BitQuery is a GitHub1 API driven and D32 based search engine for open source repositories (OSR).
BitQuery pursues two main objectives:
The BitQuery architecture consists of three abstraction layers, following the visual analytics approach3:
1. GitHub is the world's largest code hosting platform for version control and collaboration.
3. Visual analytics: Definition, process, and challenges. Lecture notes in computer science, 4950:154–176 (D. Keim et al., 2008)
BitQuery GitHub Edition is designed to explore and query GitHub organizations.
With the growing popularity of GitHub, the largest host of source code and collaboration platform in the world, it has evolved to a Big Data resource offering a variety of open source repositories. Since 2010 GitHub offers organizations, simplifying management of group-owned repositories, and thus facilitating the GitHub workflow for business and large open source projects. At present, there are more than one million organizations on GitHub, among them Google, Amazon Web Services, Microsoft Azure, Google Cloud Platform, Facebook, Twitter, Yahoo, RStudio, D3, Plotly and many more.
Two plots showing the growth of the GitHub organizations over time are presented below. They were produced with the help of the rgithubS package, see also the References.
Total number (in thousands) of GitHub Organizations over time, monthly development, 2008-2013.
Growth of GitHub Organizations over time, weekly increments, 2008-2013.
BitTrinity is the driving technology of BitQuery that allows to retrieve the GitHub data, postprocess and export them to the appropriate visualization schemes. It comprises the following main components:
The API Parser Layer and Smart Data Layer have been programmed in R using various CRAN packages, see also the References. The design and implementation of the D3-3D Visu layer is described in detail in the VA-App section.
BitQuery VA-App creates an interactive network visualization that allows to overview, sort, zoom, filter and query the data. Additional components such as Legends, Tooltip and Search field provide detailed information on chosen subsets or single data nodes.
BitQuery VA-App was designed in full compliance with the visual analytics mantra:
"Analyze first - show the important - zoom, filter and analyze further - details on demand."
BitQuery VA-App infrastructure, implemented via CoffeeScript classes
Software engineer and data scientist
Data visualization specialist and data scientist