Introduction 

The Geo Data Prize recognizes and rewards outstanding datasets that make significant contributions to Geosciences within our faculty. This initiative tries to highlight high-quality, openly accessible, and impactful datasets, encouraging adherence to FAIR (Findable, Accessible, Interoperable, and Reusable) principles. By promoting these best practices, the prize aims to advance open science and foster collaboration among researchers, institutions, and the broader community. The FAIR principles, central to the prize’s criteria, ensure that data is efficiently shared, reused, and integrated across projects and disciplines, thereby amplifying the impact of the faculty’s research efforts. The link to the submission form is at the bottom of the page

Objectives 

The Geo Data Prize aims to incentivize researchers and teams to apply the principles of FAIR to their datasets, promoting transparency and accessibility in research. By encouraging the FAIRification and open publication of research data, the prize supports scientific progress and fosters interdisciplinary collaboration. Through accessible and well-documented datasets, the prize aims to amplify the impact of research, creating wider opportunities for innovation, discovery, and application across various fields. 

Eligibility Criteria 

The following criteria will guide the evaluation of datasets nominated for the prize. Each criterion focuses on important aspects of data management, accessibility, and quality to ensure that nominated datasets meet high standards for research and community impact. 

1. Openness of Data 

The dataset should be accessible to others through public repositories like Yoda or Zenodo, increasing the transparency and accessibility of research. If access is restricted, the reason should be valid, such as privacy protection or ethical guidelines (e.g., restricted due to personal data protection). 

2. Clear Documentation & Metadata 

The dataset should include clear, understandable documentation detailing the data’s collection and processing, such as a README file explaining the methodology used. 

Sufficient metadata should accompany the dataset, ensuring others can interpret and utilize the data easily. This includes defining variables and parameters within a metadata file. 

3. Privacy & Ethics 

When applicable, personal data should be safeguarded, and ethical guidelines adhered to, even if the dataset cannot be fully open. This might include anonymization techniques or the removal of identifiers to protect individuals. 

4. Data Quality & Impact 

The dataset should demonstrate accuracy, completeness, and consistency in its structure and format. Additionally, it should provide value to researchers or the broader community, as evidenced by citations or demonstrated societal impact. 

5. Interoperability & Ease of Use 

Datasets should use accessible formats and compatible tools that are widely recognized. For example, data provided in open formats or through a web portal with interactive tools can facilitate use and analysis across various platforms. 

Submission

Please take a moment to submit any dataset(s) you believe align with the criteria above at any level: