Would you like to contribute to open science? Do you like a bit of coding? Are you maybe interested in empirical studies?
MAP-VERSE (MAP Usability – Validated Empirical Research by Systematic Evaluation) metadata repository (https://map-verse.github.io/) was established by an international research initiative (https://map-verse.github.io/Repository/page/about/) that believes in open science. This platform provides researchers with structured access to best-practice datasets, specifically from eye tracking, neuroimaging (EEG, fMRI), and human sensing (EDA, cardiovascular activity, skin temperature) collected across various geospatial tasks in-lab, online, in virtual environments, or in real-world scenarios (see Keskin et al. 2025, https://doi.org/10.5194/agile-giss-6-30-2025).
The MSc thesis will focus on systematizing the data discovery functionality of MAP-VERSE by developing
- Strategies for expanding dataset diversity (e.g. including studies using thematic maps, dashboards, mobile maps, etc.), and
- Tools for relevant data collection such as API querying and, when necessary, web crawling on large open-access research data repositories (e.g., Harvard Dataverse, Zenodo, arXiv).
The student is expected to develop a metadata search and dataset validation tool to ensure metadata consistency and accuracy before inclusion in MAP-VERSE.
This research is planned to be co-supervised by Assoc. Prof. Dr. Vassilios Krassanakis from the University of West Attica and (when necessary) in collaboration with Tong Qin and Bing He from the MAP-VERSE initiative.
For more information:
Contact: Dr. Merve Keskin, merve.keskin@plus.ac.at
Start: As soon as possible
Prerequisites/qualification: Python and HTML basics
Keywords: knowledge discovery, development, metadata repository, open science
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