Latest News on Information Engineering : April 21

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Latest News on Information Engineering : April 21

April 26, 2021 Engineering 0

[1] The Contradictory Structure of Systems Development Methodologies: Deconstructing the IS-User Relationship in Information Engineering

In this paper we show that systems development methodologies may contain incompatible assumptions about the role of users and information systems (IS) personnel during systems development. Using deconstruction, we analyze and interpret a systems development methodology currently receiving considerable attention—Information Engineering. We find that this methodology’s characterization of IS-user relations and, in particular, its recommended partitioning of responsibility between IS and users is inconsistent and contradictory. Despite a heavy emphasis on user involvement, users are given a relatively passive role to play during development. At the same time, users are expected to sign off on projects and take responsibility for project outcomes. We suggest that such prescriptions, when put into action during systems development, make the relationship between users and IS personnel problematic. Further, we argue that the contradictions we surface in the methodology reflect contradictions and ideologies in the context within which systems development occurs. Our analysis raises important questions about the relationship between the production and consumption of information technology in organizations.

[2] Method engineering: engineering of information systems development methods and tools

This paper proposes the term method engineering for the research field of the construction of information systems development methods and tools. Some research issues in method engineering are identified. One major research topic in method engineering is discussed in depth: situational methods, i.e. the configuration of a project approach that is tuned to the project at hand. A language and support tool for the engineering of situational methods are discussed.

[3] Understanding the Philosophical Underpinnings of Software Engineering Research in Information Systems

The Information Systems (IS) discipline, and related research, focuses on the development, understanding, and use of technology to meet business needs. Technology, in particular “software,” is the basis for IS research, making software engineering a critical component of research in the IS domain. While the importance of software development is well accepted, what constitutes high quality software engineering research is not well defined. Perhaps this is because some software development clearly is not research and it is hard to distinguish between pure application development, and systems development that pushes the boundaries of knowledge. Sir Karl Popper argued that the scientific quality of research is not based on its empirical method, but on the nature of the questions asked. Our research suggests that software engineering can meet Popper’s criteria for scientific research.


Drawing on well-established research philosophies, we propose a software engineering research methodology (SERM) and discuss the utility of this methodology for contributing to and expanding the IS body of knowledge. We also describe the considerations that need to be addressed by SERM to enhance acceptability of software engineering research in IS. Our suggestions are corroborated with a review of current IS software engineering research reported in leading IS journals.

[4] Using Ontology Engineering Methods to Improve Computer Science and Data Science Skills

This paper focuses on issues of ontology construction process, Computing Classification System and Data Science domain ontology all used to help not only IT-students but any IT-specialists from industry and academia also to tackle the problems addressing the Big Data and Data Science skills gap. We discuss some methodological aspects of ontology design process and enriching of existing free accessible ontologies and show how suggested methods and software tools help IT-specialists including master students to implement their research work and participate in real world projects. The role of visual data exploration tools for certain issues under discussion and some use cases are discussed.

[5] Diffusion of Innovations: The Status of Building Information Modelling Uptake in Nigeria

Aim: This study evaluated Building Information Modelling (BIM) awareness and adoption in Nigeria through the line of enquiry known as the ‘diffusion of innovations’ and its possible uptake.

Study Design: The study is quantitative in nature and the primary data fetched through questionnaire survey within Nigerian construction industry.

Place and Duration of the Study: Conducted within North-west, North-central and Lagos, Nigeria for a period of 4 months.

Methodology: A quantitative approach was adopted to x-ray the Nigerian construction industry; a structured questionnaire was used across the Architecture, Engineering and Construction (AEC). The generated data were analysed through descriptive statistics (in percentages) and presented in charts and graphs.

Results: The result revealed that 59.5% are aware of BIM technology; 22.8% are aware and currently using BIM and the remaining 17.7% neither aware nor using BIM; consequently, the industry was evaluated just within the Late Majority in terms of awareness and just entered the Early Majority in terms of BIM technology adoption.

Conclusion: Nigeria is at least five years behind US, UK and South Africa. In addition to lagging behind by at least five years, it is also behind by about 10% and 50% for UK and US respectively. The study also discovers the most significant barriers to BIM adoption as lack of BIM experts and lack of collaboration by its team stakeholders. The industry is likely to take the UK pattern in adopting the BIM and Recommendations are made based on the findings of the research



[1] Beath, C.M. and Orlikowski, W.J., 1994. The contradictory structure of systems development methodologies: Deconstructing the IS-user relationship in information engineering. Information Systems Research5(4), pp.350-377.

[2] Brinkkemper, S., 1996. Method engineering: engineering of information systems development methods and tools. Information and software technology38(4), pp.275-280.

[3] Gregg, D.G., Kulkarni, U.R. and Vinzé, A.S., 2001. Understanding the philosophical underpinnings of software engineering research in information systems. Information Systems Frontiers3(2), pp.169-183.

[4] Chuprina, S., Alexandrov, V. and Alexandrov, N., 2016. Using ontology engineering methods to improve computer science and data science skills. Procedia Computer Science80, pp.1780-1790.

[5] Hamma-Adama, M., Salman, H. and Kouider, T., 2017. Diffusion of innovations: the status of building information modelling uptake in Nigeria. Journal of Scientific Research and Reports, pp.1-12.


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