Towards an integrated open-access data and software service infrastructure for Earth science

2021 International Symposium on Deep Earth Exploration and Practices DEEP-2021, 1 - 6 november 2021, Virtual Meeting & International EverywhereEarth science comprises a series of interconnected disciplines that target the nature, structure andevolution of the Earth with an aim to characterize the processes across scales: from global tomicroscopic scale, and from geological to annual and/or seasonal time scales. Earth science is a data-driven and model-driven fi eld, as it combines direct measurements at or near the surface and indirectobservations of the Earth¿s interior. In that sense, seismic data are the most valuable instruments toimage the different components of the lithosphere, and the implementation of geoscientifi c softwareallows generating models that improve our understanding of natural processes. The development andimplementation of innovative geoscientifi c software together with access to quality data will providevaluable research outputs to model complex natural processes and generate improved forecasts. Theeffective integration of both data and software in Earth science is key to produce high-resolution digitalmodels of certain aspects of the Earth system, the so-called digital twins. A digital twin aims atgenerating the necessary knowledge to: i) understand global change, ii) ease a more resource-effi cient,sustainable and competitive economy, and iii) take action to achieve the Sustainable Development Goals(https://www.un.org/sustainabledevelopment/sustainable-development-goals/, last access July 2021).Despite its vital importance for understanding the subsurface, seismic data are logistically complex andexpensive to acquire, process and interpret, and their geographical coverage is limited. Their acquisitionand management often result from multi-institutional collaboration and require the investment ofsignifi cant human and material resources. Similarly, research software requires codifi cation,implementation, constant update and often high-performance computing to effi ciently process largevolumes of data. Therefore, data and software need to be preserved for its reuse by future generationsof geoscientists and to accomplish the mandates of open access