Collaborative, cross-disciplinary learning and co-emergent innovation in eScience teams

Abstract

Collaborative eScience research teams are impeded by difficulties defining problems that provide research opportunities for all participants. Problem formulation occurs early in the collaboration process when the demand for ideas is high. However, crossdisciplinary linkages and integrated conceptual frameworks from which strong interdisciplinary ideas emerge do not evolve until later. The process of co-creating interdisciplinary research ideas is fundamentally a learning problem; participants from different disciplines must learn enough about each other's research interests to construct an integrated conceptual framework from which joint problems of interest can be created. However, participants rarely have the conceptual background needed to easily understand research topics in other disciplines; hence methods for enabling rapid learning in these situations are needed. Team interactions that more effectively generate interdisciplinary ideas can be enabled based on a better understanding the process of crossdisciplinary, collaborative learning. This article postulates several models of collaborative learning in these settings and discusses the implications for orchestrating team activities to achieve better outcomes.

Research Collaboration as “Layers of Engagement”: INKE in Year Four

“…Not all teams can move from grant development to an actual functioning collaboration (Pennington, 2011b). To achieve this mature state, INKE has drawn upon formal and informal faceto-face meetings, conference calls, online collaborative tools, and joint activities between the sub-research areas, including prototype development, articles, conference papers, and others.…”

“…e team is demonstrating a confidence in their interactions that is allowing them to experiment with alternative work patterns, including the use and support of GRAs and postdoctoral fellows. Ultimately, INKE is demonstrating participants' ability to learn from each other, be in consistent communication with each other, and be flexible and adaptable, which helps reinforce common ground and a shared vision while working out the specifics of tasks and roles (Pennington, 2011b).…”

“…At the same time, the emergent team must also negotiate tasks, budgets, and timelines (Bennett & Kidwell, 2001;Birnbaum, 1979;Bruhn, 2000;Fennel & Sandefur, 1983;Hara et al, 2003;Lawrence, 2006). is process ultimately takes time and energy and may (or may not) result in a grant application (Pennington, 2011b;Siemens, 2010a). Once a team is successful in securing the necessary resources, it must focus on building from the grant application to more specific articulations of ways that members will work together and achieve task completion (Siemens & INKE Research Group, 2012b, 2012c.…”

Fostering ecological data sharing: collaborations in the International Long Term Ecological Research Network

“…v www.esajournals.org technical (Pennington 2011). Recognizing that this communication problem is a barrier to developing information management systems in the ILTER Network, TERN and US LTER Network information managers undertook to learn more about this issue.…”

Toward cyberinfrastructure to facilitate collaboration and reproducibility for marine integrated ecosystem assessments

“…Indicators tend to be derived datasets and are often "synthesized 77 products" (term used in NOAA 2014), resulting from complex data processing workflows that 78 integrate not only data and models but also subjective choices made by scientists based on 79 knowledge in their domain. Social challenges include scientists of different domains using 80 different terms to describe their data and different software and tools to work with data (e.g., without conceptual integration between the scientists and IT experts" (Pennington 2011). …”