Nanopublication

ID

https://w3id.org/sciencelive/np/RAHSt0SAMA5XrHxNMDwauFeL_zVChpuSPbfyfTJwA2014
Formats

Content

@prefix this: <https://w3id.org/sciencelive/np/RAHSt0SAMA5XrHxNMDwauFeL_zVChpuSPbfyfTJwA2014> .
@prefix sub: <https://w3id.org/sciencelive/np/RAHSt0SAMA5XrHxNMDwauFeL_zVChpuSPbfyfTJwA2014/> .
@prefix np: <http://www.nanopub.org/nschema#> .
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix prov: <http://www.w3.org/ns/prov#> .
@prefix npx: <http://purl.org/nanopub/x/> .
@prefix dc: <http://purl.org/dc/terms/> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .

sub:Head {
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    np:hasProvenance sub:provenance;
    np:hasPublicationInfo sub:pubinfo .
}

sub:assertion {
  <https://w3id.org/np/RA5e5XeXy_-aNK5giB7kBAEQslTLVydHeM4YYEzhmEE2w/comparatorGroup>
    dc:description "The Normalized Difference Water Index (NDWI), the standard remote-sensing index for delineating surface water from green and near-infrared reflectance." .
  
  <https://w3id.org/np/RA5e5XeXy_-aNK5giB7kBAEQslTLVydHeM4YYEzhmEE2w/interventionGroup>
    dc:description "A deep-learning nucleus/boundary-segmentation model from the BioImage Model Zoo, originally trained on fluorescence-microscopy images of cell nuclei, applied without retraining to the satellite imagery through a Galaxy BioImage.IO inference workflow — i.e. a cross-discipline transfer of a bioimaging segmentation model to remote sensing." .
  
  <https://w3id.org/np/RA5e5XeXy_-aNK5giB7kBAEQslTLVydHeM4YYEzhmEE2w/outcomeGroup> dc:description
      "Delineation of open-water bodies — the total water area and the count of distinct water bodies — and the degree to which these agree with the NDWI baseline." .
  
  <https://w3id.org/np/RA5e5XeXy_-aNK5giB7kBAEQslTLVydHeM4YYEzhmEE2w/population> dc:description
      "Optical multispectral satellite imagery of landscapes containing many small open-water bodies — here Landsat surface-reflectance scenes of the Arctic Coastal Plain of northern Alaska, a terrain dense with thermokarst ponds." .
  
  sub:bmz-nuclei-model-eo-water a <http://data.cochrane.org/ontologies/pico/PICO>, <https://w3id.org/sciencelive/o/terms/EffectivenessResearchQuestions>;
    <http://data.cochrane.org/ontologies/pico/comparatorGroup> <https://w3id.org/np/RA5e5XeXy_-aNK5giB7kBAEQslTLVydHeM4YYEzhmEE2w/comparatorGroup>;
    <http://data.cochrane.org/ontologies/pico/interventionGroup> <https://w3id.org/np/RA5e5XeXy_-aNK5giB7kBAEQslTLVydHeM4YYEzhmEE2w/interventionGroup>;
    <http://data.cochrane.org/ontologies/pico/outcomeGroup> <https://w3id.org/np/RA5e5XeXy_-aNK5giB7kBAEQslTLVydHeM4YYEzhmEE2w/outcomeGroup>;
    <http://data.cochrane.org/ontologies/pico/population> <https://w3id.org/np/RA5e5XeXy_-aNK5giB7kBAEQslTLVydHeM4YYEzhmEE2w/population>;
    dc:description "In Landsat satellite imagery of an Arctic thermokarst-pond landscape, does a BioImage Model Zoo nucleus-segmentation deep-learning model applied without retraining through a Galaxy BioImage.IO workflow, compared with the standard NDWI water index, delineate open-water bodies with a comparable total water area and number of distinct bodies?";
    <http://www.w3.org/2000/01/rdf-schema#label> "Can a bioimaging nucleus-segmentation model segment open water in satellite imagery via Galaxy?" .
}

sub:provenance {
  sub:assertion prov:wasAttributedTo <https://orcid.org/0000-0002-1784-2920> .
}

sub:pubinfo {
  <https://orcid.org/0000-0002-1784-2920> <http://xmlns.com/foaf/0.1/name> "Anne Fouilloux" .
  
  this: dc:created "2026-06-21T09:17:03.296Z"^^xsd:dateTime;
    dc:creator <https://orcid.org/0000-0002-1784-2920>;
    dc:license <https://creativecommons.org/licenses/by/4.0/>;
    npx:introduces sub:bmz-nuclei-model-eo-water;
    npx:wasCreatedAt <https://platform.sciencelive4all.org>;
    <http://www.w3.org/2000/01/rdf-schema#label> "Can a bioimaging nucleus-segmentation model segment open water in satellite imagery via Galaxy?";
    <https://w3id.org/np/o/ntemplate/wasCreatedFromTemplate> <https://w3id.org/np/RA5e5XeXy_-aNK5giB7kBAEQslTLVydHeM4YYEzhmEE2w> .
  
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    npx:signedBy <https://orcid.org/0000-0002-1784-2920> .
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