Abstract
Nowadays databases are storing huge volumes of data which are referenced in space and time, representing spatio-temporal dynamism with multivariate connections, containing implicit structures, relationships and interactions. When we are dealing with complex data in Business Intelligent (BI) systems, it is likely that the decision maker does not know what useful information (interesting pat- terns, relationships and correlations) can or should be obtained from the dataset available to him. This problem is mentioned in Geovisual Analytics (GA) area as the information overload problem (IOP). To address it, a conceptual analysis mode emerge “Analyze first, show the important, zoom, filter analyze further, details on demand”, which has underlying a model that combines the strengths of automatic data analysis and interactive visualization. This paper proposes an approach to address the IOP by providing the user with syntheses of changes that could be significant as a way to show the important. Finally, we will sketch a research path discussing how this proposal should be evaluated, its applicability as well its potential for further research.
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BibTeX (Download)
@inproceedings{silva2012information,
title = {Information Overload Problem in Decision Making: The Important Relies on Changes},
author = { Ricardo Filipe Silva},
url = {http://agile-online.org/Conference_Paper/images/phddocs/Proceedings_AGILE_PhD_School_2012.pdf#page=33},
isbn = {978-3-8440-0873-9},
year = {2012},
date = {2012-01-01},
journal = {1st AGILE PhD School},
pages = {29},
abstract = {Nowadays databases are storing huge volumes of data which are referenced in space and time, representing spatio-temporal dynamism with multivariate connections, containing implicit structures, relationships and interactions. When we are dealing with complex data in Business Intelligent (BI) systems, it is likely that the decision maker does not know what useful information (interesting pat- terns, relationships and correlations) can or should be obtained from the dataset available to him. This problem is mentioned in Geovisual Analytics (GA) area as the information overload problem (IOP). To address it, a conceptual analysis mode emerge “Analyze first, show the important, zoom, filter analyze further, details on demand”, which has underlying a model that combines the strengths of automatic data analysis and interactive visualization. This paper proposes an approach to address the IOP by providing the user with syntheses of changes that could be significant as a way to show the important. Finally, we will sketch a research path discussing how this proposal should be evaluated, its applicability as well its potential for further research.},
keywords = {Geovisual Analytics, Information Overload Problem, Spatio-temporal},
pubstate = {published},
tppubtype = {inproceedings}
}