Wiki source code of Data Curation

Version 225.1 by adavison on 2024/07/05 18:54

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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	// //
168.1	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
200.1	111	(% style="text-align:center" %)
	112	[[[[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/]]
	113	)))
	114
172.1	115	(% 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	116
200.1	117	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	118
172.1	119	(% 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	120
176.1	121	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	122
176.1	123	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	124
	125
	126	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.
	127
10.1	128	If a data collection is already uploaded elsewhere, we may link to the already existing repository.
	129
	130
160.1	131	==== 3. Submit metadata ====
147.8	132
	133
174.1	134	(% 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	135
175.1	136	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	137
175.1	138	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	139
	140	* 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.
	141	* [[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.
	142	* [[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.
	143
218.1	144	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	145
	146
173.1	147	==== 4. Write a Data Descriptor ====
10.1	148
173.1	149
	150
175.1	151	(% 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	152
151.1	153	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	154
151.1	155	See our infographic about the data descriptor for inspiration or guidance.
10.1	156
151.1	157	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	158
10.1	159	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.
	160
173.1	161
168.1	162	(% class="box floatinginfobox" id="data-descriptor-infographic" %)
	163	(((
	164	(% style="text-align:center" %)
200.1	165	//Download our infographic
	166	about the EBRAINS Data//
	167	//Descriptor//
168.1	168	// //
	169	[[[[image:image-20230324171109-1.png\|\|height="150" width="106"]]>>https://drive.ebrains.eu/f/c1ccb78be52e4bdba7cf/]]
	170	)))
10.1	171
173.1	172	==== 5. Preview and publish ====
10.1	173
	174
172.1	175	(% 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	176
172.1	177	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	178
147.3	179
10.1	180
	181
	182	----
	183
	184	=== Step by Step - Models ===
	185
127.1	186
194.2	187	==== 1. Start early ====
	188
	189	It is not necessary to wait until you are ready to publish to register your model with EBRAINS.
	190
	191	By registering a model early in your project, you can take advantage of EBRAINS tools
	192	to keep track of simulations and to share them with your collaborators.
	193
	194	==== 2. Create/choose a Collab workspace ====
	195
	196	We use EBRAINS Collaboratory "collab" workspaces to help manage the model curation process.
	197
	198	In particular, we use collab membership (the "Team") to control who can view or edit your model metadata prior to publication.
	199
	200	It is up to you whether you create a new collab for each model, or reuse an existing collab
	201	(it is no problem to have multiple models associated with a single collab).
	202
	203	Collabs are also useful for storing simulation results, adding documentation for your model,
	204	and/or providing tutorials in Jupyter notebooks.
	205
195.1	206	==== 3. Upload code ====
194.2	207
195.1	208	We recommend storing model code and/or configuration files in an online Git repository, for example on GitHub.
	209	This repository should be public when you publish the model, but a private repository can be used for model development.
194.2	210
195.1	211	Alternatively, you can upload code to the Collab Drive or Bucket storage.
194.2	212
221.1	213	==== 4. Submit metadata ====
10.1	214
195.1	215	We recommend submitting metadata using the Model Catalog app, installed in your collab.
10.1	216
195.1	217	To install it:
10.1	218
195.1	219	1. click the "+ Create" button
	220	1. in the "Create Page" form, add a title, such as "Model Catalog", and select "Community App", then click "Create"
	221	1. scroll down until you find the "Model Catalog" app, click "Select", then "Save & View"
	222
	223	You will then see a table of all the models and validation tests associated with this collab.
	224	If this is your first time using the app, the table will probably be empty.
	225	To add your model, click "+", fill in the form, then click "Add model".
	226
	227	As development of your model proceeds, you can easily register new versions of the code,
196.1	228	and new parameterizations, by clicking "Add new version".
195.1	229
221.1	230	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	231	and you will be contacted by e-mail with further instructions.
	232
195.2	233	==== 5. Provide a reference dataset ====
195.1	234
	235	Once you're ready to publish your model entry in the EBRAINS Knowledge Graph,
	236	we encourage you to provide a dataset containing the simulation results produced by your model,
	237	following the process under "Step by step - Data" above.
	238
	239	These reference data will be linked to the model, and will be helpful to anyone trying to
	240	reuse your model.
	241
	242	We will soon introduce a "Reproducible" badge for all models that include a reference dataset,
	243	and whose simulation results can be reproduced by an EBRAINS curator.
	244
	245	==== 6. Request publication, preview and publish ====
	246
	247	Until you request your model entry to be published in the EBRAINS Knowledge Graph,
	248	only members of the collab will be able to view the model entry, in the Model Catalog app
	249	or using the Model Validation Python client.
	250
195.2	251	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	252
195.2	253	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	254
	255
	256	Curators will then perform a number of checks:
	257
	258	1. Does the model description provide sufficient context to understand the purpose and use of the model?
	259	1. Does the code repository contain a licence file, explaining the conditions for reusing the code?
196.1	260	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	261
	262	The curators will also take a snapshot of your model code.
	263
198.1	264	* 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"]].
195.1	265	* 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.
	266
	267	Once this is done, you will be invited to review a preview of how the model entry will appear in the KG Search,
	268	and will have the opportunity to request modifications prior to approval and publication.
	269
10.1	270	----
	271
147.6	272	=== Step by Step - Software ===
10.1	273
222.1	274	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	275
222.1	276	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.
	277	1. Place this file in the root folder of your code repository.
	278	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.
	279	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	280
222.1	281	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	282
10.1	283	----
	284
202.1	285	=== Sharing human subject data ===
	286
	287	(% class="box floatinginfobox" %)
	288	(((
	289	Human subject data that can be shared on EBRAINS:
	290	// //
	291	// - Post-mortem data//
	292	// - Aggregated data//
	293	// - Strongly pseudonymized or de-identified subject data//
	294	// with a legal basis for sharing (e.g. Informed Consent)//
	295	// //
	296
	297	(% class="small" %)
	298	//If you have human data that does not qualify as any of the above,//
	299	//please [[get in touch>>https://www.ebrains.eu/contact/]] and we will clarify the available options.//
	300	)))
	301
	302
	303	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]].
	304
	305	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).
	306
	307	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.
	308
	309	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.
	310
	311	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.
	312
	313	----
	314
152.1	315	== The openMINDS metadata framework ==
	316
193.1	317	(% class="box floatinginfobox" %)
	318	(((
	319	[[[[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]]
	320	)))
	321
219.1	322	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	323
	324	For feedback, requests, or contributions, please get in touch with the openMINDS development team via
	325
218.1	326	* [[support@openmetadatainitiative.org>>mailto:mailto:support@openmetadatainitiative.org]]
	327	* [[GitHub Issues>>https://github.com/openMetadataInitiative/openMINDS/issues]] (for metadata schemas)
	328	* [[GitHub Issues>>https://github.com/openMetadataInitiative/openMINDS_instances/issues]] (for metadata instances)
	329	* [[openMINDS Community Forum>>https://neurostars.org/t/openminds-community-forum-virtual]]
152.1	330
	331	----
	332
209.1	333	== Add practical value to your shared data, model or software ==
27.2	334
209.1	335
	336	=== Showcase shared data, models or software in other services ===
	337
	338	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.
	339
	340
	341	\|(% colspan="2" %)Viewer for 2D images
	342	\|[[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]].
	343	\|(% colspan="2" %)Viewer for sequential atlas-registered 2D images with annotation options
	344	\|[[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]].
	345	\|(% colspan="2" %)Interactive 3D atlas viewer with options for data visualization
	346	\|[[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]].
	347	\|(% colspan="2" %)Use your research product in an interactive publication
	348	\|[[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]].
	349
	350	----
	351
	352	==== Add a tutorial or learning resource ====
	353
	354	(% class="wikigeneratedid" id="H-LearningresourceA05Binformation5D" %)
219.1	355	(% style="--darkreader-inline-color:#ffffff; color:#000000" %)//More information will follow//
209.1	356
	357
	358	==== Create a workflow ====
	359
	360	(% class="wikigeneratedid" id="H-Workflows5Binformation5D" %)
219.1	361	(% style="--darkreader-inline-color:#ffffff; color:#000000" %)//More information will follow//
209.1	362
	363	----
	364
213.1	365	== EBRAINS commits to the FAIR principles ==
	366
217.1	367	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	368
214.1	369	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	370
219.1	371	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	372
214.1	373
213.1	374	----
	375
209.1	376	== General benefits of sharing data ==
	377
	378	By sharing your data via EBRAINS, you gain access to the following benefits:
	379
	380	[[image:image-20230324170841-3.png]]
	381
	382
	383
216.1	384	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	385
	386	----
	387
	388	== Frequently asked questions ==
	389
	390	>Is the curation process time consuming and difficult?
	391
	392	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.
	393
	394	>Is sharing my data also beneficial for me or only for others?
	395
	396	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.
	397
	398	>Can my data be too insignificant to share?
	399
	400	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.
	401
	402	>Can my data be easily misused if I share it?
	403
	404	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.
	405
	406	>Can I share my data before my paper is published?
	407
	408	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.
	409
	410	>Can I lose my competitive edge if I share my data before I publish the associated paper?
	411
	412	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.
	413
	414
	415	----
	416
219.1	417	== (% style="--darkreader-inline-color:#f1ede6; color:#1a202c; font-family:inherit; font-size:29px" %)The curation team: meet the curators(%%) ==
209.1	418
147.4	419	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.
27.2	420
147.4	421	The curators in EBRAINS are located in Oslo, Jülich, Trier and Paris.
	422
55.1	423
203.1	424	Located in Norway
55.1	425
98.1	426	\|(% style="width:303px" %)(((
113.1	427	[[image:My project2.jpg\|\|height="209" width="167"]]
97.2	428
105.1	429	Archana Golla
	430
111.1	431	(% class="small" %)Curation Scientist
116.1	432	Neuroscience (PhD)(%%)
219.1	433	(% class="small" style="--darkreader-inline-color:#cac2b7; color:#4a5568" %)Behavioral neuroscience and microscopy
105.1	434	)))\|(% style="width:303px" %)(((
142.2	435	[[image:Camilla.jpg\|\|alt="My project.jpg" height="209" width="167"]]
98.1	436
122.1	437	Camilla H. Blixhavn
105.1	438
122.1	439	(% class="small" %)Curation Scientist,
	440	Phd Student
	441	Neuroscience (M. Sc.)(%%)
219.1	442	(% class="small" style="--darkreader-inline-color:#cac2b7; color:#4a5568" %)Neuroanatomy and data integration
126.1	443	)))\|(% style="width:303px" %)(((
124.1	444	[[image:My project (1).jpg\|\|height="209" width="167"]]
105.1	445
	446	Ingrid Reiten
	447
111.1	448	(% class="small" %)Curation Scientist,
112.1	449	Phd Student
117.1	450	Neuroscience (M. Sc.)(%%)
219.1	451	(% class="small" style="--darkreader-inline-color:#cac2b7; color:#4a5568" %)Neuroanatomy and structural connectivity
126.1	452	)))\|(% style="width:303px" %)(((
124.1	453	[[image:My project1.jpg\|\|height="209" width="167"]]
105.1	454
122.1	455	Sophia Pieschnik
105.1	456
122.1	457	(% class="small" %)Curation Scientist
	458	Neurocognitive Psychology (M. Sc.)(%%)
219.1	459	(% class="small" style="--darkreader-inline-color:#cac2b7; color:#4a5568" %)Neuroimaging
123.1	460	)))
72.1	461
143.2	462	\|(% style="width:303px" %)(((
142.2	463	[[image:My project.jpg\|\|height="209" width="167"]]
141.2	464
142.2	465	Heidi Kleven
141.2	466
142.2	467	(% class="small" %)Curation Scientist,
	468	Phd Student
	469	Neuroscience (M. Sc.)(%%)
219.1	470	(% class="small" style="--darkreader-inline-color:#cac2b7; color:#4a5568" %)Neuroanatomy and brain atlases
142.2	471	)))\| \| \|
	472
141.2	473
203.1	474	\\Located in Germany
72.1	475
143.2	476	\|(% style="width:303px" %)(((
115.1	477	[[image:My project (2).jpg\|\|height="209" width="167"]]
72.1	478
	479	Jan Gündling
	480
143.2	481	(% class="small" %)Curation Scientist,
131.2	482	Phd Student
117.1	483	Sensors and Cognitive Psychology (M. Sc.)(%%)
219.1	484	(% class="small" style="--darkreader-inline-color:#cac2b7; color:#4a5568" %)Human-Computer Interaction
198.1	485	)))\|(% style="width:303px" %)(((
	486	[[image:Lyuba.jpg\|\|height="209" width="167"]]
72.1	487
143.2	488	Lyuba Zehl
	489
	490	(% class="small" %)Knowledge Systems Engineer
	491	Dr. rer. nat. (Systems Neuroscience)(%%)
219.1	492	(% class="small" style="--darkreader-inline-color:#cac2b7; color:#4a5568" %)Standard development, data & knowledge management, interdisciplinary communication, data analysis
198.1	493	)))\|(% style="width:303px" %) \|(% style="width:303px" %)
143.2	494
27.2	495	----
	496
10.1	497
	498
147.6	499	----
58.1	500
10.1	501	== Contact ==
	502
	503	[[curation-support@ebrains.eu>>mailto:curation-support@ebrains.eu]]
	504
209.1	505	----
10.1	506
205.1	507	== Affiliated laboratories ==
	508
	509	//Institute of Basic Medical Sciences, University of Oslo, Norway (PI: Jan G. Bjaalie, Trygve B. Leergaard)//
	510
	511	//Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Germany (PI: Timo Dicksheid)//
	512
222.2	513	//Paris-Saclay Institute of Neuroscience, CNRS, Université Paris-Saclay, France (PI: Andrew P. Davison)//
	514
209.1	515	----
205.1	516
177.1	517	== References ==
	518
10.1	519	{{putFootnotes/}}