TY - GEN
T1 - A semantic approach to retrieving, linking, and integrating heterogeneous geospatial data
AU - Zhang, Ying
AU - Chiang, Yao Yi
AU - Szekely, Pedro
AU - Knoblock, Craig A.
PY - 2013
Y1 - 2013
N2 - There is a tremendous amount of geospatial data available, and there are numerous methods for extracting, processing and integrating geospatial sources. However, end-users' ability to retrieve, combine, and integrate heterogeneous geospatial data is limited. This paper presents a new semantic approach that allows users to easily extract, link, and integrate geospatial data from various sources by demonstration in an interactive interface, which is implemented in a tool called Karma. First, we encapsulate the retrieval algorithms as web services and invoke the services to extract geospatial data from various sources. Then we model and publish the extracted geospatial data to RDF for eliminating the data heterogeneity. Finally, we link the geospatial data (in RDF) from different sources using a semantic matching algorithm and integrate them using SPARQL queries. This approach empowers end users to rapidly extract geospatial data from diverse sources, to easily eliminate heterogeneity and to semantically link and integrate sources.
AB - There is a tremendous amount of geospatial data available, and there are numerous methods for extracting, processing and integrating geospatial sources. However, end-users' ability to retrieve, combine, and integrate heterogeneous geospatial data is limited. This paper presents a new semantic approach that allows users to easily extract, link, and integrate geospatial data from various sources by demonstration in an interactive interface, which is implemented in a tool called Karma. First, we encapsulate the retrieval algorithms as web services and invoke the services to extract geospatial data from various sources. Then we model and publish the extracted geospatial data to RDF for eliminating the data heterogeneity. Finally, we link the geospatial data (in RDF) from different sources using a semantic matching algorithm and integrate them using SPARQL queries. This approach empowers end users to rapidly extract geospatial data from diverse sources, to easily eliminate heterogeneity and to semantically link and integrate sources.
KW - extraction
KW - geospatial data
KW - information integration
KW - ontology
KW - semantic modeling
KW - source linking
UR - http://www.scopus.com/inward/record.url?scp=84891064282&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84891064282&partnerID=8YFLogxK
U2 - 10.1145/2516911.2516914
DO - 10.1145/2516911.2516914
M3 - Conference contribution
AN - SCOPUS:84891064282
SN - 9781450323468
T3 - ACM International Conference Proceeding Series
SP - 31
EP - 37
BT - Joint Proc. of the Workshop on AI Problems and Approaches for Intelligent Environments, AI@IE 2013 and Workshop on Semantic Cities, SemCities 2013 - In Conj. with the 23rd IJCAI 2013
T2 - Joint Workshop on AI Problems and Approaches for Intelligent Environments, AI@IE 2013 and Workshop on Semantic Cities, SemCities 2013 - In Conj. with the 23rd Int. Joint Conf. on Artificial Intelligence, IJCAI 2013
Y2 - 4 August 2013 through 5 August 2013
ER -