Summary

• Page properties (1 modified, 0 added, 0 removed)

Details

Page properties

Content

...	...	@@ -17,28 +17,28 @@
17	17	Search existing data, models and software in [[the EBRAINS Knowledge Graph Search>>https://kg.ebrains.eu/search/?facet_type[0]=Dataset]]
18	18
19	19
20		-----
21		-
22		-== ==
23		-
24		-
25	25	(% style="color:#e74c3c" %)Their comparability and
26	26
27		-(% style="color:#e74c3c" %)Sharing your data, models or code (research products) via EBRAINS makes it discoverable amongst other research products available in (%%)[[(% style="color:#e74c3c" %)the EBRAINS Knowledge Graph>>https://kg.ebrains.eu/]](%%). This is made possible by the highly flexible metadata framework describing neuroscience data in detail, [[(% style="color:#e74c3c" %)openMINDS>>https://github.com/HumanBrainProject/openMINDS]](%%). EBRAINS is gradually implementing interconnected tools and analysis workflows developed in the Human Brain Project (HBP) to further enhance the output from adding your dataset to the database.
	22	+(% style="color:#e74c3c" %)Sharing your data, models or code (research products) via EBRAINS makes it discoverable amongst other research products available in (%%)[[(% style="color:#e74c3c" %)the EBRAINS Knowledge Graph>>https://kg.ebrains.eu/]]. This is made possible by the highly flexible metadata framework describing neuroscience data in detail, (%%)[[(% style="color:#e74c3c" %)openMINDS>>https://github.com/HumanBrainProject/openMINDS]]. EBRAINS is gradually implementing interconnected tools and analysis workflows developed in the Human Brain Project (HBP) to further enhance the output from adding your dataset to the database.
28	28
29	29	----
30	30
31		-== **The EBRAINS data curation process** ==
	26	+== **The EBRAINS curation process** ==
32	32
33		-Neuroscience data are multimodal, heterogenous, and organised in different ways. All these diverse data need to be categorised and described in a standardised manner so that they can be effectively searched, compared, and analysed by using the tools and workflows on the EBRAINS platform. This effort is referred to as curation.
	28	+In EBRAINS, multimodal and heterogenous neuroscience data, models and software are categorised and described in a standardised manner so that they can be effectively searched, compared, and analysed. This effort is referred to as curation.
34	34
35		->The EBRAINS data curation process involves organising and annotating neuroscientific data to make the data discoverable and reusable.
	30	+>The EBRAINS curation process involves organising and annotating neuroscientific data to make the data discoverable and reusable.
36	36
	32	+Behind this process is the EBRAINS Curation team. Our mandate is to support you in sharing your data in line with the [[**FAIR principles**>>https://www.go-fair.org/fair-principles/]], whether you choose to describe only the key aspects of your data, or can invest in adding more detailed metadata.
37	37
38		-Our mandate is to support you in sharing your data in line with the [[**FAIR principles**>>https://www.go-fair.org/fair-principles/]], whether you choose to describe only the key aspects of your data, or can invest in adding more detailed metadata. 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.
	34	+(% class="box floatinginfobox" %)
	35	+(((
	36	+We strongly recommend to start preparing for data sharing as early as possible. With a structured data repository and adequate notes on how the data was acquired, you greatly minimize the effort required to publish your data. The time it takes to share data on EBRAINS heavily depends on on the engagement from the researcher and how well the data and metadata is prepared before-hand. **[[Contact us to prepare for sharing>>mailto:curation-support@ebrains.eu]]. **
	37	+)))
39	39
	39	+=== ===
40	40
41		-The time it takes to share data on EBRAINS heavily depends on on the engagement from the researcher and how well the data and metadata is prepared before-hand. We strongly recommend to start preparing for data sharing as early as possible. With a structured data repository and adequate notes on how the data was acquired, you greatly minimize the effort required to publish your data. **Want to learn more about how to Prepare to Share? **Contact us!
	41	+=== ===
42	42
43	43	=== Step by step - Experimental data ===
44	44
...	...	@@ -167,9 +167,10 @@
167	167	[[image:image-20230324170841-3.png]]
168	168
169	169
170		-We support you to better follow the FAIR^^ ^^guiding principles 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}}.
171	171
	171	+We support you to better follow the FAIR^^ ^^guiding principles 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.
172	172
	173	+
173	173	----
174	174
175	175	(% style="font-family:inherit" %) (% style="color:#1a202c; font-family:inherit; font-size:26px" %)**What can I share on EBRAINS? **