Combining Machine Learning tools and Terminology Services to support FAIR Data Management in ESS

Integrating diverse data in Earth System Sciences (ESS) is hindered by semantic heterogeneity, as different disciplines use inconsistent terminologies. The BITS project addresses this challenge by providing a dedicated Terminology Service (TS) with over 40 vocabularies, maintained by the TIB for long-term use. A practical use case at the Senckenberg Institute combines AI tools, edge computing, and the TS to automatically annotate and process digitized natural science collections efficiently. This workflow improves data findability and interoperability, particularly for multilingual and handwritten records, while ensuring data security through near-data processing. The Lightning Talk highlights potential risks of irresponsible AI use, despite its clear benefits when integrated with other services.