This repository is part of the [B-Cubed Hackathon](https://b-cubed.eu/b-cubed-hackathon): Hacking Biodiversity Data Cubes for Policy, taking place in Brussels, Belgium (and online) on April 2nd-5th 2024. The project is part of a doctoral thesis entitled “Improving Semantic Interoperability of observational research through data FAIRification”. As part of our work for eLTER PLUS (GA.Nr. 871128) we aim to represent eLTER Standard Observations (SOs) in a machine interpretable way. Based on eLTER’s whole system approach, the WAILS concept, the SOs will include the minimum set of variables as well as the associated method protocols that can characterize adequately the state and future trends of the Earth systems. We intend to semantically enhance the variable descriptions in EnvThes used in the site and dataset registry DEIMS-SDR with the I-ADOPT Framework endorsed by RDA. I-ADOPT enables semantically precise and machine-readable descriptions of variables decomposing them into atomic components each described with concepts from semantic artefacts. It acts as a semantic broker between different variable representations enabling interoperability across annotated datasets. To capture the methods and protocols for applicable EUNIS habitat types including the automatic SO classification of sites based on their observation capabilities we also develop a supporting observation ontology. For the B-Cubed project we focus on biodiversity variables includin vegetation composition, expressed as coverage in percentage, occurrence of birds, and weather data observed and measured on the LTER Site “Zöbelboden”, Austria (https://deims.org/8eda49e9-1f4e-4f3e-b58e-e0bb25dc32a6). In order to prevent our approach from functioning solely tailored to eLTER requirements, we want to design our approach building on top of existing specifications as the Species occurrence cube and seek for active collaboration in their further development to contribute to FAIR, semantically rich representations. With our involvement in GO FAIR Foundation we will help in the further dissemination of these FAIR data practices published as nanopublications via the FAIR Connect search engine (https://fairconnect.pro/) (available in 2024).