Design Science Research: Evaluation in the Lens of Big Data Analytics

Given the different types of artifacts and their various evaluation methods, one of the main challenges faced by researchers in design science research (DSR) is choosing suitable and efficient methods during the artifact evaluation phase. With the emergence of big data analytics, data scientists con...

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Bibliographic Details
Main Authors: Ahmed Elragal, Moutaz Haddara
Format: Article
Language:English
Published: MDPI AG 2019-05-01
Series:Systems
Subjects:
DSR
Online Access:https://www.mdpi.com/2079-8954/7/2/27
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spelling doaj-571a1db543594bde8bd94ae44d2059bf2020-11-24T21:15:54ZengMDPI AGSystems2079-89542019-05-01722710.3390/systems7020027systems7020027Design Science Research: Evaluation in the Lens of Big Data AnalyticsAhmed Elragal0Moutaz Haddara1Department of Computer Science, Electrical and Space Engineering, Computer and Systems Science, Luleå University of Technology, 97187 Luleå, SwedenDepartment of Technology, Kristiania University College, 0186 Oslo, NorwayGiven the different types of artifacts and their various evaluation methods, one of the main challenges faced by researchers in design science research (DSR) is choosing suitable and efficient methods during the artifact evaluation phase. With the emergence of big data analytics, data scientists conducting DSR are also challenged with identifying suitable evaluation mechanisms for their data products. Hence, this conceptual research paper is set out to address the following questions. Does big data analytics impact how evaluation in DSR is conducted? If so, does it lead to a new type of evaluation or a new genre of DSR? We conclude by arguing that big data analytics should influence how evaluation is conducted, but it does not lead to the creation of a new genre of design research.https://www.mdpi.com/2079-8954/7/2/27DSRbig data analyticsevaluation
collection DOAJ
language English
format Article
sources DOAJ
author Ahmed Elragal
Moutaz Haddara
spellingShingle Ahmed Elragal
Moutaz Haddara
Design Science Research: Evaluation in the Lens of Big Data Analytics
Systems
DSR
big data analytics
evaluation
author_facet Ahmed Elragal
Moutaz Haddara
author_sort Ahmed Elragal
title Design Science Research: Evaluation in the Lens of Big Data Analytics
title_short Design Science Research: Evaluation in the Lens of Big Data Analytics
title_full Design Science Research: Evaluation in the Lens of Big Data Analytics
title_fullStr Design Science Research: Evaluation in the Lens of Big Data Analytics
title_full_unstemmed Design Science Research: Evaluation in the Lens of Big Data Analytics
title_sort design science research: evaluation in the lens of big data analytics
publisher MDPI AG
series Systems
issn 2079-8954
publishDate 2019-05-01
description Given the different types of artifacts and their various evaluation methods, one of the main challenges faced by researchers in design science research (DSR) is choosing suitable and efficient methods during the artifact evaluation phase. With the emergence of big data analytics, data scientists conducting DSR are also challenged with identifying suitable evaluation mechanisms for their data products. Hence, this conceptual research paper is set out to address the following questions. Does big data analytics impact how evaluation in DSR is conducted? If so, does it lead to a new type of evaluation or a new genre of DSR? We conclude by arguing that big data analytics should influence how evaluation is conducted, but it does not lead to the creation of a new genre of design research.
topic DSR
big data analytics
evaluation
url https://www.mdpi.com/2079-8954/7/2/27
work_keys_str_mv AT ahmedelragal designscienceresearchevaluationinthelensofbigdataanalytics
AT moutazhaddara designscienceresearchevaluationinthelensofbigdataanalytics
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