Trends, indicators and facts derived from the analysis and synthesis of biodiversity data can be used for planning conservation areas, assessing the impact of large construction works and preventing zoonoses. Since such decisions can have large-scale impacts on society, being able to track the processes involved in their making is an essential property. Therefore, it is important to use reproducible methodologies and techniques. Some initial advances were achieved using virtualization techniques and recording provenance information, data and processes. However, reproducibility in data science in general is still a challenge. We aim to advance in the development of reproducible techniques for activities of analysis and synthesis of biodiversity.