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...
Main Authors: | , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-05-01
|
Series: | Systems |
Subjects: | |
Online Access: | https://www.mdpi.com/2079-8954/7/2/27 |
id |
doaj-571a1db543594bde8bd94ae44d2059bf |
---|---|
record_format |
Article |
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 |
_version_ |
1716744261877104640 |