@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 = {A decade of surveys on attitudes to data sharing highlights three factors for achieving open science}, year = {2023}, month = {08/2023}, type = {Blog}, url = {https://blogs.lse.ac.uk/impactofsocialsciences/2023/08/22/a-decade-of-surveys-on-attitudes-to-data-sharing-highlights-three-factors-for-achieving-open-science/}, author = {Joshua Borycz and Alison Specht and Kevin Crowston} } @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 {2023, title = {Surveys Provide Insight Into Three Factors That Encourage Open Data and Science}, year = {2023}, month = {9/2023}, type = {Blog}, url = {https://www.socialsciencespace.com/2023/09/surveys-provide-insight-into-three-factors-that-encourage-open-data-and-science/}, author = {Joshua Borycz and Alison Specht and Kevin Crowston} } @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 {soni2021discovering, title = {Discovering features in gravitational-wave data through detector characterization, citizen science and machine learning}, journal = {Classical and Quantum Gravity}, volume = {38}, year = {2021}, doi = {10.1088/1361-6382/ac1ccb}, author = {S Soni and C P L Berry and S B Coughlin and M Harandi and C B Jackson and K Crowston and C {\O}sterlund and O Patane and A K Katsaggelos and L Trouille and V-G Baranowski and W F Domainko and K Kaminski and M A Lobato Rodriguez and U Marciniak and P Nauta and G Niklasch and R R Rote and B T{\'e}gl{\'a}s and C Unsworth and C Zhang} } @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 {2021, title = {Imagine All the People: Citizen Science, Artificial Intelligence, and Computational Research}, year = {2021}, institution = {Computing Community Consortium (CCC)}, address = {Washington, DC}, abstract = {

Machine learning, artificial intelligence, and deep learning have advanced significantly over the past decade. Nonetheless, humans possess unique abilities such as creativity, intuition, context and abstraction, analytic problem solving, and detecting unusual events. To successfully tackle pressing scientific and societal challenges, we need the complementary capabilities of both humans and machines. The Federal Government could accelerate its priorities on multiple fronts through judicious integration of citizen science and crowdsourcing with artificial intelligence (AI), Internet of Things (IoT), and cloud strategies.

}, url = {https://cra.org/ccc/wp-content/uploads/sites/2/2021/03/CCC-TransitionPaperImagine-All-the-People.pdf}, author = {Lea A. Shanley and Lucy Fortson and Tanya Berger-Wolf and Kevin Crowston and Pietro Michelucci} } @proceedings {9999, title = {Impacts of the Use of Machine Learning on Work Design}, year = {2020}, month = {11/2020}, publisher = {ACM}, address = {Virtual Event, NSW, Australia}, abstract = {

The increased pervasiveness of technological advancements in automation makes it urgent to address the question of how work is changing in response. Focusing on applications of machine learning (ML) to automate information tasks, we draw on a simple framework for identifying the impacts of an automated system on a task that suggests 3 patterns for the use of ML{\textemdash}decision support, blended decision making and complete automation. In this paper, we extend this framework by considering how automation of one task might have implications for interdependent tasks and how automation applies to coordination mechanisms.

}, keywords = {artificial intelligence, automation, Coordination, machine learning, work design}, isbn = {978-1-4503-8054-6/20/11}, doi = {10.1145/3406499.3415070}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/Impacts_of_ML_for_HAI_2020.pdf}, author = {Kevin Crowston and Bolici, Francesco} } @article {9998, title = {Knowledge Tracing to Model Learning in Online Citizen Science Projects}, journal = {IEEE Transactions on Learning Technologies}, volume = {13}, year = {2020}, pages = {123-134}, abstract = {

We present the design of a citizen science system that uses machine learning to guide the presentation of image classification tasks to newcomers to help them more quickly learn how to do the task while still contributing to the work of the project. A Bayesian model for tracking volunteer learning for training with tasks with uncertain outcomes is presented and fit to data from 12,986 volunteer contributors. The model can be used both to estimate the ability of volunteers and to decide the classification of an image. A simulation of the model applied to volunteer promotion and image retirement suggests that the model requires fewer classifications than the current system.

}, issn = {1939-1382}, doi = {10.1109/TLT.2019.2936480 }, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/transaction\%20paper\%20final\%20figures\%20in\%20text.pdf}, author = {Kevin Crowston and Carsten {\O}sterlund and Tae Kyoung Lee and Corey Brian Jackson and Mahboobeh Harandi and Sarah Allen and Sara Bahaadini and Scott Coughlin and Aggelos Katsaggelos and Shane Larson and Neda Rohani and Joshua Smith and Laura Trouille and Michael Zevin} } @article {9999, title = {Teaching Citizen Scientists to Categorize Glitches using Machine-Learning-Guided Training}, journal = {Computers in Human Behavior}, volume = {105}, year = {2020}, pages = {106198}, abstract = {

Training users in online communities is important for making high performing contributors. However, several conundrums exists in choosing the most effective approaches to training users. For example, if it takes time to learn to do the task correctly, then the initial contributions may not be of high enough quality to be useful. We conducted an online field experiment where we recruited users (N = 386) in a web-based citizen-science project to evaluate the two training approaches. In one training regime, users received one-time training and were asked to learn and apply twenty classes to the data. In the other approach, users were gradually exposed to classes of data that were selected by trained machine learning algorithms as being members of particular classes. The results of our analysis revealed that the gradual training produced {\textquotedblleft}high performing contributors{\textquotedblright}. In our comparison of the treatment and control groups we found users who experienced gradual training performed significantly better on the task (an average accuracy of 90\% vs. 54\%), contributed more work (an average of 228 vs. 121 classifications), and were retained in the project for a longer period of time (an average of 2.5 vs. 2 sessions). The results suggests online production communities seeking to train newcomers would benefit from training regimes that gradually introduce them to the work of the project using real tasks.

}, doi = {10.1016/j.chb.2019.106198}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/MLGT-preprint.pdf}, author = {Corey Jackson and Carsten {\O}sterlund and Kevin Crowston and Mahboobeh Harandi and Sarah Allen and Sara Bahaadini and Scott Coughlin and Vicky Kalogera and Aggelos Katsaggelos and Shane Larson and Neda Rohani and Joshua Smith and Laura Trouille and Michael Zevin} } @article {2019, title = {Classifying the unknown: Discovering novel gravitational-wave detector glitches using similarity learning}, journal = {Physical Review D}, volume = {99}, year = {2019}, pages = {082002}, abstract = {

The observation of gravitational waves from compact binary coalescences by LIGO and Virgo has begun a new era in astronomy. A critical challenge in making detections is determining whether loud transient features in the data are caused by gravitational waves or by instrumental or environmental sources. The citizen-science project Gravity Spy has been demonstrated as an efficient infrastructure for classifying known types of noise transients (glitches) through a combination of data analysis performed by both citizen volunteers and machine learning. We present the next iteration of this project, using similarity indices to empower citizen scientists to create large data sets of unknown transients, which can then be used to facilitate supervised machine-learning characterization. This new evolution aims to alleviate a persistent challenge that plagues both citizen-science and instrumental detector work: the ability to build large samples of relatively rare events. Using two families of transient noise that appeared unexpectedly during LIGO{\textquoteright}s second observing run, we demonstrate the impact that the similarity indices could have had on finding these new glitch types in the Gravity Spy program.

}, issn = {2470-0010}, doi = {10.1103/PhysRevD.99.082002}, author = {Scott Coughlin and Sara Bahaadini and Neda Rohani and Michael Zevin and Patane, Oli and Mahboobeh Harandi and Corey Brian Jackson and Noroozi, V. and Sarah Allen and Areeda, J. and Coughlin, M. and Ruiz, P. and Berry, C. P. L. and Kevin Crowston and Aggelos Katsaggelos and Andrew Lundgren and Carsten {\O}sterlund and Joshua Smith and Laura Trouille and Vicky Kalogera} } @proceedings {9999, title = {Impacts of machine learning on work}, year = {2019}, address = {Wailea, HI}, abstract = {

The increased pervasiveness of technological advancements in automation makes it urgent to address the question of how work is changing in response. Focusing on applications of machine learning (ML) that automate information tasks, we present a simple framework for identifying the impacts of an automated system on a task. From an analysis of popular press articles about ML, we develop 3 patterns for the use of ML--decision support, blended decision making and complete automation--with implications for the kinds of tasks and systems. We further consider how automation of one task might have implications for other interdependent tasks. Our main conclusion is that designers have a range of options for systems and that automation of tasks is not the same as automation of work.

}, keywords = {artificial intelligence, automation, machine learning, work design}, doi = {10.24251/HICSS.2019.719}, url = { http://hdl.handle.net/10125/60031}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/Impacts_of_machine_learning_on_work__revision_.pdf}, author = {Kevin Crowston and Bolici, Francesco} } @article {657, title = {Gravity Spy: Integrating Advanced LIGO Detector Characterization, Machine Learning, and Citizen Science}, journal = {Classical and Quantum Gravity}, volume = {34}, year = {2017}, pages = {064003}, type = {Journal Article}, doi = {10.1088/1361-6382/aa5cea}, author = {Michael Zevin and Scott Coughlin and Sara Bahaadini and Emre Besler and Neda Rohani and Sarah Allen and Miriam Cabero and Kevin Crowston and Aggelos Katsaggelos and Shane Larson and Tae Kyoung Lee and Chris Lintott and Tyson Littenberg and Andrew Lundgren and Carsten Oesterlund and Joshua Smith and Laura Trouille and Vicky Kalogera} } @article {2017, title = {A pragmatic approach to managing enterprise IT infrastructures in the era of consumerization and individualization of IT}, journal = {International Journal of Information Management}, volume = {37}, year = {2017}, pages = {566-575}, type = {Journal Article}, abstract = {Historically, organizations owned and controlled the information technologies (IT) their employees used: telephone, inter-office memos, mainframes and timesharing systems. Today, employees often want to use their own IT: not only personal smart phones and tablets, but also Twitter and Google Docs. This new trend can diversify and extend enterprise IT infrastructure, but leaves organizations struggling with technology uses that they cannot control. With the emergence of new technological paradigms in consumer markets and organizations, the management of IT infrastructure requires a more pragmatic and holistic approach that goes beyond simple technological considerations. In this paper, we present a three-part framework{\textemdash}technology, people and practice{\textemdash}that helps managers understand and mitigate these tensions. Drawing on two empirical studies of European executives and consultants form multiple management consulting firms, the paper further outlines changes taking place along the three aspects of the framework. It concludes by discussing three distinct approaches to the management of organizational IT infrastructure (passive, reactive, and pragmatic), and by offering greater insight regarding a pragmatic approach.}, issn = {0268-4012}, doi = {10.1016/j.ijinfomgt.2017.05.016}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/Jarrahi\%20et\%20al\%20\%282017\%29\%20A\%20pragmatic\%20approach\%20to\%20managing\%20enterprise\%20IT\%20infrastructures\%20in\%20the\%20era\%20of\%20consumerization\%20and\%20individualization\%20of\%20IT.pdf}, author = {Mohammad Hossein Jarrahi and Kevin Crowston and Bondar, Kateryna and Bernhard Katzy} } @article {2017, title = {Work~features to support stigmergic coordination in distributed teams}, year = {2017}, type = {Interactive paper}, abstract = {

When work products are shared via a computer system, members of distributed teams can see the work products produced by remote colleagues as easily as those from local colleagues. Drawing on coordination theory and work in computer-supported cooperative work (CSCW), we theorize that these work products can provide information to support team coordination, that is, that work can be coordinated through the outcome of the work itself, a mode of coordination analogous to the biological process of stigmergy. Based on studies of documents and work, we postulate three features of work products that enable them to support team coordination, namely having a clear genre, being visible and mobile, and being combinable. These claims are illustrated with examples drawn from free/libre open source software development teams. We conclude by discussing how the proposed theory might be empirically tested.

}, keywords = {Coordination, Stigmergy}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/Stigmergy\%20theory\%20paper\%20to\%20share.pdf}, author = {Kevin Crowston and James Howison and Bolici, Francesco and Carsten {\O}sterlund} } @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 {9998, title = {Stigmergic coordination in FLOSS development teams: Integrating explicit and implicit mechanisms}, journal = {Cognitive Systems Research}, volume = {38}, year = {2016}, pages = {14{\textendash}22}, keywords = {Coordination, Stigmergy}, doi = {10.1016/j.cogsys.2015.12.003}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/COGSYS-RS-\%28HHS\%29-\%282015\%29-\%283\%29.pdf}, author = {Bolici, Francesco and James Howison and Kevin Crowston} } @inbook {2015, title = {Open Source Technology Development}, booktitle = {Handbook of Science and Technology Convergence}, year = {2015}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-04033-2}, doi = {10.1007/978-3-319-04033-2_29-1}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/chp\%253A10.1007\%252F978-3-319-04033-2_29-1.pdf}, author = {Kevin Crowston}, editor = {Bainbridge, William Sims and Roco, Mihail C.} } @conference {2013, title = {Forgotten island: A story-driven citizen science adventure}, booktitle = {CHI {\textquoteright}13 Extended Abstracts on Human Factors in Computing Systems}, year = {2013}, month = {4/2013}, pages = {2643{\textendash}2646}, publisher = {ACM Press}, organization = {ACM Press}, address = {Paris, France}, abstract = {

Forgotten Island, a citizen science video game, is part of an NSF-funded design science research project, Citizen Sort. It is a mechanism to help life scientists classify photographs of living things and a research tool to help HCI and information science scholars explore storytelling, engagement, and the quality of citizenproduced data in the context of citizen science.

}, isbn = {9781450319522}, doi = {10.1145/2468356.2479484}, url = {http://delivery.acm.org/10.1145/2480000/2479484/p2643-prestopnik.pdf}, author = {Nathan Prestopnik and Souid, Dania} } @proceedings {crowston2012, title = {Amazon Mechanical Turk: A research tool for organizations and information systems scholars}, volume = {389}, year = {2012}, month = {12/2012}, pages = {210-221}, publisher = {Springer}, address = {Tampa, FL}, isbn = {978-3-642-35141-9}, issn = {1868-4238}, doi = {10.1007/978-3-642-35141-9}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/3890210.pdf}, author = {Kevin Crowston}, editor = {Anol Bhattacherjee and Brian Fitzgerald} } @conference {2011, title = {Work as coordination and coordination as work: A process perspective on FLOSS development projects}, booktitle = {Third International Symposium on Process Organization Studies}, year = {2011}, month = {6/2011}, address = {Corfu, Greece}, url = {http://www.process-symposium.com/}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/PROS-134.pdf}, author = {Kevin Crowston and Carsten {\O}sterlund and James Howison and Bolici, Francesco} } @article {2010, title = {The under-appreciated role of stigmergic coordination in software development}, year = {2010}, abstract = {

Coordination in software development teams has been a topic of perennial interest in empirical software engineering research. The vast majority of this literature has drawn on a conceptual separation between work and coordination mechanisms, separate from the work itself, which enable groups to achieve coordination. Traditional recommendations and software methods focused on planning: using analysis to predict and manage dependencies. Empirical research has demonstrated the limits of this approach, showing that many important dependencies are emergent and pointing to the persistent importance of explicit discussion to managing these dependencies as they arise. Drawing on work in Computer-Supported Collaborative Work and building from an analogy to collaboration amongst insects (stigmergy), we argue that the work product itself plays an under-appreciated role in helping software developers manage dependencies as they arise. This short paper presents the conceptual argument with empirical illustrations and explains why this mechanism would have significant implications for Software Engineering coordination research. We discuss issues in marshaling clear positive evidence, arguing that these issues are responsible, in part, for the under-consideration of this mechanism in software engineering and outlining research strategies which may overcome these issues.

}, keywords = {Coordination, FLOSS, Stigmergy}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/stigmergy-short.pdf}, author = {Bolici, Francesco and James Howison and Kevin Crowston} } @conference {Bolici:2009, title = {Coordination without discussion? Socio-technical congruence and Stigmergy in Free and Open Source Software projects}, booktitle = {2nd International Workshop on Socio-Technical Congruence, ICSE}, year = {2009}, month = {19 May}, address = {Vancouver, Canada}, keywords = {Coordination, FLOSS}, url = {http://docs.google.com/View?id=dhncd3jd_405fzt842gv}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/Coordination\%20without\%20discussion\%3F\%20Socio-technical\%20congruence.pdf}, author = {Bolici, Francesco and James Howison and Kevin Crowston} } @proceedings {Scialdone:2009, title = {Group Maintenance Behaviours of Core and Peripheral Members of Free/Libre Open Source Software Teams}, year = {2009}, address = {Skövde, Sweden, 3-6 June}, abstract = {Group Maintenance is pro-social, discretionary, and relation-building behavior that occurs between members of groups in order to maintain reciprocal trust and cooperation. This paper considers how Free/libre Open Source Software (FLOSS) teams demonstrate such behaviors within the context of e-mail, as this is the primary medium through which such teams communicate. We compare group maintenance behaviors between both core and peripheral members of these groups, as well as behaviors between a group that remains producing software today and one which has since dissolved. Our findings indicate that negative politeness tactics (those which show respect for the autonomy of others) may be the most instrumental group maintenance behaviors that contribute to a FLOSS group{\textquoteleft}s ability to survive and continue software production. }, keywords = {FLOSS, Group Maintenance}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/34finalmjs.pdf}, author = {Scialdone, Michael J. and Heckman, Robert and Kevin Crowston}, editor = {Boldyreff, Cornelia and Kevin Crowston and Lundell, Bj{\"o}rn and Wasserman, Tony} } @proceedings {Wiggins:2009, title = {Heartbeat: Measuring Active User Base and Potential User Interest in FLOSS Projects}, volume = {299}, year = {2009}, pages = {94-104}, publisher = {Springer Boston}, address = {Skövde, Sweden, 3-6 June}, abstract = {This paper presents a novel method and algorithm to measure the size of an open source project{\textquoteright}s user base and the level of potential user interest that it generates. Previously unavailable download data at a daily resolution confirms hypothesized patterns related to release cycles. In short, regular users rapidly download the software after a new release giving a way to measure the active user base. In contrast, potential new users download the application independently of the release cycle, and the daily download figures tend to plateau at this rate when a release has not been made for some time. An algorithm for estimating these measures from download time series is demonstrated and the measures are examined over time in two open source projects.}, isbn = {978-3-642-02031-5}, issn = {978-3-642-02031-5}, doi = {10.1007/978-3-642-02032-2\%5f10}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/heartbeat.pdf}, author = {Wiggins, Andrea and James Howison and Kevin Crowston}, editor = {Boldyreff, Cornelia and Kevin Crowston and Lundell, Bj{\"o}rn and Wasserman, Tony} } @booklet {2009, title = {ICIS 2008 Panel Report: Open Access Publishing to Nurture the Sprouts of Knowledge and the Future of Information Systems Research}, howpublished = {Communications of the Association for Information Systems}, volume = {24}, year = {2009}, abstract = {

The advent of the Internet and the subsequent adoption of Open Access schemata are changing the nature of the scholarly discourse. In response, we seek to stimulate a debate about the role and desired forms of Open Access publishing in the context of the Information System (IS) discipline. We explore the potential contribution of an Open Access perspective on publishing IS-related research and also discuss the roles of traditional journals and their prospects in the contexts of our observations. In particular, we focus on the new possibilities of publishing work-in-progress and its potential benefit for knowledge dissemination including the prospects of turning today{\textquoteright}s limited scholarly exchange into mass collaboration. We illustrate our vision with a working prototype of an Open Access disciplinary repository entitled Sprouts (http://sprouts.aisnet.org). Our aim is to inspire new thinking about the role of Open Access publishing, the potential of its application to disciplinary repositories of emergent work, its anticipated repercussions on our work practices, and its long-term implication for the impact of IS scholarship and the well-being of our community at large. We call for participation and further action in realizing a global repository of IS research in progress. This paper builds on a panel on Open Access that was presented at the 2008 International Conference on Information Systems (ICIS), held in Paris, France, in December 2008.

}, keywords = {Information System}, doi = {10.17705/1CAIS.02430}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/ICIS\%20Panel\%20Open\%20Access\%20Publishing.pdf}, author = {Avital, Michel and Bj{\"o}rk, Bo-Christer and Boland, Richard J and Kevin Crowston and Lyytinen, Kalle and Majchrzak, Ann} } @conference {2004, title = {Effective work practices for software engineering}, booktitle = {Proceedings of the 2004 ACM workshop on Interdisciplinary software engineering research (WISER {\textquoteright}04)}, year = {2004}, pages = {18}, publisher = {ACM Press}, organization = {ACM Press}, address = {Newport Beach, CA, USA}, abstract = {We review the literature on Free/Libre Open Source Software (FLOSS) development and on software development, distributed work and teams more generally to develop a theoretical model to explain the performance of FLOSS teams. The proposed model is based on Hackman{\textquoteright}s [34] model of effectiveness of work teams, with coordination theory [52] and collective mind [79] to extend Hackman{\textquoteright}s model by elaborating team practices relevant to effectiveness in software development. We propose a set of propositions to guide further research.}, keywords = {FLOSS}, isbn = {1581139888}, doi = {10.1145/1029997.1030003}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/p18-crowston.pdf}, author = {Kevin Crowston and Annabi, Hala and James Howison and Masango, Chengetai} } @article {Malone:1999, title = {Tools for inventing organizations: Toward a handbook of organizational processes}, journal = {Management Science}, volume = {45}, number = {3}, year = {1999}, note = {Reprinted in Malone, T. W., Crowston, K. \& Herman, G. (Eds.) Organizing Business Knowledge: The MIT Process Handbook. Cambridge, MA: MIT Press, 2003. Reprinted in Malone, T. W., Laubacher, R. \& Scott Morton, M. S. (Eds.). Inventing the Organizations of the 21st Century. Cambridge, MA: MIT Press, 2003.}, pages = {425{\textendash}443}, abstract = {This paper describes a novel theoretical and empirical approach to tasks such as business process redesign and knowledge management. The project involves collecting examples of how different organizations perform similar processes, and organizing these examples in an on-line "process handbook." The handbook is intended to help people: (1) redesign existing organizational processes, (2) invent new organizational processes (especially ones that take advantage of information technology), and (3) share ideas about organizational practices. A key element of the work is an approach to analyzing processes at various levels of abstraction, thus capturing both the details of specific processes as well as the "deep structure" of their similarities. This approach uses ideas from computer science about inheritance and from coordination theory about managing dependencies. A primary advantage of the approach is that it allows people to explicitly represent the similarities (and differences) among related processes and to easily find or generate sensible alternatives for how a given process could be performed. In addition to describing this new approach, the work reported here demonstrates the basic technical feasibility of these ideas and gives one example of their use in a field study.}, keywords = {Coordination, Handbook, Process}, doi = {10.1287/mnsc.45.3.425}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/ms99.pdf}, author = {Malone, Thomas W. and Kevin Crowston and Lee, Jintae and Pentland, Brian and Dellarocas, Chrysanthos and Wyner, George and Quimby, John and Osborn, Charley and Bernstein, Avi and Herman, George and Klein, Mark and O{\textquoteright}Donnell, Elissa} } @proceedings {Mackay:1989, title = {How do experienced Information Lens users use rules?}, year = {1989}, note = {Proceedings Reprinted as ACM SIGCHI Bulletin, Volume 20, Issue SI.}, pages = {211{\textendash}216}, address = {Austin, TX}, abstract = {The Information Lens provides electronic mail users with the ability to write rules that automatically sort, select, and filter their messages. This paper describes preliminary results from an eighteen-month investigation of the use of this system at a corporate test site. We report the experiences of 13 voluntary users who have each had at least three months experience with the most recent version of the system. We found that: 1. People without significant computer experience are able to create and use rules effectively. 2. Useful rules can be created based on the fields present in all messages (e.g., searching for distribution lists or one{\textquoteright}s own name in the address fields or for character strings in the subject field), even without any special message templates. 3. People use rules both to prioritize messages before reading them and to sort messages into folders for storage after reading them. 4. People use delete rules primarily to filter out messages from low-priority distribution lists, not to delete personal messages to themselves.}, keywords = {Computer-Mediated Communication}, doi = {10.1145/67449.67491}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/sigchi89.pdf}, author = {Mackay, Wendy E. and Malone, Thomas W. and Kevin Crowston and Rao, Ramana and Rosenblitt, David and Card, Stuart K.}, editor = {Bice, Ken and Lewis, Clayton} }