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==This is outdated. Shall we remove it ?==

Introduction

In order to perform spatio-temporal query, spatial data and temporal data should be indexed and spatio-temporal operations should be supported. Supporting these capabilities can be achieved via adapting the way that Alejandro Rodriguez developed Data Stream API 2.0). The goal of this project is

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The Figure 1 shows the Spatio-Temporal composite context that supports spatio-temporal queries. The composite context will analyze the query and store temporal data and temporal data to database tables that supports temporal index and spatial index.

Image Modified
Figure 1. Spatio-temporal Composite Context

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If there is “ogc:hasWKT” predicate, then write WKT geometry to the PostGIS table

// hasWKT predicate needs to write geometry to spatial db
if (t.getPredicate().equals(HAS_WKT) && t.getObject() != null) {
	// writing geometry to spatial db
	insertGeom.setString(1, "u" + t.getSubject().getUri().toString());
	insertGeom.setString(2, getPolygon(t.getObject()));
	insertGeom.executeUpdate();
}

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• Classify patterns into spatial pattern and non-spatial pattern
• Create regular sql statement with non-spatial pattern

• Wrap the sql statement for non-spatial pattern with spatial sql statement

  Code Block

  private String addSpatialQuery(Unifier spatialUnifier, PreparedStatement statement, int numCol) { String polygon = spatialUnifier.getPatterns().get(0).getObject() .toString(); String sql = "SELECT "; for (int i = 0; i < numCol; i++ ) { if (i == 0) sql = sql + "a.c" + i + " as c" + i + ","; else sql = sql + "a.c" + i + " as c" + i + ",a.c" + i + "_typ as c" + i + "_typ,"; } sql = sql.substring(0, sql.length() - 1) + " FROM (" + statement.toString() + ") as a " + "LEFT JOIN " + GEOMETRY_TABLE + " as b " + "ON a.c0 = b.uri " + "where ST_Within(b.the_geom, ST_GeomFromText('" + polygon + "'," + WGS84 + ")) and a.c0 = b.uri"; return sql; }

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columns: ?s, ?flavor, ?temp
pattern 1: ?s urn:flavor "pistachio"
pattern 3: ?s urn:flavor ?flavor
pattern 4: ?s["37".."39"] urn:temp ?temp

select distinct
(select sym from sym where uid=p0.sub) as c0, tok1.token_id as c0_frame_id, tok1.start as c0_time,
(select sym from sym where uid=p1.obj) as c1, (select sym from sym where uid=p1.typ) as c1_typ,
(select sym from sym where uid=p2.obj) as c2, (select sym from sym where uid=p2.typ) as c2_typ
from tup p0
join tup p1 on p1.sub=p0.sub and p1.pre=(select uid from sym where md5(sym)=md5('uurn:flavor'))
join tup p2 on p2.sub=p0.sub and p2.pre=(select uid from sym where md5(sym)=md5('uurn:temperature'))
join tokens tok1 on tok1.uid=p1.sub and tok1.start >= 37 and tok1.end <= 39
where p0.pre=(select uid from sym where md5(sym)=md5('uurn:flavor'))
and p0.obj=(select uid from sym where md5(sym)=md5('lpistachio'));