Wiki source code of test-ir2

Version 199.1 by ingrreit on 2023/06/21 12:10

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	19
47.2	20	== Publishing neuroscience data, models and software via EBRAINS ==
10.1	21
25.2	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/]]
	86
	87
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
	109
172.1	110	(% 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	111
151.1	112	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// //[[collection of guidelines on data organization>>https://drive.ebrains.eu/smart-link/25299f04-c4e5-4028-8f5f-3b8208f9a532/]] for further guidance.
	113
172.1	114	(% 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	115
176.1	116	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	117
176.1	118	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	119
	120
	121	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.
	122
10.1	123	If a data collection is already uploaded elsewhere, we may link to the already existing repository.
	124
	125
160.1	126	==== 3. Submit metadata ====
147.8	127
	128
174.1	129	(% 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	130
175.1	131	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	132
175.1	133	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	134
	135	* 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.
	136	* [[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.
	137	* [[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.
	138
	139	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.
	140
	141
173.1	142	==== 4. Write a Data Descriptor ====
10.1	143
173.1	144
	145
175.1	146	(% 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	147
151.1	148	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	149
151.1	150	See our infographic about the data descriptor for inspiration or guidance.
10.1	151
151.1	152	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	153
10.1	154	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.
	155
173.1	156
168.1	157	(% class="box floatinginfobox" id="data-descriptor-infographic" %)
	158	(((
	159	(% style="text-align:center" %)
	160	//Download our infographic: //
	161	//The EBRAINS Data//
	162	//Descriptor at a glance//
	163	// //
	164	[[[[image:image-20230324171109-1.png\|\|height="150" width="106"]]>>https://drive.ebrains.eu/f/c1ccb78be52e4bdba7cf/]]
	165
	166	)))
10.1	167
173.1	168	==== 5. Preview and publish ====
10.1	169
	170
172.1	171	(% 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	172
172.1	173	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	174
147.3	175
10.1	176	----
	177
173.1	178	==== ====
10.1	179
173.1	180	==== Sharing human subject data ====
	181
10.1	182	(% class="box floatinginfobox" %)
1.1	183	(((
156.1	184	Human subject data that can be shared on EBRAINS:
168.1	185	// //
	186	// - Post-mortem data//
	187	// - Aggregated data//
	188	// - Strongly pseudonymized or de-identified subject data//
	189	// with a legal basis for sharing (e.g. Informed Consent)//
	190	// //
1.1	191
168.1	192	(% class="small" %)
	193	//If you have human data that does not qualify as any of the above,//
	194	//please [[get in touch>>https://www.ebrains.eu/contact/]] and we will clarify the available options.//
1.1	195	)))
	196
173.1	197
157.1	198	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]].
1.1	199
147.3	200	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).
128.1	201
147.3	202	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.
1.1	203
147.3	204	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.
1.1	205
147.3	206	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.
	207
	208
10.1	209	----
	210
	211	=== Step by Step - Models ===
	212
127.1	213
194.2	214	==== 1. Start early ====
	215
	216	It is not necessary to wait until you are ready to publish to register your model with EBRAINS.
	217
	218	By registering a model early in your project, you can take advantage of EBRAINS tools
	219	to keep track of simulations and to share them with your collaborators.
	220
	221	==== 2. Create/choose a Collab workspace ====
	222
	223	We use EBRAINS Collaboratory "collab" workspaces to help manage the model curation process.
	224
	225	In particular, we use collab membership (the "Team") to control who can view or edit your model metadata prior to publication.
	226
	227	It is up to you whether you create a new collab for each model, or reuse an existing collab
	228	(it is no problem to have multiple models associated with a single collab).
	229
	230	Collabs are also useful for storing simulation results, adding documentation for your model,
	231	and/or providing tutorials in Jupyter notebooks.
	232
195.1	233	==== 3. Upload code ====
194.2	234
195.1	235	We recommend storing model code and/or configuration files in an online Git repository, for example on GitHub.
	236	This repository should be public when you publish the model, but a private repository can be used for model development.
194.2	237
195.1	238	Alternatively, you can upload code to the Collab Drive or Bucket storage.
194.2	239
195.1	240	==== 4.Submit metadata ====
10.1	241
195.1	242	We recommend submitting metadata using the Model Catalog app, installed in your collab.
10.1	243
195.1	244	To install it:
10.1	245
195.1	246	1. click the "+ Create" button
	247	1. in the "Create Page" form, add a title, such as "Model Catalog", and select "Community App", then click "Create"
	248	1. scroll down until you find the "Model Catalog" app, click "Select", then "Save & View"
	249
	250	You will then see a table of all the models and validation tests associated with this collab.
	251	If this is your first time using the app, the table will probably be empty.
	252	To add your model, click "+", fill in the form, then click "Add model".
	253
	254	As development of your model proceeds, you can easily register new versions of the code,
196.1	255	and new parameterizations, by clicking "Add new version".
195.1	256
	257	If you prefer not to use the app, you can instead fill in the [[Curation request form>>https://nettskjema.no/a/277393#/]].,
	258	and you will be contacted by e-mail with further instructions.
	259
195.2	260	==== 5. Provide a reference dataset ====
195.1	261
	262	Once you're ready to publish your model entry in the EBRAINS Knowledge Graph,
	263	we encourage you to provide a dataset containing the simulation results produced by your model,
	264	following the process under "Step by step - Data" above.
	265
	266	These reference data will be linked to the model, and will be helpful to anyone trying to
	267	reuse your model.
	268
	269	We will soon introduce a "Reproducible" badge for all models that include a reference dataset,
	270	and whose simulation results can be reproduced by an EBRAINS curator.
	271
	272	==== 6. Request publication, preview and publish ====
	273
	274	Until you request your model entry to be published in the EBRAINS Knowledge Graph,
	275	only members of the collab will be able to view the model entry, in the Model Catalog app
	276	or using the Model Validation Python client.
	277
195.2	278	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	279
195.2	280	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	281
	282
	283	Curators will then perform a number of checks:
	284
	285	1. Does the model description provide sufficient context to understand the purpose and use of the model?
	286	1. Does the code repository contain a licence file, explaining the conditions for reusing the code?
196.1	287	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	288
	289	The curators will also take a snapshot of your model code.
	290
198.1	291	* 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	292	* 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.
	293
	294	Once this is done, you will be invited to review a preview of how the model entry will appear in the KG Search,
	295	and will have the opportunity to request modifications prior to approval and publication.
	296
10.1	297	----
	298
147.6	299	=== Step by Step - Software ===
10.1	300
127.1	301
170.1	302	(% class="box floatinginfobox" id="software-curation-infographic" %)
	303	(((
	304	(% style="text-align:center" %)
	305	//Software curation at a glance//
	306	// //
	307	[[[[image:Thumb2.png\|\|alt="EBRAINS-Share-Software.pdf" height="287" width="197"]]>>attach:EBRAINS-Share-Software-4.pdf]]
	308	)))
10.1	309
170.1	310	(% 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	311
170.1	312	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.
	313	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.
	314	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	315
	316	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]].
	317
170.1	318	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	319
	320
10.1	321	----
	322
152.1	323	== The openMINDS metadata framework ==
	324
193.1	325	(% class="box floatinginfobox" %)
	326	(((
	327	[[[[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]]
	328	)))
	329
152.1	330	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]].
	331
	332	For feedback, requests, or contributions, please get in touch with the openMINDS development team via
	333
	334	* the support-email: [[openminds@ebrains.eu>>path:mailto:openminds@ebrains.eu]]
	335	* the [[GitHub issue tracker>>url:https://github.com/HumanBrainProject/openMINDS/issues]]
	336	* the INCF NeuroStars [[openMINDS Community Forum>>url:https://neurostars.org/t/openminds-community-forum-virtual/20156]]
	337
	338	----
	339
147.4	340	== The curation team: meet the curators ==
27.2	341
147.4	342	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	343
147.4	344	The curators in EBRAINS are located in Oslo, Jülich, Trier and Paris.
	345
55.1	346
72.1	347	Located in Norway:
55.1	348
98.1	349	\|(% style="width:303px" %)(((
113.1	350	[[image:My project2.jpg\|\|height="209" width="167"]]
97.2	351
105.1	352	Archana Golla
	353
111.1	354	(% class="small" %)Curation Scientist
116.1	355	Neuroscience (PhD)(%%)
166.1	356	(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)Behavioral neuroscience and microscopy
105.1	357	)))\|(% style="width:303px" %)(((
142.2	358	[[image:Camilla.jpg\|\|alt="My project.jpg" height="209" width="167"]]
98.1	359
122.1	360	Camilla H. Blixhavn
105.1	361
122.1	362	(% class="small" %)Curation Scientist,
	363	Phd Student
	364	Neuroscience (M. Sc.)(%%)
166.1	365	(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)Neuroanatomy and data integration
126.1	366	)))\|(% style="width:303px" %)(((
124.1	367	[[image:My project (1).jpg\|\|height="209" width="167"]]
105.1	368
	369	Ingrid Reiten
	370
111.1	371	(% class="small" %)Curation Scientist,
112.1	372	Phd Student
117.1	373	Neuroscience (M. Sc.)(%%)
166.1	374	(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)Neuroanatomy and structural connectivity
126.1	375	)))\|(% style="width:303px" %)(((
124.1	376	[[image:My project1.jpg\|\|height="209" width="167"]]
105.1	377
122.1	378	Sophia Pieschnik
105.1	379
122.1	380	(% class="small" %)Curation Scientist
	381	Neurocognitive Psychology (M. Sc.)(%%)
166.1	382	(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)Neuroimaging
123.1	383	)))
72.1	384
143.2	385	\|(% style="width:303px" %)(((
142.2	386	[[image:My project.jpg\|\|height="209" width="167"]]
141.2	387
142.2	388	Heidi Kleven
141.2	389
142.2	390	(% class="small" %)Curation Scientist,
	391	Phd Student
	392	Neuroscience (M. Sc.)(%%)
166.1	393	(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)Neuroanatomy and brain atlases
142.2	394	)))\| \| \|
	395
141.2	396
128.1	397	\\Located in Germany:
72.1	398
143.2	399	\|(% style="width:303px" %)(((
115.1	400	[[image:My project (2).jpg\|\|height="209" width="167"]]
72.1	401
	402	Jan Gündling
	403
143.2	404	(% class="small" %)Curation Scientist,
131.2	405	Phd Student
117.1	406	Sensors and Cognitive Psychology (M. Sc.)(%%)
166.1	407	(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)Human-Computer Interaction
198.1	408	)))\|(% style="width:303px" %)(((
	409	[[image:Lyuba.jpg\|\|height="209" width="167"]]
72.1	410
143.2	411	Lyuba Zehl
	412
	413	(% class="small" %)Knowledge Systems Engineer
	414	Dr. rer. nat. (Systems Neuroscience)(%%)
166.1	415	(% class="small" style="--darkreader-inline-color:#d3cbbf; color:#4a5568" %)Standard development, data & knowledge management, interdisciplinary communication, data analysis
198.1	416	)))\|(% style="width:303px" %) \|(% style="width:303px" %)
143.2	417
27.2	418	----
	419
147.6	420	== Add practical value to your shared data, model or software ==
10.1	421
	422
147.6	423	----
58.1	424
147.6	425	=== Showcase shared data, models or software in other services ===
58.1	426
190.1	427	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.
58.1	428
55.1	429
192.1	430	\|(% colspan="2" %)Viewer for 2D images
	431	\|[[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]].
	432	\|(% colspan="2" %)Viewer for sequential atlas-registered 2D images with annotation options
	433	\|[[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]].
	434	\|(% colspan="2" %)Interactive 3D atlas viewer with options for data visualization
	435	\|[[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]].
	436	\|(% colspan="2" %)Use your research product in an interactive publication
	437	\|[[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]].
	438
60.1	439	----
	440
160.1	441	==== Add a tutorial or learning resource ====
	442
	443	(% class="wikigeneratedid" id="H-LearningresourceA05Binformation5D" %)
166.1	444	(% style="--darkreader-inline-color:#ffffff; color:#000000" %)//More information will follow//
160.1	445
	446
	447	==== Create a workflow ====
	448
	449	(% class="wikigeneratedid" id="H-Workflows5Binformation5D" %)
166.1	450	(% style="--darkreader-inline-color:#ffffff; color:#000000" %)//More information will follow//
160.1	451
	452	----
	453
37.1	454	=== The benefits of sharing data ===
27.1	455
	456	By sharing your data via EBRAINS, you gain access to the following benefits:
	457
	458	[[image:image-20230324170841-3.png]]
	459
	460
	461
159.1	462	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.
27.1	463
	464	----
	465
148.1	466	=== Frequently asked questions ===
10.1	467
1.1	468	(((
166.1	469	==== ====
1.1	470
23.2	471	(((
168.2	472	>Is the curation process time consuming and difficult?
1.1	473	)))
19.1	474	)))
10.1	475
168.2	476	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.
10.1	477
168.2	478	>Is sharing my data also beneficial for me or only for others?
10.1	479
	480	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.
	481
168.2	482	>Can my data be too insignificant to share?
10.1	483
168.2	484	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.
10.1	485
168.2	486	>Can my data be easily misused if I share it?
10.1	487
168.2	488	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.
10.1	489
168.2	490	>Can I share my data before my paper is published?
10.1	491
168.2	492	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.
10.1	493
168.2	494	>Can I lose my competitive edge if I share my data before I publish the associated paper?
10.1	495
168.2	496	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.
10.1	497
	498
	499	----
	500
	501	== Contact ==
	502
	503	[[curation-support@ebrains.eu>>mailto:curation-support@ebrains.eu]]
	504
	505
177.1	506	== References ==
	507
10.1	508	{{putFootnotes/}}

Wiki source code of test-ir2

data-curation-copy