Wiki source code of data-curation-copy

Last modified by eapapp on 2023/07/04 16:46

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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
10.1	70
34.1	71	----
	72
147.3	73	=== Step by step - Data ===
10.1	74
	75
23.2	76	[[image:image-20230326054341-1.png]]
10.1	77
167.1	78	(% class="box floatinginfobox" id="share-data-infographic" %)
	79	(((
	80	(% style="text-align:center" %)
	81	//Download our infographic//
	82	//with all you need to know//
	83	//to share data on EBRAINS: //
	84	// //
168.1	85	[[[[image:image-20230324171114-2.png\|\|height="150" width="106"]]>>https://drive.ebrains.eu/f/dfd374b9b43a458192e9/]]
167.1	86	)))
36.1	87
147.8	88
10.1	89	==== 1. Provide some general information about your dataset ====
	90
173.1	91
	92
172.1	93	(% 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	94
151.1	95	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	96
147.3	97
172.1	98	(% 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	99
151.1	100	This form collects the necessary information needed for us to evaluate whether we can ethically and legally share the data via EBRAINS.
	101
158.1	102	See below for information about the ethical and legal aspects concerning sharing of human subject data.
151.1	103
158.1	104
10.1	105	==== 2. Upload data ====
	106
200.1	107	(% class="box floatinginfobox" id="share-data-infographic" %)
	108	(((
	109	(% style="text-align:center" %)
	110	//Download our infographic//
	111	//with guidelines
	112	on data organization: //
10.1	113
200.1	114	(% style="text-align:center" %)
	115	[[[[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/]]
	116	)))
	117
172.1	118	(% 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	119
200.1	120	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	121
172.1	122	(% 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	123
176.1	124	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	125
176.1	126	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	127
	128
	129	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.
	130
10.1	131	If a data collection is already uploaded elsewhere, we may link to the already existing repository.
	132
	133
160.1	134	==== 3. Submit metadata ====
147.8	135
	136
174.1	137	(% 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	138
175.1	139	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	140
175.1	141	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	142
	143	* 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.
	144	* [[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.
	145	* [[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.
	146
	147	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.
	148
	149
173.1	150	==== 4. Write a Data Descriptor ====
10.1	151
173.1	152
	153
175.1	154	(% 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	155
151.1	156	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	157
151.1	158	See our infographic about the data descriptor for inspiration or guidance.
10.1	159
151.1	160	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	161
10.1	162	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.
	163
173.1	164
168.1	165	(% class="box floatinginfobox" id="data-descriptor-infographic" %)
	166	(((
	167	(% style="text-align:center" %)
200.1	168	//Download our infographic
	169	about the EBRAINS Data//
	170	//Descriptor//
168.1	171	// //
	172	[[[[image:image-20230324171109-1.png\|\|height="150" width="106"]]>>https://drive.ebrains.eu/f/c1ccb78be52e4bdba7cf/]]
	173	)))
10.1	174
173.1	175	==== 5. Preview and publish ====
10.1	176
	177
172.1	178	(% 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	179
172.1	180	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	181
147.3	182
10.1	183
	184
	185	----
	186
	187	=== Step by Step - Models ===
	188
127.1	189
194.2	190	==== 1. Start early ====
	191
	192	It is not necessary to wait until you are ready to publish to register your model with EBRAINS.
	193
	194	By registering a model early in your project, you can take advantage of EBRAINS tools
	195	to keep track of simulations and to share them with your collaborators.
	196
	197	==== 2. Create/choose a Collab workspace ====
	198
	199	We use EBRAINS Collaboratory "collab" workspaces to help manage the model curation process.
	200
	201	In particular, we use collab membership (the "Team") to control who can view or edit your model metadata prior to publication.
	202
	203	It is up to you whether you create a new collab for each model, or reuse an existing collab
	204	(it is no problem to have multiple models associated with a single collab).
	205
	206	Collabs are also useful for storing simulation results, adding documentation for your model,
	207	and/or providing tutorials in Jupyter notebooks.
	208
195.1	209	==== 3. Upload code ====
194.2	210
195.1	211	We recommend storing model code and/or configuration files in an online Git repository, for example on GitHub.
	212	This repository should be public when you publish the model, but a private repository can be used for model development.
194.2	213
195.1	214	Alternatively, you can upload code to the Collab Drive or Bucket storage.
194.2	215
195.1	216	==== 4.Submit metadata ====
10.1	217
195.1	218	We recommend submitting metadata using the Model Catalog app, installed in your collab.
10.1	219
195.1	220	To install it:
10.1	221
195.1	222	1. click the "+ Create" button
	223	1. in the "Create Page" form, add a title, such as "Model Catalog", and select "Community App", then click "Create"
	224	1. scroll down until you find the "Model Catalog" app, click "Select", then "Save & View"
	225
	226	You will then see a table of all the models and validation tests associated with this collab.
	227	If this is your first time using the app, the table will probably be empty.
	228	To add your model, click "+", fill in the form, then click "Add model".
	229
	230	As development of your model proceeds, you can easily register new versions of the code,
196.1	231	and new parameterizations, by clicking "Add new version".
195.1	232
	233	If you prefer not to use the app, you can instead fill in the [[Curation request form>>https://nettskjema.no/a/277393#/]].,
	234	and you will be contacted by e-mail with further instructions.
	235
195.2	236	==== 5. Provide a reference dataset ====
195.1	237
	238	Once you're ready to publish your model entry in the EBRAINS Knowledge Graph,
	239	we encourage you to provide a dataset containing the simulation results produced by your model,
	240	following the process under "Step by step - Data" above.
	241
	242	These reference data will be linked to the model, and will be helpful to anyone trying to
	243	reuse your model.
	244
	245	We will soon introduce a "Reproducible" badge for all models that include a reference dataset,
	246	and whose simulation results can be reproduced by an EBRAINS curator.
	247
	248	==== 6. Request publication, preview and publish ====
	249
	250	Until you request your model entry to be published in the EBRAINS Knowledge Graph,
	251	only members of the collab will be able to view the model entry, in the Model Catalog app
	252	or using the Model Validation Python client.
	253
195.2	254	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	255
195.2	256	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	257
	258
	259	Curators will then perform a number of checks:
	260
	261	1. Does the model description provide sufficient context to understand the purpose and use of the model?
	262	1. Does the code repository contain a licence file, explaining the conditions for reusing the code?
196.1	263	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	264
	265	The curators will also take a snapshot of your model code.
	266
198.1	267	* 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	268	* 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.
	269
	270	Once this is done, you will be invited to review a preview of how the model entry will appear in the KG Search,
	271	and will have the opportunity to request modifications prior to approval and publication.
	272
10.1	273	----
	274
147.6	275	=== Step by Step - Software ===
10.1	276
127.1	277
170.1	278	(% class="box floatinginfobox" id="software-curation-infographic" %)
	279	(((
	280	(% style="text-align:center" %)
	281	//Software curation at a glance//
	282	// //
	283	[[[[image:Thumb2.png\|\|alt="EBRAINS-Share-Software.pdf" height="287" width="197"]]>>attach:EBRAINS-Share-Software-4.pdf]]
	284	)))
10.1	285
170.1	286	(% 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	287
170.1	288	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.
	289	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.
	290	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	291
	292	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]].
	293
170.1	294	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	295
	296
10.1	297	----
	298
202.1	299	=== Sharing human subject data ===
	300
	301	(% class="box floatinginfobox" %)
	302	(((
	303	Human subject data that can be shared on EBRAINS:
	304	// //
	305	// - Post-mortem data//
	306	// - Aggregated data//
	307	// - Strongly pseudonymized or de-identified subject data//
	308	// with a legal basis for sharing (e.g. Informed Consent)//
	309	// //
	310
	311	(% class="small" %)
	312	//If you have human data that does not qualify as any of the above,//
	313	//please [[get in touch>>https://www.ebrains.eu/contact/]] and we will clarify the available options.//
	314	)))
	315
	316
	317	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]].
	318
	319	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).
	320
	321	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.
	322
	323	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.
	324
	325	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.
	326
	327	----
	328
152.1	329	== The openMINDS metadata framework ==
	330
193.1	331	(% class="box floatinginfobox" %)
	332	(((
	333	[[[[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]]
	334	)))
	335
152.1	336	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]].
	337
	338	For feedback, requests, or contributions, please get in touch with the openMINDS development team via
	339
	340	* the support-email: [[openminds@ebrains.eu>>path:mailto:openminds@ebrains.eu]]
	341	* the [[GitHub issue tracker>>url:https://github.com/HumanBrainProject/openMINDS/issues]]
	342	* the INCF NeuroStars [[openMINDS Community Forum>>url:https://neurostars.org/t/openminds-community-forum-virtual/20156]]
	343
	344	----
	345
209.1	346	== Add practical value to your shared data, model or software ==
27.2	347
209.1	348
	349	=== Showcase shared data, models or software in other services ===
	350
	351	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.
	352
	353
	354	\|(% colspan="2" %)Viewer for 2D images
	355	\|[[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]].
	356	\|(% colspan="2" %)Viewer for sequential atlas-registered 2D images with annotation options
	357	\|[[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]].
	358	\|(% colspan="2" %)Interactive 3D atlas viewer with options for data visualization
	359	\|[[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]].
	360	\|(% colspan="2" %)Use your research product in an interactive publication
	361	\|[[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]].
	362
	363	----
	364
	365	==== Add a tutorial or learning resource ====
	366
	367	(% class="wikigeneratedid" id="H-LearningresourceA05Binformation5D" %)
	368	(% style="--darkreader-inline-color:#ffffff; color:#000000" %)//More information will follow//
	369
	370
	371	==== Create a workflow ====
	372
	373	(% class="wikigeneratedid" id="H-Workflows5Binformation5D" %)
	374	(% style="--darkreader-inline-color:#ffffff; color:#000000" %)//More information will follow//
	375
	376	----
	377
	378	== General benefits of sharing data ==
	379
	380	By sharing your data via EBRAINS, you gain access to the following benefits:
	381
	382	[[image:image-20230324170841-3.png]]
	383
	384
	385
	386	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.
	387
	388	----
	389
	390	== Frequently asked questions ==
	391
	392	>Is the curation process time consuming and difficult?
	393
	394	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.
	395
	396	>Is sharing my data also beneficial for me or only for others?
	397
	398	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.
	399
	400	>Can my data be too insignificant to share?
	401
	402	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.
	403
	404	>Can my data be easily misused if I share it?
	405
	406	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.
	407
	408	>Can I share my data before my paper is published?
	409
	410	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.
	411
	412	>Can I lose my competitive edge if I share my data before I publish the associated paper?
	413
	414	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.
	415
	416
	417	----
	418
	419	== (% style="color:#1a202c; font-family:inherit; font-size:29px" %)The curation team: meet the curators(%%) ==
	420
147.4	421	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	422
147.4	423	The curators in EBRAINS are located in Oslo, Jülich, Trier and Paris.
	424
55.1	425
203.1	426	Located in Norway
55.1	427
98.1	428	\|(% style="width:303px" %)(((
113.1	429	[[image:My project2.jpg\|\|height="209" width="167"]]
97.2	430
105.1	431	Archana Golla
	432
111.1	433	(% class="small" %)Curation Scientist
116.1	434	Neuroscience (PhD)(%%)
166.1	435	(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)Behavioral neuroscience and microscopy
105.1	436	)))\|(% style="width:303px" %)(((
142.2	437	[[image:Camilla.jpg\|\|alt="My project.jpg" height="209" width="167"]]
98.1	438
122.1	439	Camilla H. Blixhavn
105.1	440
122.1	441	(% class="small" %)Curation Scientist,
	442	Phd Student
	443	Neuroscience (M. Sc.)(%%)
166.1	444	(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)Neuroanatomy and data integration
126.1	445	)))\|(% style="width:303px" %)(((
124.1	446	[[image:My project (1).jpg\|\|height="209" width="167"]]
105.1	447
	448	Ingrid Reiten
	449
111.1	450	(% class="small" %)Curation Scientist,
112.1	451	Phd Student
117.1	452	Neuroscience (M. Sc.)(%%)
166.1	453	(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)Neuroanatomy and structural connectivity
126.1	454	)))\|(% style="width:303px" %)(((
124.1	455	[[image:My project1.jpg\|\|height="209" width="167"]]
105.1	456
122.1	457	Sophia Pieschnik
105.1	458
122.1	459	(% class="small" %)Curation Scientist
	460	Neurocognitive Psychology (M. Sc.)(%%)
166.1	461	(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)Neuroimaging
123.1	462	)))
72.1	463
143.2	464	\|(% style="width:303px" %)(((
142.2	465	[[image:My project.jpg\|\|height="209" width="167"]]
141.2	466
142.2	467	Heidi Kleven
141.2	468
142.2	469	(% class="small" %)Curation Scientist,
	470	Phd Student
	471	Neuroscience (M. Sc.)(%%)
166.1	472	(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)Neuroanatomy and brain atlases
142.2	473	)))\| \| \|
	474
141.2	475
203.1	476	\\Located in Germany
72.1	477
143.2	478	\|(% style="width:303px" %)(((
115.1	479	[[image:My project (2).jpg\|\|height="209" width="167"]]
72.1	480
	481	Jan Gündling
	482
143.2	483	(% class="small" %)Curation Scientist,
131.2	484	Phd Student
117.1	485	Sensors and Cognitive Psychology (M. Sc.)(%%)
166.1	486	(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)Human-Computer Interaction
198.1	487	)))\|(% style="width:303px" %)(((
	488	[[image:Lyuba.jpg\|\|height="209" width="167"]]
72.1	489
143.2	490	Lyuba Zehl
	491
	492	(% class="small" %)Knowledge Systems Engineer
	493	Dr. rer. nat. (Systems Neuroscience)(%%)
166.1	494	(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)Standard development, data & knowledge management, interdisciplinary communication, data analysis
198.1	495	)))\|(% style="width:303px" %) \|(% style="width:303px" %)
143.2	496
27.2	497	----
	498
10.1	499
	500
147.6	501	----
58.1	502
10.1	503	== Contact ==
	504
	505	[[curation-support@ebrains.eu>>mailto:curation-support@ebrains.eu]]
	506
209.1	507	----
10.1	508
205.1	509	== Affiliated laboratories ==
	510
	511	//Institute of Basic Medical Sciences, University of Oslo, Norway (PI: Jan G. Bjaalie, Trygve B. Leergaard)//
	512
	513	//Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Germany (PI: Timo Dicksheid)//
	514
209.1	515	----
205.1	516
177.1	517	== References ==
	518
10.1	519	{{putFootnotes/}}