Automatic Data Enrichment in GIS Through Condensate Textual Information

Automatic Data Enrichment in GIS Through Condensate Textual Information

Khaoula Mahmoudi (High School of Communications-Tunis (SUPCOM), Tunisia) and Sami Faïz (National Institute in Applied Sciences and Technology (INSAT), Tunisia)
DOI: 10.4018/978-1-60566-242-8.ch031
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Geographic Information Systems (GIS) (Faïz, 1999) are being increasingly used to manage, retrieve, and store large quantities of data which are tedious to handle manually. The GIS power is to help managers make critical decisions they face daily. The ability to make sound decisions relies upon the availability of relevant information. Typically, spatial databases do not contain much information that could support the decision making process in all situations. Besides, Jack Dangermond, president of a private GIS software company, argued that “The application of GIS is limited only by the imagination of those who use it”. Hence, it is of primary interest to provide other data sources to make these systems rich information sources.
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Typically the database enrichment can be classified as; spatial enrichment and semantic one.

Spatial enrichment is interested to the spatial aspect of the GDB. One use of this enrichment is its application within the overall generalization process. In this context, the newly acquired information are used to provide geometrical knowledge and procedural knowledge in terms of generalisation algorithms and operations order, to guide the choice of the generalization solution (Plazanet, 1996).

For the semantic enrichment, it aims to link unstructured data to the already available structured thematic data (also referred as aspatial, descriptive or semantic) stored in the GDB. The works classified under this category are: Metacarta (MetaCarta, 2005), GeoNode (Hyland et al., 1999), Persus (David, 2002).

MetaCarta’s technology provides a bridge between document systems and GIS systems. MetaCarta, allows the semantic enrichment through the Geographic Text Search (GTS). GTS allows to link textual documents to geographic entities localised in digital maps to add supplementary data to GDB. GTS is offered as an extension to the GIS ArcGIS.

For GeoNode (Geographic News On Demand Environment), given a sequence of news stories, GeoNode, can identify different events that happen at particular time and place. GeoNode makes use of the Information Extraction technique and more precisely the Alembic system to accomplish the enrichment. The latter allows to determine the named entities for geospatial visualizations. The GIS ArcView supports GeoNode.

Key Terms in this Chapter

Rhetorical Structure Tree: A binary tree, which describes the rhetorical structure of every coherent discourse.

MDS: Multi-Document Summarization (MDS) is the process of distilling the most important information from a corpus of documents.

GIS: Geographic Information System (GIS) is a computer system capable of capturing, storing, analyzing, and displaying geographically referenced information. These latter are stored in a Geographic database (GDB).

Segmentation: Text segmentation is the process of segmenting a text stream into topically coherent segments.

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