Infrastructures of ‘Integrative and Transformative Research on Earth & Societies’

he Integrative and Transformative Research on Earth & Societies WG9 aims to be an international knowledge exchange platform supporting the identification of infrastructure challenges and the development of practical infrastructure solutions for transdisciplinary data and knowledge synthesis and integration. The WG9 welcomes members interested in this subject matter, infrastructure providers and toolmakers, researchers contributing to knowledge production at the Earth & Societies interface.

The Earth & Societies transdisciplinary research domain is both high-stakes and heterogeneous as it addresses global challenges such as climate change or biodiversity loss and impacts on socio-economic systems using diverse data and tools from a wide range of sources and providers.

To tackle such complex challenges, inter- and transdisciplinary interoperable digital infrastructures are urgently needed to support the efficient production and stakeholder-tailored effective utilization of high-quality (scientific) data and knowledge. Infrastructure must be able to manage and exchange heterogeneous data from different fields, including environmental science, social studies, and economics.

Existing approaches, such as dimensional modelling (e.g., the data cube), have been used, but the persistent challenges in reuse of data across sources demonstrates a continued need for FAIR data principles implementation. Inspired by traditional data repositories with high data curation standards (e.g., PANGAEA), FAIR-supporting resources such as the Knowledge Loom advance the state of the art by providing access to granular, reproducible, richly described, and machine-actionable (scientific) knowledge to enable the efficient, machine-assisted production of new, or the tailoring of existing, knowledge, for instance through knowledge synthesis and integration. Powered by a multitude of standard technologies, ranging from databases to vocabularies and protocols (e.g., I-ADOPT, Schema.org), such resources increasingly guarantee FAIR data (in addition to FAIR metadata) to enable advanced transdisciplinary data and knowledge integration and processing.