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		<issn>1983-8409</issn>
		<issn>2177-8833</issn>
		<citationkey>VeroneseRosaVijaBolz:2009:GeNuLa</citationkey>
		<title>Generalized numerical lattices for time series representation in complex data systems</title>
		<year>2009</year>
		<month>June</month>
		<secondarytype>PRE PI</secondarytype>
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		<author>Veronese, Thalita B.,</author>
		<author>Rosa, Reinaldo Roberto,</author>
		<author>Vijaykumar, Nandamudi Lankalapali,</author>
		<author>Bolzan, Maurício J. A.,</author>
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		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Universidade do Vale do Paraíba</affiliation>
		<journal>Journal of Computational Interdisciplinary Sciences</journal>
		<volume>1</volume>
		<number>2</number>
		<pages>175-184</pages>
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		<keywords>multivariate time series, complex data systems, data representation, data integration, data modeling, data mining, systemic analysis.</keywords>
		<abstract>Analysis of information from multiple data sources obtained through high resolution instrumental measurements has become a fundamental task in all scientific areas. The development of expert methods able to treat such multi-source data systems, with both large variability and measurement extension, is a key for studying complex scientific phenomena, especially those related to systemic analysis in space and environmental sciences. In this paper, we propose a time series generalization introducing the concept of generalized numerical lattice, which represents a discrete sequence of temporal measures for a given variable. In this novel representation approach each generalized numerical lattice brings post-analytical data information. We define a generalized numerical lattice  as a set of three coefficients, representing the following data properties: dimensionality, size and post-analytical parameters, respectively. From this generalization, any multi-source database can be reduced to a closed set a classified time series in spatio-temporal generalized dimensions. As a case study, we show a preliminary application in space science data, highlighting the possibility of a real time analysis expert system to be developed in a future work.</abstract>
		<area>COMP</area>
		<language>en</language>
		<targetfile>generalized numerical lattices.pdf</targetfile>
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