Changes for page kg-spatial-search
Last modified by oschmid on 2023/08/22 11:23
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... ... @@ -22,15 +22,12 @@ 22 22 23 23 = What data is registered in the spatial search? = 24 24 25 -Theoretically, all data which is anchored in their respective coordinate space can be registered in the KG Spatial Search. We currently provide ingestion pipelines for data annotated with the[[ locareJSON format>>https://github.com/blixilla/LocareJSON]]. Please note that complex, planar and volumetric geometries such as polyhedrons, spheres, etc. are translated into point clouds of a configurable density during the ingestion process to ensure better performance at query time for the cost for potential false-negatives in highly fine-granular queries. Please also note that currently only datasets can be registered for which the spatial location information is regarded to be non-sensitive from a GDPR perspective.25 +Theoretically, all data which is anchored in their respective coordinate space can be registered in the KG Spatial Search. We currently provide ingestion pipelines for data annotated with the[[ locareJSON format>>https://github.com/blixilla/LocareJSON]]. Please note that complex, planar and volumetric geometries such as polyhedrons, spheres, etc. are translated into point clouds of a configurable density during the ingestion process to ensure better performance at query time for the cost for potential false-negatives in highly fine-granular queries. 26 26 27 27 = How do I query the KG Spatial Search? = 28 28 29 - Simply use the API endpointat[[https:~~/~~/spatial.kg.ebrains.eu/api/>>https://spatial.kg.ebrains.eu/api/]] by running queries according to the following examples:29 +Go to 30 30 31 - 32 - 33 - 34 34 Theoretically, all data which is anchored in their respective coordinate space can be registered in the KG Spatial Search. We currently provide ingestion pipelines for data annotated with the[[ locareJSON format>>https://github.com/blixilla/LocareJSON]]. Please note that complex, planar and volumetric geometries such as polyhedrons, spheres, etc. are translated into point clouds of a configurable density during the ingestion process to ensure better performance at query time for the cost for potential false-negatives in highly fine-granular queries. 35 35 36 36