Wiki source code of Data Curation

Version 214.1 by ingrreit on 2023/09/27 16:22

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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
147.2	32	[[REQUEST CURATION>>https://nettskjema.no/a/277393#/]] to share data, simulations, computational models, and software, - or to add a new version of an existing one.
	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
172.1	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 [[Curation request form>>https://nettskjema.no/a/277393#/]].
10.1	96
151.1	97	This form 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.
10.1	98
147.3	99
172.1	100	(% style="margin-right:10px" %)[[image:https://lh6.googleusercontent.com/yw442oS6BwZOlY-_0BoVxyCW3DrdcJ5ogCes92iOD16_rgNEVk56aNMDaVWXFfBLYv24bHzmGgBF9wg0szjH70xzuRTqxoQAeuy3knNO7axCHoyZDXwtyTcMgFnYwbOYxOT29LK-zchrUKLW6Mle93kOkQ=s2048\|\|height="94px;" width="94px;"]](%%)Fill in the [[Ethics and Regulatory compliance form>>https://nettskjema.no/a/224765]].
147.3	101
151.1	102	This form collects the necessary information needed for us to evaluate whether we can ethically and legally share the data via EBRAINS.
	103
158.1	104	See below for information about the ethical and legal aspects concerning sharing of human subject data.
151.1	105
158.1	106
10.1	107	==== 2. Upload data ====
	108
200.1	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: //
10.1	115
200.1	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
172.1	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.
10.1	121
200.1	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.
151.1	123
172.1	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).
10.1	125
176.1	126	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	127
176.1	128	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	129
	130
	131	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.
	132
10.1	133	If a data collection is already uploaded elsewhere, we may link to the already existing repository.
	134
	135
160.1	136	==== 3. Submit metadata ====
147.8	137
	138
174.1	139	(% 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	140
175.1	141	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	142
175.1	143	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	144
	145	* 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.
	146	* [[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.
	147	* [[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.
	148
	149	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/lib/47995dbc-f576-4008-a76c-eefbfd818529/file/ebrains-minimum-required-metadata.xlsx]] on EBRAINS.
	150
	151
173.1	152	==== 4. Write a Data Descriptor ====
10.1	153
173.1	154
	155
175.1	156	(% 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	157
151.1	158	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	159
151.1	160	See our infographic about the data descriptor for inspiration or guidance.
10.1	161
151.1	162	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	163
10.1	164	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.
	165
173.1	166
168.1	167	(% class="box floatinginfobox" id="data-descriptor-infographic" %)
	168	(((
	169	(% style="text-align:center" %)
200.1	170	//Download our infographic
	171	about the EBRAINS Data//
	172	//Descriptor//
168.1	173	// //
	174	[[[[image:image-20230324171109-1.png\|\|height="150" width="106"]]>>https://drive.ebrains.eu/f/c1ccb78be52e4bdba7cf/]]
	175	)))
10.1	176
173.1	177	==== 5. Preview and publish ====
10.1	178
	179
172.1	180	(% 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	181
172.1	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.
10.1	183
147.3	184
10.1	185
	186
	187	----
	188
	189	=== Step by Step - Models ===
	190
127.1	191
194.2	192	==== 1. Start early ====
	193
	194	It is not necessary to wait until you are ready to publish to register your model with EBRAINS.
	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
	199	==== 2. Create/choose a Collab workspace ====
	200
	201	We use EBRAINS Collaboratory "collab" workspaces to help manage the model curation process.
	202
	203	In particular, we use collab membership (the "Team") to control who can view or edit your model metadata prior to publication.
	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).
	207
	208	Collabs are also useful for storing simulation results, adding documentation for your model,
	209	and/or providing tutorials in Jupyter notebooks.
	210
195.1	211	==== 3. Upload code ====
194.2	212
195.1	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.
194.2	215
195.1	216	Alternatively, you can upload code to the Collab Drive or Bucket storage.
194.2	217
195.1	218	==== 4.Submit metadata ====
10.1	219
195.1	220	We recommend submitting metadata using the Model Catalog app, installed in your collab.
10.1	221
195.1	222	To install it:
10.1	223
195.1	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"
	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,
196.1	233	and new parameterizations, by clicking "Add new version".
195.1	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
195.2	238	==== 5. Provide a reference dataset ====
195.1	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
195.2	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.
195.1	257
195.2	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.
195.1	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?
196.1	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.
195.1	266
	267	The curators will also take a snapshot of your model code.
	268
198.1	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"]].
195.1	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
10.1	275	----
	276
147.6	277	=== Step by Step - Software ===
10.1	278
127.1	279
170.1	280	(% class="box floatinginfobox" id="software-curation-infographic" %)
	281	(((
	282	(% style="text-align:center" %)
	283	//Software curation at a glance//
	284	// //
	285	[[[[image:Thumb2.png\|\|alt="EBRAINS-Share-Software.pdf" height="287" width="197"]]>>attach:EBRAINS-Share-Software-4.pdf]]
	286	)))
10.1	287
170.1	288	(% style="margin-left:15px" %)[[[[image:Screenshot 2023-06-06 1122082.png\|\|alt="swc-flow.png" height="136" width="637"]]>>https://www.ebrains.eu/tools/ebrains-curation-request-form\|\|rel="noopener noreferrer" target="_blank"]]
130.1	289
170.1	290	1. Fill in the [[request form>>https://www.ebrains.eu/tools/ebrains-curation-request-form]]. You'll be contacted by a curator with further instructions. In these instructions, you will find the links to your software and software version entries in the Knowledge Graph.
	291	1. Enter the metadata of your software in your private space of the [[Knowledge Graph Editor>>url:https://editor.kg.ebrains.eu/]] by using the links provided by the curator. Please provide the metadata for your software as complete as possible. This makes it easier for users to find and use your software. If you have questions feel free to contact the curation support. After you have finished editing your entries, please let the curators know by replying to your ticket. We curate your metadata and get back to you, if necessary.
	292	1. After a quality check, we integrate and publish the information to the Knowledge Graph. Your software is then searchable and usable for the neuroscience community.
147.5	293
	294	If you want to add a new version to an already curated software, please request this via the [[curation request form>>https://nettskjema.no/a/277393]].
	295
170.1	296	For more information, visit our [[Guide to Software Curation in the EBRAINS Knowledge Graph>>url:https://wiki.ebrains.eu/bin/view/Collabs/swc-guide]] or see our infographic on the right.
147.5	297
	298
10.1	299	----
	300
202.1	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
152.1	331	== The openMINDS metadata framework ==
	332
193.1	333	(% class="box floatinginfobox" %)
	334	(((
	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]]
	336	)))
	337
152.1	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]].
	339
	340	For feedback, requests, or contributions, please get in touch with the openMINDS development team via
	341
	342	* the support-email: [[openminds@ebrains.eu>>path:mailto:openminds@ebrains.eu]]
	343	* the [[GitHub issue tracker>>url:https://github.com/HumanBrainProject/openMINDS/issues]]
	344	* the INCF NeuroStars [[openMINDS Community Forum>>url:https://neurostars.org/t/openminds-community-forum-virtual/20156]]
	345
	346	----
	347
209.1	348	== Add practical value to your shared data, model or software ==
27.2	349
209.1	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
213.1	380	== EBRAINS commits to the FAIR principles ==
	381
214.1	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.
213.1	383
214.1	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.
213.1	385
214.1	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);"]]:
213.1	387
214.1	388
213.1	389	----
	390
209.1	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
147.4	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.
27.2	435
147.4	436	The curators in EBRAINS are located in Oslo, Jülich, Trier and Paris.
	437
55.1	438
203.1	439	Located in Norway
55.1	440
98.1	441	\|(% style="width:303px" %)(((
113.1	442	[[image:My project2.jpg\|\|height="209" width="167"]]
97.2	443
105.1	444	Archana Golla
	445
111.1	446	(% class="small" %)Curation Scientist
116.1	447	Neuroscience (PhD)(%%)
166.1	448	(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)Behavioral neuroscience and microscopy
105.1	449	)))\|(% style="width:303px" %)(((
142.2	450	[[image:Camilla.jpg\|\|alt="My project.jpg" height="209" width="167"]]
98.1	451
122.1	452	Camilla H. Blixhavn
105.1	453
122.1	454	(% class="small" %)Curation Scientist,
	455	Phd Student
	456	Neuroscience (M. Sc.)(%%)
166.1	457	(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)Neuroanatomy and data integration
126.1	458	)))\|(% style="width:303px" %)(((
124.1	459	[[image:My project (1).jpg\|\|height="209" width="167"]]
105.1	460
	461	Ingrid Reiten
	462
111.1	463	(% class="small" %)Curation Scientist,
112.1	464	Phd Student
117.1	465	Neuroscience (M. Sc.)(%%)
166.1	466	(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)Neuroanatomy and structural connectivity
126.1	467	)))\|(% style="width:303px" %)(((
124.1	468	[[image:My project1.jpg\|\|height="209" width="167"]]
105.1	469
122.1	470	Sophia Pieschnik
105.1	471
122.1	472	(% class="small" %)Curation Scientist
	473	Neurocognitive Psychology (M. Sc.)(%%)
166.1	474	(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)Neuroimaging
123.1	475	)))
72.1	476
143.2	477	\|(% style="width:303px" %)(((
142.2	478	[[image:My project.jpg\|\|height="209" width="167"]]
141.2	479
142.2	480	Heidi Kleven
141.2	481
142.2	482	(% class="small" %)Curation Scientist,
	483	Phd Student
	484	Neuroscience (M. Sc.)(%%)
166.1	485	(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)Neuroanatomy and brain atlases
142.2	486	)))\| \| \|
	487
141.2	488
203.1	489	\\Located in Germany
72.1	490
143.2	491	\|(% style="width:303px" %)(((
115.1	492	[[image:My project (2).jpg\|\|height="209" width="167"]]
72.1	493
	494	Jan Gündling
	495
143.2	496	(% class="small" %)Curation Scientist,
131.2	497	Phd Student
117.1	498	Sensors and Cognitive Psychology (M. Sc.)(%%)
166.1	499	(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)Human-Computer Interaction
198.1	500	)))\|(% style="width:303px" %)(((
	501	[[image:Lyuba.jpg\|\|height="209" width="167"]]
72.1	502
143.2	503	Lyuba Zehl
	504
	505	(% class="small" %)Knowledge Systems Engineer
	506	Dr. rer. nat. (Systems Neuroscience)(%%)
166.1	507	(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)Standard development, data & knowledge management, interdisciplinary communication, data analysis
198.1	508	)))\|(% style="width:303px" %) \|(% style="width:303px" %)
143.2	509
27.2	510	----
	511
10.1	512
	513
147.6	514	----
58.1	515
10.1	516	== Contact ==
	517
	518	[[curation-support@ebrains.eu>>mailto:curation-support@ebrains.eu]]
	519
209.1	520	----
10.1	521
205.1	522	== Affiliated laboratories ==
	523
	524	//Institute of Basic Medical Sciences, University of Oslo, Norway (PI: Jan G. Bjaalie, Trygve B. Leergaard)//
	525
	526	//Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Germany (PI: Timo Dicksheid)//
	527
209.1	528	----
205.1	529
177.1	530	== References ==
	531
10.1	532	{{putFootnotes/}}