DiversityOne Open Challenge: Exploring People's Everyday Life Behavior with Mobile Data

Combining passive smartphone sensor data with self-reports enables the study of everyday life behavior. The DiversityOne dataset, recently released to the UbiComp community, overcomes the limitation of existing datasets by containing data from eight countries from both Global South and Global North, including data from 782 college students, combining the data from 26 smartphone sensors and 350K+ self-reports, and extensive demographic and psychosocial survey data from 18K college students. The richness of the dataset opens the way to investigating important problems in multiple disciplines. Existing studies that leverage the dataset have only scratched the surface of the potential research questions it can help answer. Thus, we are organizing this workshop to foster creative and multidisciplinary works on this dataset: from AI and ubiquitous and mobile computing to computational social science and design.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-01
DOI
https://doi.org/10.5281/zenodo.16539803
Primary Topic
Innovative Human-Technology Interaction
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

DiversityOne Open Challenge: Exploring People's Everyday Life Behavior with Mobile Data

Zenodo (CERN European Organization for Nuclear Research)
Innovative Human-Technology Interaction
article

DiversityOne Open Challenge: Exploring People's Everyday Life Behavior with Mobile Data

article en

Abstract

Combining passive smartphone sensor data with self-reports enables the study of everyday life behavior. The DiversityOne dataset, recently released to the UbiComp community, overcomes the limitation of existing datasets by containing data from eight countries from both Global South and Global North, including data from 782 college students, combining the data from 26 smartphone sensors and 350K+ self-reports, and extensive demographic and psychosocial survey data from 18K college students. The richness of the dataset opens the way to investigating important problems in multiple disciplines. Existing studies that leverage the dataset have only scratched the surface of the potential research questions it can help answer. Thus, we are organizing this workshop to foster creative and multidisciplinary works on this dataset: from AI and ubiquitous and mobile computing to computational social science and design.

Zenodo (CERN European Organization for Nuclear Research)
University of Trento (IT), École Polytechnique Fédérale de Lausanne (CH), Idiap Research Institute (CH), Aalborg University (DK)
Openalex Percentile: Top 49%
Innovative Human-Technology Interaction
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.