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The democratization of data science and open government data initiatives are inspiring groups from civic hackers to data journalists to use data to address social issues. The analysis of open government data is expected to encourage citizens to participate in government as well as to improve transparency and efficiency in government processes. Through interviews and survey responses we gathered information on forty projects that involved the analysis of open data. We found that collaborations were interdisciplinary, small in scale, with low turnover, and synchronous communication. Most of the projects asked exploratory questions and made use of descriptive statistics and visualizations. We discuss how these findings contribute to an understanding of the emerging practice of open data analysis and to a broader understanding of open collaboration.

In spite of the lack of organizational control, a large number of these self-organized groups have successfully developed high quality software in open source software projects. We examined the process through which coordinated action emerges from the collection of individual developers' choices, i.e., how bottom-up coordination occurs and argue that developer herding on a social coding platform may have a positive impact on OSSD outcomes. As an exploratory study, we analyzed the participation patterns in 10 randomly sampled OSSD projects on a social open source code foundry, Github. Based on the findings we generate theoretical propositions regarding developer herding behavior in OSSD.