The reality of cross-disciplinary energy research in the United Kingdom: A social science perspective

Connective knowledge: what we need to know about other fields to ‘envision’ cross-disciplinary collaboration

“…From researchers in one field being misunderstood by others so that they become an 'appendix' to projects [57], performing 'service roles' , e.g. social scientists being asked to 'stuff envelopes' to 'being the general person for anything to do with people' [15], to the overestimation of what one knows or can know about other fields [49,61,3], to the side-lining of conceptual and theoretical contributions different disciplines can make [49,3] the variety of problems that unfold in the 'doing' of cross-disciplinary work as a result of what is 'not known' seems to tantalisingly lead to the conclusion that knowing more about something relating to other fields might be the solution.…”

“…The presence of these challenges becomes far more apparent to scholars who attempt to translate the wish for researchers to 'know more' into a positive theory and practical agenda. Mallaband et al [49], for example, highlight that while 'comprehension of other subject areas' would be valuable to ensure that members of cross-disciplinary teams worth and value is appreciated, would facilitate stronger communication and support the development of shared understanding and innovative outcomes, the achievement of that level of integration is nevertheless quite a 'challenge' (p. 13). In turn, the often extensive periods of time it can take to achieve the kinds of collaborative skill and cross-disciplinary learning necessary for integrative work is also frequently highlighted as a key challenge [34,57,58].…”

“…That connective ' About-Knowledge' , rather than more sophisticated forms of extra-disciplinary 'Of-Knowledge' , might be more valuable for stimulating cross-disciplinary collaborative connections also finds support from other quarters. There is now a developing body of work that highlight fundamental misconceptions and stereotypical ideas about what researchers within non-home fields actually do [62] in ways that lead researchers to erroneously overlook and exclude particular domains for cross-disciplinary projects [2,49,3]. Addressing basic misconceptions about fields and specialisms-for example, that legal academics researchers are typically involved in 'litigating cases' [62], or wholly non-specified ideas about social science so that social scientists are seen as the 'people people' [49]-do not require much 'corrective' information beyond highlighting the richer range of research problem domains in which those disciplines are engaged, and the potential contributions that those fields can make to cross-disciplinary collaborations.…”

“…In contrast with the epistemic clashes described in the first context which relate to a deficit in knowledge of another field-the second context concerns an absence of knowledge about fields. For example, a group of engineers or computer scientists working on a problem domain that while having 'human users' , believe that their technical knowledge of engineering or computer science is enough because they 'speak human' and 'already "know" what people think/do' ( [49], p. 13). Or indeed, researchers come to believe that future studies 'is primarily about "prediction" and "forecasting" to the idea that future studies can be nothing more than "ungrounded speculation", because the future is inherently unknowable' ( [28], p. 24).…”

Achieving Data Synergy: The Socio-Technical Process of Handling Data

“…Notwithstanding their size, samples and research scope, many studies experience similar pitfalls in their data collection processes. Despite recognition of the need to combine multiple methods to understand the multidimensional socio-technical issues (Topouzi et al 2016) and ongoing recognition of the ontological and language challenges of multidisciplinary work (Mallaband et al 2017;Robison and Foulds 2017;Sovacool et al 2015), there is less focus on the challenge of data collection and the implementation of these methodologies. This chapter reflects on the socio-technical nature of data collection and sharing in multi-partner multidisciplinary 1 projects: not just the fact that different types of data need to be collected and analysed but the expectations different disciplines have of data 2 and the different skills they bring to the analysis.…”