The open geospatial consortium (OGC) provides standards to store and transport geospatial data. A new family of standards around the OGC API seeks to replace the well established standard WFS (Web feature service), WMS (Web map service) or WCS (Web coverage service) for transporting geospatial data. The old standards were designed nearly 20 years ago. They are based on XML and define a now outdated interface to interact with geospatial data.

At the same time new kinds of geospatial data evolved. The new OGC API standard defines a shared, extensible REST interface based on JSON endpoints for managing geospatial data. The OGC API unifies the various W*S and extends them with support for new kinds of geospatial data. The standard consists of various parts and pieces that can be combined as required by specific usecases.

As part of this talk I want to demonstrate how to use various parts of the OGC API to share geological subsurface models to different shareholders for visualisation and modelling purposes. Finally I want to outline various limitations of the current set of OGC API standards for describing and transporting geological subsurface models.

3D Infrastructure is a key area of work at the LBEG (State Authority for Mining, Energy and Geology, Lower Saxony), encompassing the technical support required for 3D modeling, including software provision, data management, tool development, and visualization systems. It supports the creation, processing, and publication of three dimensional geodata.

The various software needed for the 3D modelling are procured, internally distributed and carefully maintained. In-house developments supplement standard software by adding functionalities tailored to LBEG’s use cases—such as generating geological cross sections, well generator for borehole data, and data conversions. A 3D printer is available to create realistic and demonstrable 3D models which could then be displayed at events and exhibitions.

The 3D models created by the (hydro-)geologists are made available to both professionals and the general public through the web-based NIBIS3D Viewer. This platform hosts geological and hydrogeological models at state, regional, and local levels, accompanied by metadata, reports, and other relevant documentation. Additionally, the potential of virtual and augmented reality is actively explored and utilized wherever applicable.

Numerous ongoing projects with external partners enable knowledge exchange and cooperation. The GEVISGEO3D project, for instance, extends LBEG‘s infrastructure by hosting two new web instances for the states of Schleswig-Holstein and Hamburg.

Regular interaction with geological surveys of other federal states, through working groups and discussion forums, ensures alignment with current developments in the field of 3D geoscience.

Display of fossils in museum exhibitions bears a great value in teaching the public about various aspects of earth history. However, fossils integrated in exhibitions face the risk of being damaged, especially through frequent handling, as for example in travelling exhibitions. In addition, when on display for years, fossils are not easily accessible for research purposes.

The recently conceptualised and implemented travelling exhibition Molassic Park deals with the fossil record from the Miocene Upper Freshwater Molasse of southern Germany and its ecological interpretations. The included mammal remains are in most cases unique with two type specimens and are very fragile. In order to avoid damage and research-restriction effects, the curator decided on replacement by 3D printed models.

Ca. 30 fossils were surface-scanned with blue-light technology using the precision 3D hand scanner Space Spider of Artec 3D. Virtual 3D models were calculated in Artec Studio 17 and 3D printed with an FDM printer. In preparation for colouration with acrylic paint, visible extruded material steps were covered with beige acrylic paint thickened with aerosil.

We found that printed 3D models are a much more gentle alternative to the objects than making traditional moulds and casts, and visitors receive a realistic impression of the fossil evidence. Hence, printed 3D models are a suitable replacement of real fossils in travelling exhibitions.

Throughout the last years, several physically based models have been introduced that allow to estimate the seismic signatures of environmental processes. Hence, in an inverse way, we can turn seismometers into efficient probes of earth surface dynamics that are otherwise hard to quantify, such as snow avalanches, debris flows, river sediment transport, rain intensity and large scale atmospheric pressure systems. However, most of these models lack a profound geomorphic representation or operate under very simplified assumptions. In addition, novel methods of seismic noise cross correlation are increasingly utilised to probe the water fluxes as well as geomorphically driven material property changes within the shallow to deep subsurface. These techniques also operate under sometimes very simplified representations of the Critical Zone’s architecture, water flow paths, and hydrological or geomorphic concepts.

Here, I survey geomorphic processes and landscape dynamics that are already represented by environmental seismic models and summarise, which unique insights they allow beyond what classic survey techniques can deliver. I also point out important processes that hitherto lack proper representation. I argue for an alliance across disciplines to close these gaps in knowledge, skill and application, to further boost our scientific capabilities to understand landscape reaction to ongoing change.

The DroneSOM project, co-funded by EIT RawMaterials, aims to develop an integrated approach to geophysical data acquisition and interpretation for mineral exploration. Drones are used to collect gravity and electromagnetic data, that is subsequently analyzed using specialized software. The three-year project is coordinated by the Geological Survey of Finland (GTK) and carried out in partnership with RADAI Oy, the Technical University of Denmark (DTU), and Beak Consultants GmbH. It comprises six work packages that include field measurements at various sites in Finland, Germany, and Sweden, as well as data integration and interpretation.

This contribution focuses on the application of Self-Organizing Maps (SOM) for the analysis of three-dimensional geophysical voxel data derived from 3D inversion of the surface-based measurements. The methodology involves preprocessing and normalization of the input data, SOM-based clustering, and subsequent evaluation and validation using sensitivity analyses, boxplots to assess data distribution within the resulting clusters, and evaluate spatial correlation with existing geological knowledge.

Results from the application of this method to a test site in Finland are presented. The analysis demonstrates how 3D-inverted geophysical data can be structured and visualized using 3D SOM to reveal geological patterns. The combination of 3D data processing and unsupervised machine learning enables the interpretation of subsurface structures and opens new perspectives for geoscientific data analysis.

Technological and computational advancements have led to a significant increase in the volume and complexity of geoscientific research data. This provides new opportunities for data-driven methods, but also poses new challenges for research data management. It is not only the increasing demands of the data that make data management more difficult; recent techniques, particularly machine learning approaches, require re-evaluating data handling practices, as these not only place higher storage demands and processing power, but also involve more extensive data processing, resulting in more intricate data workflows. To address these challenges, we present a modular pipeline framework designed to automate the key stages of the research data lifecycle (acquisition, transformation, processing and storage) of heterogeneous geomorphological and geochronological research data across disciplinary boundaries. This approach not only focuses on data storage but also provides an end-to-end data pipeline that bridges the gap between fieldwork, laboratory analysis, and scientific evaluation. By automating data workflows, the pipeline enables seamless flow of heterogeneous data from acquisition into a relational database and its subsequent transfer to an analytical database optimised for multidimensional queries. This dual-database architecture enables scalable storage, reproducible workflows, and the automation of complex analyses, including statistical and machine learning modelling. A case study in Western Romania illustrates the application of our approach in an interdisciplinary geoarchaeological project, focusing on integrating diverse, high-dimensional sedimentological datasets. Our work shows that research data pipelines can be essential in promoting reproducibility and replication in geoscience.