Open AhmetNSimsek opened 1 year ago
I would argue, the name should be concise but descriptive enough for user of siibra-python
Naming examples for queries with the region siibra.get_region("2.9", 'hoc1 left')
as of 0.4a59 - dfce6eccb9bd36659125b390a8e2ca3c256ea002:
(Ebrains query)
(gene=siibra.vocabularies.GENE_ NAMES.GABARAP
)
For the other voi:
Querry for julich brain 2.9 parcellation:
Dev meeting 07.12.2023 update:
Several attributes describing siibra concepts are not necessarily clearly defined. The table below shows what it should be and the restrictions on the attributes.
Concept | Name | Shortname | key | id | description |
---|---|---|---|---|---|
Atlas | title of a panel or a window | to label UI elements | autocompletion and registry at run time | to encode the state | |
Parcellation | title of a panel or a window | to label UI elements | autocompletion and registry at run time | to encode the state | |
Region | title of a panel or a window | ||||
Parc map | title of a panel or a window | autocompletion and registry at run time | |||
Space | title of a panel or a window | to label UI elements | autocompletion and registry at run time | to encode the state | |
Feature | title of a panel or a window | search lists and title on side bar | to encode the state | ||
style | human readable | human readable | upper case wo special chars | uuid and persistent | human readable |
length | 120 chrs or so: important words show up in truncated version too | fits to the chips | not constrained | a paragraph |
see features names in version v0.4a59 see features names in version 1.0a05
Names as of v1.0a05 (see comment for v.04a59)
CompoundFeature of 1579 BigBrainIntensityProfile features grouped by (Modified silver staining modality) anchored at Area hOc1 (V1, 17, CalcS) left with Set of 1579 points in the Bounding box from (-63.69,-59.94,-29.09) mm to (0.91,77.90,54.03)mm in BigBrain microscopic template (histology) space
CompoundFeature of 10 CellDensityProfile features grouped by (Segmented cell body density modality) anchored at Area hOc1 (V1, 17, CalcS) with Set of 10 points in the Bounding box from (-3.95,-65.80,-0.44) mm to (20.20,-42.70,9.71)mm in BigBrain microscopic template (histology) space
CompoundFeature of 16 ReceptorDensityProfile features grouped by (Receptor density modality) anchored at Area hOc1 (V1, 17, CalcS)
LayerwiseBigBrainIntensities (Modified silver staining) anchored at Area hOc1 (V1, 17, CalcS) left with Set of 1579 points in the Bounding box from (-63.69,-59.94,-29.09) mm to (0.91,77.90,54.03)mm in BigBrain microscopic template (histology) space
LayerwiseCellDensity (Cell body density) anchored at Area hOc1 (V1, 17, CalcS) with Set of 10 points in the Bounding box from (-3.95,-65.80,-0.44) mm to (20.20,-42.70,9.71)mm in BigBrain microscopic template (histology) space
The Enriched Connectome - Block face images of full sagittal human brain sections (blockface)
CHENONCEAU: dti fractional anisotropy - 200um (DTI)
VOI2: Cellular level 3D reconstructed volumes at 1µm resolution within the BigBrain occipital cortex (v1.0) (cell body staining)
(Ebrains query)
(gene=siibra.vocabularies.GENE_ NAMES.GABARA
)
(Connectivity for Julich Brain 3.0)
(gene=siibra.vocabularies.GENE_ NAMES.GABARAP
)
GABARAP gene expression in 64 points in ([-17.00,-99.00,-7.00], [0.06,-59.00,14.00])mm in ICBM 2009c nonl asym
Layerwise modified silver staining at 1579 points in ([-63.69,-59.94,-29.09], [0.91,77.90,54.03])mm on BigBrain assigned to Area hOc1 (V1, 17, CalcS) left of Julich Brain 2.9
Layerwise cell body density anchored at 10 points in ([-3.95,-65.80,-0.44], [20.20,-42.70,9.71])mm on BigBrain assigned to Area hOc1 (V1, 17, CalcS) left of Julich Brain 2.9
Section 47: 1-micron cell-body-staining scans of BigBrain (v1.0)
The Enriched Connectome - Block face images of full sagittal human brain sections
CHENONCEAU: DTI fractional anisotropy - 200um
(Connectivity for Julich Brain 3.0)
(Ebrains query)
n.b. changing names will change the feature id.
This invalidates all URLs that has feature selected.
as discussed with @AhmetNSimsek :
id
attribute to the preconfigure json. This id will be derived from the id as they appear in siibra-python v0.4a<latest>
Also to consider: how to more efficiently encode the id of compound/live query feature
Are the suggestions above for the name
attribute?
I think we have to suggest the complete picture of all necessary attributes, building on the table from Dec 7 where we outlines the use of the different properties. I suggest to expand the suggestions above into a table, with columns "name", "shortname", "description".
One particular issue is in my eyes, whether the location information is needed in the name at all. I think the location (assigned region, coordinate[s], bounding box) could well be a separate attribute, or be requested from the str representation of the anatomical anchors when needed. The question is wether the location is required in the name to disambiguate in any of the relevant use cases.
re: if location is needed at all in name
and/or shortname
attribute
correct me if I am wrong, but in some cases, the location is the only differentiator, e.g. big brain cell intensity (?)
ping @AhmetNSimsek
Are the suggestions above for the
name
attribute?
Yes since the explorer currently uses the name
property to populate the text for a feature. Ideally, we should define and discuss all. However, this is currently a blocking issue for the release of next siibra-explorer version (which includes some improvements along with compound features (so F-Tract as well)). Therefore, we wanted to start "small" and go for a release ASAP.
One particular issue is in my eyes, whether the location information is needed in the name at all. I think the location (assigned region, coordinate[s], bounding box) could well be a separate attribute, or be requested from the str representation of the anatomical anchors when needed. The question is wether the location is required in the name to disambiguate in any of the relevant use cases.
There are features that has an anchor with location only. Therefore, distinguishing them is impossible without the location information. We could remedy this by indexing the points for example, i.e., "Modified silver staining intensity - point #1" (since it will be a compound feature). (Then the user can check the exact location by location
property.) BUT this is not a guaranteed for features to be introduced in the future.
I think we have to suggest the complete picture of all necessary attributes, building on the table from Dec 7 where we outlines the use of the different properties. I suggest to expand the suggestions above into a table, with columns "name", "shortname", "description".
Concept | Name | Shortname | key | id | description |
---|---|---|---|---|---|
CF BigBrainIntensityProfile | 1579 modified silver staining profiles - Area hOc1 (V1, 17, CalcS) left, 1579 points in ([-63.69,-59.94,-29.09], [0.91,77.90,54.03])mm in BigBrain | ||||
GeneExpression | GABARAP gene expression in 64 points in ([-17.00,-99.00,-7.00], [0.06,-59.00,14.00])mm in ICBM 2009c nonl asym | ||||
LayerwiseBigBrainIntensity | Layerwise cell body density anchored at 10 points in ([-3.95,-65.80,-0.44], [20.20,-42.70,9.71])mm on BigBrain assigned to Area hOc1 (V1, 17, CalcS) left of Julich Brain 2.9 | ||||
Sections | Section 47: 1-micron cell-body-staining scans of BigBrain (v1.0) | ||||
BlockfaceVOI | The Enriched Connectome - Block face images of full sagittal human brain sections | ||||
CF AnatomoFunctionalConnectivity | 78 anatomo functional connectivity matrices for Julich-Brain 3.0.3 - cohort: adult pharmaco-resistant focal epilepsy patients | ||||
AnatomoFunctionalConnectivity | P_01: amplitude__mad anatomo functional connectivity for Julich-Brain 3.0.3 - cohort: adult pharmaco-resistant focal epilepsy patients | ||||
CF FunctionalConnectivity | 200 functional connectivity matrices for Julich-Brain 3.0.3 - cohort: HCP, paradigm: Resting state (EmpCorrFC concatenated) | ||||
FunctionalConnectivity | Subject 000 functional connectivity for Julich-Brain 3.0.3 - cohort: HCP, paradigm: Resting state (EmpCorrFC concatenated) | ||||
EbrainsDataset | Ebrains Dataset: CEREBRUM-7T: Fast and Fully-volumetric Brain Segmentation of 7 Tesla MR Volumes (v1) | ||||
ReceptorDensityFingerprint | 16 receptor density profiles - Area hOc1 (V1, 17, CalcS) | ||||
ReceptorDensityProfile | 5-HT1A receptor density profile - Area hOc1 (V1, 17, CalcS) |
Each feature name should be informative but as brief as possible especially considering the display in the explorer.
EDT: Feature names need to be reworked for the next release of siibra-explorer