@article {9998,
	title = {Assessment, Usability, and Sociocultural Impacts of DataONE: A Global Research Data Cyberinfrastructure Initiative},
	journal = {International Journal of Digital Curation},
	volume = {16},
	year = {2021},
	month = {04/2021},
	abstract = {<p>DataONE, funded from 2009-2019 by the U.S. National Science Foundation, is an early example of a large-scale project that built both a cyberinfrastructure and culture of data discovery, sharing, and reuse. DataONE used a Working Group model, where a diverse group of participants collaborated on targeted research and development activities to achieve broader project goals. This article summarizes the work carried out by two of DataONE{\textquoteright}s working groups: Usability \&amp; Assessment (2009-2019) and Sociocultural Issues (2009-2014). The activities of these working groups provide a unique longitudinal look at how scientists, librarians, and other key stakeholders engaged in convergence research to identify and analyze practices around research data management through the development of boundary objects, an iterative assessment program, and reflection. Members of the working groups disseminated their findings widely in papers, presentations, and datasets, reaching international audiences through publications in 25 different journals and presentations to over 5,000 people at interdisciplinary venues. The working groups helped inform the DataONE cyberinfrastructure and influenced the evolving data management landscape. By studying working groups over time, the paper also presents lessons learned about the working group model for global large-scale projects that bring together participants from multiple disciplines and communities in convergence research.</p>},
	doi = {10.2218/ijdc.v16i1.678 },
	author = {Robert J. Sandusky and Suzie Allard and Lynn Baird and Leah Cannon and Kevin Crowston and Amy Forrester and Bruce Grant and Rachael Hu and Robert Olendorf and Danielle Pollock and Alison Specht and Carol Tenopir and Rachel Volentine}
}
@article {9998,
	title = {Examining Open Innovation in Science (OIS): What Open Innovation can and cannot offer the science of science},
	journal = {Innovation: Organization \& Management},
	year = {2021},
	abstract = {<p>Scholars across disciplines increasingly hear calls for more open and collaborative approaches to scientific research. The concept of Open Innovation in Science (OIS) provides a framework that integrates dispersed research efforts aiming to understand the antecedents, contingencies, and consequences of applying open and collaborative research practices. While the OIS framework has already been taken up by science of science scholars, its conceptual underpinnings require further specification. In this essay, we critically examine the OIS concept and bring to light two key aspects: 1) how OIS builds upon Open Innovation (OI) research by adopting its attention to boundary-crossing knowledge flows and by adapting other concepts developed and researched in OI to the science context as exemplified by two OIS cases in the area of research funding; 2) how OIS conceptualises knowledge flows across boundaries. While OI typically focuses on well-defined organizational boundaries, we argue that blurry and even invisible boundaries between communities of practice may more strongly constrain flows of knowledge related to openness and collaboration in science. Given the uptake of this concept, this essay brings needed clarity to the meaning of OIS, which has no particular normative orientation toward a close coupling between science and industry. We end by outlining the essay{\textquoteright}s contributions to OI and the science of science, as well as to science practitioners.</p>},
	doi = {10.1080/14479338.2021.1999248},
	author = {Susanne Beck and Marcel LaFlamme and Carsten Bergenholtz and Marcel Bogers and Tiare-Maria Brasseur and Marie-Louise Conradsen and Kevin Crowston and Diletta Di Marco and Agnes Effert and Despoina Filiou and Lars Frederiksen and Thomas Gillier and Marc Gruber and Carolin Haeussler and Karin Hoisl and Olga Kokshagina and Maria-Theresa Norn and Marion Poetz and Gernot Pruschak and Laia Pujol Priego and Agnieszka Radziwon and Alexander Ruser and Henry Sauermann and Sonali Shah and Julia Suess-Reyes and Christopher L. Tucci and Philipp Tuertscher and Jane Bj{\o}rn Vedel and Roberto Verganti and Jonathan Wareham and Sunny Mosangzi Xu}
}
@inbook {2019,
	title = {Comprehensive collaboration plans: Practical considerations spanning across individual collaborators to institutional supports},
	booktitle = {Strategies for Team Science Success},
	year = {2019},
	pages = {587-611},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {This chapter provides a framework for integrating and applying the principles and strategies for effective team science that are described in this volume. The framework, called Collaboration Planning, aims to guide a deliberative approach to assess and plan for ten key influences on both scientific and collaborative success. These influences range from the initial scientific rationale for a team science approach to the collaboration readiness of participating individuals and institutions to team communication and coordination mechanisms to quality improvement for team functioning. The Collaboration Planning framework guides current or future collaborators through dialogue and planning around each influence. It draws their attention to key issues for consideration related to each influence, and facilitates discussion of how to leverage facilitating factors and plan for, or mitigate, challenges. Decisions are captured in a resulting written document called the Collaboration Plan. The Collaboration Plan summarizes the various ways the team plans to build the foundation for, and support, effective collaboration across the lifespan of the team science initiative. Collaboration Plans can be used in multiple ways. The Plans{\textquoteright} core function is as a roadmap to facilitate effective team formation and functioning. The Plan also can be used for benchmarking or guiding quality improvement-oriented evaluation. Collaboration Plans also can be used to communicate a team{\textquoteright}s likelihood of collaborative success, goals, and needs to a wide variety of audiences, including funders, current and future team members, stakeholders in the team{\textquoteright}s success, and organizational leaders. In addition, they can be used as models to guide future teams in laying the foundation for success.},
	isbn = {978-3-030-20990-2},
	doi = {10.1007/978-3-030-20992-6_45},
	author = {Hall, Kara L. and Vogel, Amanda L. and Crowston, Kevin},
	editor = {Hall, Kara L. and Vogel, Amanda L. and Croyle, Robert T.}
}
@article {2016,
	title = {Manifesto on Engineering Academic Software (Dagstuhl Perspectives Workshop 16252)},
	volume = {6},
	year = {2016},
	month = {12/2106},
	institution = {Schloss Dagstuhl {\textendash} Leibniz Center for Informatics},
	address = {Wadern, Germany},
	abstract = {Software is often a critical component of scientific research.  It can be a component of the academic research methods used to produce research results, or it may itself be an academic research result. Software, however, has rarely been considered to be a citable artifact in its own right. With the advent of open-source software, artifact evaluation committees of conferences, and journals that include source code and running systems as part of the published artifacts, we foresee that software will increasingly be recognized as part of the academic process. The quality and sustainability of this software must be accounted for, both a priori and a posteriori. 

The Dagstuhl Perspectives Workshop on {\textquotedblleft}Engineering Academic Software{\textquotedblright} has examined the strengths, weaknesses, risks, and opportunities of academic software engineering. A key outcome of the workshop is this Dagstuhl Manifesto, serving as a roadmap towards future professional software engineering for software-based research instruments and other software produced and used in an academic context.  The manifesto is expressed in terms of a series of actionable {\textquotedblleft}pledges{\textquotedblright} that users and developers of academic research software can take as concrete steps towards improving the environment in which that software is produced.},
	author = {Alice Allen and Cecilia Aragon and Christoph Becker and Jeffrey Carver and Andrei Chi{\c s} and Benoit Combemale and Mike Croucher and Kevin Crowston and Daniel Garijo and Ashish Gehani and Carole Goble and Robert Haines and Robert Hirschfeld and James Howison and Kathryn Huff and Caroline Jay and Daniel S. Katz and Claude Kirchner and Katie Kuksenok and Ralf L{\"a}mmel and Oscar Nierstrasz and Matt Turk and van Nieuwpoort, Rob and Matthew Vaughn and Jurgen Vinju}
}
@article {2014,
	title = {How to Write a Collaboration Plan},
	year = {2014},
	institution = {National Cancer Institute},
	address = {Bethesda, MD},
	abstract = {Collaboration plans are written documents that investigators may use as a {\textquotedblleft}roadmap{\textquotedblright} for future collaborations. Funding agencies may ask investigators to submit Collaboration Plans as part of their funding applications, analogous to submitting research plans. Submitted collaboration plans can then be used by reviewers to help assess the capacity of a proposed team to collaboratively execute its scientific objectives. Collaboration plans address a range of issues relevant to laying the foundation for the collaboration, implementing and managing the collaboration, and engaging in quality improvement activities specific to collaborative interactions. These plans identify existing supports and challenges relevant to the collaboration, and describe a program of action that will be implemented to help support smooth collaboration. This working document, called {\textquotedblleft}How to Write a Collaboration Plan{\textquotedblright} is a product of a federal subcommittee on Collaboration and Team Science. The document provides guidance for writing a collaboration plan. It identifies ten key aspects of collaboration planning, and highlights specific issues for investigators to consider related to each of the ten aspects of planning. Collaboration planning may benefit any scientific endeavor that includes two or more investigators working together. Though as a proposed scientific collaboration grows in scope and size, such plans become increasingly important. More information on the origins of this document: The White House Office of National Science and Technology Policy{\textquoteright}s (OSTP) NITRD Program (Networking and Information Technology Research and Development Program) provides a forum where many federal agencies come together to coordinate their networking and information technology (IT) research and development (R\&D) efforts. (More information at: https://www.nitrd.gov.) Team Science is of particular interest, given the prevalence of virtual collaboration in IT R\&D. In response, the NITRD Coordination Group on Social, Economic, and Workforce Implications of IT and IT Workforce Development (NITRD-SEW), developed a subcommittee on Collaboration and Team Science. The subcommittee includes members from the National Institutes of Health (NIH), National Science Foundation (NSF), Department of Justice (DOJ), NASA, and other federal agencies. In 2014, the subcommittee hosted a series of topical meetings on enhancing support for collaboration in science, which resulted in this document, {\textquotedblleft}How to Write a Collaboration Plan{\textquotedblright}, authored by subcommittee co-chairs Dr. Kara Hall (NIH) and Dr. Kevin Crowston (NSF), along with subcommittee member Dr. Amanda Vogel (Leidos Biomed).},
	url = {https://www.teamsciencetoolkit.cancer.gov/Public/TSResourceBiblio.aspx?tid=3\&rid=3119},
	attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/How\%20to\%20write\%20a\%20collaboration\%20plan\%20_Working\%20Draft\%202014_1122.pdf},
	author = {Kara L. Hall and Kevin Crowston and Amanda L. Vogel}
}
