This research project fetches event-data from githubarchives.org, filters the data to extract the information of interest, generates basic statistics and plots regarding to these statistics. The experiment is deployed to gain general knowledge on basic github-usage. Therefore, the following questions were followed: 1) How are GitHub-events distributed? - This can be derived by quantitative analysis of the distribution of different Event-Types. 2) What is the common ratio of commits per push, what are extremes? - again quantitative analysis of push-events is used. To visualize the results of this analysis, two plots are created. Each plot addresses one of the research-questions described above. Additionally, textual output is written to the terminal containing the precise numbers of the analysis and can be captured via native terminal functions. The data-files created by downloading and unzipping are just used as input for analysis and do not depict "final output". The given results were collected/created for the default time-period: 01.01.2015 00:00 to 01:00. The python3-Scripts need python version 3 and were executed on Linux! Additional libraries are required: matplotlib for python3

scripts are for python3! Need additional packages (e.g. matplotlib for python3) The files validation_requirements_for_reexecution.pdf contains requirements that should be fulfilled and help to check if the reexecution was successful. The context-model context_model_for_validation.owl is a ontology that helps understanding the context of the experiment and helps to validate any reexecution etc.