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An Empirical Study on Data-driven Requirements Elicitation : Reflections from Nordic Enterprises

Martinez, Alejandro (author)
Nexer Group AB, Sweden
Melin, Marcus (author)
Stockholms universitet,Institutionen för data- och systemvetenskap
Koutsopoulos, Georgios (author)
Stockholms universitet,Institutionen för data- och systemvetenskap
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Zdravkovic, Jelena (author)
Stockholms universitet,Institutionen för data- och systemvetenskap
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 (creator_code:org_t)
RWTH Aachen University, 2021
2021
English.
In: Proceedings of the Forum at Practice of Enterprise Modeling 2021 (PoEM-Forum 2021). - : RWTH Aachen University. ; , s. 39-48
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • There is a plethora of digital data sources that may be exploited for collecting requirements for system development and evolution. In contrast to human sources, i.e. stakeholders, digital sources continuously generate data that is often not originally created for the purposes of requirements elicitation, e.g. on forums, microblogs, machine-generated trace logs, and sensor data. Streams of large volumes of data can be exploited to enable automation of a continuous requirements elicitation process using AI techniques that combine natural language or machine data processing, with machine learning. On the other hand, the complex characteristics of big data due to its size, lack of structure, high dynamics, and low predictability, present numerous challenges on the process of extracting requirements-related information that would be of a clear value for companies. The purpose of this interview study was to, from the practitioners’ perspective, elicit their overall expectations and needs for a method for the elicitation of system requirements from digital data sources. Semi-structured interviews were conducted with several industrial experts from different business domains and the collected empirical data has been analyzed using thematic analysis. The results lead to the identification of a set of hig-hlevel requirements related to the method for the elicitation from digital data sources.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Systemvetenskap, informationssystem och informatik (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Information Systems (hsv//eng)

Keyword

Data-driven Requirements Engineering
Big Data
Requirements Elicitation
Agile Requirements Engineering
Enterprise Modeling
data- och systemvetenskap
Computer and Systems Sciences

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