Data quilting: Art and science of analyzing disparate data

Motivated by incongruences between today’s complex data, problems and requirements and available methodological frameworks, we propose data quilting as a means of combining and presenting the analysis of multiple types of data to create a single cohesive deliverable. We introduce data quilting as a...

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Main Authors: Murugan Anandarajan, Chelsey Hill
Format: Article
Language:English
Published: Taylor & Francis Group 2019-01-01
Series:Cogent Business & Management
Subjects:
Online Access:http://dx.doi.org/10.1080/23311975.2019.1629095
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spelling doaj-08e2f4b5643c4e4bae97db189e6c8ad62021-07-15T13:47:56ZengTaylor & Francis GroupCogent Business & Management2331-19752019-01-016110.1080/23311975.2019.16290951629095Data quilting: Art and science of analyzing disparate dataMurugan Anandarajan0Chelsey Hill1Drexel UniversityMontclair State UniversityMotivated by incongruences between today’s complex data, problems and requirements and available methodological frameworks, we propose data quilting as a means of combining and presenting the analysis of multiple types of data to create a single cohesive deliverable. We introduce data quilting as a new analysis methodology that combines both art and science to address a research problem. Using a three-layer approach and drawing on the comparable and parallel process of quilting, we introduce and describe each layer: backing, batting and top. The backing of the data quilt is the research problem and method, which supports the upper layers. The batting of the data quilt is the data and data analysis, which adds depth and dimension to the data quilt. Finally, the top layer of the data quilt is the presentation, visualization and storytelling, which pieces together the results into a single, cohesive deliverable. For illustrative purposes, we demonstrate a data quilt analysis using a real-world example concerning identity theft.http://dx.doi.org/10.1080/23311975.2019.1629095data quiltingmixed methodstext analyticsvisual analyticsstory tellingresearch methods
collection DOAJ
language English
format Article
sources DOAJ
author Murugan Anandarajan
Chelsey Hill
spellingShingle Murugan Anandarajan
Chelsey Hill
Data quilting: Art and science of analyzing disparate data
Cogent Business & Management
data quilting
mixed methods
text analytics
visual analytics
story telling
research methods
author_facet Murugan Anandarajan
Chelsey Hill
author_sort Murugan Anandarajan
title Data quilting: Art and science of analyzing disparate data
title_short Data quilting: Art and science of analyzing disparate data
title_full Data quilting: Art and science of analyzing disparate data
title_fullStr Data quilting: Art and science of analyzing disparate data
title_full_unstemmed Data quilting: Art and science of analyzing disparate data
title_sort data quilting: art and science of analyzing disparate data
publisher Taylor & Francis Group
series Cogent Business & Management
issn 2331-1975
publishDate 2019-01-01
description Motivated by incongruences between today’s complex data, problems and requirements and available methodological frameworks, we propose data quilting as a means of combining and presenting the analysis of multiple types of data to create a single cohesive deliverable. We introduce data quilting as a new analysis methodology that combines both art and science to address a research problem. Using a three-layer approach and drawing on the comparable and parallel process of quilting, we introduce and describe each layer: backing, batting and top. The backing of the data quilt is the research problem and method, which supports the upper layers. The batting of the data quilt is the data and data analysis, which adds depth and dimension to the data quilt. Finally, the top layer of the data quilt is the presentation, visualization and storytelling, which pieces together the results into a single, cohesive deliverable. For illustrative purposes, we demonstrate a data quilt analysis using a real-world example concerning identity theft.
topic data quilting
mixed methods
text analytics
visual analytics
story telling
research methods
url http://dx.doi.org/10.1080/23311975.2019.1629095
work_keys_str_mv AT murugananandarajan dataquiltingartandscienceofanalyzingdisparatedata
AT chelseyhill dataquiltingartandscienceofanalyzingdisparatedata
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