Skip to main content

Utility tools for handling the guidaeta dataset.

Project description

GUIDÆTA

A Versatile Interactions Dataset with extensive Context Information and Metadata

PyPI GitHub Repo License Downloads DOI

The GUIDÆTA interactions dataset was collected within an online user study in the A+CHIS project on Human-Centered Interactive Adaptive Visual Approaches in High-Quality Health Information, conducted between May 12 and June 23, 2025.

Extensive information on scope, data collection, metadata, preliminary analysis can be found in the respective paper ("GUIDÆTA – A Versatile Interactions Dataset with extensive Context Information and Metadata"), published at Smart Tools and Applications in Graphics (STAG) 2025, an annual international conference organized by the Italian Chapter of the Eurographics association.

The raw dataset is publicly available on OSF: https://osf.io/fhvbm/.

Install

pip install guidaeta

Usage

This repository contains everything necessary for handling the raw dataset. A few selected use cases are given below:

import guidaeta


# The path pointing to the root of the data
DATA_ROOT = "<PATH_TO_YOUR_DATA_ROOT>"

# load everything from files and initialize
sentences, sessions, users, task_answers = guidaeta.load_data(DATA_ROOT)

# get the cognitive load experienced for task two
task_two_answers = [ta for ta in task_answers if ta.task_no==2]
cl = sum([
	sum(ta.cl.scores)/len(ta.cl.scores) for ta in task_two_answers
])/len(task_two_answers)

# get all sessions associated with the 3rd task
s = [s for ta in task_answers for s in ta.sessions if ta.task_no==3]

Contributing

Contributions are welcome!
Feel free to open issues or pull requests at
https://github.com/lenxn/apchis-guidaeta

Acknowledgement

This work was funded by the Austrian Science Fund (FWF) as part of the project 'Human-Centered Interactive Adaptive Visual Approaches in High-Quality Health Information' (A+CHIS; Grant No. FG 11-B).

When referring to the dataset please cite:

  • S. Lengauer, S.A. von Götz, M.T. Hoesch, F. Steinwidder, M. Tytarenko, M.A. Bedek, T. Schreck, GUIDÆTA - A Versatile Interactions Dataset with extensive Context Information and Metadata, 2025, DOI: 10.2312/stag.202513359.

Bibtex:

@inproceedings{10.2312:stag.20251335,
	booktitle = {Smart Tools and Applications in Graphics - Eurographics Italian Chapter Conference},
	editor = {Comino Trinidad, Marc and Mancinelli, Claudio and Maggioli, Filippo and Romanengo, Chiara and Cabiddu, Daniela and Giorgi, Daniela},
	title = {{GUIDÆTA - A Versatile Interactions Dataset with extensive Context Information and Metadata}},
	author = {Lengauer, Stefan and Götz, Sarah Annabelle von and Hoesch, Marie-Therese and Steinwidder, Florian and Tytarenko, Mariia and Bedek, Michael A. and Schreck, Tobias},
	year = {2025},
	publisher = {The Eurographics Association},
	ISSN = {2617-4855},
	ISBN = {978-3-03868-296-7},
	DOI = {10.2312/stag.20251335}
}

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

guidaeta-0.2.0.tar.gz (15.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

guidaeta-0.2.0-py3-none-any.whl (14.2 kB view details)

Uploaded Python 3

File details

Details for the file guidaeta-0.2.0.tar.gz.

File metadata

  • Download URL: guidaeta-0.2.0.tar.gz
  • Upload date:
  • Size: 15.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.2

File hashes

Hashes for guidaeta-0.2.0.tar.gz
Algorithm Hash digest
SHA256 d06d06e5e2c1117b7582f9416af01d934c59441584fe669b15f89fef33f1d863
MD5 480fface58f8e11cd8d142be56f9e817
BLAKE2b-256 9979b088b4417e272533b2b3c571592e457402dbacb330a191ba1335716b4be5

See more details on using hashes here.

File details

Details for the file guidaeta-0.2.0-py3-none-any.whl.

File metadata

  • Download URL: guidaeta-0.2.0-py3-none-any.whl
  • Upload date:
  • Size: 14.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.2

File hashes

Hashes for guidaeta-0.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 67458301a867633519383ca88972eeb7bf4bd2bd02d121398a4c84256f3bfcfe
MD5 2f7f4fafcd9d948d24e8c281b50a2981
BLAKE2b-256 c02e6ff5dd103116b9a0bbbc4ce8cc7d324b72cee162c81ab79213235815c5dd

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page