Abstract
A framework for reproducible data analysis is only half the battle if it comes to reproducible
research. Additional essential requirements are a way to safely store both, raw data and metadata
and a method to uniquely refer to a dataset or any piece of information. Such unique identifier is
fully independent of the actual place the information referred to is stored and does not change over
time. Additionally, numeric IDs for samples and alike come in quite handy. A knowledge base and
an electronic lab notebook, both based on wiki software and thus easily accessible requiring only
a web browser and connection to the intranet, complete the system. Overarching design rules are
simplicity, robustness and sustainability, focussing on small-scale deployment of the system retaining
compatibility with future developments and community efforts. Key aspects in setting up the system
are its use of well-proven open-source tools combined with maximal modularity, resulting in a low
entry threshold and allowing to implement and develop it along the way of focussing on actual
research.