Data and Knowledge
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Join the Data Sharing and Knowledge space in the EBRAINS Community
The EBRAINS Data and Knowledge Services increase the efficiency and productivity in research by making data discoverable and reusable.
The ability for scientists to easily share, find, integrate, analyse and simulate data is a central factor in accelerating the global effort to understand how the human brain functions. The vast amount of neuroscientific data, its multimodal and heterogenous nature in addition to the fragmentation in research efforts across nations and disciplines pose a challenge towards creating the necessary synergies for scientific findings to translate into real progress.
A major goal of the HBP is to contribute to understanding the human brain in health and disease through experiments, theoretical modelling and data-driven simulations, which “cross-talk” to each other. The EBRAINS Data and Knowledge services have been developed in the Human Brain Project (HBP) and are openly available to everyone through the EBRAINS infrastructure.
Advancing Open Science
Our services provide access to and storage of high-quality neuroscientific data, facilitating data discovery and re-use in the scientific community by providing an online conduit for both sharing and easy access to research data, computational models, and software. These services revolve around an expert-driven Knowledge Graph which combines metadata ingestion pipelines, human user input, and multiple quality assurance processes to ensure consistency and quality to aid researchers who wish to contribute.
Neuroscientists looking to make their data, models, and software FAIR (Findable, Accessible, Interoperable, and Reusable) can apply for user support for curation and annotation with standardised metadata facilitating discovery and reuse by the broader research community.
Find and access multi-modal data, models and software in EBRAINS Knowledge Graph
The EBRAINS Knowledge Graph (KG) is a multi-modal metadata store which brings together information from different fields on brain research. It provides fundamental services for making neuroscientific data, models, and related software FAIR.
The KG integrates registered data, models, and software into a graph database, and outlines their relationship to each other (e.g. connecting a dataset to software tools for analysis and visualisation). In addition to providing an intuitive search interface, it supports more extensive data reuse and complex computational research by supporting linked “smarter” searches.
Learn more about EBRAINS Find services here
FIND data, models and software
Use multimodal data, models and software from the EBRAINS Knowledge Graph
The EBRAINS Data and Knowledge Services integrate the data and metadata provided by the community into the research infrastructure so that other researchers can access research data. The EBRAINS Knowledge Graph (KG) integrates registered data, models, and software into a graph database, and outlines their relationship to each other, i.e. allowing you to connect a dataset to software tools for analysis and visualisation. Where possible, research data is also linked to the atlas viewers (https://ebrains.eu/services#category1).
Data accessible from the Knowledge Graph can be downloaded and visualised via other services within EBRAINS. For example, there are tools for analysing structural and functional data and tools to build models and run simulations. The data and tools can be accessed via the EBRAINS Collaboratory, a cloud workspace, so that you can directly work with the analysis pipelines and workflows that EBRAINS has developed without having to download or install data and software on your local computer.
The EBRAINS Data and Knowledge Services also host a number of Live Papers, which are structured and interactive documents that complement published scientific articles.
Explore the EBRAINS Knowledge Graph and find the data and models that will help you make your next discovery.EBRAINS Knowledge Graph
What EBRAINS Data and Knowledge Services enable you to do
EBRAINS Data and Knowledge Services offer online solutions to facilitate sharing of and access to research data, computational models and software
- Publish your datasets, computational models or software with the help of the EBRAINS Curation Service
- Leverage EBRAINS to help create data papers. Increase the visibility of your work and receive the appropriate credit via citable DOIs.
- Access standardised metadata via openMINDS
- Find data, models and software with the public search UI
- Enter, manage and publish metadata
- Find precise descriptions of the conditions of use of the data, models, and software, including licenses and information on how to cite
- Visualise and analyse data accessible via the Knowledge Graph using software and services in EBRAINS
- Build models and run simulations with data, tools and services available in EBRAINS
- The EBRAINS Data and Knowledge Services also host a number of Live Papers, which are structured and interactive documents that complement published scientific articles
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Bjerke IE, Øvsthus M, Andersson KA, Blixhavn CH, Kleven H, Yates SC, Puchades MA, Bjaalie JG, Leergaard TB. Navigating the Murine Brain: Toward Best Practices for Determining and Documenting Neuroanatomical Locations in Experimental Studies. Front Neuroanat. 2018 Nov 2;12:82. doi: 10.3389/fnana.2018.00082
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Bjerke IE, Puchades MA, Bjaalie JG, Leergaard TB. Database of literature derived cellular measurements from the murine basal ganglia. Sci Data. 2020 Jul 6;7(1):211. doi: 10.1038/s41597-020-0550-3
Eke DO, Bernard A, Bjaalie JG, Chavarriaga R, Hanakawa T, Hannan AJ, Hill SL, Martone ME, McMahon A, Ruebel O, Crook S, Thiels E, Pestilli F. International data governance for neuroscience. Neuron. 2022 Feb 16;110(4):600-612. doi: 10.1016/j.neuron.2021.11.017
Eke DO, Aasebø IE, Akintoye S, Knight W, Karakasidis A, Mikulan E, Ochang P, Ogoh G, Oostenveld R, Pigorini A, Stahl BC, White T, Zehl L. Pseudonymisation of neuroimages and data protection: Increasing access to data while retaining scientific utility. Neuroimage: Reports, Volume 1, Issue 4, 2021. doi: 10.1016/j.ynirp.2021.100053.