Science is increasingly defined by multidimensional collaborative networks. Despite the unprecedented growth of scientific collaboration around the globe – the collaborative turn – geography still matters for the cognitive enterprise. This book explores how geography conditions scientific collaboration and how collaboration affects the spatiality of science. This book offers a complex analysis of the spatial aspects of scientific collaboration, addressing the topic at a number of levels: individual, organizational, urban, regional, national, and international. Spatial patterns of scientific collaboration are analysed along with their determinants and consequences. By combining a vast array of approaches, concepts, and methodologies, the volume offers a comprehensive theoretical framework for the geography of scientific collaboration. The examples of scientific collaboration policy discussed in the book are taken from the European Union, the United States, and China. Through a number of case studies the authors analyse the background, development and evaluation of these policies. This book will be of interest to researchers in diverse disciplines such as regional studies, scientometrics, R&D policy, socio-economic geography and network analysis. It will also be of interest to policymakers, and to managers of research organisations.

In recent years a global network of science has emerged as a result of thousands of individual scientists seeking to collaborate with colleagues around the world, creating a network which rises above national systems. The globalization of science is part of the underlying shift in knowledge creation generally: the collaborative era in science. Over the past decade, the growth in the amount of knowledge and the speed at which it is available has created a fundamental shift—where data, information, and knowledge were once scarce resources, they are now abundantly available. Collaboration, openness, customer- or problem-focused research and development, altruism, and reciprocity are notable features of abundance, and they create challenges that economists have not yet studied. This book defines the collaborative era, describes how it came to be, reveals its internal dynamics, and demonstrates how real-world practitioners are changing to take advantage of it. Most importantly, the book lays out a guide for policymakers and entrepreneurs as they shift perspectives to take advantage of the collaborative era in order to create social and economic welfare.

How technology and bureaucracy shape collaborative scientific research projects: an empirical study of multiorganizational collaboration in the physical sciences. Collaboration among organizations is rapidly becoming common in scientific research as globalization and new communication technologies make it possible for researchers from different locations and institutions to work together on common projects. These scientific and technological collaborations are part of a general trend toward more fluid, flexible, and temporary organizational arrangements, but they have received very limited scholarly attention. Structures of Scientific Collaboration is the first study to examine multi-organizational collaboration systematically, drawing on a database of 53 collaborations documented for the Center for History of Physics of the American Institute of Physics. By integrating quantitative sociological analyses with detailed case histories, Shrum, Genuth, and Chompalov pioneer a new and truly interdisciplinary method for the study of science and technology. Scientists undertake multi-organizational collaborations because individual institutions often lack sufficient resources--including the latest technology--to achieve a given research objective. The authors find that collaborative research depends on both technology and bureaucracy; scientists claim to abhor bureaucracy, but most collaborations use it constructively to achieve their goals. The book analyzes the structural elements of collaboration (among them formation, size and duration, organization, technological practices, and participant experiences) and the relationships among them. The authors find that trust, though viewed as positive, is not necessarily associated with successful projects; indeed, the formal structures of bureaucracy reduce the need for high levels of trust--and make possible the independence so valued by participating scientists.

Today in most scientific and technical fields more than 90% of research studies and publications are collaborative, often resulting in high-impact research and development of commercial applications, as reflected in patents. Nowadays in many areas of science, collaboration is not a preference but, literally, a work prerequisite. The purpose of this book is to review and critique the burgeoning scholarship on research collaboration. The authors seek to identify gaps in theory and research and identify the ways in which existing research can be used to improve public policy for collaboration and to improve project-level management of collaborations using Scientific and Technical Human Capital (STHC) theory as a framework. Broadly speaking, STHC is the sum of scientific and technical and social knowledge, skills and resources embodied in a particular individual. It is both human capital endowments, such as formal education and training and social relations and network ties that bind scientists and the users of science together. STHC includes the human capital which is the unique set of resources the individual brings to his or her own work and to collaborative efforts. Generally, human capital models have developed separately from social capital models, but in the practice of science and the career growth of scientists, the two are not easily disentangled. Using a multi-factor model, the book explores various factors affecting collaboration outcomes, with particular attention on institutional factors such as industry-university relations and the rise of large-scale university research centers.

An examination of the uses of data within a changing knowledge infrastructure, offering analysis and case studies from the sciences, social sciences, and humanities. “Big Data” is on the covers of Science, Nature, the Economist, and Wired magazines, on the front pages of the Wall Street Journal and the New York Times. But despite the media hyperbole, as Christine Borgman points out in this examination of data and scholarly research, having the right data is usually better than having more data; little data can be just as valuable as big data. In many cases, there are no data—because relevant data don't exist, cannot be found, or are not available. Moreover, data sharing is difficult, incentives to do so are minimal, and data practices vary widely across disciplines. Borgman, an often-cited authority on scholarly communication, argues that data have no value or meaning in isolation; they exist within a knowledge infrastructure—an ecology of people, practices, technologies, institutions, material objects, and relationships. After laying out the premises of her investigation—six “provocations” meant to inspire discussion about the uses of data in scholarship—Borgman offers case studies of data practices in the sciences, the social sciences, and the humanities, and then considers the implications of her findings for scholarly practice and research policy. To manage and exploit data over the long term, Borgman argues, requires massive investment in knowledge infrastructures; at stake is the future of scholarship.

This book delves into two divergent, yet parallel themes; first is an examination of how educators can design the experiences of learning, with a focus on the learner and the end results of education; and second, how educators learn to design educational products, processes and experiences. The book seeks to understand how to design how learning occurs, both in the instructional design studio and as learning occurs throughout the world. This will change the area's semantics; at a deeper level, it will change its orientation from instructors and information to learners; and it will change how educators take advantage of new and old technologies. This book is the result of a research symposium sponsored by the Association for Educational Communications and Technology [AECT].

Computing and communications are becoming essential tools of science. Together, they make possible new kinds and degrees of collaboration. This book addresses technical, scientific, and social aspects of fostering scientific collaboration using information technology. It explores issues in molecular biology, oceanography, and space physics, and derives recommendations for a partnership between scientists and technologists to develop better collaboration technology to support science.

Why collaborations in STEM fields succeed or fail and how to ensure success Once upon a time, it was the lone scientist who achieved brilliant breakthroughs. No longer. Today, science is done in teams of as many as hundreds of researchers who may be scattered across continents. These collaborations can be powerful, but they also demand new ways of thinking. The Strength in Numbers illuminates the nascent science of team science by synthesizing the results of the most far-reaching study to date on collaboration among university scientists. Drawing on a national survey with responses from researchers at more than one hundred universities, archival data, and extensive interviews with scientists and engineers in over a dozen STEM disciplines, Barry Bozeman and Jan Youtie establish a framework for characterizing different collaborations and their outcomes, and lay out what they have found to be the gold-standard approach: consultative collaboration management. The Strength in Numbers is an indispensable guide for scientists interested in maximizing collaborative success.