Preprints
https://doi.org/10.5194/egusphere-2025-4832
https://doi.org/10.5194/egusphere-2025-4832
07 Oct 2025
 | 07 Oct 2025
Status: this preprint is open for discussion and under review for Geoscientific Instrumentation, Methods and Data Systems (GI).

A database-driven research data framework for integrating and processing high-dimensional geoscientific data

Dennis Handy, W. Marijn Van der Meij, Mirijam Zickel, and Tony Reimann

Abstract. This paper introduces a modular research data framework designed for geoscientific research across disciplinary boundaries. It is specifically designed to support small research projects, that need to adhere to strict data management requirements from funding bodies, but often lack the financial and human resources to do so. The framework supports the transformation of raw research data into scientific knowledge. It addresses critical challenges, such as the rapid increase in the volume, variety and complexity of geoscientific datasets, data heterogeneity, spatial complexity, and the need to comply to the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. The approach optimises the research management process by enhancing scalability and enabling interdisciplinary integration. It is adaptable to evolving research requirements and it supports various data types and methodological approaches, such as machine learning and deep learning, that have high requirements on the used data and their formats. A case study in Western Romania presents the data framework's application in an interdisciplinary geoarchaeological research project by processing and storing heterogeneous datasets, demonstrating its potential to support geoscientific research data management by reducing data management efforts, improving replicability, findability and reproducibility and streamlining the integration of high-dimensional data.

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Dennis Handy, W. Marijn Van der Meij, Mirijam Zickel, and Tony Reimann

Status: open (until 12 Nov 2025)

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Dennis Handy, W. Marijn Van der Meij, Mirijam Zickel, and Tony Reimann
Dennis Handy, W. Marijn Van der Meij, Mirijam Zickel, and Tony Reimann

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Short summary
Geoscientific projects often struggle to manage complex data effectively, resulting in valuable information being lost due to poor findability and accessibility. To address this, we present a comprehensive research data framework for storing and processing data throughout a project, from fieldwork to data analysis. This ensures that datasets are clearly defined, reproducible and adhere to the FAIR principles (findability, accessibility, interoperability and reusability).
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