Wiki source code of Data Curation

Version 229.2 by abonard on 2025/06/03 10:55

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201.1	20	(% class="wikigeneratedid" id="HPublishingneurosciencedata2CmodelsandsoftwareviaEBRAINS" %)
	21	(% style="font-size:2em" %)Publishing neuroscience data, models and software via EBRAINS
10.1	22
146.1	23	(% class="wikigeneratedid" %)
146.2	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]].
146.1	25
10.1	26	{{box title="Contents"}}
	27	{{toc depth="3" start="2"/}}
	28	{{/box}}
	29
146.2	30	== Information to get started ==
10.1	31
220.1	32	[[REQUEST CURATION>>https://nettskjema.no/a/386195]] to share data, simulations, computational models, and software, - or to add a new version of an existing one.
147.2	33
146.2	34	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.
10.1	35
	36
171.1	37	(% class="box" style="text-align: center; font-size: 1.2em" %)
	38	(((
172.1	39	Search existing data, models and software in the [[EBRAINS Knowledge Graph>>https://kg.ebrains.eu/search/?facet_type[0]=Dataset]]
171.1	40	)))
146.2	41
	42
	43	EBRAINS accepts data from all modalities and from all species, as well as models, software, web services and metadata models (collectively referred to as research products) for sharing. You'll find detailed information about how to share each research product below.
	44
	45
	46	(% class="box infomessage" %)
	47	(((
	48	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.
	49	)))
	50
	51	(% class="box successmessage" %)
	52	(((
159.1	53	Particular needs? Contact us! The workflows for sharing can be modified for researchers or research groups aiming to frequently publish larger numbers of their research products through EBRAINS. Please contact the curation service team in such cases. Reach us at [[curation-support@ebrains.eu>>mailto:curation-support@ebrains.eu]]
146.2	54	)))
	55
10.1	56	----
	57
30.1	58	== The EBRAINS curation process ==
10.1	59
29.1	60	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.
10.1	61
30.1	62	>The EBRAINS curation process involves organising and annotating neuroscientific data to make the data discoverable and reusable.
10.1	63
30.1	64	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.
10.1	65
147.2	66	Curated data, models and software are made available in [[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 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 defined in [[openMINDS>>url:https://github.com/HumanBrainProject/openMINDS/wiki]].Data and models are linked to and discoverable via the species-specific [[EBRAINS siibra 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]].
34.1	67
147.2	68	The curation of data, models and software is different. Thus, below we explain the process for sharing for each research product separately.
47.3	69
212.1	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.
10.1	71
212.1	72
34.1	73	----
	74
147.3	75	=== Step by step - Data ===
10.1	76
	77
23.2	78	[[image:image-20230326054341-1.png]]
10.1	79
167.1	80	(% class="box floatinginfobox" id="share-data-infographic" %)
	81	(((
	82	(% style="text-align:center" %)
	83	//Download our infographic//
	84	//with all you need to know//
	85	//to share data on EBRAINS: //
	86	// //
227.1	87	[[~[~[image:image-20230324171114-2.png~\|~\|height="150" width="106"~]~]>>https://drive.ebrains.eu/f/dfd374b9b43a458192e9/]]
167.1	88	)))
36.1	89
147.8	90
10.1	91	==== 1. Provide some general information about your dataset ====
	92
173.1	93
	94
219.1	95	(% style="margin-right:10px" %)[[image:https://lh3.googleusercontent.com/zh7TvO6w04YGW9jIhfhmdT6CexdGs-AWOLfJXKRq7-tdHOu6ar1rOQx8o4rZevrjXqgPZ7-Ejv4b6X9XpgXuHpdUXi-mBTHIUnv5Vz-DktHt0sP-PZ3gE8XgZid3TV3swV1uTCBhHx11ge0pjP7RVxswGQ=s2048\|\|height="85px;" width="91px;"]](%%) Fill in the [[EBRAINS Curation Request Form>>https://nettskjema.no/a/386195]].
10.1	96
219.1	97	The form collects general 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 and follow up on incoming requests.
10.1	98
219.1	99	You will also be asked to fill in information related to ethics and regulatory compliance, so that we can evaluate whether we can ethically and legally share the data via EBRAINS (earlier, this was recorded via a [[separate form>>https://nettskjema.no/a/224765]]). See below for information about the ethical and legal aspects concerning sharing of human subject data.
147.3	100
	101
10.1	102	==== 2. Upload data ====
	103
200.1	104	(% class="box floatinginfobox" id="share-data-infographic" %)
	105	(((
	106	(% style="text-align:center" %)
	107	//Download our infographic//
	108	//with guidelines
	109	on data organization: //
10.1	110
227.1	111	[[~[~[image:image-20230621121014-1.png~\|~\|data-xwiki-image-style-alignment="center" height="150" width="106"~]~]>>https://drive.ebrains.eu/lib/f5cf4964-f095-49bd-8c34-e4ffda05a497/file/ebrains-infographic-data-organisation.pdf/]]
200.1	112	)))
	113
172.1	114	(% 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.
10.1	115
200.1	116	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.
151.1	117
172.1	118	(% 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).
10.1	119
176.1	120	Opt. 1. 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.
147.3	121
176.1	122	Opt. 2. 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.
147.3	123
	124
226.1	125	EBRAINS offers secure, long-term storage at FENIX Supercomputing Centres in Europe.
147.3	126
10.1	127	If a data collection is already uploaded elsewhere, we may link to the already existing repository.
	128
	129
160.1	130	==== 3. Submit metadata ====
147.8	131
	132
174.1	133	(% style="margin-right:10px" %)[[image:https://lh5.googleusercontent.com/WS4T2LhF9znWWChn3Z550agLrrb-KTWdYVsJSv0lh4cGjKbjuN1WV68WER9xkYqi1UqN7KYZz7bImYz3_TpOuTuvma7T192QUiUZoyJVPk1fj5NSDSQh_kpIeBufAOdDtsDRpPKK_P5EDPqRCTAaOTNyCw=s2048\|\|height="91px;" width="91px;"]](%%)Submit metadata using the [[EBRAINS Metadata Wizard>>https://ebrains-metadata-wizard.apps.hbp.eu/]] (opt. 1), or directly via the Knowledge Graph (opt. 2)
10.1	134
175.1	135	Opt. 1. Manually submit the minimal required metadata via the [[EBRAINS Metadata Wizard>>https://ebrains-metadata-wizard.apps.hbp.eu/]]. The minimal required metadata covers extended bibliographic information necessary to publish your dataset on EBRAINS. The submitted information, including uploaded files, will be sent to the Curation team automatically
10.1	136
175.1	137	Opt. 2. To go beyond the minimal required metadata, you can directly interact with the Knowledge Graph (KG) in your private space. Within the private space, you can upload metadata and interact with them, moreover you can connect your metadata to existing publicly accessible entries. Access to your private space is granted upon the initiation of the curation process. You can access your private space via:
147.3	138
	139	* Knowledge Graph Editor: This User Interface allows you to manually enter metadata into your KG space and validate metadata that are programmatically uploaded. The Editor contains a basic set of openMINDS metadata templates, but can be extended to the full openMINDS metadata model on request. Access is granted once the request is accepted.
	140	* [[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.
	141	* [[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.
	142
218.1	143	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.
147.3	144
	145
173.1	146	==== 4. Write a Data Descriptor ====
10.1	147
173.1	148
	149
175.1	150	(% style="margin-right:10px" %)[[image:https://lh4.googleusercontent.com/lMYEKOXzejbBydOdotWWteXQo7j363xRyntBGjcPZVEdtIU1CJYX7q1STpdr2JPZK4hpWWXk20UlkUOqDGL5kX6vnQVBSdrfUo6EGfXOwpuGq1Uygv0tTZJ0lRO6voJvg56QC2mufvjAcRXGfAKFOjtc6w=s2048\|\|height="94px;" width="94px;"]](%%)Write a data descriptor by filling in [[this template>>https://drive.ebrains.eu/f/a2e07c95b1a54090bbbc/?dl=1]].
10.1	151
151.1	152	The Data Descriptor is a document helping others interpret and reuse (and prevent misuse) of your data, and is critical to achieve a basic level of FAIR. The document will be uploaded in the repository of the data, shared as a PDF.
10.1	153
151.1	154	See our infographic about the data descriptor for inspiration or guidance.
10.1	155
151.1	156	Check out previous examples in the KG Search. See e.g., the data descriptor for the dataset "[[Anterogradely labeled axonal projections from the orbitofrontal cortex in rat>>https://doi.org/10.25493/2MX9-3XF]]".
147.3	157
10.1	158	Journal publications sufficiently describing the shared data, such as made available through [[Nature Scientific Data>>http://www.nature.com/sdata/about]], [[Elsevier Data in Brief>>http://www.journals.elsevier.com/data-in-brief/]], [[BMC Data note>>https://bmcresnotes.biomedcentral.com/submission-guidelines/preparing-your-manuscript/data-note]] and more, can replace the EBRAINS Data Descriptor.
	159
173.1	160
168.1	161	(% class="box floatinginfobox" id="data-descriptor-infographic" %)
	162	(((
	163	(% style="text-align:center" %)
200.1	164	//Download our infographic
	165	about the EBRAINS Data//
	166	//Descriptor//
168.1	167	// //
227.1	168	[[~[~[image:image-20230324171109-1.png~\|~\|height="150" width="106"~]~]>>https://drive.ebrains.eu/f/c1ccb78be52e4bdba7cf/]]
168.1	169	)))
10.1	170
173.1	171	==== 5. Preview and publish ====
10.1	172
	173
172.1	174	(% style="margin-right:10px" %)[[image:https://lh4.googleusercontent.com/XqT26Q4yWJK26cjtjhI4ToXoZZMxhT9LimG4Hk9mePxy0-KPKgpVIzcuiP5mOQowBgf2JjkrWUq2VbCmafWWZPJplEZALnFOlCZHLlQgzOx7fFwoBteyi_IlMLkPBS9vtOcdNIZ59HyLnQz4RsTQ0lUrSw=s2048\|\|height="91px;" width="91px;"]](%%)Preview and approve the release of your dataset.
173.1	175
172.1	176	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.
10.1	177
147.3	178
10.1	179
	180
	181	----
	182
	183	=== Step by Step - Models ===
	184
127.1	185
194.2	186	==== 1. Start early ====
	187
	188	It is not necessary to wait until you are ready to publish to register your model with EBRAINS.
	189
	190	By registering a model early in your project, you can take advantage of EBRAINS tools
	191	to keep track of simulations and to share them with your collaborators.
	192
	193	==== 2. Create/choose a Collab workspace ====
	194
	195	We use EBRAINS Collaboratory "collab" workspaces to help manage the model curation process.
	196
	197	In particular, we use collab membership (the "Team") to control who can view or edit your model metadata prior to publication.
	198
	199	It is up to you whether you create a new collab for each model, or reuse an existing collab
	200	(it is no problem to have multiple models associated with a single collab).
	201
	202	Collabs are also useful for storing simulation results, adding documentation for your model,
	203	and/or providing tutorials in Jupyter notebooks.
	204
195.1	205	==== 3. Upload code ====
194.2	206
195.1	207	We recommend storing model code and/or configuration files in an online Git repository, for example on GitHub.
	208	This repository should be public when you publish the model, but a private repository can be used for model development.
194.2	209
229.1	210	Alternatively, you can upload code to the Collab Drive (in this case, curators will copy it to a read-only Bucket upon publication) or Bucket storage.
194.2	211
221.1	212	==== 4. Submit metadata ====
10.1	213
195.1	214	We recommend submitting metadata using the Model Catalog app, installed in your collab.
10.1	215
195.1	216	To install it:
10.1	217
195.1	218	1. click the "+ Create" button
	219	1. in the "Create Page" form, add a title, such as "Model Catalog", and select "Community App", then click "Create"
	220	1. scroll down until you find the "Model Catalog" app, click "Select", then "Save & View"
	221
	222	You will then see a table of all the models and validation tests associated with this collab.
	223	If this is your first time using the app, the table will probably be empty.
	224	To add your model, click "+", fill in the form, then click "Add model".
	225
	226	As development of your model proceeds, you can easily register new versions of the code,
196.1	227	and new parameterizations, by clicking "Add new version".
195.1	228
221.1	229	If you prefer not to use the app, you can instead fill in the [[EBRAINS Curation Request Form>>https://nettskjema.no/a/386195]].,
195.1	230	and you will be contacted by e-mail with further instructions.
	231
195.2	232	==== 5. Provide a reference dataset ====
195.1	233
	234	Once you're ready to publish your model entry in the EBRAINS Knowledge Graph,
	235	we encourage you to provide a dataset containing the simulation results produced by your model,
	236	following the process under "Step by step - Data" above.
	237
	238	These reference data will be linked to the model, and will be helpful to anyone trying to
	239	reuse your model.
	240
	241	We will soon introduce a "Reproducible" badge for all models that include a reference dataset,
	242	and whose simulation results can be reproduced by an EBRAINS curator.
	243
	244	==== 6. Request publication, preview and publish ====
	245
	246	Until you request your model entry to be published in the EBRAINS Knowledge Graph,
	247	only members of the collab will be able to view the model entry, in the Model Catalog app
	248	or using the Model Validation Python client.
	249
195.2	250	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.
195.1	251
195.2	252	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.
195.1	253
	254
	255	Curators will then perform a number of checks:
	256
	257	1. Does the model description provide sufficient context to understand the purpose and use of the model?
	258	1. Does the code repository contain a licence file, explaining the conditions for reusing the code?
196.1	259	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.
195.1	260
	261	The curators will also take a snapshot of your model code.
	262
229.2	263	* 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"]] (via the updateSWH extension).
195.1	264	* 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.
	265
	266	Once this is done, you will be invited to review a preview of how the model entry will appear in the KG Search,
	267	and will have the opportunity to request modifications prior to approval and publication.
	268
10.1	269	----
	270
147.6	271	=== Step by Step - Software ===
10.1	272
222.1	273	We ask software developers to provide their metadata in the "CodeMeta" format. [[CodeMeta>>https://codemeta.github.io/]] is a common format for software metadata, supported by GitHub, Zenodo, FigShare, DataCite, and the US National Science Foundation.
147.5	274
222.1	275	1. Create a codemeta.json file for your software. There are several [[tools>>https://codemeta.github.io/tools/]] to help you do this, for example the [[CodeMeta generator>>https://codemeta.github.io/codemeta-generator]] app. Please fill in as many of the fields as possible.
	276	1. Place this file in the root folder of your code repository.
	277	1. Contact [[EBRAINS support>>https://www.ebrains.eu/contact/]] to request curation of your software, letting us know the URL of your code repository. If you need help hosting your code online, please also let us know.
	278	1. After a quality check, we integrate and publish the information contained in your codemeta.json file to the Knowledge Graph. Your software is then searchable and usable for the neuroscience community.
147.5	279
222.1	280	When you release a new version of your software, just update the codemeta.json file in your repository. We will check the repository on a regular basis, and if the version identifier has changed the Knowledge Graph will be updated accordingly.
147.5	281
10.1	282	----
	283
202.1	284	=== Sharing human subject data ===
	285
	286	(% class="box floatinginfobox" %)
	287	(((
	288	Human subject data that can be shared on EBRAINS:
	289	// //
	290	// - Post-mortem data//
	291	// - Aggregated data//
	292	// - Strongly pseudonymized or de-identified subject data//
	293	// with a legal basis for sharing (e.g. Informed Consent)//
	294	// //
	295
	296	(% class="small" %)
	297	//If you have human data that does not qualify as any of the above,//
	298	//please [[get in touch>>https://www.ebrains.eu/contact/]] and we will clarify the available options.//
	299	)))
	300
	301
	302	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]].
	303
	304	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).
	305
	306	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.
	307
	308	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.
	309
	310	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.
	311
	312	----
	313
152.1	314	== The openMINDS metadata framework ==
	315
193.1	316	(% class="box floatinginfobox" %)
	317	(((
227.1	318	[[~[~[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]]
193.1	319	)))
	320
219.1	321	openMINDS is a community-driven, open-source metadata framework for linked data, as used in graph database systems, such as the EBRAINS Knowledge Graph. It is composed of multiple metadata models with interlinked schemas, libraries of serviceable metadata instances, and supportive tooling (e.g., [[openMINDS Python>>https://github.com/openMetadataInitiative/openMINDS_Python]] or [[openMINDS Matlab>>https://github.com/openMetadataInitiative/openMINDS_MATLAB]]). A full documentation (for users and contributors) of the openMINDS framework can be found on [[ReadTheDocs>>https://openminds-documentation.readthedocs.io\|\|rel="noopener noreferrer" target="_blank"]].
152.1	322
	323	For feedback, requests, or contributions, please get in touch with the openMINDS development team via
	324
218.1	325	* [[support@openmetadatainitiative.org>>mailto:mailto:support@openmetadatainitiative.org]]
	326	* [[GitHub Issues>>https://github.com/openMetadataInitiative/openMINDS/issues]] (for metadata schemas)
	327	* [[GitHub Issues>>https://github.com/openMetadataInitiative/openMINDS_instances/issues]] (for metadata instances)
	328	* [[openMINDS Community Forum>>https://neurostars.org/t/openminds-community-forum-virtual]]
152.1	329
	330	----
	331
209.1	332	== Add practical value to your shared data, model or software ==
27.2	333
209.1	334
	335	=== Showcase shared data, models or software in other services ===
	336
	337	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.
	338
	339
	340	\|(% colspan="2" %)Viewer for 2D images
228.1	341	\|[[image:MIO_screenshot.PNG]]\|Integrate image data with //SeriesZoom viewer//: EBRAINS 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 [[viewer links available for this dataset>>https://search.kg.ebrains.eu/?category=Dataset&q=nr2f1#9677359c-73fa-4425-b8fa-3de794e9017a]] as an example.
209.1	342	\|(% colspan="2" %)Viewer for sequential atlas-registered 2D images with annotation options
	343	\|[[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]].
	344	\|(% colspan="2" %)Interactive 3D atlas viewer with options for data visualization
	345	\|[[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]].
	346	\|(% colspan="2" %)Use your research product in an interactive publication
	347	\|[[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]].
	348
	349	----
	350
	351	==== Add a tutorial or learning resource ====
	352
	353	(% class="wikigeneratedid" id="H-LearningresourceA05Binformation5D" %)
219.1	354	(% style="--darkreader-inline-color:#ffffff; color:#000000" %)//More information will follow//
209.1	355
	356
	357	==== Create a workflow ====
	358
	359	(% class="wikigeneratedid" id="H-Workflows5Binformation5D" %)
219.1	360	(% style="--darkreader-inline-color:#ffffff; color:#000000" %)//More information will follow//
209.1	361
	362	----
	363
213.1	364	== EBRAINS commits to the FAIR principles ==
	365
217.1	366	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.
213.1	367
214.1	368	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.
213.1	369
219.1	370	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: #1c1e1f;"]]: see our [[FAIR assessment of EBRAINS datasets>>doc:.FAIR assessment of EBRAINS datasets.WebHome]].
213.1	371
214.1	372
213.1	373	----
	374
209.1	375	== General benefits of sharing data ==
	376
	377	By sharing your data via EBRAINS, you gain access to the following benefits:
	378
	379	[[image:image-20230324170841-3.png]]
	380
	381
	382
216.1	383	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.
209.1	384
	385	----
	386
	387	== Frequently asked questions ==
	388
	389	>Is the curation process time consuming and difficult?
	390
	391	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.
	392
	393	>Is sharing my data also beneficial for me or only for others?
	394
	395	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.
	396
	397	>Can my data be too insignificant to share?
	398
	399	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.
	400
	401	>Can my data be easily misused if I share it?
	402
	403	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.
	404
	405	>Can I share my data before my paper is published?
	406
	407	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.
	408
	409	>Can I lose my competitive edge if I share my data before I publish the associated paper?
	410
	411	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.
	412
	413
10.1	414	== Contact ==
	415
	416	[[curation-support@ebrains.eu>>mailto:curation-support@ebrains.eu]]
	417
209.1	418	----
10.1	419
205.1	420	== Affiliated laboratories ==
	421
	422	//Institute of Basic Medical Sciences, University of Oslo, Norway (PI: Jan G. Bjaalie, Trygve B. Leergaard)//
	423
	424	//Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Germany (PI: Timo Dicksheid)//
	425
222.2	426	//Paris-Saclay Institute of Neuroscience, CNRS, Université Paris-Saclay, France (PI: Andrew P. Davison)//
	427
209.1	428	----
205.1	429
177.1	430	== References ==
	431
10.1	432	{{putFootnotes/}}