# Open Neuroscience Graph Welcome! This graph maps the open science ecosystem for neuroscience, covering the frameworks, data standards, platforms, infrastructures, initiatives and working groups that shape the field today. Navigating this landscape can be overwhelming. The aim is to make it easier by making the connections and dependencies between its many components explicit as nodes, and providing clear, consistent descriptions of each one. It is set up to be easily extendable and editable, as the field is rapidly evolving. Whether you're a researcher, data steward, or infrastructure developer, this map is for anyone trying to find their bearings in open neuroscience. The graph covers the full international open neuroscience ecosystem, with particular depth in the French and European context. ## Structural axes ### French-to-global infrastructure [[France Life Imaging]], [[France BioImaging]], [[IFB]], [[NeurATRIS]], and [[France Génomique]] are the French national research infrastructures connecting upward to their European counterparts ([[Euro-BioImaging]], [[ELIXIR]], [[EATRIS]], [[EOSC]]), which in turn participate in global networks including [[GA4GH]], [[INCF]], and [[RDA]]. Individual platforms are labelled and funded through [[IBiSA]], which feeds into the [[INBS]] umbrella. The overarching global policy framework is provided by the [[UNESCO Open Science Recommendation]] (2021). ### Open science policy [[Ouvrir la Science]] drives French open science mandates, implemented through [[ANR Open Science Policy]], [[CNRS Open Science]], and [[Inserm Open Science]], directing deposits to [[HAL]] (publications), [[Recherche Data Gouv]] (data), and [[Software Heritage]] (code), with [[OPIDoR]] providing the DMP infrastructure. These align upward to [[EOSC]] and [[OpenAIRE]] at the European level, and to the [[UNESCO Open Science Recommendation]] and [[cOAlition S]] at the global level. ### International neuroscience community [[INCF]] coordinates standards governance across [[BIDS Steering Group]], [[NWB Working Group]], and [[INCF Working Groups]]. The [[NIH BRAIN Initiative]] funds key open neuroscience infrastructure in the US, including [[DANDI Archive]] and the [[NWB]] mandate. Large-scale federated neuroimaging meta-analysis is coordinated through the [[ENIGMA Consortium]]. European neurodegeneration research alliances include [[CURE-ND]] and [[JPND]], linking institutes such as [[DZNE]], [[UK DRI]], [[Mission Lucidity]], and [[Paris Brain Institute]]. ### Neuroimaging data [[BIDS]] is the organising standard for neuroimaging datasets, governing file structure and metadata across MRI, PET, and related modalities. [[CATI]] handles multisite MRI harmonisation for large cohort studies across French and European sites. Open neuroimaging data is deposited in [[OpenNeuro]] and [[EBRAINS]], with [[NeuroVault]] hosting statistical maps and atlases. The [[Human Connectome Project]] and [[ADNI]] are landmark open neuroimaging cohorts. ### Electrophysiology and neurophysiology data [[NWB]] and [[BIDS]] together form the open data infrastructure for electrophysiology: [[BIDS]] organises EEG, MEG, and iEEG datasets using [[EDF]] and [[BrainVision]] as accepted file formats, while [[NWB]] is the rich single-file format for neurophysiology recordings archived on [[DANDI Archive]]. [[EDF]] is the universal clinical EEG format, connecting hospital recordings to open research pipelines. The [[IBL]] and the [[Allen Institute for Brain Science]] are major global producers of open neurophysiology datasets, both archived on [[DANDI Archive]] in [[NWB]] format. [[HED]] provides structured event annotation across both [[BIDS]] and [[NWB]]. At [[Paris Brain Institute]], [[CENIR]] acquires MEG and EEG data. ### Cognitive and behavioural neuroscience Cognitive and behavioural neuroscience lacks the unified data standard that [[BIDS]] and [[NWB]] provide for imaging and electrophysiology. What exists are ontologies and annotation frameworks rather than file format standards. [[Cognitive Atlas]] provides a controlled vocabulary of cognitive processes and experimental tasks, enabling semantic cross-study comparison of fMRI datasets and required by [[NeuroVault]] for statistical map uploads. [[NBO]] (Neurobehavior Ontology) covers behavioural and neurological phenotypes across species, bridging preclinical model organism data and clinical behavioural assessments. [[HED]] provides structured event annotation at the trial level, applicable to any paradigm producing time-stamped events. [[BIDS]] covers behavioural event files and has extension proposals for motion capture and eye-tracking, though community standards for wearables, digital phenotyping, and continuous ecological monitoring are still emerging. ### Microscopy and bioimaging [[OME File Formats]] (OME-TIFF and OME-Zarr) are the open standards for biological microscopy data, produced by the [[OME]] consortium and implemented through the [[OMERO]] image management platform. Data quality and metadata are governed through [[QUAREP-LiMi]] and [[REMBI]]. Reference datasets from published studies are curated in [[IDR]], while [[BioImage Archive]] serves as the broad-intake archive for all biological image data submitted under open access mandates. National platforms are federated through [[France BioImaging]] and its European counterpart [[Euro-BioImaging]], with [[GT-GeDeM]] coordinating FAIR data management practices for microscopy platforms in France. ### Genomics and single-cell data Genomic sequencing produces data at three successive levels, each with its own formats and repositories. **Raw reads** ([[FASTQ]]) are the direct sequencer output and are deposited in open archives ([[ENA]], [[DDBJ]], NCBI SRA) or in controlled-access repositories ([[EGA]], [[dbGaP]]) for sensitive human data. **Aligned reads** ([[SAM-BAM-CRAM]]) are produced by mapping FASTQ reads to a reference genome and are the working format for all downstream analyses. Human BAM/CRAM is typically archived in [[EGA]] or [[dbGaP]] under controlled access. **Variants** ([[VCF]]) are derived from aligned reads by variant calling and represent an anonymised, aggregate summary that can usually be shared openly; they are deposited in [[EVA]] (Europe) or dbSNP (US). For expression studies, the endpoint is count matrices rather than VCF, deposited in [[NCBI GEO]] (open) or [[EGA]] (controlled access). All of these are governed by [[GA4GH]] standards for data access and interoperability. Single-cell data uses [[AnnData]] as the exchange format and [[Cell Ontology]] for cell type annotation, with [[BICAN]] providing the international cell atlas reference. ### Rare disease and phenotyping [[HPO]] and [[ORDO]] are the primary phenotyping standards for rare neurological disease. [[HPO]] is used for phenotype annotation in controlled-access genomic repositories and linked through [[Phenopackets]] — the [[GA4GH]] standard for computable genotype-phenotype data exchange — for genotype-phenotype association. [[MONDO]] harmonises disease classifications across [[ICD-10]], [[OMIM]], and [[ORDO]] into a single hierarchy. [[BBMRI-ERIC]] promotes [[Phenopackets]] and [[OMOP CDM]] for cross-biobank discoverability across European biobank networks. ### Health data and interoperability [[OMOP CDM]], [[HL7 FHIR]], and [[SNOMED CT]] are the interoperability standards connecting hospital clinical data warehouses such as [[EDS AP-HP]], national health data platforms such as [[Health Data Hub]] and [[SNDS]], and the European [[EHDS]]. The OMOP vocabulary draws on [[ICD-10]], [[LOINC]], [[RxNorm]], and [[CCAM]] as source terminologies. [[OMOP CDM]] is maintained by [[OHDSI]], which coordinates a global network of 700M+ patient records. [[BBMRI-ERIC]] promotes [[OMOP CDM]] for cross-biobank data standardisation across Europe. ### Clinical trials [[CDISC]] (SDTM, ADaM, CDASH) is the standard for clinical trial data required for regulatory submissions to the FDA and EMA (the US and European medicines regulators). It is the data infrastructure for interventional research conducted through [[ECRIN]] and [[NeurATRIS]]. Trial registration is mandatory in [[ClinicalTrials.gov]] and the EU [[CTIS]]. Individual patient data from completed trials can be shared via platforms such as [[VIVLI]] and [[YODA Project]]. ### Data description and discoverability Making data findable and reusable requires description at two levels. At the experiment level, [[OBI]] (Ontology for Biomedical Investigations) provides a formal vocabulary for study design and protocols, [[NIDM]] represents the full neuroimaging research workflow as a machine-readable provenance graph built on [[PROV-O]], and [[UBERON]] provides cross-species anatomical annotation used across repositories and standards. At the repository and infrastructure level, [[DCAT]] is the W3C catalogue vocabulary underpinning discoverability across [[EOSC]] and [[Recherche Data Gouv]], [[Dublin Core]] provides the base metadata layer present in virtually every repository, and [[ROR]], [[ORCID]], [[RRID]], and [[DataCite]] provide persistent identifiers for institutions, researchers, resources, and datasets respectively. ### Study registration and data management planning Open science mandates require that studies are registered and data management planned before data collection begins. [[OSF]] supports pre-registration and registered reports, reducing publication bias by committing hypotheses and analysis plans in advance. For clinical trials, registration in [[ClinicalTrials.gov]] or the EU [[CTIS]] is legally mandatory. [[OPIDoR]] provides the French national infrastructure for data management plans, aligned with [[ANR Open Science Policy]] and [[FAIR Principles]]. [[CDISC]] defines the structure of clinical trial data from protocol through to regulatory submission, forming the data management backbone for interventional studies conducted through [[ECRIN]] and [[NeurATRIS]]. ## Browse by directory The graph is organised across four directories, each with a dedicated sub-MOC with a full alphabetical index of its nodes. - [[_Actors]] — research institutes, consortia, initiatives, biobanks and core facilities - [[_Standards]] — data format standards, terminologies, ontologies and metadata frameworks - [[_Platforms]] — repositories, data platforms and clinical data capture systems - [[_Governance]] — national and European infrastructures, policies, working groups and frameworks ## Node structure Every node uses a lean, non-redundant YAML frontmatter schema. The following fields and values are used: | Field | Values | | ------------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `type` | `standard` `terminology` `framework` `platform` `repository` `infrastructure` `facility` `institute` `consortium` `initiative` `working-group` `policy` `biobank` | | `domain` | `neuroimaging` `electrophysiology` `clinical` `genomics` `multimodal` `bioimaging` `behavior` `health` | | `scope` | `french` `european` `international` | | `tags: icm/uses` | ICM operationally uses this standard, platform or tool | | `tags: icm/participates` | ICM is an active member or participant in this body | The `domain` values map to the structural axes above as follows. `multimodal` covers nodes that span several domains and is not tied to a single axis. | Axis | `domain` value(s) | | ---- | ----------------- | | Neuroimaging data | `neuroimaging` | | Electrophysiology and neurophysiology data | `electrophysiology` | | Cognitive and behavioural neuroscience | `behavior` | | Microscopy and bioimaging | `bioimaging` | | Genomics and single-cell data | `genomics` | | Rare disease and phenotyping | `genomics` `clinical` | | Health data and interoperability | `health` `clinical` | | Clinical trials | `clinical` | | Cross-domain | `multimodal` | For naming conventions and writing style guidance, see the [README](https://gitlab.com/icm-institute/dac/opensciencegraph/-/blob/main/README.md). ## Get involved The graph is built as an [Obsidian](https://obsidian.md/) vault, published [here](https://publish.obsidian.md/openscience), and openly available in the [git repository](https://gitlab.com/icm-institute/dac/opensciencegraph). It started as a working reference at the [[Paris Brain Institute]] and continues to reflect that perspective in places, with nodes for ICM platforms and French infrastructure covered in particular depth. The `icm/uses` and `icm/participates` tags make this perspective explicit and filterable without imposing it on the graph as a whole. The vault is intentionally open and decentralised: any institute, lab, or individual is welcome to use it, adapt it, or contribute to it. Contributions, corrections and suggestions are welcome. Just open an issue or pull request there, or [email me](mailto:[email protected]) directly. In open science perhaps more than anywhere else, this quote by W.B. Yeats rings true: > *There are no strangers here, just friends you haven't met yet*