¶
16.15.4. GEO Spatial Examples
¶
Example 1
## Get All Stuff For Given Coordinates
SQL>SPARQL
SELECT ?c COUNT (*)
WHERE
{
?m geo:geometry ?geo .
?m a ?c .
FILTER (bif:st_intersects (?geo, bif:st_point (0, 52), 100))
}
GROUP BY ?c
ORDER BY desc 2;
c callret-1
VARCHAR VARCHAR
_______________________________________________________________________________
http://linkedgeodata.org/vocabulary#node 2317684
http://linkedgeodata.org/vocabulary#way 85315
http://linkedgeodata.org/vocabulary#building 14257
http://dbpedia.org/class/yago/Landmark108624891 9093
http://linkedgeodata.org/vocabulary#wood 7155
....
¶
Example 2
## Get City Stuff Around Catholic Churches In Paris
SQL>
SPARQL
SELECT ?m (bif:st_distance (?geo, bif:st_point (0, 52)))
WHERE
{
?m geo:geometry ?geo .
?m a <http://dbpedia.org/ontology/City> .
FILTER (bif:st_intersects (?geo, bif:st_point (0, 52), 30))
}
ORDER BY DESC 2
LIMIT 20;
m callret-1
VARCHAR VARCHAR
_______________________________________________________________________________
http://dbpedia.org/resource/Stansted_Mountfitchet 39.13180985471543
http://dbpedia.org/resource/Stansted_Mountfitchet 39.13180985471543
http://dbpedia.org/resource/Stansted_Mountfitchet 39.13180985471543
http://dbpedia.org/resource/Stansted_Mountfitchet 39.13180985471543
http://dbpedia.org/resource/Stansted_Mountfitchet 37.36907252285992
http://dbpedia.org/resource/Stansted_Mountfitchet 34.49432513061792
http://dbpedia.org/resource/Stansted_Mountfitchet 33.7676326404143
http://dbpedia.org/resource/Stansted_Mountfitchet 33.24238654570499
http://dbpedia.org/resource/Stansted_Mountfitchet 32.60139660515003
http://dbpedia.org/resource/Stansted_Mountfitchet 32.60139660515003
http://dbpedia.org/resource/Stansted_Mountfitchet 31.45681319171456
http://dbpedia.org/resource/Stansted_Mountfitchet 31.115377038
http://dbpedia.org/resource/Stansted_Mountfitchet 31.115377038
http://dbpedia.org/resource/Stansted_Mountfitchet 30.56388658524301
http://dbpedia.org/resource/Stansted_Mountfitchet 29.89662974046085
http://dbpedia.org/resource/Stansted_Mountfitchet 29.85090625132639
http://dbpedia.org/resource/Stansted_Mountfitchet 29.82605254366244
http://dbpedia.org/resource/Stansted_Mountfitchet 29.60102064794003
http://dbpedia.org/resource/Stansted_Mountfitchet 29.44147385851453
http://dbpedia.org/resource/Stansted_Mountfitchet 29.421242437379
¶
Example 3
## Get City Stuff Around Catholic Churches In Paris Extended
SQL>
SPARQL
SELECT ?m (bif:st_distance (?geo, bif:st_point (0, 52)))
WHERE
{
?m geo:geometry ?geo .
?m a <http://dbpedia.org/ontology/City> .
FILTER (bif:st_intersects (?geo, bif:st_point (0, 52), 100))
}
ORDER BY DESC 2
LIMIT 20;
m callret-1
VARCHAR VARCHAR
_______________________________________________________________________________
http://dbpedia.org/resource/Weston-on-Trent 138.7082197019335
http://dbpedia.org/resource/Weston-on-Trent 137.7213767969613
http://dbpedia.org/resource/Weston-on-Trent 136.4597167847218
http://dbpedia.org/resource/Weston-on-Trent 134.1807668663677
http://dbpedia.org/resource/Weston-on-Trent 133.104337839536
http://dbpedia.org/resource/Weston-on-Trent 133.104337839536
http://dbpedia.org/resource/Nonington 132.7368236183588
http://dbpedia.org/resource/Nonington 132.1339163200362
http://dbpedia.org/resource/Nonington 132.1339163200362
http://dbpedia.org/resource/Nonington 130.5478483560461
http://dbpedia.org/resource/Nonington 130.1620410981843
http://dbpedia.org/resource/Nonington 129.8549842943355
http://dbpedia.org/resource/Nonington 129.6459280567849
http://dbpedia.org/resource/Nonington 129.4504858595742
http://dbpedia.org/resource/Nonington 129.2790713235814
http://dbpedia.org/resource/Nonington 128.9081040147881
http://dbpedia.org/resource/Nonington 128.8845164618929
http://dbpedia.org/resource/Nonington 128.6676189617872
http://dbpedia.org/resource/Nonington 128.2565253458452
http://dbpedia.org/resource/Nonington 128.2551696344652
20 Rows. -- 120 msec.
¶
Example 4
## Text Or Geo
SQL>
SPARQL
SELECT ?c COUNT (*)
WHERE
{
?m geo:geometry ?geo .
?m a ?c .
FILTER (bif:st_intersects (?geo, bif:st_point (0, 52), 100) && REGEX (str (?c), "London") )
}
GROUP BY ?c
ORDER BY DESC 2
LIMIT 10;
c callret-1
____________________________________________________________________________
http://dbpedia.org/class/yago/DistrictsOfLondon 861
http://dbpedia.org/class/yago/GradeIListedBuildingsInLondon 199
http://dbpedia.org/class/yago/MuseumsInLondon 107
http://dbpedia.org/class/yago/ArtMuseumsAndGalleriesInLondon 92
http://dbpedia.org/class/yago/GradeIIListedBuildingsInLondon 89
http://dbpedia.org/class/yago/SportsVenuesInLondon 80
http://dbpedia.org/class/yago/RoyalBuildingsInLondon 72
http://dbpedia.org/class/yago/LondonOvergroundStations 69
http://dbpedia.org/class/yago/NationalGovernmentBuildingsInLondon 69
http://dbpedia.org/class/yago/SkyscrapersInLondon 60
¶
Example 5
## Example "Places Of Worship, Within 5 km Of Paris":
## Describes places of worship, within 5 km of Paris,
## that have cafes in close proximity(0.2 km).
## The query requires V6 or higher.
SQL>
PREFIX lgv: <http://linkedgeodata.org/vocabulary#>
DESCRIBE ?cafe ?church
WHERE
{
?church a lgv:place_of_worship .
?church geo:geometry ?churchgeo .
?church lgv:name ?churchname .
?cafe a lgv:cafe .
?cafe lgv:name ?cafename .
?cafe geo:geometry ?cafegeo .
?cafe geo:lat ?lat .
?cafe geo:long ?long .
FILTER ( bif:st_intersects ( ?churchgeo, bif:st_point ( 2.3498, 48.853 ), 5 ) &&
bif:st_intersects ( ?cafegeo, ?churchgeo, 0.2 ) )
}
LIMIT 10;
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix ns1: <http://linkedgeodata.org/triplify/node/243360870#> .
@prefix ns2: <http://linkedgeodata.org/vocabulary#> .
ns1:id rdf:type ns2:place_of_worship ,
ns2:node .
@prefix geo: <http://www.w3.org/2003/01/geo/wgs84_pos#> .
ns1:id geo:lat 48.8794 ;
geo:long 2.3748 ;
ns2:created_by "Potlatch 0.6c" ;
ns2:name "Saint-Georges de la Villette" ;
ns2:religion "christian" ,
ns2:christian .
@prefix virtrdf: <http://www.openlinksw.com/schemas/virtrdf#> .
ns1:id geo:geometry "POINT(2.3748 48.8794)"^^virtrdf:Geometry .
@prefix ns5: <http://linkedgeodata.org/triplify/node/266632049#> .
ns5:id rdf:type ns2:node ,
ns2:cafe ;
geo:lat 48.8518 ;
geo:long 2.325 ;
ns2:created_by "Potlatch 0.9a" ;
ns2:name "Le Babylone" ;
geo:geometry "POINT(2.325 48.8518)"^^virtrdf:Geometry .
....
¶
Example 6
## Count Geo
SQL>
SPARQL
SELECT ?c COUNT (*)
WHERE
{
?s geo:geometry ?geo .
FILTER (bif:st_intersects (?geo, bif:st_point (2.3498, 48.853), 5)) .
?s a ?c
}
GROUP BY ?c
ORDER BY desc 2
LIMIT 10;
c callret-1
VARCHAR VARCHAR
_______________________________________________________________________________
http://linkedgeodata.org/vocabulary#node 37792
http://dbpedia.org/class/yago/Landmark108624891 4003
http://linkedgeodata.org/vocabulary#way 1688
http://linkedgeodata.org/vocabulary#building 719
http://linkedgeodata.org/vocabulary#station 257
http://linkedgeodata.org/vocabulary#post_box 247
http://www.w3.org/2002/07/owl#Thing 227
http://linkedgeodata.org/vocabulary#park 208
http://linkedgeodata.org/vocabulary#restaurant 198
http://dbpedia.org/ontology/Place 192
10 Rows. -- 932 msec.
¶
Example 7
## Get Stuff Around Notre Dame De Paris
SQL>
SPARQL
SELECT ?c COUNT (*)
WHERE
{
?s a ?c .
?s geo:geometry ?geo .
FILTER (bif:st_intersects (?geo, bif:st_point (2.3498, 48.853), 0.3))
}
GROUP BY ?c
ORDER BY desc 2
LIMIT 10;
c callret-1
VARCHAR VARCHAR
_______________________________________________________________________________
http://linkedgeodata.org/vocabulary#node 408
http://dbpedia.org/class/yago/Landmark108624891 134
http://linkedgeodata.org/vocabulary#way 17
http://dbpedia.org/class/yago/RomanCatholicChurchesInParis 17
http://dbpedia.org/class/yago/TallBuildingsAndStructuresInParis 13
http://dbpedia.org/class/yago/CathedralsInFrance 13
http://sw.opencyc.org/2008/06/10/concept/Mx4rvVigPpwpEbGdrcN5Y29ycA 13
http://sw.opencyc.org/2008/06/10/concept/Mx4rjm5QanS6EdaAAACgyZzFrg 13
http://sw.opencyc.org/2008/06/10/concept/Mx4rwQwtGpwpEbGdrcN5Y29ycA 13
http://www.w3.org/2002/07/owl#Thing 10
10 Rows. -- 241 msec.
¶
Example 8
## Things within 10 km proximity of place of worship
SQL>
SPARQL
PREFIX lgv: <http://linkedgeodata.org/vocabulary#>
SELECT ?c COUNT (*)
WHERE
{
?s a ?c .
?s a lgv:place_of_worship .
?s geo:geometry ?geo .
FILTER (bif:st_intersects (?geo, bif:st_point (2.3498, 48.853), 10))
}
GROUP BY ?c
ORDER BY desc 2
LIMIT 10;
c callret-1
VARCHAR VARCHAR
_______________________________________________________________________________
http://linkedgeodata.org/vocabulary#place_of_worship 147
http://linkedgeodata.org/vocabulary#node 146
http://linkedgeodata.org/vocabulary#way 46
http://linkedgeodata.org/vocabulary#building 36
http://linkedgeodata.org/vocabulary#attraction 3
http://linkedgeodata.org/vocabulary#church 1
6 Rows. -- 120 msec.
¶
Example 9
## Get Stuff Around Notre Dame De Paris with Names
SQL>
SPARQL
PREFIX lgv: <http://linkedgeodata.org/vocabulary#>
SELECT ?cn
WHERE
{
?s lgv:name ?cn .
?s geo:geometry ?geo .
FILTER (bif:st_intersects (?geo, bif:st_point (2.3498, 48.853), 0.3))
}
LIMIT 20;
cn
VARCHAR
_______________________________________________________________________________
Parking Lagrange
Maitre Albert B&B
Le Grenier de Notre Dame
Eglise Saint-Julien-le-Pauvre
Eglise Saint Julien le Pauvre
Polly Magoo
Point 0 des Routes de France
Square Jean XXIII
....
20 Rows. -- 140 msec.
¶
Example 10
## Get Churches With The Most Bars
SQL>
SPARQL
PREFIX lgv: <http://linkedgeodata.org/vocabulary#>
SELECT ?churchname ?cafename (bif:st_distance (?churchgeo, ?cafegeo))
WHERE
{
?church a lgv:place_of_worship .
?church geo:geometry ?churchgeo .
?church lgv:name ?churchname .
?cafe a lgv:cafe .
?cafe lgv:name ?cafename .
?cafe geo:geometry ?cafegeo .
FILTER (bif:st_intersects (?churchgeo, bif:st_point (2.3498, 48.853), 5)
&& bif:st_intersects (?cafegeo, ?churchgeo, 0.2))
}
LIMIT 10;
churchname cafename callret-2
VARCHAR VARCHAR VARCHAR
_______________________________________________________________________________
Eglise Saint-Julien-le-Pauvre Le Saint R+?-?gis 0.09759308692691648
Eglise Saint-Germain des Pr+?-?s Caf+?-? de Flore 0.08774468391412803
Eglise Saint-Germain des Pr+?-?s Les Deux Magots 0.05235923473923059
Eglise Saint-Germain des Pr+?-?s Caf+?-? Mabillon 0.1712042770289815
Eglise Saint-Germain-des-Pr+?-?s Caf+?-? de Flore 0.1466502865197912
Eglise Saint-Germain-des-Pr+?-?s Les Deux Magots 0.1096767137079839
Eglise Saint-Germain-des-Pr+?-?s Bar du march+?-? 0.1831441251868126
Eglise Saint-Germain-des-Pr+?-?s Caf+?-? Mabillon 0.1174051745495528
Synagogue La Chaise au Plafond 0.1038387283609551
Synagogue Le Loir dans la Th+?-?i+?-?re 0.1632848322062273
10 Rows. -- 511225 msec.
¶
Example 11
## Things around highly populated places
SQL>
SPARQL
SELECT ?s ( sql:num_or_null (?o) ) COUNT (*)
WHERE
{
?s <http://dbpedia.org/ontology/populationTotal> ?o .
FILTER ( sql:num_or_null (?o) > 6000000 ) .
?s geo:geometry ?geo .
FILTER ( bif:st_intersects (?pt, ?geo,2) ) .
?xx geo:geometry ?pt
}
GROUP BY ?s ( sql:num_or_null (?o) )
ORDER BY desc 3
LIMIT 20;
s callret-1 callret-2
VARCHAR VARCHAR VARCHAR
_______________________________________________________________________________
http://dbpedia.org/resource/London 7556900 312307
http://dbpedia.org/resource/Toronto 8102163 115859
http://dbpedia.org/resource/New_York_City 8363710 95629
http://dbpedia.org/resource/The_Hague 6659300 84410
http://dbpedia.org/resource/Tokyo 12790000 78618
http://dbpedia.org/resource/Philadelphia 6385461 67115
http://dbpedia.org/resource/Los_Angeles 17755322 64394
http://dbpedia.org/resource/Bangkok 8160522 62519
http://dbpedia.org/resource/Barcelona 2147483648 57635
http://dbpedia.org/resource/Cairo 6758581 52738
http://dbpedia.org/resource/Istanbul 12697164 50745
http://dbpedia.org/resource/Seoul 10421782 43962
http://dbpedia.org/resource/Beijing 17430000 35979
http://dbpedia.org/resource/Purmerend 6659300 33508
http://dbpedia.org/resource/Baghdad 6554126 33426
http://dbpedia.org/resource/Bogot%C3%A1 6776009 30429
http://dbpedia.org/resource/Mexico_City 8836045 30127
http://dbpedia.org/resource/Jakarta 8500000 28944
http://dbpedia.org/resource/Boston 7514759 27705
http://dbpedia.org/resource/Baden-W%C3%BCrttemberg 10755000 25112
20 Rows. -- 4296 msec.
¶
Example 12
## Example "Places Of Worship, Within 5 km Of Paris":
## Constructs a custom Linked Data Mesh (graph) about
## places of worship, within 5 km of Paris, that have
## cafes in close proximity(0.2 km).
## Note: we have distinct pin colors that identify
## for places of worship distinct from cafes.
## The query requires V6 or higher.
SQL>
SPARQL
PREFIX lgv: <http://linkedgeodata.org/vocabulary#>
PREFIX rtb: <http://www.openlinksw.com/schemas/oat/rdftabs#>
CONSTRUCT
{
?cafe geo:geometry ?cafegeo ;
rtb:useMarker '01' ;
lgv:name ?cafename .
?church geo:geometry ?churchgeo ;
rtb:useMarker '02' ;
lgv:name ?churchname .
}
WHERE
{
?church a lgv:place_of_worship .
?church geo:geometry ?churchgeo .
?church lgv:name ?churchname .
?cafe a lgv:cafe .
?cafe lgv:name ?cafename .
?cafe geo:geometry ?cafegeo .
?cafe geo:lat ?lat .
?cafe geo:long ?long .
FILTER ( bif:st_intersects ( ?churchgeo, bif:st_point ( 2.3498, 48.853 ), 5 ) &&
bif:st_intersects ( ?cafegeo, ?churchgeo, 0.2 ) )
}
LIMIT 10;
@prefix ns0: <http://linkedgeodata.org/vocabulary#> .
@prefix ns1: <http://linkedgeodata.org/triplify/node/237435716#> .
ns1:id ns0:name "Chapelle du Val de Gr\u00C3\u00A2ce" .
@prefix ns2: <http://www.openlinksw.com/schemas/oat/rdftabs#> .
ns1:id ns2:useMarker "02" .
@prefix virtrdf: <http://www.openlinksw.com/schemas/virtrdf#> .
@prefix geo: <http://www.w3.org/2003/01/geo/wgs84_pos#> .
ns1:id geo:geometry "POINT(2.3418 48.8406)"^^virtrdf:Geometry .
@prefix ns5: <http://linkedgeodata.org/triplify/node/218147750#> .
ns5:id ns0:name "Synagogue" ;
ns2:useMarker "02" ;
geo:geometry "POINT(2.3593 48.857)"^^virtrdf:Geometry .
@prefix ns6: <http://linkedgeodata.org/triplify/node/218145208#> .
ns6:id ns0:name "Synagogue" ;
ns2:useMarker "02" ;
geo:geometry "POINT(2.3589 48.8567)"^^virtrdf:Geometry .
...
¶
Example 13
## Example "Places Of Worship, Within 5 km Of Paris":
## Asks for places of worship, within 5 km of Paris,
## that have cafes in close proximity(0.2 km).
## The query requires V6 or higher.
SQL>
SPARQL
PREFIX lgv: <http://linkedgeodata.org/vocabulary#>
ASK
WHERE
{
?church a lgv:place_of_worship .
?church geo:geometry ?churchgeo .
?church lgv:name ?churchname .
?cafe a lgv:cafe .
?cafe lgv:name ?cafename .
?cafe geo:geometry ?cafegeo .
?cafe geo:lat ?lat .
?cafe geo:long ?long .
FILTER ( bif:st_intersects ( ?churchgeo, bif:st_point ( 2.3498, 48.853 ), 5 ) &&
bif:st_intersects ( ?cafegeo, ?churchgeo, 0.2 ) )
};
Done.
true
¶
Example 14
## Places of worship, within 5 km of Paris,
## that have cafes in close proximity(0.2 km)
SQL>
SPARQL
PREFIX lgv: <http://linkedgeodata.org/vocabulary#>
SELECT DISTINCT ?cafe ?lat ?long ?cafename ?churchname
(bif:round(bif:st_distance (?churchgeo, ?cafegeo)))
WHERE
{
?church a lgv:place_of_worship .
?church geo:geometry ?churchgeo .
?church lgv:name ?churchname .
?cafe a lgv:cafe .
?cafe lgv:name ?cafename .
?cafe geo:geometry ?cafegeo .
?cafe geo:lat ?lat.
?cafe geo:long ?long.
FILTER ( bif:st_intersects (?churchgeo, bif:st_point (2.3498, 48.853), 5) &&
bif:st_intersects (?cafegeo, ?churchgeo, 0.2) )
}
LIMIT 10;
cafe lat long cafename churchname callret-5
VARCHAR VARCHAR VARCHAR VARCHAR VARCHAR VARCHAR
_______________________________________________________________________________________________________________________________________________________________
http://linkedgeodata.org/triplify/node/321932192#id 48.8522 2.3484 Le Saint R+?-?gis Eglise Saint-Julien-le-Pauvre 0
http://linkedgeodata.org/triplify/node/251699776#id 48.8541 2.3326 Caf+?-? de Flore Eglise Saint-Germain des Pr+?-?s 0
http://linkedgeodata.org/triplify/node/251699775#id 48.854 2.3331 Les Deux Magots Eglise Saint-Germain des Pr+?-?s 0
http://linkedgeodata.org/triplify/node/315769036#id 48.8533 2.3358 Caf+?-? Mabillon Eglise Saint-Germain des Pr+?-?s 0
http://linkedgeodata.org/triplify/node/251699776#id 48.8541 2.3326 Caf+?-? de Flore Eglise Saint-Germain-des-Pr+?-?s 0
http://linkedgeodata.org/triplify/node/251699775#id 48.854 2.3331 Les Deux Magots Eglise Saint-Germain-des-Pr+?-?s 0
http://linkedgeodata.org/triplify/node/315769035#id 48.8539 2.3371 Bar du march+?-? Eglise Saint-Germain-des-Pr+?-?s 0
http://linkedgeodata.org/triplify/node/315769036#id 48.8533 2.3358 Caf+?-? Mabillon Eglise Saint-Germain-des-Pr+?-?s 0
http://linkedgeodata.org/triplify/node/251126326#id 48.8572 2.3577 La Chaise au Plafond Synagogue 0
http://linkedgeodata.org/triplify/node/251043135#id 48.8562 2.361 Le Loir dans la Th+?-?i+?-?re Synagogue 0
10 Rows. -- 120 msec.
¶
Example 15
## Stuff around Notre Dame de Paris
SQL>
SPARQL
PREFIX lgv: <http://linkedgeodata.org/vocabulary#>
SELECT ?s ?cn ?lat ?long
WHERE
{
?s lgv:name ?cn .
?s geo:geometry ?geo .
?s geo:lat ?lat.
?s geo:long ?long.
FILTER ( bif:st_intersects (?geo, bif:st_point (2.3498, 48.853), 0.3) )
}
LIMIT 20;
s cn lat long
VARCHAR VARCHAR VARCHAR VARCHAR
______________________________________________________________________________________________________________
http://linkedgeodata.org/triplify/node/237004656#id Parking Lagrange 48.8506 2.3487
http://linkedgeodata.org/triplify/node/237003117#id Mus+?-?e de l'Assistance Publique H+?-opitaux de Paris 48.8507 2.3519
http://linkedgeodata.org/triplify/way/23071565#id Jardin de la Rue de Bi+?-?vre 48.8504 2.3502
http://linkedgeodata.org/triplify/node/251652818#id Maitre Albert B&B 48.8507 2.3496
http://linkedgeodata.org/triplify/node/251373384#id Le Grenier de Notre Dame 48.8513 2.35
http://linkedgeodata.org/triplify/node/205266764#id Eglise Saint-Julien-le-Pauvre 48.852 2.3471
http://linkedgeodata.org/triplify/way/19741083#id Eglise Saint Julien le Pauvre 48.8521 2.3469
http://linkedgeodata.org/triplify/node/251474112#id Polly Magoo 48.8526 2.3467
http://linkedgeodata.org/triplify/node/251531803#id H+?-otel Esmerelda 48.8523 2.3468
http://linkedgeodata.org/triplify/node/191031796#id Point 0 des Routes de France 48.8533 2.3489
http://linkedgeodata.org/triplify/way/20444455#id Square Jean XXIII 48.8529 2.3511
http://linkedgeodata.org/triplify/way/19740745#id Square Ren+?-? Viviani 48.8525 2.3476
http://linkedgeodata.org/triplify/node/321932192#id Le Saint R+?-?gis 48.8522 2.3484
http://linkedgeodata.org/triplify/node/27440965#id Notre-Dame de Paris 48.853 2.3499
http://linkedgeodata.org/triplify/node/243461762#id Parking Notre-Dame 48.8537 2.3475
http://linkedgeodata.org/triplify/way/21816758#id Notre-Dame de Paris 48.8531 2.349
http://linkedgeodata.org/triplify/way/22972062#id La Seine 48.8538 2.3531
http://linkedgeodata.org/triplify/way/25463927#id La Seine 48.8548 2.3518
http://linkedgeodata.org/triplify/node/251128395#id H+?-otel Hospitel 48.854 2.3484
http://linkedgeodata.org/triplify/way/14155323#id H+?-otel Dieu 48.8555 2.3485
20 Rows. -- 167 msec.
¶
Example 16
## Stuff around Notre Dame de Paris
SQL>
SPARQL
PREFIX lgv: <http://linkedgeodata.org/vocabulary#>
DESCRIBE ?s
WHERE
{
?s lgv:name ?cn .
?s geo:geometry ?geo .
?s geo:lat ?lat.
?s geo:long ?long.
FILTER (bif:st_intersects (?geo, bif:st_point (2.3498, 48.853), 0.3))
}
LIMIT 20;
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix ns1: <http://linkedgeodata.org/triplify/node/27440966#> .
@prefix ns2: <http://linkedgeodata.org/vocabulary#> .
ns1:id rdf:type ns2:node ,
ns2:police .
@prefix geo: <http://www.w3.org/2003/01/geo/wgs84_pos#> .
ns1:id geo:lat 48.8542 ;
geo:long 2.3473 ;
ns2:created_by "Potlatch 0.6a" ;
ns2:name "Pr\u00C3\u00A9fecture de Police de Paris" ,
"Pr\u00E9fecture de Police de Paris" .
@prefix virtrdf: <http://www.openlinksw.com/schemas/virtrdf#> .
ns1:id geo:geometry "POINT(2.3473 48.8542)"^^virtrdf:Geometry .
@prefix ns5: <http://linkedgeodata.org/triplify/node/27440965#> .
ns5:id rdf:type ns2:node ,
ns2:place_of_worship ;
geo:lat 48.853 ;
geo:long 2.3499 ;
ns2:denomination "catholic" ;
ns2:name "Notre-Dame de Paris" ;
ns2:religion "christian" ,
ns2:christian ;
geo:geometry "POINT(2.3499 48.853)"^^virtrdf:Geometry .
......
¶
Example 17
## Cities within 30 km proximity of London
SQL>
SPARQL
SELECT ?m (bif:round(bif:st_distance (?geo, ?gm)))
WHERE
{
<http://dbpedia.org/resource/London> geo:geometry ?gm .
?m geo:geometry ?geo .
?m a <http://dbpedia.org/ontology/City> .
FILTER (bif:st_intersects (?geo, ?gm, 30))
}
ORDER BY DESC 2
LIMIT 20;
m callret-1
VARCHAR VARCHAR
____________________________________________________________
http://dbpedia.org/resource/Bletchingley 30
http://dbpedia.org/resource/Bletchingley 30
http://dbpedia.org/resource/Bletchingley 30
http://dbpedia.org/resource/Bletchingley 30
http://dbpedia.org/resource/Bletchingley 30
http://dbpedia.org/resource/Bletchingley 30
http://dbpedia.org/resource/Bletchingley 30
http://dbpedia.org/resource/Bletchingley 30
http://dbpedia.org/resource/Bletchingley 30
http://dbpedia.org/resource/Bletchingley 30
http://dbpedia.org/resource/Bletchingley 30
http://dbpedia.org/resource/Bletchingley 30
http://dbpedia.org/resource/Bletchingley 30
http://dbpedia.org/resource/Bletchingley 30
http://dbpedia.org/resource/Bletchingley 30
http://dbpedia.org/resource/Ebbsfleet_Valley 30
http://dbpedia.org/resource/Bletchingley 30
http://dbpedia.org/resource/Bletchingley 30
http://dbpedia.org/resource/Bletchingley 30
http://dbpedia.org/resource/Bletchingley 30
20 Rows. -- 727666 msec.
¶
Example 18
## Motorways across England & Scotland from DBpedia
SQL>
SPARQL
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX dbpprop: <http://dbpedia.org/property/>
PREFIX yago: <http://dbpedia.org/class/yago/>
SELECT ?road ?services ?lat ?long
WHERE
{
{
?services dbpprop:road ?road .
?road a yago:MotorwaysInEngland .
?services dbpprop:lat ?lat .
?services dbpprop:long ?long .
}
UNION
{
?services dbpprop:road ?road .
?road a yago:MotorwaysInScotland .
?services dbpprop:lat ?lat .
?services dbpprop:long ?long .
}
}
LIMIT 20;
road services lat long
VARCHAR VARCHAR VARCHAR VARCHAR
______________________________________________________________________________________________________________________________________
http://dbpedia.org/resource/M90_motorway http://dbpedia.org/resource/Kinross_services 56.209628 -3.439257
http://dbpedia.org/resource/M1_motorway http://dbpedia.org/resource/Leicester_Forest_East_services 52.6192 -1.206
http://dbpedia.org/resource/M1_motorway http://dbpedia.org/resource/Woodall_services 53.3152 -1.2813
http://dbpedia.org/resource/M1_motorway http://dbpedia.org/resource/Tibshelf_services 53.13708 -1.33179
http://dbpedia.org/resource/M1_motorway http://dbpedia.org/resource/London_Gateway_services 51.631 -0.264
http://dbpedia.org/resource/M1_motorway http://dbpedia.org/resource/Donington_Park_services 52.823651 -1.305887
http://dbpedia.org/resource/M1_motorway http://dbpedia.org/resource/Watford_Gap_services 52.3069 -1.1226
http://dbpedia.org/resource/M1_motorway http://dbpedia.org/resource/Newport_Pagnell_services 52.083066 -0.748508
http://dbpedia.org/resource/M1_motorway http://dbpedia.org/resource/Trowell_services 52.963198 -1.265988
http://dbpedia.org/resource/M1_motorway http://dbpedia.org/resource/Woolley_Edge_services 53.62259 -1.549422
http://dbpedia.org/resource/M1_motorway http://dbpedia.org/resource/Toddington_services 51.9478 -0.502075
http://dbpedia.org/resource/M1_motorway http://dbpedia.org/resource/Northampton_services 52.209201 -0.944799
http://dbpedia.org/resource/M4_motorway http://dbpedia.org/resource/Chieveley_services 51.449 -1.3112
http://dbpedia.org/resource/M4_motorway http://dbpedia.org/resource/Magor_services 51.58786 -2.83713
http://dbpedia.org/resource/M4_motorway http://dbpedia.org/resource/Pont_Abraham_services 51.74712 -4.0655
http://dbpedia.org/resource/M4_motorway http://dbpedia.org/resource/Swansea_services 51.678197 -3.994646
http://dbpedia.org/resource/M4_motorway http://dbpedia.org/resource/Leigh_Delamere_services 51.511528 -2.159468
http://dbpedia.org/resource/M4_motorway http://dbpedia.org/resource/Reading_services 51.424527 -1.035633
http://dbpedia.org/resource/M4_motorway http://dbpedia.org/resource/Cardiff_West_services 51.50626 -3.30535
http://dbpedia.org/resource/M4_motorway http://dbpedia.org/resource/Heston_services 51.48807 -0.39106
20 Rows. -- 531 msec.
¶
Example 19
SELECT DISTINCT ?s (bif:round(?lat)) as ?lat (bif:round(?long)) as ?long
WHERE
{
{
SELECT ?g ?s WHERE
{
graph ?g {
?s geo:geometry ?geo }
}
LIMIT 100
}
graph ?g {
?s geo:lat ?lat .
?s geo:long ?long . }
FILTER (datatype (?lat) in (xsd:integer, xsd:float, xsd:double)) .
FILTER (datatype (?long) in (xsd:integer, xsd:float, xsd:double))
}
s lat long
ANY ANY ANY
________________________________________________________________________________________________
http://dbpedia.org/resource/QUaD -90 -139
http://dbpedia.org/resource/Amundsen-Scott_South_Pole_Station -90 -139
http://dbpedia.org/resource/Amundsen-Scott_South_Pole_Station -90 0
http://dbpedia.org/resource/Degree_Angular_Scale_Interferometer -90 -139
http://dbpedia.org/resource/South_Pole_Telescope -90 -139
http://dbpedia.org/resource/Arcminute_Cosmology_Bolometer_Array_Receiver -90 -139
http://dbpedia.org/resource/Viper_telescope -90 -139
http://dbpedia.org/resource/Mount_Weaver -87 -154
http://dbpedia.org/resource/Axel_Heiberg_Glacier -85 -163
http://dbpedia.org/resource/Mount_Ray -85 -171
http://linkedgeodata.org/triplify/node/275487234#id -85 -142
http://linkedgeodata.org/triplify/node/303732928#id -85 -142
http://linkedgeodata.org/triplify/node/332036611#id -85 -85
http://linkedgeodata.org/triplify/node/303732935#id -85 -143
http://linkedgeodata.org/triplify/node/303732951#id -85 -144
http://linkedgeodata.org/triplify/node/303732953#id -85 -144
http://linkedgeodata.org/triplify/node/276208684#id -85 -166
¶
Example 19
## "Find things within 20km of New York City":
SELECT DISTINCT ?resource ?label ?location
WHERE
{
<http://dbpedia.org/resource/New_York_City>
geo:geometry ?sourcegeo .
?resource geo:geometry ?location ;
rdfs:label ?label .
FILTER( bif:st_intersects( ?location, ?sourcegeo, 20 ) ) .
FILTER( lang(?label) = "en" )
}
¶
Example 20
## "Find Distance between New York City
## and London, England":
SELECT ( bif:st_distance( ?nyl,?ln ) )
AS ?distanceBetweenNewYorkCityAndLondon
WHERE
{
<http://dbpedia.org/resource/New_York_City>
geo:geometry ?nyl .
<http://dbpedia.org/resource/London>
geo:geometry ?ln .
}
¶
Example 21
## "Find "All Educational Institutions
## within 10km of Oxford, UK; ordered by
## date of establishment":
SELECT DISTINCT ?thing AS ?uri
?thingLabel AS ?name
?date AS ?established
?matchgeo AS ?location
WHERE
{
<http://dbpedia.org/resource/Oxford>
geo:geometry ?sourcegeo .
?resource geo:geometry ?matchgeo .
FILTER( bif:st_intersects( ?matchgeo, ?sourcegeo, 5 ) ) .
?thing ?somelink ?resource ;
<http://dbpedia.org/ontology/established> ?date ;
rdfs:label ?thingLabel .
FILTER( lang(?thingLabel) = "en" )
}
ORDER BY ASC( ?date )
¶
Example 22
## "Find Historical cross section of events related
## to Edinburgh and the surrounding area (within 30km)
## during the 19th century":
SELECT DISTINCT ?thing ?thingLabel
?dateMeaningLabel ?date ?matchgeo
WHERE
{
{
SELECT DISTINCT ?thing ?matchgeo
WHERE
{
<http://dbpedia.org/resource/Edinburgh>
geo:geometry ?sourcegeo .
?resource geo:geometry ?matchgeo .
FILTER( bif:st_intersects (
?matchgeo, ?sourcegeo, 30 ) ) .
?thing ?somelink ?resource
}
}
{
?property rdf:type owl:DatatypeProperty ;
rdfs:range xsd:date
} .
?thing ?dateMeaning ?date .
FILTER( ?dateMeaning IN ( ?property ) ) .
FILTER( ?date >= xsd:gYear("1800")
&& ?date <= xsd:gYear("1900") )
?dateMeaning rdfs:label ?dateMeaningLabel .
FILTER( lang(?dateMeaningLabel) = "en" ) .
?thing rdfs:label ?thingLabel .
FILTER( lang(?thingLabel) = "en" )
}
ORDER BY ASC ( ?date )