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edited by ingrreit
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1 +== Publishing data, models and software via EBRAINS ==
3 3  
3 +The aim of this collab is to provide you with all the information you need to publish your experimental data, simulations, computational models, and software via EBRAINS. Have you already published your data somewhere else? You can increase the exposure and impact of your shared dataset by also listing it on EBRAINS.
4 +
4 4  {{box title="**Contents**"}}
5 5  {{toc depth="3" start="2"/}}
6 6  {{/box}}
7 7  
8 -== Publishing data via EBRAINS ==
9 9  
10 -The aim of this collab is to provide you with all the information you need to publish your neuroscience data via the EBRAINS Knowledge Graph. By "neuroscience data," we mean experimental datasets collected from living organisms, but also simulations, computational models, and software. Have you already published your data somewhere else? You can increase the exposure and impact of your shared dataset by re-sharing its metadata via EBRAINS.
11 -
12 -
13 13  (% style="text-align: center;" %)
14 14  **Get started! **
15 15  
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17 17  **[[REQUEST CURATION>>https://nettskjema.no/a/277393#/]] **
18 18  
19 19  (% style="text-align: center;" %)
20 - Search existing data, models and code in [[the EBRAINS Knowledge Graph>>https://kg.ebrains.eu/search/?facet_type[0]=Dataset]]
17 + Search existing data, models and software in [[the EBRAINS Knowledge Graph Search>>https://kg.ebrains.eu/search/?facet_type[0]=Dataset]]
21 21  
22 22  
23 23  ----
24 24  
25 -=== **All neuroscience data are welcome** ===
22 +== **The EBRAINS curation process** ==
26 26  
27 -(% class="wikigeneratedid" id="H" %)
28 -[[image:image-20230324170829-2.png]]
24 +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. 
29 29  
30 -----
26 +>The EBRAINS curation process involves organising and annotating neuroscientific data to make the data discoverable and reusable.
31 31  
32 -=== **Benefits of sharing data ** ===
33 33  
34 -By sharing your data via EBRAINS, you gain access to the following benefits:
29 +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.
35 35  
36 -[[image:image-20230324170841-3.png]]
37 37  
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33 +(((
34 +**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 for personalised guidance on how to prepare for sharing>>mailto:curation-support@ebrains.eu]]. **
35 +)))
38 38  
39 39  
40 -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}}.
41 41  
42 -----
43 43  
44 -== **What is curation?** ==
45 45  
46 ->The EBRAINS data curation process involves organising and annotating neuroscientific data to make the data discoverable and reusable.
47 47  
48 -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 integrated tools and workflows on the EBRAINS platform. This effort is referred to as curation.
49 49  
50 -
51 -Sharing your data, models or code via EBRAINS makes your data discoverable amongst other neuroscience research products available in [[the EBRAINS Knowledge Graph>>https://kg.ebrains.eu/]]. The data are easily discoverable in our online search engine: the [[EBRAINS Knowledge Graph Search>>https://search.kg.ebrains.eu/]] and can also be accessed programmatically. This search is made possible by the integration of the Knowledge Graph with a highly flexible metadata framework describing neuroscience data in detail, [[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.
52 -
53 53  ----
54 54  
55 -== **The process** ==
56 -
57 -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.
58 -
59 -
60 -Data, models and code are integrated into the [[EBRAINS Knowledge Graph>>url:https://kg.ebrains.eu/]] by using interoperable metadata schemas as defined in [[openMINDS>>url:https://github.com/HumanBrainProject/openMINDS/wiki]]. This makes the data and metadata discoverable in the [[KG Search>>url:https://search.kg.ebrains.eu/]] and programmatically via the [[KG API>>url:https://docs.kg.ebrains.eu/8387ccd27a186dea3dd0b949dc528842/api_endpoints.html]].
61 -
62 -Data and models are linked to and discoverable via the species-specific [[EBRAINS Interactive Atlas Viewer>>url:https://ebrains.eu/services/atlases/brain-atlases]] by using interoperable metadata schemas as defined in [[SANDS>>url:https://github.com/HumanBrainProject/SANDS/wiki]].
63 -
64 -
65 -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!
66 -
67 67  === Step by step - Experimental data ===
68 68  
69 69  
70 70  [[image:image-20230326054341-1.png]]
71 71  
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51 +==== ====
52 +
72 72  ==== **1. Provide some general information about your dataset** ====
73 73  
74 74  The [[Curation request form>>https://nettskjema.no/a/277393#/]] collects preliminary information about your data, allowing us to assess whether the dataset fits within the scope of EBRAINS. The submission generates a curation ID allowing us to track the case.
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80 80  
81 81  EBRAINS offers secure, long-term storage at [[CSCS Swiss National Supercomputing Centre>>url:https://www.cscs.ch/]], with currently no upper limit of storage capacity. The data must be consistently structured prior to upload. 
82 82  
83 -For smaller datasets with a reasonable amount of files, we recommend using the **Collab-Bucket solution (drag-and-drop)**. A Collab Bucket must first be assigned to a dataset, which happens when a datasets is accepted for sharing.
64 +For smaller datasets with a reasonable amount of files, we recommend using the Collab-Bucket solution (drag-and-drop). A Collab Bucket must first be assigned to a dataset, which happens when a datasets is accepted for sharing.
84 84  
85 -For larger datasets or datasets with a large amount of files, we recommend using a **programmatic approach**. The [[python script>>https://github.com/eapapp/ebrains-data-storage/tree/main/data-proxy]] is interactive and does not require any additional programming.
66 +For larger datasets or datasets with a large amount of files, we recommend using a programmatic approach. The [[python script>>https://github.com/eapapp/ebrains-data-storage/tree/main/data-proxy]] is interactive and does not require any additional programming.
86 86  
87 87  
88 88  If a data collection is already uploaded elsewhere, we may link to the already existing repository.
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133 133  
134 134  **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.
135 135  \\**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.
136 -\\**Human Data Gateway, Background**
137 -HDG was introduced in February 2021 and developed across multiple teams in the HBP. The initiative to create the service and the initial design originated from EBRAINS Curation in close collaboration with the Data compliance team and the HBP Data Governance Working Group. HDG is a response to the needs of multiple data providers who are bringing data of human origin to EBRAINS. HDG covers the sharing of a limited range of data of human origin, i.e., data without direct identifiers and with very few indirect identifiers (strongly pseudonymized, de-identified). It 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.
117 +\\The Human Data Gateway (HDG) was introduced in February 2021 and developed across multiple teams in the HBP. The initiative to create the service and the initial design originated from EBRAINS Curation in close collaboration with the Data compliance team and the HBP Data Governance Working Group. HDG is a response to the needs of multiple data providers who are bringing data of human origin to EBRAINS. HDG covers the sharing of a limited range of data of human origin, i.e., data without direct identifiers and with very few indirect identifiers (strongly pseudonymized, de-identified). It 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.
138 138  
139 139  
140 140  ----
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170 170  
171 171  ----
172 172  
153 +=== Output / result, when you've completed the curation process, what do you get ===
154 +
155 +Curated data, models and software are made available in the [[the EBRAINS Knowledge Graph>>https://kg.ebrains.eu/]]. This makes the data and metadata discoverable in the [[Knowledge Graph Search>>url:https://search.kg.ebrains.eu/]] and programmatically via the [[Knowledge Graph API>>url:https://docs.kg.ebrains.eu/8387ccd27a186dea3dd0b949dc528842/api_endpoints.html]]. The data, models and software are integrated in the EBRAINS Knowledge Graph by interoperable metadata schemas as defined in [[openMINDS>>url:https://github.com/HumanBrainProject/openMINDS/wiki]].
156 +
157 +Data and models are linked to and discoverable via the species-specific [[EBRAINS Interactive Atlas Viewer>>url:https://ebrains.eu/services/atlases/brain-atlases]] by using interoperable metadata schemas as defined in [[SANDS>>url:https://github.com/HumanBrainProject/SANDS/wiki]].
158 +
159 +----
160 +
173 173  == **Resources for researchers looking to share data** ==
174 174  
175 175  Below you can find some resources that can come in handy if you are looking to share data via EBRAINS, or in general.
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176 176  
177 177  ----
178 178  
167 +=== **Why should I share data?** ===
168 +
169 +(% style="color:#e74c3c" %)[EDIT required]
170 +
171 +(% style="color:#e74c3c" %)Sharing your data, models or code (research products) via EBRAINS makes it discoverable amongst other research products available in the [[EBRAINS Knowledge Graph>>https://kg.ebrains.eu/]]. This is made possible by the highly flexible metadata framework describing neuroscience data in detail. 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.
172 +
173 +
174 +By sharing your data via EBRAINS, you gain access to the following benefits:
175 +
176 +[[image:image-20230324170841-3.png]]
177 +
178 +
179 +
180 +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.
181 +
182 +
183 +----
184 +
185 +(% style="font-family:inherit" %) (% style="color:#1a202c; font-family:inherit; font-size:26px" %)**What can I share on EBRAINS? **
186 +
187 +(% class="wikigeneratedid" id="H" %)
188 +[[image:image-20230324170829-2.png]]
189 +
190 +
191 +----
192 +
179 179  === **Useful information about sharing of experimental data on EBRAINS ** ===
180 180  
181 181