Speaker
Description
Structured and machine-readable experiment metadata enable various analysis and visualizations of the stored data and metadata, which may not be easily achievable with unstructured metadata such as free texts. On top of that, structured metadata increases the findability and re-usability of said metadata (and the data to which the metadata is attached) for other purposes following the spirits of the FAIR data principles. Adamant is a browser-based research data management (RDM) tool, specifically developed to systematically collect experiment metadata that is both machine- and human-readable. It makes use of the JavaScript Object Notation (JSON) schema, where valid schemas can be rendered as an interactive and user-friendly web form. Researchers may create a JSON schema that describes their experiments from scratch using the Adamant user interface or provide an existing schema. At its current state, Adamant is mainly used to compile structured experiment metadata in conjunction with a generic electronic lab notebook. In this talk, we will present the current features of Adamant and production-ready RDM workflows involving Adamant and other RDM tools, as well as concepts for future development of Adamant. These concepts include an ontology and knowledge graph integration for a guided acquisition of structured metadata, and visualization of graph data for better browsing and navigation through the stored metadata. Overall, the ultimate goal of Adamant is to make FAIR RDM activities as easy as possible for researchers.
