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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Taylor & Francis Group
2019
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oai:doaj.org-article:08e2f4b5643c4e4bae97db189e6c8ad62021-12-02T18:31:22ZData quilting: Art and science of analyzing disparate data2331-197510.1080/23311975.2019.1629095https://doaj.org/article/08e2f4b5643c4e4bae97db189e6c8ad62019-01-01T00:00:00Zhttp://dx.doi.org/10.1080/23311975.2019.1629095https://doaj.org/toc/2331-1975Motivated 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.Murugan AnandarajanChelsey HillTaylor & Francis Grouparticledata quiltingmixed methodstext analyticsvisual analyticsstory tellingresearch methodsBusinessHF5001-6182Management. Industrial managementHD28-70ENCogent Business & Management, Vol 6, Iss 1 (2019) |
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data quilting mixed methods text analytics visual analytics story telling research methods Business HF5001-6182 Management. Industrial management HD28-70 |
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data quilting mixed methods text analytics visual analytics story telling research methods Business HF5001-6182 Management. Industrial management HD28-70 Murugan Anandarajan Chelsey Hill Data quilting: Art and science of analyzing disparate data |
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. |
format |
article |
author |
Murugan Anandarajan Chelsey Hill |
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 |
publishDate |
2019 |
url |
https://doaj.org/article/08e2f4b5643c4e4bae97db189e6c8ad6 |
work_keys_str_mv |
AT murugananandarajan dataquiltingartandscienceofanalyzingdisparatedata AT chelseyhill dataquiltingartandscienceofanalyzingdisparatedata |
_version_ |
1718377960505868288 |