TY - GEN
T1 - Enabling semantic search and knowledge discovery for arcgis online
T2 - 18th AGILE International Conference on Geographic Information Science, AGILE 2015
AU - Hu, Yingjie
AU - Janowicz, Krzysztof
AU - Prasad, Sathya
AU - Gao, Song
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - ArcGIS Online is a unified Web portal designed by Environment System Research Institute (ESRI). It contains a rich collection of Web maps, layers, and services contributed by GIS users throughout the world. The metadata about these GIS resources reside in data silos that can be accessed via a Web API. While this is sufficient for simple syntax-based searches, it does not support more advanced queries, e.g., finding maps based on the semantics of the search terms, or performing customized queries that are not pre-designed in the API. In metadata, titles and descriptions are commonly available attributes which provide important information about the content of the GIS resources. However, such data cannot be easily used since they are in the form of unstructured natural language. To address these difficulties, we combine data-driven techniques with theory-driven approaches to enable semantic search and knowledge discovery for ArcGIS Online. We develop an ontology for ArcGIS Online data, convert the metadata into Linked Data, and enrich the metadata by extracting thematic concepts and geographic entities from titles and descriptions. Based on a human participant experiment, we calibrate a linear regression model for semantic search, and demonstrate the flexible queries for knowledge discovery that are not possible in the existing Web API. While this research is based on the ArcGIS Online data, the presented methods can also be applied to other GIS cloud services and data infrastructures.
AB - ArcGIS Online is a unified Web portal designed by Environment System Research Institute (ESRI). It contains a rich collection of Web maps, layers, and services contributed by GIS users throughout the world. The metadata about these GIS resources reside in data silos that can be accessed via a Web API. While this is sufficient for simple syntax-based searches, it does not support more advanced queries, e.g., finding maps based on the semantics of the search terms, or performing customized queries that are not pre-designed in the API. In metadata, titles and descriptions are commonly available attributes which provide important information about the content of the GIS resources. However, such data cannot be easily used since they are in the form of unstructured natural language. To address these difficulties, we combine data-driven techniques with theory-driven approaches to enable semantic search and knowledge discovery for ArcGIS Online. We develop an ontology for ArcGIS Online data, convert the metadata into Linked Data, and enrich the metadata by extracting thematic concepts and geographic entities from titles and descriptions. Based on a human participant experiment, we calibrate a linear regression model for semantic search, and demonstrate the flexible queries for knowledge discovery that are not possible in the existing Web API. While this research is based on the ArcGIS Online data, the presented methods can also be applied to other GIS cloud services and data infrastructures.
KW - ArcGIS online
KW - Geoportal
KW - Linked data
KW - Metadata
KW - Semantic search
UR - https://www.scopus.com/pages/publications/84945928681
U2 - 10.1007/978-3-319-16787-9_7
DO - 10.1007/978-3-319-16787-9_7
M3 - Conference contribution
AN - SCOPUS:84945928681
SN - 9783319167862
T3 - Lecture Notes in Geoinformation and Cartography
SP - 107
EP - 124
BT - AGILE 2015 - Geographic Information Science as an Enabler of Smarter Cities and Communities
A2 - Santos, Maribel Yasmina
A2 - Bacao, Fernando
A2 - Painho, Marco
PB - Kluwer Academic Publishers
Y2 - 9 June 2015 through 12 June 2015
ER -