Many scientists are using a laboratory notebook when conducting experiments. The scientist documents each step, either taken in the experiment or afterwards when processing data. Due to computerized research systems, acquired data increases in volume and becomes more elaborate. This increases the need to migrate from originally paper-based to electronic notebooks with data storage, computational features and reliable electronic documentation. This talks describes a laboratory notebook based on the Python data management software DataFinder. It allows to manage data from experiments and simulations, to run analysis software and to create visualizations of results. The laboratory notebook assures that the complete history of all performed steps ("Provenance") is recorded, that results can be signed digitally, and that results can be archived in a secure archive to avoid and prevent legal issues.