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Phenomena: a visual query language for continuous fields
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Source Geographic Information Systems archive
Proceedings of the 11th ACM international symposium on Advances in geographic information systems table of contents
New Orleans, Louisiana, USA
Pages: 147 - 153  
Year of Publication: 2003
ISBN:1-58113-730-3
Authors
Luca Paolino  University of Salerno, Baronissi, Italy
Genoveffa Tortora  University of Salerno, Baronissi, Italy
Monica Sebillo  University of Salerno, Baronissi, Italy
Giuliana Vitiello  University of Salerno, Baronissi, Italy
Robert Laurini  INSA de Lyon, Villerurbane Cedex, France
Sponsors
ACM: Association for Computing Machinery
SIGMIS: ACM Special Interest Group on Management Information Systems
SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
ACM  New York, NY, USA
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ABSTRACT

In the present paper we introduce a visual query language, Phenomena, able to manage continuous fields, which represent real-world events. In GIS applications, continuous fields represent phenomena related to the environment and its resources. Recently, much attention has been devoted to the field view of geographic phenomena, where the geographic world can be described by a number of variables, each measurable at any point. While objects are distinguished by their dimensions, and can be associated with points, lines, or areas, fields can be distinguished by what varies, and how smoothly. Thus, when dealing with continuous fields, a basic requirement is represented by users' capability to capture some features of a scenario, by selecting an area of interest and handling the heterogeneous events involved. Phenomena makes this task easy to implement, thanks to a quite intuitive visual representation of both continuous fields and conditions, which involve them. A peculiar feature of the visual language is the use of geometries to select portions of continuous fields, on the basis of spatial conditions. The heterogeneous nature of fields and objects is also reflected in the visualization of query results.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Luca Paolino: colleagues
Genoveffa Tortora: colleagues
Monica Sebillo: colleagues
Giuliana Vitiello: colleagues
Robert Laurini: colleagues

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