=Paper=
{{Paper
|id=None
|storemode=property
|title=SexTant: Visualizing Time-Evolving Linked Geospatial Data
|pdfUrl=https://ceur-ws.org/Vol-1035/iswc2013_demo_45.pdf
|volume=Vol-1035
|dblpUrl=https://dblp.org/rec/conf/semweb/BeretaNKKK13
}}
==SexTant: Visualizing Time-Evolving Linked Geospatial Data==
https://ceur-ws.org/Vol-1035/iswc2013_demo_45.pdf
SexTant: Visualizing Time-Evolving Linked
Geospatial Data ?
Konstantina Bereta1 , Charalampos Nikolaou1 , Manos Karpathiotakis2 ,
Kostis Kyzirakos1 , and Manolis Koubarakis1
1
National and Kapodistrian University of Athens, Greece
2
École Polytechnique Fédérale de Lausanne, Switzerland
Abstract. We present SexTant, a Web-based system for the visualiza-
tion and exploration of time-evolving linked geospatial data and the cre-
ation, sharing, and collaborative editing of “temporally-enriched” the-
matic maps which are produced by combining different sources of such
data.
1 Introduction and Motivation
Linked geospatial data has recently received attention as researchers and prac-
titioners have started tapping the wealth of geospatial information available in
the archives of various national cartographic agencies and making it available
on the Web as linked data [2]. As a result, in the last few years, the Web of
data is being rapidly populated with geospatial information. As the real-world
entities represented in linked geospatial datasets evolve over time, the datasets
themselves get updated and both the spatial and the temporal dimension of data
become significant for users.
In the demo paper [4] we presented Sextant3 , a tool that enables the vi-
sualization and exploration of the spatial dimension of linked geospatial data.
Sextant enables map creation and sharing, as well as the visualization and ex-
ploration of data by evaluating GeoSPARQL queries on SPARQL endpoints. In
this way rich thematic maps can be created by layering information coming from
the evaluation of GeoSPARQL queries. Sextant is based on standards defined
by the Open Geospatial Consortium (OGC), thus it is interoperable with other
well-known GIS and Web tools such as Google Earth.
In this demo paper we turn our attention to the temporal dimension of linked
geospatial data and present a new version of Sextant that we now rename Sex-
Tant (the capital “T” in the new name emphasizes the time dimension). SexTant
extends the functionalities of the earlier tool by visualizing the temporal dimen-
sion of data having a spatial extent simultaneously on a map and a timeline. The
new capabilities of SexTant build on the temporal features of the data model
?
This work was supported by the EU FP7 project TELEIOS (257662), the Greek
NSRF project SWeFS (180), and the EU project Optique (318338).
3
See http://wikipedia.org/wiki/Sextant for the explanation of the name.
stRDF, the query language stSPARQL, and their efficient implementation in the
geospatial RDF store Strabon [1]. stRDF and stSPARQL go beyond the OGC
standard GeoSPARQL by allowing the representation and querying of linked
geospatial data that changes over time [1,3]. SexTant (and this demo paper)
extends the research presented in [1] by demonstrating how graphs defined in
stRDF/stSPARQL can be explored and visualized.
In related work, the French project GEOPEUPLE is also studying the model-
ing and visualization of spatiotemporal data. As an example, the demo available
at http://www.rotefabrik.free.fr/geopeuple/en/onglets-33038.html vi-
sualizes the evolution of administrative regions in France over the time.
2 New Functionalities of SexTant
SexTant extends the architecture of our earlier system presented in [4] and shown
in Fig. 1a as follows (new and modified components are highlighted with pink
boxes). First, apart from the the map ontology used by the earlier system and
shown in Fig. 1b, SexTant employs the temporal ontology dictated by stRDF
and stSPARQL for the modeling of valid time [1]. This ontology enables the
introduction of user-defined time and valid time of a triple in stRDF data.
Times are modelled as instants or intervals and are represented using values
of the datatypes xsd:dateTime and strf:period respectively. Second, one can
now use all the temporal features of stSPARQL to query linked spatiotemporal
data encoded in stRDF. In this way the full capabilities of endpoints using the
spatiotemporal RDF store Strabon can be exploited. Third, the module that
translates the results of stSPARQL queries from XML to KML format has been
extended so that the temporal primitives of stRDF that we mentioned above
are translated into the respective temporal primitives of the KML standard.
An example of this transformation is provided in Fig. 1c. Last, SexTant builds
on the Timemap Javascript library (https://code.google.com/p/timemap/)
for visualizing “temporally-enriched” KML files. This enables the visualization
of geospatial features with associated temporal information on a map and a
timeline simultaneously. Timemap has been transparently integrated in the im-
plementation of the earlier system which is based on the Google Web Toolkit
framework.
3 Demonstration Overview
The demonstration of the spatio-temporal features of SexTant will be based on
a real scenario in which an Earth Observation (EO) scientist studies the changes
in the land cover of an area and assesses the damage caused by fires. This sce-
nario is very common in the EO domain, where data is constantly produced
by satellite sensors and is associated with metadata containing, among others,
temporal attributes, such as the time that an image was acquired. Satellite ac-
quisitions are utilized in related applications such as the CORINE Land Cover
(a) (b)
...
SPARQL
query
SPARQL
XML
results
SELECT DISTINCT ?area ?t (strdf:transform(?geometry,
) as ?geo ) http://www.linkedopendata.gr/corineArea_34063
WHERE { 2000-01-01T00:00:00
2012-09-30T00:00:00
?area clc:hasLandUse clc:sclerophyllousVegetation ?t .
?area clc:hasGeometry ?geometry . POLYGON((21.821 38.283,21.821 38.282,...)) Result0
?ba rdf:type noa:BurnedArea ?t2.
21.821,38.283 21.821,38.282...
?ba noa:hasGeometry ?geometry2 .
[2000-01-01T00:00:00,2012-09-30T00:00:00)
FILTER(strdf:mbbIntersects(?geometry, ?geometry2))
FILTER(strdf:before(?t, ?t2))
[2000-01-01T00:00:00,2012-09-30T00:00:00)
}
...
Query
http://www.linkedopendata.gr/corineArea_34063
evalua9on
SPARQL
XML
results
to
KML
file
format
(c)
Fig. 1: (a) SexTant overview and (b) Map ontology (c) Translation of SPARQL
XML results to KML
programme operated by the European Environment Agency that makes available
as a cartographic product the land cover of European areas over time.
To achieve the goal of our scenario, we will combine information derived from
the following datasets that were produced within the project TELEIOS (http:
//www.earthobservatory.eu/): the CORINE Land Cover dataset of year 2000,
a Fire Hotspots dataset that provides information about fire hotspots in Greece,
and a Burned Areas dataset that provides detailed information about areas of
Greece that have been affected by fires during a recent fire season. The EO
scientist will use SexTant to visualize the results of stSPARQL queries that use
several thematic, spatial and temporal criteria so that she will be able to derive
implicit links among the involved datasets due to their spatial and temporal
correlation.
In our scenario, first we will visualize on a map the areas that have been
classified as “sclerophyllous vegetation” according to the CORINE Land Cover
dataset of year 2000. The valid time of the triples that encode information about
these areas will be projected on the timeline. Next, a new layer that visualizes
the hotspots that have been identified during the fire season will be displayed
on the map while the timeline will display the time when the hotspots were
detected. Then, a new layer that depicts the areas that were burned during the
forest fires of 2012 will be overlayed on the map and the timeline. The resulting
map will display to the EO scientist the schlerophyllous forests that got burnt by
Fig. 2: A screenshot from SexTant depicting the evolution of the land cover
the forest fires of 2012 along with a preview of the evolution of the forest fires as
they were detected by satellites so that she can assess the severity of the damage
caused by fires. A similar procedure will be used in order to discover implicit
links among the datasets enriched with provenance information, e.g., discover the
cause of changes in the land cover of areas as represented in CORINE through
the visualization and overlay of the other datasets. Such implicit links can later
on be asserted to enrich all datasets.
Layers that contain solely geospatial information will be retrieved by eval-
uating a GeoSPARQL query on a Strabon, Oracle, Parliament, or Virtuoso
endpoint, while layers that contain spatial and temporal information will be
retrieved by evaluating an stSPARQL query on Strabon. The reason for this
choice is that stSPARQL is the only language that provides the spatial and
temporal primitives that are needed for this scenario, while Strabon is cur-
rently the only “temporally-enabled” geospatial RDF store as we have dis-
cussed in [1]. In this respect our demo will also serve to showcase the new
functionalities of the system Strabon as presented in [1]. A video demonstra-
tion of SexTant that follows the scenario described in this section is available at
http://strabon.di.uoa.gr/sexTant/sexTant-demo-full-version.ogv.
References
1. Bereta, K., Smeros, P., Koubarakis, M.: Representation and querying of valid time
of triples in linked geospatial data. In: ESWC. LNCS, vol. 7882, pp. 259–274 (2013)
2. Koubarakis, M., Karpathiotakis, M., Kyzirakos, K., Nikolaou, C., Sioutis, M.: Data
Models and Query Languages for Linked Geospatial Data. LNCS, vol. 7487, pp.
290–328. Springer (2012)
3. Kyzirakos, K., Karpathiotakis, M., Koubarakis, M.: Strabon: A Semantic Geospatial
DBMS. In: ISWC. LNCS, vol. 7649, pp. 295–311. Springer (2012)
4. Nikolaou, C., Dogani, K., Kyzirakos, K., Koubarakis, M.: Sextant: Browsing and
Mapping the Ocean of Linked Geospatial Data. ESWC 2013. Demo paper