Publishing reproducible results supported by FAIR data

We discuss two techniques for processing and analysing data that at the same time generate the required metadata to create FAIR digital objects. These objects can then be published as supporting information for the results obtained. This approach requires minimum intervention from the researcher performing the processing and analysis tasks. Consequently, these methods are ideal for improving the practices of publishing data, facilitate reproducibility of results, and support greater reuse of published data.

Both techniques produce the metadata required for reproducing the results, including data used, parameters set at each stage, sequence of operations and mapping between inputs and outputs. The use of these type of tools reduces the work for documenting supporting data, enables comparison of results when varying parameters, and supports exploratory testing of different parameter combinations.