1. An Introduction to Linked Geospatial Data Manolis Koubarakis http://www.di.uoa.gr/~koubarak Web Intelligence Summer School 2015 Dept. of Informatics and Telecommunications National and Kapodistrian University of Athens

2. WISS 2015 2 Outline Why geospatial data? Geospatial data in the linked data cloud Representation and querying of linked geospatial data: GeoSPARQL stRDF/stSPARQL Implemented RDF stores with geospatial functionality Comparison Open research problems

3. WISS 2015 3 Why Geospatial Information? Geospatial, and in general geographical, information is very important in reality: everything that happens, happens somewhere (location). Decision making can be substantially improved if we know where things take place.

4. WISS 2015 4 Geospatial data on the Web

5. WISS 2015 5 Open Government Data

6. WISS 2015 6 Linked geospatial data – Ordnance Survey

7. WISS 2015 7 Linked geospatial data – Open Street Map

8. WISS 2015 8 http://www.linkedopendata.gr

9. WISS 2015 9 LOD Cloud

10. WISS 2015 10 Representation and Querying of Linked Geospatial Data Early papers: Kollas (2007) Perry’s Ph.D. dissertation (2008) Koubarakis and Kyzirakos (2010) We concentrate on two recent proposals: GeoSPARQL (2012) stRDF/stSPARQL (2012)

11. WISS 2015 11 Common Approach The two proposals offer constructs for: o Developing ontologies for spatial and temporal data. o Encoding spatial and temporal data that use these ontologies in RDF. o Extending SPARQL to query spatial and temporal data. Temporal data are covered only by stRDF/stSPARQL

12. WISS 2015 12 GeoSPARQL GeoSPARQL is an OGC standard. Main functionalities:  Representing geospatial information is done using high level ontologies inspired from GIS terminology.  Geometries are represented using literals of spatial datatypes.  Literals are serialized using OGC standards WKT and GML.  Families of functions are offered for querying geometries. [ Perry and Herring, 2012 ]

13. WISS 2015 GeoSPARQL Components Core Topology Vocabulary Extension - relation family Geometry Extension - serialization - version Geometry Topology Extension - serialization - version - relation family Query Rewrite Extension - serialization - version - relation family RDFS Entailment Extension - serialization - version - relation family Parameters Serialization WKT GML Relation Family Simple Features RCC-8 Egenhofer

14. WISS 2015 14 GeoSPARQL Core Defines two top level classes that can be used to organize geospatial data.

15. WISS 2015 15 Geographic Feature Geographic feature or geographic object: a domain entity that can have various attributes that describe spatial and non- spatial characteristics. Example: the country Greece with attributes Population Flag Capital Geographical area Coastline Bordering countries

16. WISS 2015 16 Geographic Feature (cont’d ) Geographic features can be atomic or complex. Example: According to the Kallikratis administrative reform of 2010, Greece consists of: 13 regions (e.g., Crete) Each region consists of regional units (e.g., Heraklion) Each regional unit consists of municipalities (e.g., Dimos Chersonisou) …

17. WISS 2015 17 Geographic Feature (cont’d) The spatial characteristics of a feature can involve: Geometric information (location in the underlying geographic space, shape etc.) Topological information (containment, adjacency etc.). Municipalities of the regional unit of Heraklion: 1. Dimos Irakliou 2. Dimos Archanon-Asterousion 3. Dimos Viannou 4. Dimos Gortynas 5. Dimos Maleviziou 6. Dimos Minoa Pediadas 7. Dimos Festou 8. Dimos Chersonisou

18. WISS 2015 18 GeoSPARQL Geometry Extension Provides vocabulary for asserting and querying data about the geometric attributes of a feature.

19. WISS 2015 19 Well-Known Text (WKT) WKT is an OGC and ISO standard for representing geometries, coordinate reference systems, and transformations between coordinate reference systems. WKT is specified in OpenGIS Simple Feature Access - Part 1: Common Architecture standard which is the same as the ISO 19125-1 standard. Download from http://portal.opengeospatial.org/files/?artifact_id=25355. http://portal.opengeospatial.org/files/?artifact_id=25355 This standard concentrates on simple features: features with all spatial attributes described piecewise by a straight line or a planar interpolation between sets of points.

20. WISS 2015 20 WKT Class Hierarchy

21. WISS 2015 21 Example WKT representation: GeometryCollection( Point(5 35), LineString(3 10,5 25,15 35,20 37,30 40), Polygon((5 5,28 7,44 14,47 35,40 40,20 30,5 5), (28 29,14.5 11,26.5 12,37.5 20,28 29)) )

22. WISS 2015 22 Geography Markup Language (GML) GML is an XML-based encoding standard for the representation of geospatial data. GML provides XML schemas for defining a variety of concepts: geographic features, geometry, coordinate reference systems, topology, time and units of measurement. GML profiles are subsets of GML that target particular applications. Examples: Point Profile, GML Simple Features Profile etc.

23. WISS 2015 23 GML Simple Features: Class Hierarchy

24. WISS 2015 24 Example GML representation: 5,5 28,7 44,14 47,35 40,40 20,30 5,5

25. WISS 2015 25 Example: Greek Administrative Geography

26. WISS 2015 26 Domain Ontology

27. WISS 2015 27 Greek Administrative Geography

28. WISS 2015 28 Greek Administrative Geography

29. ESWC 2015 Tutorial 29 Example Data gag:Olympia rdf:type gag:MunicipalCommunity; gag:name "Ancient Olympia"; gag:population "184"^^xsd:int; geo:hasGeometry ex:polygon1. ex:polygon1 rdf:type geo:Geometry; geo:asWKT " http://www.opengis.net/def/crs/OGC/1.3/CRS84 POLYGON((21.5 18.5,23.5 18.5, 23.5 21,21.5 21,21.5 18.5))" ^^sf:wktLiteral. Datatype from Geometry extension Coordinate Reference System Property from Geometry extension Class from Geometry extension Geometry literal

30. WISS 2015 30 Non-Topological Query Functions of the Geometry Extension  The following non-topological query functions are also offered:  geof:distance  geof:buffer  geof:convexHull  geof:intersection  geof:union  geof:difference  geof:symDifference  geof:envelope  geof:boundary  The Egenhofer relations e.g., geo:ehMeet  The RCC-8 relations e.g., geo:rcc8ec

31. WISS 2015 31 GeoSPARQL: An example SELECT ?r ?c WHERE { ?r rdf:type clc:Region; geo:hasGeometry ?rGeom; clc:hasCorineLandCover ?f. ?f rdfs:subClassOf clc:Forest. ?c rdf:type gag:MunicipalCommunity; geo:hasGeometry ?cGeom. FILTER( geof:distance(?rGeom,?cGeom,uom:metre) < 1000)} Non-topological query function from Geometry extension Find forests near municipal communities

32. WISS 2015 32 GeoSPARQL Topology Vocabulary Extension The extension is used for representing topological information about features. Topological information is inherently qualitative and it is expressed in terms of topological relations (e.g., containment, adjacency, overlap etc.). Topological information can be derived from geometric information or it might be captured by asserting explicitly the topological relations between features.

33. WISS 2015 33 Topological Relations The study of topological relations has produced a lot of interesting results by researchers in: GIS Spatial databases Artificial Intelligence (qualitative reasoning and knowledge representation)

34. WISS 2015 34 DE-9IM The dimensionally extended 9-intersection model (DE-9IM) of Clementini and Felice. It is based on the point-set topology of R 2. It deals with simple, closed and connected geometries (areas, lines, points). It is an extension of earlier approaches: the 4- intersection (4IM) and 9-intersection (9IM) models by Egenhofer and colleagues.

35. WISS 2015 35 Topological Relations in DE-9IM It captures topological relationships between two geometries a and b in R 2 by considering the dimensions of the intersections of the boundaries, interiors and exteriors of the two geometries: The dimension can be 2, 1, 0 and -1 (dimension of the empty set).

36. WISS 2015 36 Example I(C)B(C)E(C) I(A) 2 B(A) 1 E(A)212 A C

37. WISS 2015 37 Topological Relations in DE-9IM The following five named relationships between two different geometries can be distinguished: disjoint, touches, crosses, within and overlaps. The named relationships have a reasonably intuitive meaning for users. They are jointly exclusive and pairwise disjoint (JEPD). The model can also be defined using an appropriate calculus of geometries that uses these 5 binary relations and boundary operators.

38. WISS 2015 38 Example: A disjoint C I(C)B(C)E(C) I(A)FF* B(A)FF* E(A)*** A C Notation: T = { 0, 1, 2 } F = -1 * = don’t care = { -1, 0, 1, 2 }

39. WISS 2015 39 Example: A within C I(C)B(C)E(C) I(A)T*F B(A)**F E(A)*** C A Notation equivalent to 3x3 matrix: String of 9 characters representing the above matrix in row major order. In this case: T*F**F***

40. WISS 2015 40 DE-9IM Relation Definitions

41. WISS 2015 41 Simple Features Relation Definitions A equals B can be defined by the pattern TFFFTFFFT. A intersects B is the negation of A disjoint B A contains B is equivalent to B within A

42. WISS 2015 42 The Region Connection Calculus (RCC) The primitives of the calculus are spatial regions. These are non-empty, regular closed subsets of a topological space. The calculus is based on a single binary predicate C that formalizes the “connectedness” relation. C(a,b) is true when the closure of a is connected to the closure of b i.e., they have at least one point in common. It is axiomatized using first order logic.

43. WISS 2015 43 RCC-8 This is a set of eight JEPD binary relations that can be defined in terms of predicate C.

44. WISS 2015 44 RCC-5 The RCC-5 subset has also been studied. The granularity here is coarser. The boundary of a region is not taken into consideration: No distinction among DC and EC, called just DR. No distinction among TPP and NTPP, called just PP. RCC-8 and RCC-5 relations can also be defined using point-set topology, and there are very close connections to the models of Egenhofer and others.

45. WISS 2015 45 GeoSPARQL Topology Vocabulary Extension  The extension is parameterized by the family of topological relations supported:  Topological relations for simple features  The Egenhofer relations e.g., geo:ehMeet  The RCC-8 relations e.g., geo:rcc8ec

46. WISS 2015 gag:Olympia rdf:type gag:MunicipalCommunity; gag:name "Ancient Olympia". gag:OlympiaMUnit rdf:type gag:MunicipalityUnit; gag:name "Municipality Unit of Ancient Olympia". gag:OlympiaMunicipality rdf:type gag:Municipality; gag:name "Municipality of Ancient Olympia". gag:Olympia geo:sfWithin gag:OlympiaMUnit. gag:OlympiaMUnit geo:sfWithin gag:OlympiaMunicipality. 46 Greek Administrative Geography Simple Features topological relation

47. WISS 2015 47 GeoSPARQL: An example SELECT ?m WHERE { ?m rdf:type gag:MunicipalityUnit. ?m geo:sfContains gag:Olympia. } Find the municipality unit that contains the community of Ancient Olympia Simple Features topological relation Answer : ?m = gag:OlympiaMUnit

48. WISS 2015 48 GeoSPARQL: An example SELECT ?m WHERE { ?m rdf:type gag:Municipality. ?m geo:sfContains gag:Olympia. } Find the municipality that contains the community of Ancient Olympia Answer : ?m = gag:OlympiaMunicipality

49. ESWC 2015 Tutorial 49 Example (cont’d) The answer to the previous query can be computed by reasoning about the transitivity of relation geo:sfContains. Implementation options: Use rules Use constraint-based techniques

50. ESWC 2015 Tutorial 50 GeoSPARQL Geometry Topology Extension Offers vocabulary for querying topological properties of geometry literals. Simple Features geof:relate geof:sfEquals geof:sfDisjoint geof:sfIntersects geof:sfTouches geof:sfCrosses geof:sfWithin geof:sfContains geof:sfOverlaps Egenhofer (e.g., geof:ehDisjoint ) RCC-8 (e.g., geof:rcc8dc )

51. WISS 2015 51 Example Query SELECT ?name WHERE { ?commrdf:type gag:LocalCommunity; gag:name ?name; geo:hasGeometry ?commGeo. ?ba rdf:type noa:BurntArea; geo:hasGeometry ?baGeo. FILTER(geof:sfOverlaps(?commGeo,?baGeo)) } Geometry Topology Extension Function Return the names of local communities that have been affected by fires Geometry Extension Property

52. WISS 2015 52 GeoSPARQL Query Rewrite Extension  Provides a collection of RIF rules that use functions of the Geometry Topology extension to establish the existence of predicates of the Topology extension.  Example: given the RIF rule named geor:sfWithin, the serializations of the geometries of gag:Athens and gag:Greece named AthensWKT and GreeceWKT and the fact that geof:sfWithin(AthensWKT, GreeceWKT) returns true from the computation of the two geometries, we can derive the triple gag:Athens geo:sfWithin gag:Greece  One possible implementation is to re-write a given SPARQL query.

53. WISS 2015 53 RIF Rule Forall ?f1 ?f2 ?g1 ?g2 ?g1Serial ?g2Serial (?f1[geo:sfWithin->?f2] :- Or( And (?f1[geo:hasDefaultGeometry->?g1] ?f2[geo:hasDefaultGeometry->?g2] ?g1[ogc:asGeomLiteral->?g1Serial] ?g2[ogc:asGeomLiteral->?g2Serial] External(geof:sfWithin (?g1Serial,?g2Serial))) And (?f1[geo:hasDefaultGeometry->?g1] ?g1[ogc:asGeomLiteral->?g1Serial] ?f2[ogc:asGeomLiteral->?g2Serial] External(geof:sfWithin (?g1Serial,?g2Serial))) And (?f2[geo:hasDefaultGeometry->?g2] ?f1[ogc:asGeomLiteral->?g1Serial] ?g2[ogc:asGeomLiteral->?g2Serial] External(geof:sfWithin (?g1Serial,?g2Serial))) And (?f1[ogc:asGeomLiteral->?g1Serial] ?f2[ogc:asGeomLiteral->?g2Serial] External(geof:sfWithin (?g1Serial,?g2Serial))) )) Feature - Feature Feature - Geometry Geometry - Feature Geometry - Geometry

54. WISS 2015 54 Example SELECT ?feature WHERE { ?feature geo:sfWithin geonames:OlympiaMunicipality. } Find all features that are inside the municipality of Ancient Olympia

55. WISS 2015 55 Rewritten Query SELECT ?feature WHERE { {?feature geo:sfWithin geonames:Olympia } UNION { ?feature geo:hasDefaultGeometry ?featureGeom. ?featureGeom geo:asWKT ?featureSerial. geonames:Olympia geo:hasDefaultGeometry ?olGeom. ?olGeom geo:asWKT ?olSerial. FILTER (geof:sfWithin (?featureSerial, ?olSerial)) } UNION { ?feature geo:hasDefaultGeometry ?featureGeom. ?featureGeom geo:asWKT ?featureSerial. geonames:Olympia geo:asWKT ?olSerial. FILTER (geof:sfWithin (?featureSerial, ?olSerial)) } UNION { ?feature geo:asWKT ?featureSerial. geonames:Olympia geo:hasDefaultGeometry ?olGeom. ?olGeom geo:asWKT ?olSerial. FILTER (geof:sfWithin (?featureSerial, ?olSerial)) } UNION { ?feature geo:asWKT ?featureSerial. geonames:Olympia geo:asWKT ?olSerial. FILTER (geof:sfWithin (?featureSerial, ?olSerial)) }

56. WISS 2015  Specifies the RDFS entailments that follow from the class and property hierarchies defined in the other components e.g., the Geometry Extension.  Systems should use an implementation of RDFS entailment to allow the derivation of new triples from those already in a graph. 56 GeoSPARQL RDFS Entailment Extension

57. WISS 2015 57 Example Given the triples ex:f1 geo:hasGeometry ex:g1. geo:hasGeometry rdfs:domain geo:Feature. we can infer the following triples: ex:f1 rdf:type geo:Feature. ex:f1 rdf:type geo:SpatialObject.

58. WISS 2015 58 Representation and Querying of Linked Geospatial Data We concentrate on two recent proposals: GeoSPARQL stRDF/stSPARQL

59. WISS 2015 59 The data model stRDF  An extension of RDF for the representation of geospatial information that changes over time.  Geospatial dimension:  Spatial data types are introduced.  Geospatial information is representing using spatial literals of these datatypes.  OGC standards WKT and GML are used for the serialization of spatial literals.  Temporal dimension  Proposed independently and around the same time as GeoSPARQL (starting with an ESWC 2010 paper by Koubarakis and Kyzirakos). [ Kyzirakos, Karpathiotakis & Koubarakis 2012 ]

60. WISS 2015 60 The Query Language stSPARQL  It is an extension of SPARQL 1.1  It offers families of functions for querying geometries. The same functions as in the Geometry Extension and Geometry Topology Extension of GeoSPARQL.  In addition the following spatial aggregate functions are offered: strdf:geometry strdf:union(set of strdf:geometry A) strdf:geometry strdf:intersection(set of strdf:geometry A) strdf:geometry strdf:extent(set of strdf:geometry A) No functionality similar to the Topology Extension or Query Rewrite Extension is offered. Temporal dimension

61. WISS 2015 Spatial Function 61 SELECT ?burntArea (strdf:intersection(?baGeom, strdf:union(?fGeom)) AS ?burntForest) WHERE { ?burntArea rdf:type noa:BurntArea; noa:hasGeometry ?baGeom. ?forestrdf:type clc:Region; clc:hasLandCover clc:ConiferousForest; clc:hasGeometry ?fGeom. FILTER(strdf:intersects(?baGeom,?fGeom)) } GROUP BY ?burntArea ?baGeom Compute the parts of burnt areas that lie in coniferous forests. stSPARQL: An example Spatial Aggregate

62. WISS 2015 Time dimensions in Linked Data User-defined time: A time value (literal) with no special semantics. Valid time: The time when a fact (represented by a triple) is true in the modeled reality. Transaction time: The time when the triple is current in the database.

63. WISS 2015 The time dimension of stRDF: The valid time of triples The following extensions are introduced in stRDF: Timeline: the (discrete) value space of the datatype xsd:dateTime of XML-Schema Two kinds of time primitives are supported: time instants and time periods. A time instant is an element of the time line. A time period is an expression of the form [B, E) or [B, E] or (B, E] or (B, E) where B and E are time instants called the beginning and ending time of the period. The new datatype strdf:period is introduced. 63

64. WISS 2015 The time dimension of stRDF (cont’d) Triples are extended to quads. A temporal triple (quad) is an expression of the form s p o t. where s p o. is an RDF triple and t is a time instant or time period called the valid time of the triple. The temporal constants NOW and UC (“until changed”) are introduced. 64

65. WISS 2015 An example with valid time 65 25/08/0625/08/07 25/08/09 Forest

66. WISS 2015 66 25/08/0625/08/07 25/08/09 Forest clc:region1 clc:hasLandCover clc:Forest "[2006-08-25T11:00:00+02, "UC")"^^strdf:period. An example with valid time

67. WISS 2015 An example with valid time 67 25/08/0625/08/07 25/08/09 Forest clc:region1 clc:hasLandCover clc:Forest "[2006-08-25T11:00:00+02, "UC")"^^strdf:period. Burnt area

68. WISS 2015 68 25/08/0625/08/07 25/08/09 Forest Burnt area noa:ba1 rdf:type noa:BurntArea "[2007-08-25T11:00:00+02, "UC")"^^strdf:period. clc:region1 clc:hasLandCover clc:Forest "[2006-08-25T11:00:00+02, "UC")"^^strdf:period. An example with valid time

69. WISS 2015 69 25/08/0625/08/07 25/08/09 Forest Burnt area noa:ba1 rdf:type noa:BurntArea "[2007-08-25T11:00:00+02, "UC"))"^^strdf:period. clc:region1 clc:hasLandCover clc:Forest "[2006-08-25T11:00:00+02,2007-08-25T11:00:00+02)"^^strdf:period. An example with valid time

70. WISS 2015 70 25/08/0625/08/07 25/08/09 Forest Burnt area Agricultural area clc:region1 clc:hasLandCover clc:AgriculturalArea "[2009-08-25T11:00:00+02, "UC")"^^strdf:period. noa:ba1 rdf:type noa:BurntArea "[2007-08-25T11:00:00+02,2009-08-25T11:00:00+02)"^^strdf:period. clc:region1 clc:hasLandCover clc:Forest "[2006-08-25T11:00:00+02,2007-08-25T11:00:00+02)"^^strdf:period. An example with valid time

71. WISS 2015 The time dimension of stSPARQL The following extensions are introduced: Triple patterns are extended to quad patterns (the last component is a temporal term: variable or constant) Temporal extension functions are introduced: Allen's temporal relations (e.g., strdf:after ) Period constructors (e.g., strdf:period_intersect ) Temporal aggregates (e.g., strdf:maximalPeriod ) 71

72. WISS 2015 Find the current land cover of all areas in the dataset SELECT ?clc WHERE { ?R rdf:type clc:Region. ?R clc:hasLandCover ?clc ?t1. FILTER(strdf:during ("NOW", ?t1)) } Temporal extension function Temporal constant Example Query 72 Quad Pattern

73. WISS 2015 Implemented RDF Stores with Geospatial Functionality AllegroGraph Brodt et al. Oracle 11c OWLIM Parliament Perry’s Ph.D. thesis Strabon uSeekM Virtuoso 73

74. WISS 2015 Strabon Strabon is a state-of-the-art spatiotemporal RDF store implemented at the University of Athens. 74 Find more about Strabon at http://strabon.di.uoa.gr/ Find more about Strabon at http://strabon.di.uoa.gr/ O PEN S OURCE stRDF graphs stSPARQL/ GeoSPARQL queries WKTGML [ISWC2012, ESWC2013]

75. SystemLanguageIndexGeometriesCRS support Relation Families in Geometry Topology Topology Extension StrabonstSPARQL/ GeoSPARQL R-tree- over- GiST WKT / GMLYesSF Egenhofer RCC-8 No ParliamentGeoSPARQLR-TreeWKT / GMLYesSF Egenhofer RCC-8 Yes Brodt et al. (RDF-3X) SPARQLR-TreeWKTNoSFNo PerrySPARQL-STR-TreeGeoRSS GML YesRCC8No Oracle 11cGeoSPARQLR-TreeWKT / GMLYesSFYes uSeekMSPARQLR-tree- over GiST WKTNoSF Egenhofer RCC-8 Yes Functional Comparison

76. SystemLanguageIndexGeometriesCRS supportFunctions Available AllegroGraphExtended SPARQL Distribution sweeping technique 2D point geometries PartialBuffer Bounding Box Distance OWLIMExtended SPARQL Custom2D point geometries (W3C Basic Geo Vocabulary) No Point-in-polygon Buffer Distance VirtuosoSPARQLR-Tree2D point geometries (in WKT) YesSQL/MM (subset) Functional Comparison (cont’d)

77. WISS 2015 Performance Evaluation Our detailed performance evaluation (with real and simulated data) shows that Strabon is the world's fastest and most functional RDF store. The functional and performance benchmark Geographica for geospatial RDF stores has been used to show this. 77 Find more about Geographica at http://geographica.di.uoa.gr/ Find more about Geographica at http://geographica.di.uoa.gr/ [ISWC2013]

78. WISS 2015 Open Problems Query optimization in spatiotemporal RDF stores Efficient implementation of the reasoning component needed by the Topology Extension in an RDF store Federated geospatial RDF stores GeoSPARQL query processing on elastic clouds Keyword query processing in spatiotemporal RDF stores 78

79. WISS 2015 Readings 79 The GeoSPARQL standard found at http://www.opengeospatial.org/standards/geosparql http://www.opengeospatial.org/standards/geosparql The following tutorial paper which introduces to the topic of linked geospatial data: M. Koubarakis, M. Karpathiotakis, K. Kyzirakos, C. Nikolaou and M. Sioutis. Data Models and Query Languages for Linked Geospatial Data. Reasoning Web Summer School 2012. http://strabon.di.uoa.gr/files/survey.pdf The following paper which introduces stSPARQL and Strabon: K. Kyzirakos, M. Karpathiotakis and M. Koubarakis. Strabon: A Semantic Geospatial DBMS. 11th International Semantic Web Conference (ISWC 2012). November 11-15, 2012. Boston, USA. http://iswc2012.semanticweb.org/sites/default/files/76490289.pdf The following paper which introduces the temporal features of stSPARQL and Strabon: K. Bereta, P. Smeros and M. Koubarakis. Representing and Querying the Valid Time of Triples for Linked Geospatial Data. In the 10th Extended Semantic Web Conference (ESWC 2013). Montpellier, France. May 26-30, 2013. http://www.strabon.di.uoa.gr/files/eswc2013.pdf

80. WISS 2015 Readings (cont’d) 80 The following paper which introduces the RDF i framework which goes beyond GeoSPARQL in the representation of geospatial data: Charalampos Nikolaou and Manolis Koubarakis. Incomplete Information in RDF. In the 7th International Conference on Web Reasoning and Rule Systems (RR 2013). Mannheim, Germany. July 27-29, 2013. http://cgi.di.uoa.gr/~koubarak/publications/rr2013.pdf The following paper which introduces the benchmark Geographica: G. Garbis, K. Kyzirakos and M. Koubarakis. Geographica: A Benchmark for Geospatial RDF Stores. In the 12th International Semantic Web Conference (ISWC 2013). Sydney, Australia. October 21-25, 2013. http://cgi.di.uoa.gr/~koubarak/publications/Geographica.pdf The work of the W3C/OGC working group on Spatial Data on the Web (http://www.w3.org/2015/spatial/wiki/Main_Page).http://www.w3.org/2015/spatial/wiki/Main_Page