Analysis and Visualization of Large-Scale Time Series Network Data

Patricia Morreale, Allan Goncalves, Carlos Silva

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Large amounts of data ("big data") are readily available and collected daily by global networks worldwide. However, much of the real-time utility of this data is not realized, as data analysis tools for very large datasets, particularly time series data are cumbersome. A methodology for data cleaning and preparation needed to support big data analysis is presented, along with a comparative examination of three widely available data mining tools. This methodology and offered tools are used for analysis of a large-scale time series dataset of environmental data. The case study of environmental data analysis is presented as visualization, providing future direction for data mining on massive data sets gathered from global networks, and an illustration of the use of big data technology for predictive data modeling and assessment.

Original languageEnglish
Title of host publicationModeling and Optimization in Science and Technologies
PublisherSpringer Verlag
Pages211-229
Number of pages19
DOIs
StatePublished - 2015

Publication series

NameModeling and Optimization in Science and Technologies
Volume4
ISSN (Print)2196-7326
ISSN (Electronic)2196-7334

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