Multi-representation Lens For Visual Analytics

dc.creatorGatto S.D.
dc.creatorSantanche A.
dc.date2012
dc.date2015-06-25T20:27:09Z
dc.date2015-11-26T15:12:36Z
dc.date2015-06-25T20:27:09Z
dc.date2015-11-26T15:12:36Z
dc.date.accessioned2018-03-28T22:22:41Z
dc.date.available2018-03-28T22:22:41Z
dc.identifier9780769547480
dc.identifierProceedings - 2012 Ieee 28th International Conference On Data Engineering Workshops, Icdew 2012. , v. , n. , p. 341 - 346, 2012.
dc.identifier
dc.identifier10.1109/ICDEW.2012.58
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-84869036512&partnerID=40&md5=31dc2ec4583bf9116ae0d8de56c36249
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/90683
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/90683
dc.identifier2-s2.0-84869036512
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1258420
dc.descriptionModern data analysis deeply relies on computational visualization tools, specially when spatial data is involved. Important efforts in governmental and private agencies are looking for patterns and insights buried in dispersive, massive amounts of data (conventional, spatiotemporal, etc.). In Visual Analytics users must be empowered to analyze data from different perspectives, integrating, transforming, aggregating and deriving new representations of conventional as well as spatial data. However, a challenge for visual analysis tools is how to articulate such wide variety of data models and formats, specially when multiple representations of geographic elements are involved. A usual approach is to convert data to a database - e.g., a multirepresentation database - which centralizes and homogenizes them. This approach has restrictions when facing the dynamic and distributed model of the Web. In this paper we propose an on the fly and on demand multi-representation data integration and homogenization approach, named Lens, as an alternative that fits better with the Web. It combines a metamodel driven approach to transform data to a unifying multidimensional and multirepresentation model, with a middleware-based architecture for seamless and on-the-fly data access, tailored to Visual Analytics. © 2012 IEEE.
dc.description
dc.description
dc.description341
dc.description346
dc.descriptionMicrosoft,National Science Foundation,EMC,Greenplum,HP
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dc.languageen
dc.publisher
dc.relationProceedings - 2012 IEEE 28th International Conference on Data Engineering Workshops, ICDEW 2012
dc.rightsfechado
dc.sourceScopus
dc.titleMulti-representation Lens For Visual Analytics
dc.typeActas de congresos


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