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-0.2.1.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-0.2.1-py3-none-any.whl (14.2 kB view details)

Uploaded Python 3

File details

Details for the file guidaeta-0.2.1.tar.gz.

File metadata

  • Download URL: guidaeta-0.2.1.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-0.2.1.tar.gz
Algorithm Hash digest
SHA256 a30ab97218356e66aa9a2a7bee6793e20bb04b08607322751abb577b15c9a329
MD5 51ef3f9151ed1a9421598559d28a2424
BLAKE2b-256 f08acd04184c8db66fba9afafee5fe7fb17090d46f4ccbf089b3f7e0a7afa487

See more details on using hashes here.

File details

Details for the file guidaeta-0.2.1-py3-none-any.whl.

File metadata

  • Download URL: guidaeta-0.2.1-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-0.2.1-py3-none-any.whl
Algorithm Hash digest
SHA256 3785c24677ca17e005ddb436e5bdb6f518ca94500344b5818b85558cf05b50df
MD5 dbdf3f6e06678806799b0587c0de213d
BLAKE2b-256 21af8011dc54c0f65cb077532d48a6b22d1767bba3f1ee12ee510ac00f35d21d

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