@proceedings {1443,
	title = {Citizen Engineering: Evolving OSS Practices to Engineering Design and Analysis},
	volume = {378},
	year = {2012},
	month = {09/2012},
	pages = {61-77},
	publisher = {IFIP AICT},
	abstract = {Open Source Software (OSS) development has much in common with concepts such as crowdsourcing, citizen science, collective intelligence, human-based computation, and what we call {\textquotedblleft}Citizen Engineering (CE){\textquotedblright}. We report on several pilot projects that apply these shared principles of OSS development to engineering activities beyond software engineering. CE models harness human computing power from open communities, which commonly consist of a cohort of geographically and/or institutionally scattered citizens - professionals or amateurs - to collaboratively solve real-world problems. In most cases, the problems targeted are challenging to computers, but manageable or trivial to human intelligence. In these systems, while humans play fundamental roles, whether they are project architects or problem solvers, the implementation of CE is greatly facilitated by the advance of information technology, particularly the Internet, considered as "creative mode of user interactivity, not merely a medium between messages and people" [10]. In this paper, we characterize existing citizen engineering practices into 6 major categories, followed by a discussion of 4 ongoing projects, aiming to provide new perspectives and insights for achieving successful CE project designs.},
	author = {Zhai, Zhi and Kijewski-Correa, Tracy and Kareem, Ashan and Hachen, David and Madey, Gregory}
}
@inbook {springerlink:10.1007/978-3-642-13244-5_20,
	title = {Download Patterns and Releases in Open Source Software Projects: A Perfect Symbiosis?},
	booktitle = {Open Source Software: New Horizons},
	series = {IFIP Advances in Information and Communication Technology},
	volume = {319},
	year = {2010},
	note = {"We apply experimentally our method to the most downloaded projects of SourceForge{\textquoteright}s history crawled through the FLOSSMole repository."},
	pages = {252-267},
	publisher = {Springer Boston},
	organization = {Springer Boston},
	abstract = {Software usage by end-users is one of the factors used to evaluate the success of software projects. In the context of open source software, there is no single and non-controversial measure of usage, though. Still, one of the most used and readily available measure is data about projects downloads. Nevertheless, download counts and averages do not convey as much information as the patterns in the original downloads time series. In this research, we propose a method to increase the expressiveness of mere download rates by considering download patterns against software releases. We apply experimentally our method to the most downloaded projects of SourceForge{\textquoteright}s history crawled through the FLOSSMole repository. Findings show that projects with similar usage can have indeed different levels of sensitivity to releases, revealing different behaviors of users. Future research will develop further the pattern recognition approach to automatically categorize open source projects according to their download patterns.},
	keywords = {flossmole, oss2010, sourceforge},
	url = {http://dx.doi.org/10.1007/978-3-642-13244-5_20},
	author = {Rossi, Bruno and Russo, Barbara and Succi, Giancarlo},
	editor = {{\r A}gerfalk, P{\"a}r and Boldyreff, Cornelia and Gonz{\'a}lez-Barahona, Jes{\'u}s and Madey, Gregory and Noll, John}
}
