A Theory of Remote Scientific Collaboration

Abstract

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 producti...

Designing for e-science: Requirements gathering for collaboration in CiteSeer

“…Clark and Brennan (1991) have identified that lack of common ground (e.g., mutual knowledge) and trust can hinder collaboration. Olson et al (2008) have corroborated these findings in their investigations with collaboratory interactions among scientists, further emphasizing the role of history and shared vocabulary among collaborators as an essential facet of successful virtual collaboration. Olson et al (2008) note in their collaboratory studies that providing support for processes of management, planning, and decision-making is important.…”

“…Olson et al (2008) have corroborated these findings in their investigations with collaboratory interactions among scientists, further emphasizing the role of history and shared vocabulary among collaborators as an essential facet of successful virtual collaboration. Olson et al (2008) note in their collaboratory studies that providing support for processes of management, planning, and decision-making is important. When there are multiple institutions involved and/or different departments (disciplines) within the same university, it is important to know who is serving in what role.…”

“…Little is known in the way of design strategies to support distributed scientific collaboration because only a few collaboratories have been evaluated from this angle (e.g., Sonnenwald et al, 2003;Olson et al, 2008), resulting in just a handful of basic design issues and heuristics related to general collaborative experiences in collaboratories (e.g., Finholt, 2002;Olson et al, 2008). Below, we review major findings from prior work in order to ground our contribution.…”

“…More recently, Olson et al (2008) proposed a work-in-progress theory of remote collaboration based largely on their experience with collaboratory development. Other classical studies, such as by Ruhleder (1994, 1996), have also analyzed distributed work in collaboratories, but these two articles represent the state-of-the-art in designing collaboratories to support scientific collaboration.…”

Rebooting science? Implications of science 2.0 main trends for scientific method and research institutions

“…www.myexperiment.org). This distributed effort brings the niche, microexpertise as well as microcontributions and microcollaboration (Olson et al 2008) in the mainstream research resulting in increased efficiency and faster solutions to complex problems (ATLAS particle detector project 19 in CERN engaged 2800 scientific authors including 1850 with a PhD and 1200 technicians from 169 institutions from 37 countries, also thousands of industrial relations were built -Hoffman, 2009). Nevertheless, the growth of open collaboration is sketchy and its usage is relatively low.…”