Successful and Abandoned Sourceforge.Net Projects in the Initiation Stage

[first paragraph] Chapter 6 provided an open source project success and abandonment dependent variable. Chapter 7 described data available in the Sourceforge.net repository and linked these data to various independent variable concepts and hypotheses presented in the theoretical part of this book. Chapter 7 also described the Classification Tree and Random Forest statistical approaches we use in this and the following chapter. This chapter presents the results of the Classification Tree analysis for successful and abandoned projects in the Initiation Stage, which in Chapter 3 (Figure 3.2), we defined as the period before and up to the time when a project completes a first release of its software. Readers are encouraged to review Chapter 6 (especially Table 6.1) for specifics on how we operationalized this definition as well as the other Initiation Stage dependent variable categories (e.g., Abandoned in Initiation, Indeterminate in Initiation)

The Open Source Software Ecosystem

[first paragraph] Open source research in the late 1990s and early 2000\u27s described open source development projects as all-volunteer endeavors without the existence of monetary incentives (Chakravarty, Haruvy and Wu, 2007), and relatively recent empirical studies (Ghosh, 2005; Wolf {{243}}) confirm that a sizable percentage of open source developers are indeed volunteers.1 Open source development projects involving more than one developer were seen to follow a “hacker ethic” (Himanen, 2000; von Hippel and von Krogh, 2003) where individuals freely give away and exchange software they had written so that it could be modified and built upon, with an expectation of reciprocation. An early puzzle, of particular interest to economists, was why people would voluntarily contribute their ideas and time to these projects (Lerner and Tirole {{243}}. We\u27ll focus on these fine-scale behavioral questions in Chapter 3, and will explain that there are clear reasons – such as distance learning, signaling, enjoyment, and “user-driven innovation” based on a need (von Hippel, 2005) – that motivate these volunteers to participate

Brooks\u27 Versus Linus\u27 Law: An Empirical Test of Open Source Projects

Free/Libre and Open Source Software (FOSS) projects are Internet-based collaborations consisting of volunteers and paid professionals who come together to create computer software..

Open Source Software Collaboration: Foundational Concepts and an Empirical Analysis

This paper has three primary goals. First, we provide an overview on some foundational concepts – “peer-production,” “user-centric innovation,” “crowdsourcing,” “task granularity,” and yes, open source and open content – for they are key elements of Internet-based collaboration we see today. Second, through this discussion on foundational concepts, we hope to make it clear why people interested in collaborative public management and administration should care about open source and open source-like collaboration. After this argument is made, we provide a very condensed summary of where we are to date on open source collaboration research. The goal of that research is to learn about the factors that lead to successful or abandoned collaborations in the open source domain, in part to help us understand how “open source-like” collaborations can be deployed in areas outside of software. We have a lot to cover. Let’s get right to it

Volume Introduction Letter

This Conference Proceedings is a collection of outstanding papers and posters submitted to the Academic Program of the International Conference for Free and Open Source Software for Geospatial (FOSS4G), 14th to 19th August 2017 in Boston, U.S.A

Lights, Camera...Citizen Science: Assessing the Effectiveness of Smartphone-Based Video Training in Invasive Plant Indentification

The rapid growth and increasing popularity of smartphone technology is putting sophisticated data-collection tools in the hands of more and more citizens. This has exciting implications for the expanding field of citizen science. With smartphonebased applications (apps), it is now increasingly practical to remotely acquire high quality citizen-submitted data at a fraction of the cost of a traditional study. Yet, one impediment to citizen science projects is the question of how to train participants. The traditional ‘‘in-person’’ training model, while effective, can be cost prohibitive as the spatial scale of a project increases. To explore possible solutions, we analyze three training models: 1) in-person, 2) app-based video, and 3) app-based text/images in the context of invasive plant identification in Massachusetts. Encouragingly, we find that participants who received video training were as successful at invasive plant identification as those trained in-person, while those receiving just text/images were less successful. This finding has implications for a variety of citizen science projects that need alternative methods to effectively train participants when in-person training is impractical

Community Service with Web-Based Geographic Information Science and Technology (GIST): Blended Pedagogies for the Twenty-First Century

This past year a team of technoacademics from the Five Colleges joined together to design, build, and implement a new course on Web-based geographic information science and technology (GIST). As is common with many GIS courses students formed small teams that worked on different projects. The projects were service-oriented, producing Web sites and interactive maps that benefited our institutions and other community organizations, and interdisciplinary, running the gamut from the geological to the conservational to the sociopolitical. Blended learning was a foundation of the course, with most materials provided online, and before class students were expected to review it, work exercises, and answer quiz questions. Once in class they actively applied what they learned to real data sets relevant to their projects, where their efforts were not so clear-cut and needed more hands-on support. As a result the course on most days was “flipped” or “workshopped”. The course also had an explicit focus on open learning, relying on open-source technology, open data sets, and openly licensed content written by ourselves or others