The IG 'Geology & Geophysics' (I3G) within the framework of NFDI4Earth addresses the growing digital requirements of the individual disciplines and sub-disciplines within geological and geophysical sciences. The I3G focuses on the data infrastructure needs of scientists and engineers who are open to share their data and software developments across disciplinary boundaries.
1. Data Queries focusses on improving metadata schemes on information systems and archives, as well as fuzzy search algorithms, spatial queries and queries referring to time-depth-litho relationships. This topic will tackle the consequent implementation of DOIs, ORCIDs and other national or international persistent identifiers in repositories. It has strong links to INSPIRE, OGC-CWS, OWL, RDF and Open Science initiatives.
2. Data Services will tackle standardization issues for interoperability, develop algorithms for data visualization, selection, including innovative concepts such as 3D subsurface data services, ontologies, artificial intelligence and machine learning.
3. Data Formats and Vocabularies covers all efforts in establishing, improving and promoting Open Data formats for geoscientific data. For example, the BoreholeML markup language developed by the Geological Surveys in Germany is successfully used for the exchange of borehole data. However, other exchange formats also exist (e. g. GeoSciML, SEP-3 etc.) and conversion tools need to be developed. Other examples are vocabularies (e.g. LithoLex of the German Geological Survey BGR). Connecting such vocabularies to information systems or databases would significantly increase their usefulness.
4. Analytics will develop data analytics frameworks for data curation and processing. Envisioned use cases are for instance geostatistics, parallel simulations or the introduction of knowledge discovery and machine learning or artificial intelligence approaches for optimized or (semi-)automated seismic data interpretation and attribute analysis. Another field of interest is the development of artificial intelligence algorithms for the interpretation of logs and time series.
5. Analogue to Digital focuses on imaging methods to rock and mineral samples as well as outcrops and their inclusion in digital collections (e.g. IGSN, OutcropWizard). Machine learning algorithms could be applied to scanned logs and seismic recordings in order to decipher analogue data resources. The objective is to preserve data and knowledge about the subsurface.
6. Quality covers all measures to assess or improve the usability, certainty, precision, and unambiguousness of data. Geoscientists often face the problem that complex data products like maps or 3D models do not come with a comprehensive documentation of all raw data included and processing steps applied and neither with a documentation of model uncertainty. Standardized workflows, versioning and documentation templates are envisaged to help to assess the usability and optimization potential of complex data products. Further measures establish common criteria to evaluate the qualities of geoscientific data. In the future, scientific data products will go through a peer-review process like today's scientific papers.
7. Multi-purpose 3D information systems will combine all of the above-mentioned tasks in the effort to develop a best practice example of an online information system for parameterized 3D geological models for spatial subsurface planning of economically and socially relevant geoscientific topics based on existing platforms (e.g. GeotIS, GeORG, WSM, etc.).
Illustrating material & further links
N4E-Konferenz_Block-III_SIG-4_G&G_Earth_Agemar (slides from 1st N4E conference Nov-2020)
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