ODAM (Open Data for Access and Mining) is an Experiment Data Table Management System (EDTMS) that implements a simple way to make research data broadly accessible and fully available for reuse, including by script languages such as R and Python. The main purpose is to make a dataset accessible online with minimal effort from the data provider, and to allow any data scientists or researchers to be able to explore the dataset and then extract a subpart or the totality of the data according to their needs. The purpose of this protocol is to describe all the steps involved in collecting, preparing and annotating the data from an experiment associated with an experimental design (DoE) that will then allow the user to benefit from the services offered by ODAM. The overall approach is based on good data management practices concerning data structuring and the description of structural metadata. Indeed, ODAM allows to put metadata in depth, i.e. at the level of the data itself (i.e. metadata at column-level such as factors, variables,...) and not only as a "hat" on the data set. Thus, having the actual data elements also machine-readable make the dataset of a higher level of interoperability and makes functional interlinking and analysis in broader context much easier.