WildKey: A Privacy-Aware Keyboard Toolkit for Data Collection In-The-Wild

Rodrigues, André, Santos, André R.B., Montague, Kyle, Nicolau, Hugo and Guerreiro, Tiago (2021) WildKey: A Privacy-Aware Keyboard Toolkit for Data Collection In-The-Wild. In: Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers. ACM, New York, pp. 542-545. ISBN 9781450384612

rodrigues et al – ubicomp 2021.pdf - Accepted Version

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Official URL: https://doi.org/10.1145/3460418.3482872


Touch data, and in particular text-entry data, has been predominantly collected in laboratory settings, under controlled conditions. While touch and text-entry data has consistently shown its potential for monitoring and detecting a variety of conditions and impairments, its deployment in-the-wild remains a challenge. In this paper, we present WildKey, an Android keyboard toolkit that allows for the usable deployment of in-the-wild user studies. WildKey is able to analyse text-entry behaviours through implicit and explicit text-entry data collection while ensuring user privacy. We detail each of the WildKey’s components and features, metrics collected, and discuss the steps taken to ensure user privacy thus promoting compliance.

Item Type: Book Section
Additional Information: Funding information: We would like to thank our collaborators from OpenLab Newcastle as the first external team to use the keyboard toolkit providing us with valuable feedback and contributions to the project. This project was partially supported by FCT through project mIDR (AAC 02/SAICT/-2017, project 30347, cofunded by COMPETE/FEDER/FNR), LASIGE Research Unit funding, ref. UIDB/00408/2020, LARSyS Research Unit funding, ref. UIDB/50009/2020, and the IDEA-FAST project which has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 853981. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA and associated partner
Uncontrolled Keywords: Text-Entry, Touch Dynamics, In-the-wild, Smartphones, Data Collection
Subjects: G400 Computer Science
G500 Information Systems
G900 Others in Mathematical and Computing Sciences
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Rachel Branson
Date Deposited: 14 Oct 2021 08:40
Last Modified: 14 Oct 2021 09:15
URI: http://nrl.northumbria.ac.uk/id/eprint/47483

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