navigation of brain region hierarchies, maps in different coordinate spaces, and linked regional data features. Furthermore, it is connected with the siibra toolsuite providing several analytical workflows. To learn more about how to register your data to atlases, read about the [[Atlas services on ebrains.eu>>https://ebrains.eu/services/atlases#Integratedatatoanatlas]].
368 +|(% colspan="2" %)**Use your research product in an interactive publication**
369 +|[[image:LivePaper_screenshot.PNG]]|Add your data, models or software to a// Live paper. //Read more about [[Live papers on ebrains.eu>>https://www.ebrains.eu/data/live-papers/live-papers]].
370 +
520 520  ----
521 521  
522 -== Affiliated laboratories ==
373 +==== **Add a tutorial or learning resource ** ====
523 523  
524 -//Institute of Basic Medical Sciences,** **University of Oslo, Norway (PI: Jan G. Bjaalie, Trygve B. Leergaard)//
375 +(% class="wikigeneratedid" id="H-LearningresourceA05Binformation5D" %)
376 +(% style="--darkreader-inline-color:#ffffff; color:#000000" %)//More information will follow//
525 525  
526 -//Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Germany (PI: Timo Dicksheid)//
527 527  
379 +==== **Create a workflow** ====
380 +
381 +(% class="wikigeneratedid" id="H-Workflows5Binformation5D" %)
382 +(% style="--darkreader-inline-color:#ffffff; color:#000000" %)//More information will follow//
383 +
528 528  ----
529 529  
386 +=== **The benefits of sharing data ** ===
387 +
388 +By sharing your data via EBRAINS, you gain access to the following benefits:
389 +
390 +[[image:image-20230324170841-3.png]]
391 +
392 +
393 +
394 +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.
395 +
396 +----
397 +
398 +=== **Frequently asked questions ** ===
399 +
400 +(((
401 +==== ====
402 +
403 +(((
404 +>Is the curation process time consuming and difficult?
405 +)))
406 +)))
407 +
408 +No, if communication is on a regular basis, we are able to finish curation within two weeks. Publishing your data naturally takes some effort but we will support you as much as possible.
409 +
410 +>Is sharing my data also beneficial for me or only for others?
411 +
412 +When you publish your data via EBRAINS, we provide comprehensive data management support and safe long term storage - all free of charge. Additionally, your data can be cited, just like a scientific journal article. Sharing your data may even lead to new funding opportunities. Many funders specifically support projects that are part of the “Open Science” initiative.
413 +
414 +>Can my data be too insignificant to share?
415 +
416 +No, there is no such thing as insignificant data. Data that is considered insignificant for a given topic, may have great significance for another. By making “insignificant” data publicly available, other researchers may find something interesting that was off-topic for your own purposes.
417 +
418 +>Can my data be easily misused if I share it?
419 +
420 +No, your data will be covered by a Creative Commons license of your choice. There are a variety of licenses available, enabling you to prevent use for specific purposes, e.g. commercial use.
421 +
422 +>Can I share my data before my paper is published?
423 +
424 +Yes, if you do not want to share your data before publishing the results in an article, you can publish your dataset with an embargo status. This will make it possible to find information about the data without making the data itself available, and give you a citeable DOI.
425 +
426 +>Can I lose my competitive edge if I share my data before I publish the associated paper?
427 +
428 +No, publishing your data does not mean that others can use it however they want. Use of your data will require citation, and by choosing an appropriate Creative Commons licence you decide what others are allowed to do with it. If you still feel worried, you can publish your data under embargo, and in this way delay the date of data release, but still make it possible for others to find the information about the data.
429 +
430 +
431 +----
432 +
433 +== Contact ==
434 +
435 +[[curation-support@ebrains.eu>>mailto:curation-support@ebrains.eu]]
436 +
437 +
530 530  == References ==
531 531  
532 532  {{putFootnotes/}}
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Data Curation