Making Science

Research scientists have become increasingly dependent on collaborations across laboratories and organizations to maintain their productivity. However, the increased specialization of individual laboratories works against the current drive toward understanding systems in the sciences. Consequently, there is a tension between the rising importance of collaborative efforts and the practical and structural challenges in establishing and managing such collaborations. Combining ethnographic case studies of three biology research labs with network data of their larger scientific community, we explore the changing process of scientific knowledge production in the age of Big Science. We find that virtual technologies open up the knowledge process as scientists have easier access to data, publications, and each other. At the same time, we find that these technologies—specifically scientific databases—do not eradicate the social aspects of scientific knowledge production as collaborative structures in science remain relatively unchanged. We discuss the implications for theory and practice of this seemingly contradictory character of scientific knowledge production.

[1]  Wai Fong Boh,et al.  Expertise and Collaboration in the Geographically Dispersed Organization , 2007, Organ. Sci..

[2]  Wanda J. Orlikowski,et al.  Knowing in practice: Enacting a collective capability in distributed organizing , 2002, STUDI ORGANIZZATIVI.

[3]  Michael Lynch,et al.  Art and artifact in laboratory science , 1985 .

[4]  Yuval Kalish.  Harnessing the power of social network analysis to explain organizational phenomena. , 2013 .

[5]  Judith S. Olson,et al.  Distance Matters , 2000, Hum. Comput. Interact..

[6]  Pamela J. Hinds,et al.  Out of Sight, Out of Sync: Understanding Conflict in Distributed Teams , 2003, Organ. Sci..

[7]  Geoffrey C. Bowker.  Biodiversity Datadiversity , 2000 .

[8]  Morten T. Hansen,et al.  The Search-Transfer Problem: The Role of Weak Ties in Sharing Knowledge across Organization Subunits , 1999 .

[9]  Beth A. Bechky,et al.  10 Coordination in Organizations: An Integrative Perspective , 2009 .

[10]  Robert J. Bloomfield,et al.  The Effect of Information Strength and Weight on Behavior in Financial Markets , 2001 .

[11]  S. Shapin.  HERE AND EVERYWHERE: Sociology of Scientific Knowledge , 1995 .

[12]  Christine Hine,et al.  Databases as Scientific Instruments and Their Role in the Ordering of Scientific Work , 2006 .

[13]  Sirkka L. Jarvenpaa,et al.  Communication and Trust in Global Virtual Teams , 1999, J. Comput. Mediat. Commun..

[14]  David Krackhardt,et al.  PREDICTING WITH NETWORKS: NONPARAMETRIC MULTIPLE REGRESSION ANALYSIS OF DYADIC DATA * , 1988 .

[15]  J. E. Hirsch,et al.  An index to quantify an individual's scientific research output , 2005, Proc. Natl. Acad. Sci. USA.

[16]  Nian Cai Liu,et al.  The Academic Ranking of World Universities. , 2005 .

[17]  Thomas Winman,et al.  Knowing In Practice , 2015 .

[18]  David Krackhardt,et al.  Sensitivity of MRQAP Tests to Collinearity and Autocorrelation Conditions , 2007, Psychometrika.

[19]  Benjamin F. Jones,et al.  Multi-University Research Teams: Shifting Impact, Geography, and Stratification in Science , 2008, Science.

[20]  Peter R. Monge,et al.  Communication Processes for Virtual Organizations , 2006 .

[21]  AC Grayling,et al.  Laboratory life Rebecca Lemov World as Laboratory: Exper , 2006, The Lancet.

[22]  Andrew Parker,et al.  Beyond answers: dimensions of the advice network , 2001, Soc. Networks.

[23]  Pamela J. Hinds,et al.  Distributed Work , 2002 .

[24]  A. Pickering.  Science as practice and culture , 1992 .

[25]  R. Merton.  The Matthew Effect in Science , 1968, Science.

[26]  Rohit Parikh,et al.  States of Knowledge , 2002, WoLLIC.

[27]  Mark S. Granovetter.  The Strength of Weak Ties , 1973, American Journal of Sociology.

[28]  Alan L. Mackay,et al.  Publish or perish , 1974, Nature.

[29]  I. Hacking.  The Social Construction of What , 1999 .

[30]  A. Strauss,et al.  The Discovery of Grounded Theory , 1967 .

[31]  David Lazer,et al.  Searching for Answers , 2011 .

[32]  S. Feld.  The Focused Organization of Social Ties , 1981, American Journal of Sociology.

[33]  Judith S. Olson,et al.  From Shared Databases to Communities of Practice: A Taxonomy of Collaboratories , 2007, J. Comput. Mediat. Commun..

[34]  E BaileyDiane,et al.  Out of Sight, Out of Sync , 2003 .

[35]  Timothy E. Loch.  Bridging Space over Time , 2007 .

[36]  Tom A. B. Snijders,et al.  Exponential Random Graph Models for Social Networks , 2013 .

[37]  R. Müller,et al.  Coordination in Organizations , 1997 .

[38]  M. Lynch,et al.  Scientific Practice and Ordinary Action , 1993 .

[39]  R. Corey,et al.  Shaping Biomedicine as an Information Science Timothy 1 enoir , 2022 .

[40]  Benjamin F. Jones,et al.  Supporting Online Material Materials and Methods Figs. S1 to S3 References the Increasing Dominance of Teams in Production of Knowledge , 2022 .

[41]  Yuval Kalish,et al.  Exponential Random Graph Models for Social Networks: Brain, Brawn, or Optimism? Structure and Correlates of Emergent Military Leadership , 2012 .

[42]  Jeffrey L. Furman,et al.  More for the research dollar , 2010, Nature.

[43]  M. McPherson,et al.  Birds of a Feather: Homophily in Social Networks , 2001 .

[44]  Curtis J. Bonk,et al.  Cross-Cultural Comparisons of Online Collaboration , 2006, J. Comput. Mediat. Commun..

[45]  Blake Ives,et al.  Virtual teams: a review of current literature and directions for future research , 2004, DATB.

[46]  M. Maznevski,et al.  Bridging Space Over Time: Global Virtual Team Dynamics and Effectiveness , 2000 .

[47]  Jonathon N. Cummings,et al.  Coordination costs and project outcomes in multi-university collaborations , 2007 .

[48]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[49]  David Krackardt,et al.  QAP partialling as a test of spuriousness , 1987 .