Contextualizing geometric data analysis and related data analytics: A virtual microscope for big data analytics

Journal article


Farid, Mohsen and Murtagh, Fionn 2017. Contextualizing geometric data analysis and related data analytics: A virtual microscope for big data analytics. Journal of Interdisciplinary Methodologies and Issues in Sciences. https://doi.org/10.18713/JIMIS-010917-3-1
AuthorsFarid, Mohsen and Murtagh, Fionn
Abstract

The relevance and importance of contextualizing data analytics is described. Qualitative characteristics might form the context of quantitative analysis. Topics that are at issue include: contrast, baselining, secondary data sources, supplementary data sources, dynamic and heterogeneous data. In geometric data analysis, especially with the Correspondence Analysis platform, various case studies are both experimented with, and are reviewed. In such aspects as paradigms followed, and technical implementation, implicitly and explicitly, an important point made is the major relevance of such work for both burgeoning analytical needs and for new analytical areas including Big Data analytics, and so on. For the general reader, it is aimed to display and describe, first of all, the analytical outcomes that are subject to analysis here, and then proceed to detail the more quantitative outcomes that fully support the analytics carried out.

Keywordsanalytical focus; contextualization of data and information; Correspondence Analysis; Multiple Correspondence Analysis; dimensionality reduction; mental health
Year2017
JournalJournal of Interdisciplinary Methodologies and Issues in Sciences
PublisherLe Centre pour la Communication Scientifique Directe
Digital Object Identifier (DOI)https://doi.org/10.18713/JIMIS-010917-3-1
Web address (URL)http://hdl.handle.net/10545/625220
http://creativecommons.org/licenses/by-nc-nd/4.0/
hdl:10545/625220
Publication dates06 Feb 2017
Publication process dates
Deposited02 Oct 2020, 13:25
Accepted12 Feb 2016
Rights

Attribution-NonCommercial-NoDerivatives 4.0 International

ContributorsUniversity of Derby and University of Huddersfield
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