Academic Journal
A database-driven research data framework for integrating and processing high-dimensional geoscientific data.
| Τίτλος: | A database-driven research data framework for integrating and processing high-dimensional geoscientific data. |
|---|---|
| Συγγραφείς: | Handy, Dennis, van der Meij, W. Marijn, Zickel, Mirijam, Reimann, Tony |
| Πηγή: | Geoscientific Instrumentation, Methods & Data Systems (GI); 2026, Vol. 15 Issue 1, p165-181, 17p |
| Θεματικοί όροι: | Data management, Geospatial data, Electronic data processing, Online data processing, Multidimensional databases, Relational databases, Data integration |
| Γεωγραφικοί όροι: | Romania |
| Περίληψη: | This paper introduces a modular research data framework designed for geoscientific research across disciplinary boundaries. It is specifically designed to support small research projects, providing a bottom-up solution that empowers individual teams 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 with the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. The framework uses a dual-component architecture. First, an Online Transaction Processing (OLTP) system features a user interface and a persistent relational database, ensuring accurate and consistent data storage when capturing and managing diverse geoscientific research data. Complementing this, an orchestration layer manages automated data pipelines to process the stored data and generate dynamic in-memory Online Analytical Processing (OLAP) databases that allow flexible, high-performance analysis. It is adaptable to evolving research requirements and supports various data types and methodological approaches, such as machine learning and deep learning, that place high demands on the data and their formats. A case study in Western Romania demonstrates the application of the data framework in an interdisciplinary geoarchaeological research project by processing and storing heterogeneous datasets, thereby reducing data management efforts, improving findability, replicability, and reproducibility, and streamlining the integration of high-dimensional data for small, interdisciplinary teams. [ABSTRACT FROM AUTHOR] |
| Copyright of Geoscientific Instrumentation, Methods & Data Systems (GI) is the property of Copernicus Gesellschaft mbH and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
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| Items | – Name: Title Label: Title Group: Ti Data: A database-driven research data framework for integrating and processing high-dimensional geoscientific data. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Handy%2C+Dennis%22">Handy, Dennis</searchLink><br /><searchLink fieldCode="AR" term="%22van+der+Meij%2C+W%2E+Marijn%22">van der Meij, W. Marijn</searchLink><br /><searchLink fieldCode="AR" term="%22Zickel%2C+Mirijam%22">Zickel, Mirijam</searchLink><br /><searchLink fieldCode="AR" term="%22Reimann%2C+Tony%22">Reimann, Tony</searchLink> – Name: TitleSource Label: Source Group: Src Data: Geoscientific Instrumentation, Methods & Data Systems (GI); 2026, Vol. 15 Issue 1, p165-181, 17p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Data+management%22">Data management</searchLink><br /><searchLink fieldCode="DE" term="%22Geospatial+data%22">Geospatial data</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+data+processing%22">Electronic data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Online+data+processing%22">Online data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Multidimensional+databases%22">Multidimensional databases</searchLink><br /><searchLink fieldCode="DE" term="%22Relational+databases%22">Relational databases</searchLink><br /><searchLink fieldCode="DE" term="%22Data+integration%22">Data integration</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Romania%22">Romania</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This paper introduces a modular research data framework designed for geoscientific research across disciplinary boundaries. It is specifically designed to support small research projects, providing a bottom-up solution that empowers individual teams 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 with the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. The framework uses a dual-component architecture. First, an Online Transaction Processing (OLTP) system features a user interface and a persistent relational database, ensuring accurate and consistent data storage when capturing and managing diverse geoscientific research data. Complementing this, an orchestration layer manages automated data pipelines to process the stored data and generate dynamic in-memory Online Analytical Processing (OLAP) databases that allow flexible, high-performance analysis. It is adaptable to evolving research requirements and supports various data types and methodological approaches, such as machine learning and deep learning, that place high demands on the data and their formats. A case study in Western Romania demonstrates the application of the data framework in an interdisciplinary geoarchaeological research project by processing and storing heterogeneous datasets, thereby reducing data management efforts, improving findability, replicability, and reproducibility, and streamlining the integration of high-dimensional data for small, interdisciplinary teams. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Geoscientific Instrumentation, Methods & Data Systems (GI) is the property of Copernicus Gesellschaft mbH and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.5194/gi-15-165-2026 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 165 Subjects: – SubjectFull: Romania Type: general – SubjectFull: Data management Type: general – SubjectFull: Geospatial data Type: general – SubjectFull: Electronic data processing Type: general – SubjectFull: Online data processing Type: general – SubjectFull: Multidimensional databases Type: general – SubjectFull: Relational databases Type: general – SubjectFull: Data integration Type: general Titles: – TitleFull: A database-driven research data framework for integrating and processing high-dimensional geoscientific data. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Handy, Dennis – PersonEntity: Name: NameFull: van der Meij, W. Marijn – PersonEntity: Name: NameFull: Zickel, Mirijam – PersonEntity: Name: NameFull: Reimann, Tony IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: 2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 21930856 Numbering: – Type: volume Value: 15 – Type: issue Value: 1 Titles: – TitleFull: Geoscientific Instrumentation, Methods & Data Systems (GI) Type: main |
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