All the points that have been exposed related to Fair Data and Open Data are important. However there is a point at the end of the road that is fundamental and is this: Can we really make use of the data even when it is fair or open theoretically?. It is important to establish standards that favor the exchange of data. Good examples of this have been initiatives such as biopax (www.biopax.org) that have tried to standardize the way in which information related to metabolic and signaling pathways can be exchanged. We can see the benefits of these in portals like Reactome.

Comments like the following (from a friend), show us that in some way the scientist community is failing in the way they express how their experiments were made. The data and metadata produced and shared about the different stages of a project's report, are fundamental to go over this very worrying problem. We need standards about this. Fortunately this is an issue that is being cared actually.

"We often find that in our own experiments, the results of publications that establish metabolic pathways and interactions, are not allowed to reproduce, which makes us distrust any automation based on them (https://www.nature.com/collections/prbfkwmwvz , https://en.wikipedia.org/wiki/Replication_crisis). When we are interested in studying a metabolic pathway, we often end up doing our own experiments in the laboratory with all the cost in time and money that implies."