BitQuery is a GitHub API driven and D3 based search engine for open source repositories.
BitQuery pursues two main objectives:
- (I) Provide an automatic OSR categorization system for data science teams and software developers promoting discoverability, technology transfer and coexistence
- (II) Establish visual data exploration and topic driven navigation of GitHub organizations for collaborative reproducible research (CRR) and web deployment
The BitQuery architecture consists of three abstraction layers, following the visual analytics approach (D. Keim, 2008):
- GitHub API based parser layer (Data Management)
- Smart Data layer (Analysis)
- D3-3D Visu layer, or BitQuery Visual Analytics application (VA-App) (Visualization)
Visual Analytics layouts of BitQuery include:
- CRAN edition - visual exploration of the R universe, a massive collection of all R packages on GitHub including CRAN and Bioconductor
- Special edition - visual data mining of 4 different metadata types: YAML, DCF, JSON, Markdown
- GitHub edition - interactive visual knowledge discovery of top GitHub organizations
- HCA Multilevel Edition
- Data Projector Edition
Presentation of BitQuery at Data Science, Statistics & Visualization Conference 2017, Lisbon, Portugal:
- Abstract: BitQuery - GitHub API driven and D3 based search engine for open source
- Talk: BitQuery - GitHub API driven and D3 based search engine for open source repositories
If you use BitQuery in your research or use it for visualizing your repositories on GitHub, please use the following BibTeX entry.
@online{BitQuery,
title = {{BitQuery: a GitHub API driven and D3 based search engine for open source repositories}},
author = {Lukas Borke and Svetlana Bykovskaya},
year = {2017},
url = {http://bitquery.de},
urldate = {2017-12-01},
NOTE = {Available at http://bitquery.de},
}
If you would like do add new views with more repositories and organizations to BitQuery, please contact the creators of BitQuery: https://github.com/orgs/bemined/people .