In Earth sciences, there is an increasing demand for long-term observation data related to the hydrosphere, pedosphere, biosphere, and lower atmosphere across multiple spatial and temporal scales. In parallel, standardized methods to manage, find, access, provide interoperability, and reuse these data (FAIR) have been developed. Numerous centralized or distributed data infrastructures (thematic silos) exist, often with similar architectures but with a diversity of access methods, vocabularies for description, and frameworks for handling data and data flows.

DataHub is an initiative of the German Helmholtz Research Field Earth and Environment (E&U) with the aim of developing and operating a scalable, FAIR, and distributed digital research infrastructure to link research data from all compartments of the Earth system. By coordinating vocabularies, persistent identifiers (PIDs), and a common nomenclature across centres, DataHub ensures interoperability with national and international systems. The goal is the transition from isolated silos to interdisciplinary infrastructures. This is achieved by creating a community-driven digital research data ecosystem characterized by collaborative software development; the provision and use of products under a common open-source license model; a harmonized architecture of data management systems; connectivity of data via standardized interfaces (e.g., OGC STA, CSW, WMS); and, most importantly, the harmonization of data descriptions and data flows. As a first step, existing data infrastructures are integrated into the jointly developed DataHub environment.

TERENO (TERrestrial ENvironmental Observatories) is used as a reference implementation for the integration of an existing distributed data infrastructure into DataHub. TERENO is an interdisciplinary, long-term research program involving five centres of the German Helmholtz Association (FZJ, GFZ, UFZ, KIT, DLR). Running since 2008, it comprises an Earth observation network across Germany and provides long-term environmental data at multiple spatial and temporal scales to study the long-term impacts of land-use and climate change. It provides more than 3.3 billion observations from over 900 sites.

During the last decade, several drawbacks have been identified in the operation of TERENO, such as inhomogeneities in metadata describing measurement instrumentation and the observed data themselves. Moreover, different data quality routines and assessment schemes are applied.