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This repository provides researchers with structured access to a wealth of metadata, specifically from eye tracking, neuroimaging (EEG, fMRI), and human sensing (EDA, cardiovascular activity, skin temperature) datasets collected during geospatial tasks in-lab, virtual environment or real-world scenarios.

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MAP-VERSE: MAP Usability - Validated Empirical Research by Systematic Evaluation 🚀

🌍 Website: MAP-VERSE Repository

📌 Introduction

Welcome to MAP-VERSE! We are building a unique data discovery repository dedicated to advancing empirical research in map usability and spatial cognition.

Our goal is to foster open science and collaboration by creating a centralized, queryable repository for metadata from open-access map usability studies. This collection includes publicly shared datasets recorded during geospatial tasks, such as map reading and navigation.

🌟 Our Mission

By developing this repository, we strive to:

Encourage standardized reporting of user studies (minimum reporting standards)
Showcase best practices in map reading studies
Increase generalizability and reproducibility of findings

📊 What’s Inside?

This repository serves as a queryable metadata repository for open-access datasets related to:

🔹 Eye Tracking 👀
🔹 Neuroimaging (EEG, fMRI) 🧠
🔹 Human Sensing (EDA, cardiovascular activity, skin temperature) ❤️‍🔥

All datasets are recorded during geospatial tasks (a.k.a. map reading user studies), and the repository links to open datasets shared elsewhere (e.g., Zenodo, Harvard Dataverse).

📂 Explore & Contribute

We welcome contributions! If you're interested in map usability research, spatial cognition, or human sensing studies, feel free to explore and collaborate.

📩 For inquiries, contact us or submit an issue on GitHub.
🚀 Let's advance open science together!

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This repository provides researchers with structured access to a wealth of metadata, specifically from eye tracking, neuroimaging (EEG, fMRI), and human sensing (EDA, cardiovascular activity, skin temperature) datasets collected during geospatial tasks in-lab, virtual environment or real-world scenarios.

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