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...	...	@@ -28,9 +28,10 @@
28	28
29	29	Simply use the API endpoint at [[https:~~/~~/spatial.kg.ebrains.eu/api/>>https://spatial.kg.ebrains.eu/api/]] by running queries according to the following examples:
30	30
31		-== Get started: Query by a "bounding box" (hyperrectangle) ==
32	32
33		-{{code language="bash" layout="LINENUMBERS"}}
	32	+==== Get started: Query by a "bounding box" (hyperrectangle) ====
	33	+
	34	+{{code}}
34	34	curl -X 'POST' \
35	35	'https://spatial.kg.ebrains.eu/spatial-search/cores/ebrains/spatial_objects' \
36	36	-H 'accept: application/json' \
...	...	@@ -42,11 +42,12 @@
42	42
43	43	As you can see, you're sending a POST request to the endpoint at **https:~/~/spatial.kg.ebrains.eu/spatial-search/cores/ebrains/spatial_objects  **with a payload defining a geometry of interest. In this case, we're looking for all objects that are **inside **a **hyperrectangle **defined by its lowest and highest point in the coordinate system of the coordinate space **AMB-CCF_v3-RAS**. This query will return you an array of ids of the objects located within the geometry which you then can use to conveniently query the KG either through the [[Instance API>>https://core.kg.ebrains.eu/swagger-ui/index.html#/2%20Advanced/getInstancesByIds]] or the [[Query API>>https://core.kg.ebrains.eu/swagger-ui/index.html#/1%20Basic/runDynamicQuery]] to access detailed meta information.
44	44
45		-== Query by hypersphere ==
46	46
	47	+==== Query by hypersphere ====
	48	+
47	47	Alongside the possibility to use hyperrectangles for querying the spatial search, you can also use hyperspheres:
48	48
49		-{{code language="javascript" layout="LINENUMBERS"}}
	51	+{{code}}
50	50	{
51	51	"filters": "inside(hypersphere{[50.0,146.0,227.0], 2, \"AMB-CCF_v3-RAS\"})"
52	52	}
...	...	@@ -54,28 +54,28 @@
54	54
55	55	It is defined by the center of the sphere with its coordinates, the radius in coordinate units and the coordinate space of the given coordinates (in this case again AMB-CCF_v3-RAS)
56	56
57		-== Advanced use: Union geometries for complex queries ==
58	58
	60	+
	61	+==== Advanced use: Union geometries for complex queries ====
	62	+
59	59	To build arbitrarily complex geometries, it is possible to combine hyperrectangles and hyperspheres via (nested) unions:
60	60
61		-{{code language="javascript" layout="LINENUMBERS"}}
	65	+{{code}}
62	62	{
63		- "filters": "union(union(inside(hyperrectangle{[50.0,146.0,227.0], [51.0, 149.0, 228.0], \"AMB-CCF_v3-RAS\"}), inside(hyperrectangle{[120.0,146.0,227.0], [150.0, 180.0, 300.0], \"AMB-CCF_v3-RAS\"})),inside(hypersphere{[50.0,146.0,227.0], 2, \"AMB-CCF_v3-RAS\"}))"
	67	+ "filters": "
	68	+ union(
	69	+ union(
	70	+ inside(hyperrectangle{[50.0,146.0,227.0], [51.0, 149.0, 228.0], \"AMB-CCF_v3-RAS\"}),
	71	+ inside(hyperrectangle{[120.0,146.0,227.0], [150.0, 180.0, 300.0], \"AMB-CCF_v3-RAS\"})
	72	+ ),
	73	+ inside(hypersphere{[50.0,146.0,227.0], 2, \"AMB-CCF_v3-RAS\"})
	74	+ )"
64	64	}
65	65	{{/code}}
66	66
67	67
68		-= Technical details of the ingestion pipeline =
69	69
70		-The current pipeline is regularly parsing locareJSON files registered in the KG.
71	71
72		-* Points are translated to the data structure of spatial search without manipulation
73		-* Polyhedrons are translated via the [[vtk>>https://pypi.org/project/vtk/]] library into a point cloud of (currently) a density of 1 coordinate unit (by ray-casting on an obb-tree)
74		-* Other geometries are work-in-progress
75		-
76		-The resulting files (all representing point-clouds) as well as the space definitions are uploaded to the [[bucket of this collab>>https://wiki.ebrains.eu/bin/view/Collabs/kg-spatial-search/Bucket]]. A cron job running on the spatial search server pulls the files from the repo and rebuilds the databases index in regular intervals.
77		-
78		-
79	79
80	80	)))
81	81