Framework of integration for collaboration and spatial data mining among heterogeneous sources in the web

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Abstract

This paper highlights the diversity of spatial data of rural and urban properties, constantly generated by different public institutions, as well as the existing problems of exchange of information among them. Firstly, this work describes the results obtained in the study and development of an agile flexible method to offer support construction, implementation and accompaniment activities of free geo-solutions for the web, aiming at a growing community of users and developers who manipulate geographic data. Next, the development of the OpenICGFw (Integration for Collaborative Geospatial Framework for the Web) that seeks, through a single environment to assist in the integration and collaboration among different sources of spatial data in synchrony with the efforts and specifications of OGC and W3C. To do this, the evaluation study for the construction of the framework is presented where it was possible to apply MCDA-C (Multi Criteria Decision Aiding - Constructivist) in the identification of the fundamental and elementary aspects for the construction of the framework. Details are presented by means of a case study that illustrates data exported from different geospatial information systems requiring the integration of census, environmental, urban and rural information over the internet. During the discussion the results obtained using this framework are presented, providing, through web mapping applications, the implementation of collaborative strategies seeking the integration of bases distributed for the use of spatial data mining techniques. © 2010 ACM.

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APA

De Moraes, A. F., & Bastos, L. C. (2010). Framework of integration for collaboration and spatial data mining among heterogeneous sources in the web. In Proc. of the 1st ACM SIGSPATIAL Int. Workshop on Data Mining for Geoinformatics, DMG 2010, offered under the auspices of the 18th Int. Conference on Advances in Geographic Information Systems, ACMGIS (pp. 19–28). https://doi.org/10.1145/1869890.1869893

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