Consistent large sample hydrological datasets have significantly shaped and advanced hydrological research and teaching in recent years. These so-called CAMELS datasets combine landscape features like geology and land use with hydro-meteorological time series such as water levels and precipitation in hundreds of different river systems (catchments). CAMELS datasets have become the basis for countless hydrological analyses and are, e.g., one important key to infer the impacts of climate change on the hydrological cycle or the fundamental prerequisite to apply data-driven models in hydrology. Although Germany has one of the most extensive hydro- meteorological measurement networks in the world, there is yet no consistent hydrological large sample dataset available. A major reason for this lack are Germany's federal structures, in which hydrology, including the monitoring networks, are largely organized at the level of federal states. Data availability, quality, resolution and metadata does hence vary greatly between states, which makes analyzes across state borders challenging. This split responsibility of the federal system has led to the fact that Hydrology in Germany is frequently perceived as a regional, partly fragmented discipline, which weakens its position in research and politics both within and outside of Germany. The importance of a uniform and consistent hydrological data set for entire Germany can therefore not be emphasized strongly enough. Numerous discussions in recent months with various researchers and practice partners have further underpinned this need. A consistent, hydrological dataset for Germany would therefore significantly strengthen hydrological research and in addition, offers the possibility to uniform hydrological teaching through an easy transfer of methods and models. Both the development of common teaching standards and the strengthening of hydrology in Germany are core objectives of the "ViTamins" strategy concept.