The world of digital technology is constantly evolving, leading to a multitude of possibilities for innovation and improvement in our lives. Key to the creation of these new technologies are the steps of designing, creating, and evaluating prototypes - a process made more effective through frameworks like the Information System Design Theory (ISDT).
So, what exactly is ISDT? In simple terms, it's an organised approach to design technology, drawn from the field of design science research. It enables us to create new prototypes systematically and evaluate their effectiveness. In the process, it helps us understand the technology better and make it more impactful.
As part of the ongoing Serendipity Engine project, we're exploring how to incorporate ISDT and bring serendipity (that delightful experience of unexpected, beneficial discoveries) into the digital sphere, specifically in web applications.
Understanding Information System Design Theories
Designing such an effective information system isn't a piece of cake. It calls for understanding user needs, technology capabilities, and the context in which the system operates. That's where ISDTs come in.
An ISDT is a prescriptive theory that provides certain principles to guide us in the design of effective information systems. It takes the form of a structured approach, involving a kernel theory (which explains why certain designs will work under certain conditions), meta-requirements (high-level requirements that define what the system should do), and meta-design (how the system should be built to meet these requirements).
This might sound a bit technical, so let's look at some examples. One well known ISDT is the relational database design model, first proposed by Edgar F. Codd in 1970. This model is built on the kernel theory that a well-designed database should have tables with well-defined relationships between them. The meta-requirements include data storage and retrieval, data integrity, and support for multiple users. The meta-design principles involve using a relational schema, normalisation of data to minimise redundancy, and the use of a query language to access and manipulate data [1, 2].
Similarly, other models have been developed following the principles of an ISDT, such as the vigilant executive information systems (providing real-time business information for executives) , learning-oriented knowledge management systems (supporting organisations to capture, share, and apply knowledge)  and the comparative judgement of competences in education .
Applying ISDT to the Serendipity Engine
One of the challenges we face in the Serendipity Engine project is finding a sound theoretical framework to guide and justify our design decisions. We believe that an ISDT provides such a framework, helping us describe our design decisions in detail across different scenarios and stakeholders.
Using an ISDT, we aim to articulate the goals, requirements, assumptions, design principles, methods, and artefacts of our project in a structured way. We're particularly keen on documenting how various factors affect the experience of serendipity when using our prototypes. These factors could range from external influences such as weather, an ongoing crisis, or even the level of inflation, but also other factors more under our control, such as the design and user experience of the mobile applications that aim to engender serendipity.
As our project progresses, we're looking forward to seeing how ISDT will help us make our technology more effective and serendipitous. The use of this theory represents a significant step forward in our ongoing efforts to make the most of digital technology in enriching the human experience.
The first version of the living document that describes our ISDT and several important design principles and affordances (D4.4a) is already available here. The document not only serves to provide an overview of the main learnings for internal use, but it can also be used by other parties as a guideline or framework to base their work on. As the project progresses, the document will be further completed with the applications of the design theory in the three pilot studies alongside with the lessons learned regarding designing for serendipity.
Does this spark your interest?
We hope to meet you along our way, serendipitously or meticulously planned. You might increase the chances of staying informed about the Serendipity Engine project by subscribing to our newsletter or connecting on LinkedIn.
This post is written by imec. It is mainly responsible for the work package on the pilot integrations and validations. Imec's researchers on this project are Casper Van Gheluwe, Thomas De Meester, Olivia Willems, Eridona Selita, and project officer Evelien Marlier.
 E. F. Codd, “A relational model of data for large shared data banks,” Communications of the ACM, vol. 13, no. 6, pp. 377-387, 1970.
 D. Jones and G. Shirley, “The anatomy of a design theory,” Journal of the Association for Information Systems, vol. 8, no. 5, 2007.
 J. G. Walls, G. R. Widmeyer and O. A. El Sawy, “Building an information system design theory for vigilant EIS,” Information systems research, vol. 3, no. 1, pp. 36-59, 1992.
 D. Hall, D. Paradice and J. F. Courtney, “Building a Theoretical Foundation for a Learning-oriented Knowledge Management System,” Journal of Information Technology Theory and Application, pp. 63 - 84, 2003.
 T. Coenen, L. Coertjens, P. Vlerick, M. Lesterhuis, A. V. Mortier, V. Donche, P. Ballon and S. De Maeyer, “An information system design theory for the comparative judgement of competences,” vol. 27, no. 2, pp. 248-261, 2018.