Availability of minimum information standards (MIS) has direct impacts on the ability to reuse experimental data and to store and manage the data according to open access and findable, accessible, interoperable, reusable (FAIR) data principles1, as well as on cost and resource efficiency. Such standards ensure that datasets are easy to find, verify and analyze for the wider scientific community2.
The absence of MIS prevents experimental data reuse, resulting in unnecessary repetition of experiments. Furthermore, it limits repeatability: a Nature survey found that more than 70% of researchers reported failing to reproduce another scientist’s experiment, and more than half were unable to reproduce their own3. Being able to reuse data can save time and resources, which can provide better value for money for publicly funded research, while accelerating research development and innovation. Leveraging the full potential of digitization and artificial intelligence makes access to usable secondary datasets increasingly important.
