@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 = {

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.

}, 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 {9999, title = {Levels of trace data for social and behavioural science research}, booktitle = {Big Data Factories: Collaborative~Approaches}, year = {2017}, publisher = {Springer Nature}, organization = {Springer Nature}, abstract = {

The explosion of data available from online systems such as social media is creating a wealth of trace data, that is, data that record evidence of human activity. The volume of data available offers great potential to advance social and behavioural science research. However, the data are of a very different kind than more conventional social and behavioural science data, posing challenges to use. This paper adopts a data framework from Earth Observation science and applies it to trace data to identify possible issues in analyzing trace data. Application of the framework also reveals issues for sharing and reusing data.

}, isbn = {978-3-319-59186-5}, doi = {10.1007/978-3-319-59186-5_4}, attachments = {https://floss.syr.edu/sites/crowston.syr.edu/files/160529\%20levels\%20book\%20chapter_0.pdf}, author = {Kevin Crowston}, editor = {Sorin Matei and Sean Goggins and Nicolas Jullien} } @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} } @inbook {Crowston:2008b, title = {The bug fixing process in proprietary and free/libre open source software: A coordination theory analysis}, booktitle = {Business Process Transformation}, year = {2008}, pages = {69-99}, publisher = {M. E. Sharpe}, organization = {M. E. Sharpe}, address = {Armonk, NY}, abstract = {To support business process transformation, we must first be able to represent business processes in a way that allows us to compare and contrast them or to design new ones. In this paper, I use coordination theory to analyze the bug fixing processes in the proprietary operating system development group of a large mini-computer manufacturer and for the Free/Libre Open Source Software Linux operating system kernel. Three approaches to identifying dependencies and coordination mechanisms are presented. Mechanisms analyzed include those for task assignment, resource sharing and managing dependencies between modules of source code. The proprietary development organization assigned problem reports to engineers based on the module that appeared to be in error, since engineers only worked on particular modules. Alternative task assignment mechanisms include assignment to engineers based on workload or voluntary assignment, as in Linux. In the proprietary process, modules of source code were not shared, but rather {\textquotedblleft}owned{\textquotedblright} by one engineer, thus reducing the need for coordination. In Linux, where multiple developers can work on the same modules, alternative resource sharing mechanisms have been developed to manage source code. Finally, the proprietary developers managed dependencies between modules informally, relying on their personal knowledge of which other engineers used their code. The Linux process allows developers to change code in multiple modules, but emphasizes modularity to reduce the need to do so.}, keywords = {Coordination, FLOSS}, isbn = {9780765611918}, attachments = {https://floss.syr.edu/sites/crowston.syr.edu/files/The\%20bug\%20fixing\%20process\%20in\%20proprietary\%20.pdf}, author = {Kevin Crowston}, editor = {Grover, Varun and Markus, M. Lynne} }