University of Oulu

Niels van Berkel, Jorge Goncalves, Katarzyna Wac, Simo Hosio, Anna L. Cox, Human accuracy in mobile data collection, International Journal of Human-Computer Studies, Volume 137, 2020, 102396, ISSN 1071-5819, https://doi.org/10.1016/j.ijhcs.2020.102396

Human accuracy in mobile data collection

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Author: van Berkel, Niels1; Goncalves, Jorge2; Wac, Katarzyna3,4;
Organizations: 1Aalborg University, Denmark
2The University of Melbourne, Australia
3University of Copenhagen, Denmark
4University of Geneva, Switzerland
5University of Oulu, Finland
6UCLIC, University College London, London, UK
Format: article
Version: accepted version
Access: embargoed
Persistent link: http://urn.fi/urn:nbn:fi-fe2020051435463
Language: English
Published: Elsevier, 2020
Publish Date: 2022-01-13
Description:

Abstract

The collection of participant data “in the wild” is widely employed by Human-Computer Interaction researchers. A variety of methods, including experience sampling, mobile crowdsourcing, and citizen science, rely on repeated participant contributions for data collection. Given this strong reliance on participant data, ensuring that the data is complete, reliable, timely, and accurate is key. Although previous work has made significant progress on ensuring that a sufficient amount of data is collected, the accuracy of human contributions has remained underexposed. In this article we argue for an emerging need for an increased focus on this aspect of human-labelled data. The articles published in this special issue demonstrate how a focus on the accuracy of the collected data has implications on all aspects of a study — ranging from study design to the analysis and reporting of results. We put forward a five-point research agenda in which we outline future opportunities in assessing and improving human accuracy in mobile data collection.

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Series: International journal of human-computer studies
ISSN: 1071-5819
ISSN-E: 1095-9300
ISSN-L: 1071-5819
Volume: 137
Article number: 102396
DOI: 10.1016/j.ijhcs.2020.102396
OADOI: https://oadoi.org/10.1016/j.ijhcs.2020.102396
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
113 Computer and information sciences
Subjects:
EMA
ESM
Copyright information: © 2020 Published by Elsevier Ltd. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.
  https://creativecommons.org/licenses/by-nc-nd/4.0/