Goals – LAIRHUB

Rouchen will conduct a literature review based on the paper titled – “The Geography of Open Source Software: Evidence from GitHub”
Nibras will review the codebase based on – “https://github.com/johanneswachs/OSS_Geography_Data“

We identified that innovation graph used data on public activity. We noticed from the paper on “Geography of OSS” they have made a data set by identifying the number of active developers within each region. They define active developer by developers who had at least 100 commit in two years.
Our first goal for this week is to read their paper carefully to understand their methodology of data collection and analysis.
Our next goal is to use their publicly available code from their repository in Github and replicate the data collection Process to get a quarterly data.
At some point of their code we expect them to use the dates of commits which we might be able to use to organize the data inn quarterly basis. The problem of innovation graph data is that it is an aggregate measurement of GitHub activity that could be skewed to towards more active developers, but the process implemented by Wachs et all is a better metric because then we can get rid of developers that aren’t active at all and see the “real” software development.

Collect 15 papers. Keywords: Open source software, metric, GitHub, Economic Development, low and middle income countries, digital economy
Identify metric of determining active GitHub, OSS software developer account.
- What do we mean by active account?
List how GitHub activity data was used in publications
Source of the dataset