Periodic Reporting for period 3 - SIRI (Serendipity in Research and Innovation)
Periodo di rendicontazione: 2021-06-01 al 2022-11-30
‘What is the issue being addressed?’
‘Why is it important for society?’
‘What are the overall objectives?’
Serendipity, the notion of researchers making unexpected and beneficial discoveries, has played an important role in debates about the feasibility and desirability of targeting public investments in research and development. This is the idea that, since the outcomes of research are impossible to predict, research itself is difficult (perhaps even impossible) to manage or direct towards specific social ends.
Research may be uncertain, but it is not random, and we know that industrial R&D managers fund research in areas where they expect returns and organise research to maximise its impact. With public policy, the scenario is slightly different, but there is limited evidence to draw on to support policy making.
Thus, in the SIRI project, we examine the nature of serendipity and develop techniques for its identification and measurement in order to get a sense of the prevalence of the phenomenon. It may well be frequent but relatively insignificant, or rare but highly consequential. We therefore also seek to develop approaches to help evaluate the significance of serendipity, primarily through mapping techniques but also by identifying salient dimensions of analysis.
Since serendipity is likely to take different forms, we examine the phenomenon across a variety of settings. We deploy mixed quantitative and qualitative methods to generate large scale evidence as well detailed case studies. We aim to focus on developing theory and implications to inform future policy on research and innovation.
‘Why is it important for society?’
‘What are the overall objectives?’
Serendipity, the notion of researchers making unexpected and beneficial discoveries, has played an important role in debates about the feasibility and desirability of targeting public investments in research and development. This is the idea that, since the outcomes of research are impossible to predict, research itself is difficult (perhaps even impossible) to manage or direct towards specific social ends.
Research may be uncertain, but it is not random, and we know that industrial R&D managers fund research in areas where they expect returns and organise research to maximise its impact. With public policy, the scenario is slightly different, but there is limited evidence to draw on to support policy making.
Thus, in the SIRI project, we examine the nature of serendipity and develop techniques for its identification and measurement in order to get a sense of the prevalence of the phenomenon. It may well be frequent but relatively insignificant, or rare but highly consequential. We therefore also seek to develop approaches to help evaluate the significance of serendipity, primarily through mapping techniques but also by identifying salient dimensions of analysis.
Since serendipity is likely to take different forms, we examine the phenomenon across a variety of settings. We deploy mixed quantitative and qualitative methods to generate large scale evidence as well detailed case studies. We aim to focus on developing theory and implications to inform future policy on research and innovation.
We have shown that serendipity can come in different forms and come about in a variety of ways. A conceptual review found four conceivable types of serendipity: targeted search solves unexpected problem, targeted search solves problem-in-hand via unexpected route, untargeted search solves an immediate problem, and untargeted search solves a later problem. It also identified four possible mechanisms of serendipity: Theory-led, Observer-led, Error-borne, and Network-emergent. The different types and mechanisms may have different implications for theory and policy.
As such, it is important to span a range of contexts and units of analysis. We have identified datasets and cases across a variety of settings, and developed frameworks to analyse them. For micro-scale settings, we focused on detailed qualitative and historical analysis to develop theoretically informed case studies. For more meso-scale settings, we focused on the interpretation of how data is often categorised, manual checks on the robustness of these classifications, and ways to frame the analysis. For macro-scale settings, we have developed algorithmic approaches to try and automate some of the analyses undertaken at the micro and meso levels.
Overall, this has so far allowed us to examine serendipity in US, UK and European research, across a range of diseases. We have also examined serendipity in the context of evidence-based policy, and drug development. Despite considerable variation across contexts, the measures we have developed indicate that serendipity is far from rare.
As such, it is important to span a range of contexts and units of analysis. We have identified datasets and cases across a variety of settings, and developed frameworks to analyse them. For micro-scale settings, we focused on detailed qualitative and historical analysis to develop theoretically informed case studies. For more meso-scale settings, we focused on the interpretation of how data is often categorised, manual checks on the robustness of these classifications, and ways to frame the analysis. For macro-scale settings, we have developed algorithmic approaches to try and automate some of the analyses undertaken at the micro and meso levels.
Overall, this has so far allowed us to examine serendipity in US, UK and European research, across a range of diseases. We have also examined serendipity in the context of evidence-based policy, and drug development. Despite considerable variation across contexts, the measures we have developed indicate that serendipity is far from rare.
Given its apparent prevalence, the work to evaluate the significance of serendipity has taken on greater importance. For this, conceptual and methodological development is challenging.
We are developing approaches to map instances of serendipity, and distinguish those that may be more significant than others. Some visualisations allow us to observe that serendipity seems to be mostly minor, and only occasionally major. However, we expect considerable variation across contexts.
In the next phase of the project, we are exploring factors that may define the scope for serendipity, and factors that may pull research towards serendipitous outcomes. Taken together, we expect to have an improved understanding of serendipity in research and new ways of studying it.
We are developing approaches to map instances of serendipity, and distinguish those that may be more significant than others. Some visualisations allow us to observe that serendipity seems to be mostly minor, and only occasionally major. However, we expect considerable variation across contexts.
In the next phase of the project, we are exploring factors that may define the scope for serendipity, and factors that may pull research towards serendipitous outcomes. Taken together, we expect to have an improved understanding of serendipity in research and new ways of studying it.