@article {zevin2023gravity, title = {Gravity Spy: Lessons Learned and a Path Forward}, journal = {European Physical Journal Plus}, volume = {139}, year = {2024}, month = {01/2024}, pages = {Article 100}, abstract = {

The Gravity Spy project aims to uncover the origins of glitches, transient bursts of noise that hamper analysis of gravitational-wave data. By using both the work of citizen-science volunteers and machine-learning algorithms, the Gravity Spy project enables reliable classification of glitches. Citizen science and machine learning are intrinsically coupled within the Gravity Spy framework, with machine-learning classifications providing a rapid first-pass classification of the dataset and enabling tiered volunteer training, and volunteer-based classifications verifying the machine classifications, bolstering the machine-learning training set and identifying new morphological classes of glitches. These classifications are now routinely used in studies characterizing the performance of the LIGO gravitational-wave detectors. Providing the volunteers with a training framework that teaches them to classify a wide range of glitches, as well as additional tools to aid their investigations of interesting glitches, empowers them to make discoveries of new classes of glitches. This demonstrates that, when giving suitable support, volunteers can go beyond simple classification tasks to identify new features in data at a level comparable to domain experts. The Gravity Spy project is now providing volunteers with more complicated data that includes auxiliary monitors of the detector to identify the root cause of glitches.

}, doi = {10.1140/epjp/s13360-023-04795-4}, author = {Michael Zevin and Corey B. Jackson and Zoheyr Doctor and Yunan Wu and Carsten {\O}sterlund and L. Clifton Johnson and Christopher P. L. Berry and Kevin Crowston and Scott B. Coughlin and Vicky Kalogera and Sharan Banagiri and Derek Davis and Jane Glanzer and Renzhi Hao and Aggelos K. Katsaggelos and Oli Patane and Jennifer Sanchez and Joshua Smith and Siddharth Soni and Laura Trouille and Marissa Walker and Irina Aerith and Wilfried Domainko and Victor-Georges Baranowski and Gerhard Niklasch and Barbara T{\'e}gl{\'a}s} } @article {9998, title = {Data quality up to the third observing run of Advanced LIGO: Gravity Spy glitch classifications}, journal = {Classical and Quantum Gravity}, volume = {40}, year = {2023}, keywords = {FOS: Physical sciences, General Relativity and Quantum Cosmology (gr-qc), Instrumentation and Methods for Astrophysics (astro-ph.IM)}, doi = {10.1088/1361-6382/acb633}, author = {Glanzer, J and Banagiri, S and Coughlin, S B and Soni, S and Zevin, M and Berry, C P L and Patane, O and Bahaadini, S and Rohani, N and Crowston, K and {\O}sterlund, C} } @article {2023, title = {Perceived benefits of open data are improving but scientists still lack resources, skills, and rewards}, journal = {Humanities and Social Sciences Communications}, volume = {10}, year = {2023}, month = {Jan-12-2023}, doi = {10.1057/s41599-023-01831-7}, author = {Borycz, Joshua and Olendorf, Robert and Specht, Alison and Grant, Bruce and Crowston, Kevin and Tenopir, Carol and Allard, Suzie and Rice, Natalie M. and Hu, Rachael and Sandusky, Robert J.} } @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 = {

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 \& 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.

}, 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 = {

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} } @article {9999, title = {Attitudes and norms affecting scientists{\textquoteright} data reuse}, journal = {PLoS ONE}, volume = {12}, year = {2017}, chapter = {e0189288}, abstract = {The value of sharing data comes partly from the data{\textquoteright}s being reused by other scientists, but questions regarding attitudes and norms that predict scientists{\textquoteright} data reuse remain open. We test the relationship between scientists{\textquoteright} beliefs and attitudes towards data reuse and their self-reported data reuse behaviour using responses to selected questions from a worldwide survey developed and administered by the DataONE Usability and Assessment Working Group. The data suggest first that data sharing and data reuse are largely separate phenomena. Second, the perceived efficacy of data reuse for answering research questions was found to be one of the strongest predictors of reuse behaviour. On the other hand, expressed lack of trust in reused data and perceived norms against data reuse did not seem to deter respondents from reuse. Finally, reported use of models and remote-sensed data was associated with more reuse. The results suggest that data reuse would be encouraged by demonstrations of the value and addressing norms about this practice. }, doi = {10.1371/journal.pone.0189288}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/PONE\%20to\%20share.pdf}, author = {Renata G. Curty and Kevin Crowston and Alison Specht and Bruce Grant and Elizabeth D. Walton} } @inbook {2017, title = {Lessons Learned from a Decade of FLOSS Data Collection}, booktitle = {Big Data Factories}, year = {2017}, pages = {79 - 100}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-59185-8}, issn = {2509-9574}, doi = {10.1007/978-3-319-59186-5}, url = {http://link.springer.com/content/pdf/10.1007/978-3-319-59186-5}, author = {Crowston, Kevin and Squire, Megan}, editor = {Matei, Sorin Adam and Jullien, Nicolas and Goggins, Sean P.} } @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://crowston.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} } @article {2012, title = {The future of citizen science: emerging technologies and shifting paradigms}, journal = {Frontiers in Ecology and the Environment}, volume = {10}, year = {2012}, month = {08/2012}, pages = {298{\textendash}304}, abstract = {

Citizen science creates a nexus between science and education that, when coupled with emerging technologies, expands the frontiers of ecological research and public engagement. Using representative technologies and other examples, we examine the future of citizen science in terms of its research processes, program and participant cultures, and scientific communities. Future citizen-science projects will likely be influenced by sociocultural issues related to new technologies and will continue to face practical programmatic challenges. We foresee networked, open science and the use of online computer/video gaming as important tools to engage non-traditional audiences, and offer recommendations to help prepare project managers for impending challenges. A more formalized citizen-science enterprise, complete with networked organizations, associations, journals, and cyberinfrastructure, will advance scientific research, including ecology, and further public education.

}, issn = {1540-9295}, doi = {10.1890/110294}, url = {http://www.esajournals.org/doi/pdf/10.1890/110294}, author = {Newman, Greg and Wiggins, Andrea and Crall, Alycia and Graham, Eric and Newman, Sarah and Kevin Crowston} } @conference {2009, title = {Designing Virtual Organizations for Citizen Science}, booktitle = {IFIP Working Group 8.2 OASIS workshop 2009}, year = {2009}, month = {12/2009}, address = {Phoenix, AZ}, url = {http://sprouts.aisnet.org/9-56/}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/WigginsOASIS2009.pdf , https://crowston.syr.edu./sites/crowston.syr.edu/files/awigginsOASIS2009.ppt}, author = {Wiggins, Andrea and Kevin Crowston}, editor = {Uri Gal} } @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://crowston.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} } @inbook {Crowston:2006c, title = {Coordination theory: A ten-year retrospective}, booktitle = {Human-Computer Interaction in Management Information Systems}, year = {2006}, pages = {120-138}, publisher = {M. E. Sharpe, Inc.}, organization = {M. E. Sharpe, Inc.}, abstract = {Since the initial publication in 1994, Coordination Theory has been referenced in nearly 300 journal articles, book chapters, conference papers and theses. Coordination Theory provides an approach to a core problem in HCI: analyzing group work to suggest alternative approaches involving computer support. Coordination Theory suggests identifying the dependencies between the tasks the different group members are carrying out and the coordination mechanisms the group use to coordinate their work and then considering alternative mechanisms. This chapter will analyze the contribution of this body of research to determine how Coordination Theory has been used for user task analysis and modelling for HCI. Issues that will be addressed include: 1)how the theory has been applied; 2) factors that led to the success of the theory; and 3)identification of areas needing further research. }, keywords = {Coordination}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/CT\%20Review\%20to\%20distribute.pdf}, author = {Kevin Crowston and Rubleske, Joe and James Howison}, editor = {Zhang, P. and Galletta, D.} } @article {Scozzi:2005, title = {Methods for modeling and supporting innovation processes in SMEs}, journal = {European Journal of Innovation Management}, volume = {8}, number = {1}, year = {2005}, pages = {120{\textendash}137}, abstract = {Purpose {\textendash} Sets out to investigate business modeling techniques (BMTs) which can be used to support and improve innovation processes within small and medium-sized enterprises (SMEs). Design/methodology/approach {\textendash} Based on a literature review, different analysis perspectives on innovation processes are identified and discussed, and some firm needs and problems are pointed out. The importance of BMTs to firms is further tested by an empirical study whose initial results are reported. Finally, by matching problems and techniques characterized by the same ontology, the BMTs most suitable to address SME needs are identified and their role within the innovation process discussed. Findings {\textendash} The main result of the paper is the identification of the problems facing SMEs in innovation processes and the possible support offered by BMTs. Though methods and models alone do not assure the success in the innovation development process (IDP), they are enabling factors and can support the creation of strategies, reasoning, insights and communication. Originality/value {\textendash} The adoption of such BMTs, facilitating the codification of the characteristics of the IDP, might be particularly useful in those environments where, due to the lack of specialized resources, it is difficult to structure all of the information related to the innovation process and to exploit the related benefits and opportunities. }, keywords = {Coordination, Organizational Modelling}, doi = {10.1108/14601060510578619}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/MethodsForModeling.pdf}, author = {Scozzi, Barbara and Garavelli, C. and Kevin Crowston} } @proceedings {Wigand:2001, title = {Information and communication technologies in the real estate industry: Results of a pilot survey [Research in progress]}, year = {2001}, pages = {339-343}, address = {Bled, Slovenia}, abstract = {We have been studying the growing use of information and communication technologies (ICT) in the residential real estate industry and the effects of this use on how realtors work. Earlier stages of our project involved qualitative research to develop a better understanding of the industry, the work of realtors and their use of ICT. In this paper we report on the results of qualitative research and a pilot of a survey intended to gather large-scale data on realtors and ICT use.}, keywords = {Real Estate}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/ecis2001.pdf}, author = {Rolf Wigand and Kevin Crowston and Sawyer, Steve and Allbritton, Marcel}, editor = {Smithson, Steve and Gricar, Joze and Podlogar, Mateja and Avgerinou, Sophia} } @proceedings {1986, title = {Cognitive science and organizational design}, year = {1986}, pages = {43-61}, publisher = {ACM Press}, address = {Austin, Texas}, abstract = {Many researchers have investigated and speculated about the link between information technology and organizational structure with very mixed results. This paper suggests that part of the reason for these mixed results is the coarseness of previous analyses of both technology and structure. The paper describes a new and much more detailed perspective for investigating this link. Using concepts of object-oriented programming from artificial intelligence, the information processing that occurs in organizations is characterized in terms of the kinds of messages people exchange and the ways they process those messages. The utility of this approach is demonstrated through the analysis of a case in which a reduction in levels of management is coupled with the introduction of a computer conferencing system. The detailed model developed for this case helps explain both macro-level data about thd changes in the organizational structure, and micro-level data about individuals{\textquoteright} use of the system.}, keywords = {Organizational Modelling}, isbn = {1234567890}, doi = {10.1145/637069.637076}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/p43-crowston.pdf}, author = {Kevin Crowston and Malone, Thomas W. and Lin, Felix} }