(Re)using Crowdsourced Health Data: Perceptions of Data Contributors (bibtex)
by Alorwu, Andy, Visuri, Aku, van Berkel, Niels and Hosio, Simo
Abstract:
Open data is often contributed by various governments and public sector actors. An increasingly popular way to collect large bespoke datasets is crowdsourcing. In this work we explore crowdsourced open data as an enabler of future software solutions. We recruited participants from an online paid crowdsourcing platform to provide open mental health related data that was used to create an interactive data-driven decision support system for self-care. We then invited a sub-sample of 80 participants back to explore the tool that was created using their own data and to provide a rich account of perceptions on issues around such health data reuse in software. Our results unfold a range of different perceived threats and opportunities in using crowdsourced data to enable software solutions, and our work contributes a topical case study and discussion toward the use of crowdsourced data in an open fashion.
Reference:
A. Alorwu, A. Visuri, N. van Berkel, S. Hosio, "(Re)using Crowdsourced Health Data: Perceptions of Data Contributors", IEEE Software, 2022, to appear.
Bibtex Entry:
@article{Alorwu2022CrowdsourceHealth,
	Abstract = {Open data is often contributed by various governments and public sector actors. An increasingly popular way to collect large bespoke datasets is crowdsourcing. In this work we explore crowdsourced open data as an enabler of future software solutions. We recruited participants from an online paid crowdsourcing platform to provide open mental health related data that was used to create an interactive data-driven decision support system for self-care. We then invited a sub-sample of 80 participants back to explore the tool that was created using their own data and to provide a rich account of perceptions on issues around such health data reuse in software. Our results unfold a range of different perceived threats and opportunities in using crowdsourced data to enable software solutions, and our work contributes a topical case study and discussion toward the use of crowdsourced data in an open fashion.},
	Author = {Alorwu, Andy and Visuri, Aku and van Berkel, Niels and Hosio, Simo},
	Doi = {10.1109/MS.2021.3117684},
	Journal = {IEEE Software},
	Pages = {to appear},
	Title = {(Re)using Crowdsourced Health Data: Perceptions of Data Contributors},
	Year = {2022},
	BFI = {BFI 2}}
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