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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.

Frontiers | Link Definition Ameliorating Community Detection in Collaboration Networks | Big Data

This important book takes seriously the importance of analyzing interorganizational scientific collaborations—an area that is of growing importance in the practice, guidance, and study of the sciences. This is an interesting and important book. The authors analyze a precious database on inter-institutional scientific collaborations and draw a number of conclusions about how such collaborations start, how they proceed, how they succeed or fail, and how they end.

This is a substantial piece of work that will be crucial for those who study science and collaborations. Zara Mirmalek. Lukas Engelmann and Christos Lynteris. Search Search. As detailed in the solicitation, international components of collaborative projects may be funded in parallel by the participating agencies.

Collaboration - the Key to Scientific Success (Episode 5)

Appropriate scientific areas of investigations may be related to the interests of any of the participating funding organizations. Questions concerning a particular project's focus, direction, and relevance to a participating funding organization should be addressed to the appropriate person in the list of agency contacts found in Section VIII of the solicitation.

NSF will coordinate and manage the review of proposals jointly with participating domestic and foreign funding organizations, through a joint panel review process used by all participating funders. Additional information is available in Section VI of the solicitation. Please note that the following information is current at the time of publishing. See program website for any updates to the points of contact.

Original Research ARTICLE

In response to this solicitation, an investigator may participate as PI or Co-PI in no more than two proposals per review cycle. In the event that a PI or Co-PI does appear in either of these roles on more than two proposals, all proposals that include that person as a PI or Co-PI will be returned without review.

Foreign organizations that do not have a current U. Foreign grantees that have a U. Other budgetary limitations apply.

The Strength of the Strongest Ties in Collaborative Problem Solving

Please see the full text of this solicitation for further information. National Science Board approved criteria. Additional merit review considerations apply. Additional award conditions apply. One of the most exciting and difficult challenges for contemporary science and engineering is to understand complex neurobiological systems, from genetic determinants to cellular processes to the complex interplay of neurons, circuits, and systems orchestrating behavior and cognition.

Disorders of the nervous system are also associated with complex neurobiological changes, which may lead to profound alterations at all levels of organization. The computational principles and strategies of the nervous system have implications for biological and engineered systems alike, opening new avenues for discovery, application, and invention.

Computational neuroscience provides a theoretical foundation and a rich set of technical approaches for understanding the principles and dynamics of the nervous system. Building on the theory, methods, and findings of computer science, neuroscience, biology, the mathematical and physical sciences, the social and behavioral sciences, engineering, and other fields, computational neuroscience employs a broad spectrum of approaches to study structure, function, organization, and computation across all levels of the nervous system.

Advances in computational neuroscience are being accelerated by new methods for integrating and analyzing complex data; conceptual frameworks deriving from many different theoretical sources; and new modalities for data collection, simulation, modeling, and experimental manipulation. Furthering these advances, collaboration plays a pivotal role.

Collaborative research enables close interaction between theory, modeling, simulation and analysis, and experimental neuroscience. This provides a framework for interpretation of empirical data, quantitative hypotheses for empirical testing, and grounding of theories and models in an empirical and evaluation context. International collaborations bring together diverse research perspectives, expand the range of research partnerships, and develop a community of globally engaged scientists and engineers. Sharing of data, software, and other resources provides a powerful modality for larger-scale interaction and collaborative discovery.

Research and research communities supported by the participating funding organizations encompass complementary approaches and investigator communities whose integrative efforts are needed for the advancement of computational neuroscience; thus, cooperation among agencies in this area is appropriate and essential.

The participating funding organizations have released parallel documents with further agency-specific information, referenced in Section VIII of this solicitation. Two classes of proposals will be considered in response to this solicitation: Research Proposals describing collaborative research projects, and Data Sharing Proposals to enable sharing of data and other resources. Domestic and international projects will be considered, as detailed in Sections V.

In general, appropriate scientific areas of investigations may be related to the missions and strategic objectives of any of the participating funding organizations. Some specific examples are given at the end of this section. Questions concerning a particular project's focus, direction, and relevance to a participating funding organization should be addressed to the appropriate person in the list of agency contacts. Each of the funding organizations participating in this program has a commitment to developing and supporting computational neuroscience research for the purpose of advancing the understanding of the neuroscience questions relevant to the missions of the organizations.

Proposals selected for funding must be responsive to the mission of a participating funding organization. Assurance of Innovative Collaborative Research Effort Across Scientific Disciplines: The driving principle behind this program is the recognition that projects crossing traditional academic disciplinary boundaries often bring about increased productivity, creativity, and capacity to tackle major challenges. Collaborative efforts that bring together investigators with complementary experience and training, and deep understanding of multiple scholarly fields, are a requirement for this program and must be convincingly demonstrated in the proposal.

A typical research collaboration might involve a computer scientist and a neurobiologist, for example, though note that this solicitation does not prescribe any particular mix of disciplinary backgrounds or scientific approaches. Proposals for research projects should describe collaborations that bring together the complementary expertise needed to achieve significant advances on challenging interdisciplinary problems. Proposals for data sharing should describe resources that respond to the needs of a broad community of investigators to enable wide-ranging research advances.

This program emphasizes innovative research and resources, encouraging the application and development of state-of-the-art computational methods by theorists, computational scientists, engineers, mathematicians, and statisticians to tackle dynamic and complex neuroscience problems. Computational research supported under this program must relate to biological processes and should lead to hypotheses that are testable in biological studies. Sharing of Data, Software, and Other Resources: Sharing of data and software is highly recommended in all CRCNS projects, to facilitate the translation and dissemination of research results, to accelerate the development of generalizable approaches and tools that can be put to wide use by researchers, and to broaden the scope of collaboration in computational neuroscience and related communities.

Data Sharing Proposals may relate to any of the scientific topics that would be appropriate for Research Proposals under this solicitation.

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Data sharing projects should be specifically aimed at the preparation and deployment of data, software, code bases, stimuli, models, or other resources in a manner that is responsive to the needs of a broad community of researchers, for example, by providing a coherent collection of data and other resources covering a set of topics, systems, or methods of interest.

The major innovation and intellectual merit of a data sharing proposal could be in the breadth, depth, or importance of the resources being shared. Technical innovation e. CRCNS support for data sharing focuses primarily on data and other resources, not more general infrastructure, or research to acquire the data. Proposers of data sharing projects are strongly encouraged to build on existing facilities and services where possible, rather than develop infrastructure from scratch.

All CRCNS investigators are encouraged to coordinate with other data sharing projects and related activities, including national and international efforts to develop sustainable, extensible neuroscience resources. Innovative educational and training opportunities are highly encouraged, to develop research capacity in computational neuroscience, broaden participation in research and education, and increase the impact of computational neuroscience research.

Activities at all levels of educational and career development are welcome under this solicitation. International research experiences for students and early-career researchers are highly encouraged in all projects involving international collaborations.

A broad range of topics and approaches is welcome under this solicitation. The list of examples below illustrates some areas of research that are appropriate under this solicitation. The following list is not intended to be exhaustive or exclusive:. Many awards will be on the smaller end of this range.

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Proposers are strongly discouraged from requesting larger budgets than are necessary for the activities being proposed. Investigators contemplating four- or five-year projects are advised to discuss their project requirements with the appropriate agency contact s before submitting. The expected range of award sizes applies to the combined direct costs, expressed in US Dollars, of all components of a collaborative project for which funding is being sought from participating funders, including components inside and outside of the United States.

The expected range of award sizes does not include the costs of foreign travel to international partnering institutions. International travel costs can be expected to vary depending on the countries and specific proposed activities, and could result in combined direct costs that exceed the expected range.

Awards for Data Sharing Projects will be scaled according to the needs of the project; typically they will be smaller in size than research awards. Estimated program budget, number of awards, and average award size and duration are subject to the availability of funds.

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Upon conclusion of the review process, meritorious research proposals may be recommended for funding by one or more of the participating funding organizations, at the option of the funders, not the proposer. Subsequent grant administration procedures will be in accordance with the individual policies of the awarding agency.

Further information about agency processes and agency-specific award information is provided in Section VI. In determining which method to utilize in the electronic preparation and submission of the proposal, please note the following:. Collaborative Proposals. All collaborative proposals submitted as separate submissions from multiple organizations must be submitted via the NSF FastLane system. Please note that the proposal preparation instructions provided in this program solicitation may deviate from the PAPPG instructions.