Aspectual Analysis as an alternative way of understanding the definitions of Big Data

Sina Joneidy; Maria Burke

Aspectual Analysis as an alternative way of understanding the definitions of Big Data

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper considers the application of philosophy to the field of Big Data. In particular, thepaper considers how “Dooyeweerd’s aspects of everyday life” can contribute to the reconceptualization of Big Data. The paper reviews recent debates relating to Big Data as a concept by investigating the meaning of Big Data definitions gathered in the De Mauro study published in 2015. In doing so, Dooyeweerd’s “philosophy of everyday life” can assist us, not only in finding the more precise meaning of definitions, but also in contributing to concepts that help our understanding of Big Data. In conclusion, this study shows a useful way of exploring the meaning of Big Data definitions towards affirming and enriching them

Original language	English
Title of host publication	International Data and Information Management Conference (IDIMC 2016)
Publisher	Loughborough University
Pages	42-53
Publication status	Published - 12 Jan 2016
Event	International Data and Information Management Conference 2016 - University, Loughborough, United Kingdom Duration: 12 Jan 2016 → 13 Jan 2016

Conference

Conference	International Data and Information Management Conference 2016
Abbreviated title	IDIMC 2016
Country/Territory	United Kingdom
City	Loughborough
Period	12/01/16 → 13/01/16

Cite this

@inproceedings{fc08df3696c94afea7d37d6fdc119d69,

title = "Aspectual Analysis as an alternative way of understanding the definitions of Big Data",

abstract = "This paper considers the application of philosophy to the field of Big Data. In particular, thepaper considers how “Dooyeweerd{\textquoteright}s aspects of everyday life” can contribute to the reconceptualization of Big Data. The paper reviews recent debates relating to Big Data as a concept by investigating the meaning of Big Data definitions gathered in the De Mauro study published in 2015. In doing so, Dooyeweerd{\textquoteright}s “philosophy of everyday life” can assist us, not only in finding the more precise meaning of definitions, but also in contributing to concepts that help our understanding of Big Data. In conclusion, this study shows a useful way of exploring the meaning of Big Data definitions towards affirming and enriching them",

author = "Sina Joneidy and Maria Burke",

year = "2016",

month = jan,

day = "12",

language = "English",

pages = "42--53",

booktitle = "International Data and Information Management Conference (IDIMC 2016)",

publisher = "Loughborough University",

note = "International Data and Information Management Conference 2016, IDIMC 2016 ; Conference date: 12-01-2016 Through 13-01-2016",

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T1 - Aspectual Analysis as an alternative way of understanding the definitions of Big Data

AU - Joneidy, Sina

AU - Burke, Maria

PY - 2016/1/12

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N2 - This paper considers the application of philosophy to the field of Big Data. In particular, thepaper considers how “Dooyeweerd’s aspects of everyday life” can contribute to the reconceptualization of Big Data. The paper reviews recent debates relating to Big Data as a concept by investigating the meaning of Big Data definitions gathered in the De Mauro study published in 2015. In doing so, Dooyeweerd’s “philosophy of everyday life” can assist us, not only in finding the more precise meaning of definitions, but also in contributing to concepts that help our understanding of Big Data. In conclusion, this study shows a useful way of exploring the meaning of Big Data definitions towards affirming and enriching them

AB - This paper considers the application of philosophy to the field of Big Data. In particular, thepaper considers how “Dooyeweerd’s aspects of everyday life” can contribute to the reconceptualization of Big Data. The paper reviews recent debates relating to Big Data as a concept by investigating the meaning of Big Data definitions gathered in the De Mauro study published in 2015. In doing so, Dooyeweerd’s “philosophy of everyday life” can assist us, not only in finding the more precise meaning of definitions, but also in contributing to concepts that help our understanding of Big Data. In conclusion, this study shows a useful way of exploring the meaning of Big Data definitions towards affirming and enriching them

M3 - Conference contribution

SP - 42

EP - 53

BT - International Data and Information Management Conference (IDIMC 2016)

PB - Loughborough University

T2 - International Data and Information Management Conference 2016

Y2 - 12 January 2016 through 13 January 2016

ER -

Aspectual Analysis as an alternative way of understanding the definitions of Big Data

Abstract

Conference

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