Metadata Management in Correlative Characterization: Tales from the Metadata WG

Correlative characterization is a highly multi-disciplinary research field where scientists often need to combine different types of information from co-referenced (in time or space) multi-modal data obtained using different techniques. Each measurement or analysis method results in datasets which have to be combined in order to obtain complementary insights on a region of interest and to relate features and properties of different samples across multiple length scales over time.

Metadata management plays an important role in correlative characterization: in particular, the combination of information and the data exchange can be facilitated if the FAIR (Findable, Accessible, Interoperable, Reusable) guiding principles are followed. In addition, effective metadata management enhances discoverability, accessibility, and reproducibility of scientific research data.

For this reason, we founded the Metadata Working Group (WG), including members of the three Helmholtz centers involved in the Joint Lab “Model and Data driven Materials Characterization” (JL MDMC) and of the Nanoscience Foundries and Fine Analysis Europe Pilot (NEP). The activities of the group are focused on the development of communal descriptions and interoperable solutions, driven by the communication with scientists to collect information and requirements.
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This talk provides an overview of the current results achieved by the Metadata WG, the ongoing collaborations with other projects, and the planned future steps.