@article {2021,
	title = {Hybrid intelligence in business networks},
	journal = {Electronic Markets},
	year = {2021},
	month = {Nov-06-2021},
	issn = {1019-6781},
	doi = {10.1007/s12525-021-00481-4},
	attachments = {https://crowston.syr.edu/sites/crowston.syr.edu/files/Ebel2021_Article_HybridIntelligenceInBusinessNe.pdf},
	author = {Ebel, Philipp and S{\"o}llner, Matthias and Leimeister, Jan Marco and Crowston, Kevin and de Vreede, Gert-Jan}
}
@proceedings {9999,
	title = {Helping data science students develop task modularity},
	year = {2019},
	abstract = {<p>This paper explores the skills needed to be a data scientist. Specifically, we report on a mixed method study of a project-based data science class, where we evaluated student effectiveness with respect to dividing a project into appropriately sized modular tasks, which we termed task modularity. Our results suggest that while data science students can appreciate the value of task modularity, they struggle to achieve effective task modularity. As a first step, based our study, we identified six task decomposition best practices. However, these best practices do not fully address this gap of how to enable data science students to effectively use task modularity. We note that while computer science/information system programs typically teach modularity (e.g., the decomposition process and abstraction), and there remains a need identify a corresponding model to that used for computer science / information system students, to teach modularity to data science students.</p>},
	keywords = {data science, modularity, Stigmergy},
	doi = {10.24251/HICSS.2019.134},
	url = {http://hdl.handle.net/10125/59549},
	attachments = {https://crowston.syr.edu/sites/crowston.syr.edu/files/modularity-HICSS-final-afterReview.pdf},
	author = {Jeffery Saltz and Heckman, Robert and Kevin Crowston and Sangseok You and Yatish Hegde}
}
@article {9999,
	title = {The Hermeneutics of Trace Data: Building an Apparatus},
	year = {2016},
	abstract = {When people interact via information systems, the data is captured by the systems as a side effect of the interaction. These data are increasingly interesting and available for research. In a sense, these systems become a new kind of research apparatus, and like all advances in instrumentation, open up new areas of study with the potential for discovery. While at first glance, such {\textquotedblleft}big data{\textquotedblright} analysis seems to be most suitable for a positivist quantitative research approach. However, a closer inspection reveals that interpretive research strategies may better support the challenges associated with digital trace data. By merging insights from hermeneutics and sociomateriality, we argue that trace data analysis entails the building of a research apparatus. Hermeneutic principles play a key role in the application of this apparatus and allow researchers to make sense of the often partial traces left by online participants. Drawing on longitudinal trace data from a study of citizen science practices the paper illustrates the value of merging insights from hermeneutics with sociomaterial insights. The approach allows researchers to account for not only the material dynamics of digital trace data but also the temporal dimension of online practices. },
	attachments = {https://crowston.syr.edu/sites/crowston.syr.edu/files/Crowston_Osterlund_Jackson_Mugar_The_Hermeneutics_of_Trace_Data_IFIP8.2_2016\%20to\%20distribute.pdf},
	author = {Carsten {\O}sterlund and Kevin Crowston and Corey Jackson}
}
@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}
}
@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}
}
@article {Crowston:2006a,
	title = {Hierarchy and centralization in Free and Open Source Software team communications},
	journal = {Knowledge, Technology \& Policy},
	volume = {18},
	number = {4},
	year = {2006},
	pages = {65{\textendash}85},
	abstract = {Free/Libre Open Source Software (FLOSS) development teams provide an interesting and convenient setting for studying distributed work. We begin by answering perhaps the most basic question: what is the social structure of these teams? Based on a social network analysis of interactions represented in 62,110 bug reports from 122 large and active projects, we find that some OSS teams are highly centralized, but contrary to expectation, others are not. Projects are mostly quite hierarchical on four measures of hierarchy, consistent with past research but contrary to the popular image of these projects. Furthermore, we find that the level of centralization is negatively correlated with project size, suggesting that larger projects become more modular. The paper makes a further methodological contribution by identifying appropriate analysis approaches for interaction data. We conclude by sketching directions for future research.},
	keywords = {FLOSS},
	attachments = {https://crowston.syr.edu/sites/crowston.syr.edu/files/HierarchyAndCentralization.pdf},
	author = {Kevin Crowston and James Howison}
}
@proceedings {Sawyer:2000,
	title = {How do information and communication technologies reshape work? Evidence from the residential real estate industry},
	year = {2000},
	address = {Brisbane, Australia, December 10{\textendash}13},
	abstract = {We are exploring how information and communication technology (ICT) use affects the work lives of real estate agents, the process of selling/buying houses, and the overall structure of the residential real estate industry. Earlier stages of our work involved intensive field research on how real estate agents use ICT. In this paper, we report on the design and analysis of a pilot survey of 868 agents intended to investigate their ICT use more generally. Analysis of the 153 responses to this survey sheds light on how ICT use supports information control, enables process support, and helps agents to extend and maintain their social capital.},
	keywords = {Real Estate},
	attachments = {https://crowston.syr.edu/sites/crowston.syr.edu/files/00RIP21.pdf},
	author = {Sawyer, Steve and Kevin Crowston and Allbritton, Marcel and Rolf Wigand}
}
@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}
}
