Finding Spatial Equivalences Across Multiple RDF Datasets. Juan Salas, Andreas Harth. Outline. Motivation NeoGeo Vocabularies Geospatial Datasets Integration Challenges Finding Geometric E quivalences Conclusion. Motivation. Geodata is becoming increasingly relevant.
Juan Salas, Andreas Harth
Finding Geometric Equivalences
Applications require integrated access to geodata.
They serve as:
Geometric shapes will not be vertex by vertex equivalent.
A sensible criterion for finding geometric equivalences is needed.
WGS-84, Plate Carrée projection
X = longitude
Y = latitude
The Hausdorff Distance provides a measure of similarity between geometric shapes.
Can be intuitively defined as
the largest distance between
the closest points of two
Smaller regions need a lower Hausdorff Distance threshold than larger regions.
We calculate the midpoint value between the Hausdorff Distances for a correct guess and the lowest wrong guess.
We perform regression on the midpoint values to obtain the Hausdorff Distance threshold function.
Sometimes location is approximated as a single point.
Can lead to false assertions while calculating containment relations.
<http://dbpedia.org/resource/Germany> geo:lat 52.516666;
geo:long 13.383333 .
<http://nuts.geovocab.org/id/DE30_geometry> rdf:type ngeo:Polygon .
Germany is not contained in Berlin.
Other properties must be considered to calculate containment relations (e.g. rdf:type).
Other spatial relations (e.g. spatial:EQ) cannot be calculated.
The cost of calculating the Hausdorff distance depends on the amount of vertices.
The Ramer-Douglas-Peucker algorithm allows to simplify geometric shapes, using an arbitrary maximum separation.
SELECT g.gadm_id, n.nuts_id
FROM nuts n
INNER JOIN gadm g ON (n.geometry && g.geometry)
n.shape_area BETWEEN (g.shape_area * 0.9)
AND (g.shape_area * 1.1)
) < g.max_hausdorff_dist;
Leicestershire, Rutland and Northamptonshire
European Commission's Seventh
(PlanetData, Grant 257641)