diff --git a/docs/data-models/brainatlas/registering-brain-atlas.html b/docs/data-models/brainatlas/registering-brain-atlas.html index 5520638a..11b47040 100644 --- a/docs/data-models/brainatlas/registering-brain-atlas.html +++ b/docs/data-models/brainatlas/registering-brain-atlas.html @@ -261,43 +261,43 @@

- SubjectCollection + SubjectCollection A collection of subject to be used in the experiment - TemplateImageData + TemplateImageData Template image data acquired and processed from the subject collection - ParcellationImageData + ParcellationImageData Parcellation image data generated from the template image data - ParcellationLabel + ParcellationLabel Parcellation labels correspond to the annotations in the parcellation image - TemplateVolume + TemplateVolume Template volume generated from the template image data - ParcellationVolume + ParcellationVolume Parcellation volume generated from the parcellation image data - ParcellationOntology + ParcellationOntology Parcellation ontology converted from the parcellation label - AtlasSpatialReferenceSystem + AtlasSpatialReferenceSystem The spatial coordinate system of the atlas space - AtlasRelease + AtlasRelease An atlas release comprises template volume, parcellation volume, parcellation ontology as well as the atlas spatial reference system - Protocol + Protocol Protocol that describes the method used in the design and execution of the experiment @@ -312,19 +312,19 @@

Atlas Construction + Atlas Construction Process to construct a brain atlas - Template Reconstruction + Template Reconstruction Reconstruct the template image data into volumetric representation - Parcellation Reconstruction + Parcellation Reconstruction Reconstruct the parcellation image data into volumetric representation - Ontology Conversion + Ontology Conversion Convert the parcellation label into ontological representation @@ -339,15 +339,15 @@

- Person + Person Person associated with an activity - SoftwareAgent + SoftwareAgent Software associated with an activity - Organization + Organization Organization associated with an activity diff --git a/docs/data-models/brainatlas/registering-whole-brain-morphology.html b/docs/data-models/brainatlas/registering-whole-brain-morphology.html index 64c4a97f..f01be0ff 100644 --- a/docs/data-models/brainatlas/registering-whole-brain-morphology.html +++ b/docs/data-models/brainatlas/registering-whole-brain-morphology.html @@ -258,31 +258,31 @@

- Subject + Subject Subject that was used in the experiment - TemplateVolume + TemplateVolume Template volume generated from the template image data - AtlasSpatialReferenceSystem + AtlasSpatialReferenceSystem The spatial coordinate system of the atlas space - ImageStack + ImageStack Image stack obtained from the brain tissue of the subject - ReconstructedCell + ReconstructedCell Reconstructed cell - Transform + Transform A linear or non-linear transform - Protocol + Protocol Protocol that describes the method used in the design and execution of the experiment @@ -297,15 +297,15 @@

BrainImaging + BrainImaging Technique used to obtain an image stack of the brain tissue containing the cells for reconstruction - ReconstructionFromImage + ReconstructionFromImage Technique used to reconstruct the stained cell - Transformation + Transformation Transform a geometric object @@ -320,15 +320,15 @@

- Person + Person Person associated with an activity - SoftwareAgent + SoftwareAgent Software associated with an activity - Organization + Organization Organization associated with an activity diff --git a/docs/data-models/electrophysiology/intracellularsharpelectrode-recording.html b/docs/data-models/electrophysiology/intracellularsharpelectrode-recording.html index 2b4057e5..4b8426ee 100644 --- a/docs/data-models/electrophysiology/intracellularsharpelectrode-recording.html +++ b/docs/data-models/electrophysiology/intracellularsharpelectrode-recording.html @@ -260,31 +260,31 @@

- Subject + Subject Subject that was used in the experiment - Slice + Slice Brain slice obtained from the subject - IntraCellularSharpElectrodeRecordedSlice + IntraCellularSharpElectrodeRecordedSlice Brain slice containing recorded cells - IntraSharpRecordedCellCollection + IntraSharpRecordedCellCollection Collection of recorded cells in a single slice - IntraCellularSharpElectrodeRecordedCell + IntraCellularSharpElectrodeRecordedCell Cell that was recorded in the slice - Trace + Trace Individual recording trace of the cell (stimulation/input and response/output trace) - Protocol + Protocol Protocol that describes the method used in the design and execution of the experiment @@ -300,15 +300,15 @@

BrainSlicing + BrainSlicing Technique used to obtain a brain slice - IntraCellularSharpElectrode + IntraCellularSharpElectrode Technique used to study electrical activity of individual living cells - StimulusExperiment + StimulusExperiment Technique used to obtain the electrical signature of cells through injection of a defined current pattern @@ -324,15 +324,15 @@

- Person + Person Person associated with an activity - SoftwareAgent + SoftwareAgent Software associated with an activity - Organization + Organization Organization associated with an activity diff --git a/docs/data-models/electrophysiology/wholecellpatchclamp-recording.html b/docs/data-models/electrophysiology/wholecellpatchclamp-recording.html index 4d9fc117..2ba321c2 100644 --- a/docs/data-models/electrophysiology/wholecellpatchclamp-recording.html +++ b/docs/data-models/electrophysiology/wholecellpatchclamp-recording.html @@ -261,31 +261,31 @@

- Subject + Subject Subject that was used in the experiment - Slice + Slice Brain slice obtained from the subject - PatchedSlice + PatchedSlice Brain slice containing patched cells - PatchedCellCollection + PatchedCellCollection Collection of patched cells in a single slice (e.g. for multi-patch recordings) - PatchedCell + PatchedCell Cell that was patched in the slice - Trace + Trace Individual recording trace of the patched cell (stimulation/input and response/output trace) - Protocol + Protocol Protocol that describes the method used in the design and execution of the experiment @@ -301,15 +301,15 @@

BrainSlicing + BrainSlicing Technique used to obtain a brain slice for patching - WholeCellPatchClamp + WholeCellPatchClamp Technique used to study electrical activity of individual living cells - StimulusExperiment + StimulusExperiment Technique used to obtain the electrical signature of cells through injection of a defined current pattern @@ -325,15 +325,15 @@

- Person + Person Person associated with an activity - SoftwareAgent + SoftwareAgent Software associated with an activity - Organization + Organization Organization associated with an activity diff --git a/docs/data-models/morphology/morphology-reconstruction.html b/docs/data-models/morphology/morphology-reconstruction.html index a4794fe7..3cb5f0b3 100644 --- a/docs/data-models/morphology/morphology-reconstruction.html +++ b/docs/data-models/morphology/morphology-reconstruction.html @@ -262,47 +262,47 @@

- Subject + Subject Subject that was used in the experiment - Slice + Slice Brain slice obtained from the subject - PatchedSlice + PatchedSlice Brain slice containing patched cells - PatchedCellCollection + PatchedCellCollection Collection of patched cells in a single slice (e.g. for multi-patch recordings) - PatchedCell + PatchedCell Cell that was patched in the slice - FixedStainedSlice + FixedStainedSlice Brain slice after fixation and staining - AnnotatedSlice + AnnotatedSlice Brain slice containing the identified and annotated stained cells - LabeledCellCollection + LabeledCellCollection Collection of labeled cells in a single slice - LabeledCell + LabeledCell Cell that was labeled in the slice - ReconstructedCell + ReconstructedCell Reconstructed cell - Protocol + Protocol Protocol that describes the method used in the design and execution of the experiment @@ -318,23 +318,23 @@

BrainSlicing + BrainSlicing Technique used to obtain a brain slice for patching - WholeCellPatchClamp + WholeCellPatchClamp Technique used to study electrical activity of individual living cells - FixationStainingMounting + FixationStainingMounting Technique used to fix and stain the slice - AcquisitionAnnotation + AcquisitionAnnotation Technique used to acquire an image of the slice and annotate the stained cells - Reconstruction + Reconstruction Technique used to reconstruct the stained cell @@ -350,15 +350,15 @@

- Person + Person Person associated with an activity - SoftwareAgent + SoftwareAgent Software associated with an activity - Organization + Organization Organization associated with an activity diff --git a/docs/data-models/morphology/whole-brain-neuron-morphology-reconstruction.html b/docs/data-models/morphology/whole-brain-neuron-morphology-reconstruction.html index d993de29..10b6dc40 100644 --- a/docs/data-models/morphology/whole-brain-neuron-morphology-reconstruction.html +++ b/docs/data-models/morphology/whole-brain-neuron-morphology-reconstruction.html @@ -262,19 +262,19 @@

- Subject + Subject Subject that was used in the experiment - ImageStack + ImageStack Image stack obtained from the brain tissue of the subject - ReconstructedCell + ReconstructedCell Reconstructed cell - Protocol + Protocol Protocol that describes the method used in the design and execution of the experiment @@ -290,11 +290,11 @@

BrainImaging + BrainImaging Technique used to obtain an image stack of the brain tissue containing the cells for reconstruction - ReconstructionFromImage + ReconstructionFromImage Technique used to reconstruct the stained cell @@ -310,15 +310,15 @@

- Person + Person Person associated with an activity - SoftwareAgent + SoftwareAgent Software associated with an activity - Organization + Organization Organization associated with an activity diff --git a/index.html b/index.html index 20598268..9e0c050c 100644 --- a/index.html +++ b/index.html @@ -1 +1 @@ - Neuroshapes | Open schemas for FAIR neuroscience data

Neuroshapes

Open schemas for FAIR neuroscience Data, Schemas and Vocabulary

Why Neuroshapes?

Motivation

Modern scientific data management requires comprehensive support for the FAIR (Findable, Accessible, Interoperable, Reusable) principles. Neuroshapes is a general approach, or design pattern, for supporting FAIR principles for diverse neuroscience data with the following benefits:

  • Neuroshapes ensures that the key scientific and technical activities and agents of the data generation process are expressed in a validatable provenance-based data model.

Neuroshapes captures the contextual information necessary to:

  • Interpret the scientific meaning of the data.
  • Infer the resulting data types.
  • Evaluate trust and quality.
  • Ensure attribution of all contributors.
  • Support data reuse, integration, interoperability and longevity.

Goals

The main goal is to provide design patterns, best practices as well as tools to promote:

  • The use of standard semantic markups and linked data principles as ways to structure metadata and related data.
  • The use of the W3C SHACL (Shapes Constraint Language) recommendation as a rich metadata schema language which is formal and expressive; interoperable; machine-readable; and domain-agnostic.
  • The reuse of existing schemas and semantic markups ( schema.org , W3C PROV-O ) and existing ontologies and controlled vocabularies (including NIFSTD - Neuroscience Information Framework Standard Ontologies).
  • The use of the W3C PROV-O recommendation as a format to record (meta)data provenance.

Get Involved

Join the INCF Neuroshapes Special Interest Group:

This SIG aims to coordinate community efforts for the development of open, use case driven and shared validatable data models (schemas, vocabularies) to enable the FAIR principles (Findable, Accessible, Interoperable and Reusable) for basic, computational and clinical neuroscience (meta)data.

How to Contribute

Found a bug ? Want a new feature ?


Get in Touch

INCF SIG on Neuroshapes

This SIG aims to coordinate community efforts for the development of open, use case driven and shared validatable data models (schemas, vocabularies) to enable the FAIR principles (Findable, Accessible, Interoperable and Reusable) for basic, computational and clinical neuroscience (meta)data.

Acknowledgements

This work has been supported by ETH Board funding to the Blue Brain Project. Portions of this work have also been supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement no.720270. (Human Brain Project).

Participants

Sean Hill, Krembil Centre for Neuroinformatics, CAMH, Chair
Andrew Davison, CNRS, Human Brain Project, Chair
Anna-Kristin Kaufmann, EPFL, Blue Brain Project
Huanxiang Lu, EPFL, Blue Brain Project
Tom Gillespie, UCSD, Neuroscience Information Framework
Genrich Ivaska, EPFL, Blue Brain Project
Oliver Schmid, EPFL, Human Brain Project
Jean-Denis Courcol, EPFL, Blue Brain Project
Samuel Kerrien, EPFL, Blue Brain Project
Jeff Muller, EPFL, Human Brain Project
Mohameth François Sy, EPFL, Blue Brain Project, Co-Chair
Bogdan Roman, EPFL, Blue Brain Project
Pierre-Alexandre Fonta, EPFL, Blue Brain Project
Coste Benoît Jean-Albert, EPFL, Blue Brain Project
Taylor MacMillan, Krembil Centre for Neuroinformatics, CAMH
David Rotenberg, Krembil Centre for Neuroinformatics, CAMH
\ No newline at end of file + Neuroshapes | Open schemas for FAIR neuroscience data

Neuroshapes

Open schemas for FAIR neuroscience Data, Schemas and Vocabulary

Why Neuroshapes?

Motivation

Modern scientific data management requires comprehensive support for the FAIR (Findable, Accessible, Interoperable, Reusable) principles. Neuroshapes is a general approach, or design pattern, for supporting FAIR principles for diverse neuroscience data with the following benefits:

  • Neuroshapes ensures that the key scientific and technical activities and agents of the data generation process are expressed in a validatable provenance-based data model.

Neuroshapes captures the contextual information necessary to:

  • Interpret the scientific meaning of the data.
  • Infer the resulting data types.
  • Evaluate trust and quality.
  • Ensure attribution of all contributors.
  • Support data reuse, integration, interoperability and longevity.

Goals

The main goal is to provide design patterns, best practices as well as tools to promote:

  • The use of standard semantic markups and linked data principles as ways to structure metadata and related data.
  • The use of the W3C SHACL (Shapes Constraint Language) recommendation as a rich metadata schema language which is formal and expressive; interoperable; machine-readable; and domain-agnostic.
  • The reuse of existing schemas and semantic markups ( schema.org , W3C PROV-O ) and existing ontologies and controlled vocabularies (including NIFSTD - Neuroscience Information Framework Standard Ontologies).
  • The use of the W3C PROV-O recommendation as a format to record (meta)data provenance.

Get Involved

Join the INCF Neuroshapes Special Interest Group:

This SIG aims to coordinate community efforts for the development of open, use case driven and shared validatable data models (schemas, vocabularies) to enable the FAIR principles (Findable, Accessible, Interoperable and Reusable) for basic, computational and clinical neuroscience (meta)data.

How to Contribute

Found a bug ? Want a new feature ?


Get in Touch

INCF SIG on Neuroshapes

This SIG aims to coordinate community efforts for the development of open, use case driven and shared validatable data models (schemas, vocabularies) to enable the FAIR principles (Findable, Accessible, Interoperable and Reusable) for basic, computational and clinical neuroscience (meta)data.

Acknowledgements

This work has been supported by ETH Board funding to the Blue Brain Project. Portions of this work have also been supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement no.720270. (Human Brain Project).

Participants

Sean Hill, Krembil Centre for Neuroinformatics, CAMH, Chair
Andrew Davison, CNRS, Human Brain Project, Chair
Anna-Kristin Kaufmann, EPFL, Blue Brain Project
Huanxiang Lu, EPFL, Blue Brain Project
Tom Gillespie, UCSD, Neuroscience Information Framework
Genrich Ivaska, EPFL, Blue Brain Project
Oliver Schmid, EPFL, Human Brain Project
Jean-Denis Courcol, EPFL, Blue Brain Project
Samuel Kerrien, EPFL, Blue Brain Project
Jeff Muller, EPFL, Human Brain Project
Mohameth François Sy, EPFL, Blue Brain Project, Co-Chair
Bogdan Roman, EPFL, Blue Brain Project
Pierre-Alexandre Fonta, EPFL, Blue Brain Project
Coste Benoît Jean-Albert, EPFL, Blue Brain Project
Taylor MacMillan, Krembil Centre for Neuroinformatics, CAMH
David Rotenberg, Krembil Centre for Neuroinformatics, CAMH
\ No newline at end of file