Correlative Characterization experiments are complex, as they have to combine different types of information, coming from different instruments/techniques, which have different coordinate systems, measured across different length scales and at different times, from different sample regions, under different experimental conditions.
Metadata management can help mainly on three areas:
Data should be described with rich metadata, and the entire experimental workflow should be documented (the so-called provenance).
Existing standards, schemas, and ontologies should be adopted. When they are not available, schemas and vocabularies should be designed in common, trying to harmonise the outputs as much as possible.
The data should be stored in a place equipped with services which provide both human and machine interpretation, as well as an easy way to interact (e.g., Graphical User Interfaces and Electronic Lab Notebooks).
Motivated by this, the Metadata WG focuses and achieves results on the following topics: