Management of Geological Data: Local and Cloud-Based

In the realm of digital geosciences, managing geological data is essential for achieving successful project outcomes. Geological data, known for its complexity and volume, presents significant challenges in organization and control. This management extends beyond the data itself to include careful oversight of its metadata. Moreover, documenting the steps involved in data acquisition and processing is crucial for ensuring data quality. The interactive component is equally significant, as it introduces a dynamic dimension to data control, as highlighted by the WIIP Approach¹. This comprehensive strategy not only enhances data integrity but also fosters effective collaboration and informed decision-making.

Importance of Geological Data Management

Effective data management is crucial for ensuring accuracy, accessibility, and usability. As geological datasets grow, the need for robust systems to handle this complexity also increases. Well-structured metadata is equally essential as it provides context and comprehension of the data, facilitating better analysis and decision-making. Investing in efficient data management strategies streamlines workflows and promotes collaboration among geoscientists. By prioritizing the organization of both data and metadata, we can fully leverage the potential of geological data in our research and applications.

Benefits of Web-Based Systems

Web-based geological data management offers significant advantages. It enables users to access essential information from virtually anywhere with an internet connection. This convenience fosters collaboration among teams, enhancing productivity and communication. Such systems are adept at managing large datasets without the need for extensive physical storage solutions. Many platforms prioritize user experience, featuring intuitive interfaces and robust tools for visualizing and analyzing data. This approach not only streamlines the management of geological data but also enhances efficiency and effectiveness in research and decision-making processes.

Here are some excellent examples of public web-based geological data management:

• USGS Data Management ²
• Geoscience Australia Portal ³
• Data - British Geological Survey ⁴
• National Geological Database of the Saudi Geological Survey ⁵

The registry of research data repositories (Figure 1) ^{6 7} and DataCite Commons ⁸ contain numerous cloud-based data repositories that include geological data alongside other data.

Figure 1: Visualizing different types of data repositories across various disciplines stored in the registry of research data repositories.

Local vs. Cloud Repositories

For researchers wishing to store their data in the cloud and associate it with their articles, Open Science frameworks and Zenodo are useful. Both provide a DOI number for the dataset and can store from 5 GB to 50 GB of data, respectively. However, deploying a local data repository offers greater control over data, security, and performance. Storing data on-premises keeps sensitive information within your infrastructure, reducing the risk of breaches. Local repositories facilitate faster access and offer customization to meet specific needs. With offline access, you can retrieve critical information without internet connectivity, making it a reliable choice for organizations. Ultimately, a local repository enables confident and adaptable data management. Here are several examples of open-source data repository platforms that can be deployed locally:

• InvenioRDM ⁹
• GKHub ¹⁰
• Harvard Dataverse ¹¹
• OneGeology ¹²

Summary

Selecting the right data management strategy—be it local or cloud-based—is vital for maximizing the effectiveness of geological data. By comprehensively understanding the strengths and challenges associated with each approach, organizations can strategically position themselves to harness geological data for research and practical applications. As technology continues to evolve, remaining informed about emerging trends will further refine data management practices in the geosciences, enabling more innovative and effective use of data.

Cite this post

If you found this post helpful, please consider citing it:

Alqubalee, A. (2025, May 27). Management of Geological Data: Local and Cloud-Based. https://qubalee.com/posts/2025/05/data-repository-platforms/

Refereces

1. Alqubalee, A. (2025, April 8). WIIP: An Approach for Leveraging Geological Data Heterogeneity through Customization of Open-Source Software. https://qubalee.com/posts/2025/04/wiip/ ↩︎

2. U.S. Geological Survey. (2025). Data management. Retrieved May 27, 2025, from https://www.usgs.gov/data-management ↩︎

3. Geoscience Australia. (2025). Geoscience Australia Portal. Retrieved May 27, 2025, from https://portal.ga.gov.au/ ↩︎

4. British Geological Survey. (2025). Data - British Geological Survey. Retrieved May 27, 2025, from https://www.bgs.ac.uk/geological-data/ ↩︎

5. Saudi Geological Survey. (2025). National geological database portal. Retrieved May 27, 2025, from https://ngdp.sgs.gov.sa/ngp/ ↩︎

6. re3data.org. (2025). Registry of research data repositories. Retrieved May 27, 2025, from https://www.re3data.org ↩︎

7. re3data.org. (2025). Browse by subject. Retrieved May 27, 2025, from https://www.re3data.org/browse/by-subject/ ↩︎

8. DataCite. (2025). DataCite commons. Retrieved May 27, 2025, from https://commons.datacite.org/ ↩︎

9. Inveniosoftware. (2025). Invenio app RDM: Turn-key research data management platform. Retrieved May 27, 2025, from https://github.com/inveniosoftware/invenio-app-rdm ↩︎

10. geo-knowledge-hub. (2025). GEO Knowledge Hub Digital Library. Retrieved May 27, 2025, from https://github.com/geo-knowledge-hub/geo-knowledge-hub ↩︎

11. Dataverse Project. (2025). Installation guide — Dataverse.org. Retrieved May 27, 2025, from https://guides.dataverse.org/en/latest/installation/index.html ↩︎

12. OneGeology. (2025). OneGeology Portal. Retrieved May 27, 2025, from https://github.com/OneGeology/OneGeology_Portal ↩︎