Virtual Scientific Teams: Life-Cycle Formation and Long-Term Scientific Collaboration (original) (raw)
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2012
Abstract Team-based scientific collaborations play a key role in the discovery and distribution of scientific knowledge. In order to determine the social and organizational factors that help support a scientific team's successful transition from short-term experiments to long-term programs of ongoing scientific research, this study used observations of teams conducting experiments at the National High Magnetic Field Laboratory to determine what teams actually do during these experiments.
Overcoming the Social and Technical Challenges to Virtual Scientific Collaboration
development, 2004
O Ov ve er rc co om mi in ng g t th he e S So oc ci ia al l a an nd d T Te ec ch hn ni ic ca al l C Ch ha al ll le en ng ge es s t to o V Vi ir rt tu ua al l S Sc ci ie en nt ti if fi ic c C Co ol ll la ab bo or ra at ti io on n The Birth of the NASA Astrobiology Institute as a Community of Practice Abstract -This paper summarizes a three-year project to create a community of practice [1] among 500+ scientists affiliated with the NASA Astrobiology Institute (NAI). Recognizing the needs to collaborate and still control travel costs, NAI engaged FutureU in 2000 to help facilitate the process of community development across distance.
Transactions on AUTOMATIC CONTROL and COMPUTER SCIENCE Vol.49 (63), 2004, ISSN 1224-600X. , 2004
This paper summarizes a three-year project to create a community of practice among 500+ scientists affiliated with the NASA Astrobiology Institute (NAI). Recognizing the needs to collaborate and still control travel costs, NAI engaged FutureU in 2000 to help facilitate the process of community development across distance. Although the process involved many technical and cultural challenges, by applying large-group intervention principles, especially that of involving the whole system, and by carefully introducing multiple collaboration support technologies, the authors were able to advance the development of a "virtual institute" that functions independent of time and distance as it collectively addresses the big questions about the origin of life (astrobiology).
2018
Making new data combinations and collaborating with researchers from different disciplines are becoming essential ingredients of scientific research. These activities are increasingly contributing to solutions for multidisciplinary global problems, such as climate change and energy transition. Virtual Research Environments (VREs) can potentially support making data combinations and researcher collaborations by providing a multiplicity of data and services. Many VREs have been developed already and are used in specific research domains. However, there is a lack of insight into what is needed to develop a multidisciplinary VRE in comparison with monodisciplinary VREs. This is currently blocking the development of innovative multidisciplinary VREs. This study aims to investigate the requirements for building a multidisciplinary VRE and to study the key differences between monodisciplinary VREs and multidisciplinary VREs. Our study shows that comprehensive requirements in nine categorie...
Discontinuities and Best Practices in Virtual Research Collaboration
2012
Research collaboration has become increasingly global, as collaboration technologies continue to advance and as research problems become more interdisciplinary and global. Virtual research teams have processes and challenges that are unique fi·om a typical virtual team, and we need a better understanding of how such teams can utilize virtual research enviro111l1ents to their advantage. We examine this question from a review of the relevant literatw·e and an analysis of experiences and reflections fi·om a doctoral seminar that studied and experienced the process of virtual research collaboration.
A Theory of Remote Scientific Collaboration
Scientific Collaboration on the Internet, 2008
In the past fifteen years, a great deal has been learned about the particular challenges of distant collaboration. Overall, we have learned that even when advanced technologies are available, distance still matters (Olson and Olson 2000). In addition, a recent seminal study of sixty-two projects sponsored by the National Science Foundation (NSF) showed that the major indicator of lower success was the number of institutions involved (Cummings and Kiesler 2005; chapter 5, this volume). The greater the number of institutions involved, the less well coordinated a project was and the fewer the positive outcomes. There are a number of reasons for these challenges. For one, distance threatens context and common ground (Cramton 2001). Second, trust is more difficult to establish and maintain when the collaborators are separated from each other (Shrum, Chompalov, and Genuth 2001; Kramer and Tyler 1995). Third, poorly designed incentive systems can inhibit collaborations and prevent the adoption of new collaboration technology (Orlikowski 1992; Grudin 1988). Finally, organizational structures and governance systems, along with the nature of the work, can either contribute to or inhibit collaboration (Larson et al. 2002; Mazur and Boyko 1981; Hesse et al. 1993; Sonnenwald 2007). This chapter describes our attempt to synthesize these findings and enumerate those factors that we (and others) believe are important in determining the success of remote collaboration in science. In working toward a theory of remote scientific collaboration (TORSC), we have drawn from data collected as part of the Science of Collaboratories (SOC) project, studies in the sociology of science, and investigations of distance collaboration in general. The Developing Theory Success We begin by discussing what we might mean by success in remote collaboration, since in the literature it can vary from revolutionary new thinking in the science to simply having some new software used. Different sets of factors may lead to different kinds of success. These outputs include effects on the science itself, science careers, learning and science education, funding and public perception, and inspiration to develop new collaboratories and new collaborative tools. The details are listed in short form in table 4.1. Effects on the Science Itself Early goals for collaboratories included that they would increase productivity and the number of participants, and democratize science through improved access to elite researchers (Finholt and Olson 1997; Hesse et al. 1993; Walsh and Bayma 1996). Similar assumptions were made with regard to interdisciplinary research (Steele and Stier 2000). These goals have to date not been tested. Today, scholars, policymakers, and scientists no longer take these assumptions for granted. Increasingly, they recognize that to define and evaluate the success of distributed and large-scale scientific collaborations is a complex task. Traditional measures of success in science are geared toward the individual, and include metrics such as productivity (e.g., counts of publications, presentations, patents, and graduate students mentored), awards and honors, and the impact of the work as determined by the prestige of the publication outlet or the number of times other researchers cite an individual scientist's papers (Merton 1988; Prpic 1996; Shrum, Chompalov, and Genuth 2001). Some of these measures can be used to evaluate the outcomes of large-scale, interdisciplinary, distributed collaborations, but most of them are inadequate to assess the full spectrum of goals of many current projects. Findings from the SOC project show that collaboratory participants and funding agency personnel frequently describe success in terms of the transformations to scientific practice along with the scale, scope, and complexity of the questions that can be answered. Both scientists and policymakers acknowledge that these outcomes take a long time to achieve and are difficult to assess using traditional measures. Social scientists have made some attempts to identify appropriate success measures and then evaluate collaborative science projects against these criteria. Methods based on the scientific outcomes of collaboration are the most common means to define and assess success. In the case of cross-disciplinary collaborations, the degree of intellectual integration, innovation (e.g., the generation of new ideas, tools, and infrastructure), and training are used as success measures (Cummings and Kiesler 2005; chapter 5, this volume; Jeffrey 2003; Stokols et al. 2003, 2005). Bradford Hesse and his colleagues (1993) used three scientific outcomes-publication, professional recognition, and social integration-to measure success among oceanographers who used computer networks to communicate with other researchers and access shared resources. We believe that both more scientists working on a common problem and the diversity among scientists working in a collaboratory can lead to bigger discoveries as well as breakthroughs, such as new ways of working, more revolutionary science, conceptual revolutions, and new models of science emerging. These are the highest-level goals.
The intellectual challenges and institutional conditions of 21 st century science and engineering necessitate collaboration. Increasingly, scholars are confronted with challenges of a scale and complexity that defy the boundaries of traditional academic fields as well as the limits of individual capacity. Scientific inquiry increasingly focuses on system-level phenomena, such as climate change, that demand the expertise of multi-disciplinary teams. Thus, there has been a growing shift away from traditions of individual, narrowly focused, discipline-based science toward more collaborative models requiring more diversified and systematized participation among teams of researchers sharing common resources.
A Typology of Virtual Research Environments
Proceedings of the 51st Hawaii International Conference on System Sciences, 2018
Virtual Research Environments (VREs) are online spaces that support communication and collaboration among scientists. Hundreds of VREs have been constructed using various configurations of research tools and information and communication technologies (ICTs) to serve many disciplines and interdisciplinary inquiry. This study characterizes a large sample of VREs in terms of the research and ICT resources they incorporate and derives a typology of VREs based on their particular ICT configurations. The four types are correlated with previous VRE typologies and disciplinary domains. Results indicate that there are correspondences, but that types of ICT configurations also exhibit complex relationships with function and discipline.
Virtual Partnerships in Research and Education
1997
(EMSL) at the Pacific Northwest National Laboratory (Washington) is a collaborative user facility with many unique scientific capabilities. The EMSL expects to support many of its remote users and collaborators by electronic means and is creating a collaborative environment for this purpose with capabilities ranging from chat and videoconferencing to shared applications, electronic notebooks, and remote-controlled instruments. This paper describes some of the particular capabilities required to support scientific collaborations, the status and direction of the EMSL tools, and several early uses of the EMSL software in both research and education collaborations. The first section presents a taxonomy of the types of research collaborations that currently exist (peer-to-peer, mentor-student, inter-disciplinary, producer-consumer) and evaluates the communications needs for each type. EMSL's real-time Collaborative Research Environment (CORE) is described in the next section, and the following capabilities/components are summarized: WebTour, file sharing, chat box, TeleViewer, Electronic Laboratory Notebook, on-line instruments, whiteboard, and audio/video conferencing. The third section describes the use of CORE in research and education settings. Together, these topics define a vision for natural, in-depth, virtual partnerships in research and education. A figure presents the CORE World Wide Web interface. (Author/AEF)