The Knowledge Laboratory, in short k.LAB, is a software stack that embraces the FAIR principles: findable, accessible, interoperable and reusable. Its objective is to support linked knowledge across the borders of the domains of single modelers and scientists. k.LAB’s fascinating novelty is the use of semantics to create a natural language to describe the models and the qualities that want to be observed. Modelers can develop their models and publish them to the network. Publishing makes them findable and accessible within the network. Since everything in the network is observable, when running a model, k.LAB looks for the best knowledge unit able to resolve the particular request. Interoperability is build and reusability is a natural consequence. The k.LAB software stack is free and open source and relies on various projects of the Osgeo community as Geoserver, Openlayers and the Hortonmachine. It has been in development for almost 2 two decades and got a particular visibility boost in 2021, when the Statistics Division of the UN Department of Economic and Social Affairs and the UN Environment Program, in collaboration with the Artificial Intelligence for Environment & Sustainability at the Basque Centre for Climate Change, launched the Artificial Intelligence powered application for rapid natural capital accounting: the ARIES for SEEA Explorer. Lately a python client that allows interaction with k.LAB has been released. This opens up to new ways to observe the world from within common GIS tools as for example QGIS. In this talk, an overview of the state of the art of the project will be given.