University of Oulu

Tuovinen, L., Smeaton, A., Remote collaborative knowledge discovery for better understanding of self-tracking data, Proceedings of the FRUCT’25, Helsinki, Finland, 5-8 November 2019, ISSN: 2305-7254, p. 324-332. https://doi.org/10.23919/FRUCT48121.2019.8981506

Remote collaborative knowledge discovery for better understanding of self-tracking data

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Author: Tuovinen, Lauri1,2; Smeaton, Alan F.1
Organizations: 1Dublin City University, Dublin, Ireland
2University of Oulu, Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 0.4 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe202001162359
Language: English
Published: FRUCT, 2019
Publish Date: 2020-01-16
Description:

Abstract

Wearable self-tracking devices are an increasingly popular way for people to collect information relevant to their own health and well-being, but maximising the benefits derived from such information is hindered by the complexity of analysing it. To gain deeper insights into their own information generated by such products, a user with no data analysis expertise could collaborate with someone who does have the required knowledge and skills. To achieve such a successful collaboration, several tasks need to be completed: finding a collaborator, negotiating the terms of the collaboration, obtaining the necessary resources, analysing the data and evaluating the results of the analysis. To support the execution of these tasks, we have developed and deployed an online software platform that enables data collectors and owners to find experts and collaborate with them so they can extract additional knowledge from the self-tracking data. The functionality and user interface of the platform are demonstrated by presenting an application scenario where a data owner shares their sleep data with an expert who applies periodicity analysis to discover cyclical patterns from the data.

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Series: Proceedings of Conference of Open Innovations Association FRUCT
ISSN: 2305-7254
ISSN-E: 2343-0737
ISSN-L: 2305-7254
ISBN: 978-952-69244-0-3
ISBN Print: 978-1-7281-2786-6
Pages: 324 - 332
DOI: 10.23919/FRUCT48121.2019.8981506
OADOI: https://oadoi.org/10.23919/FRUCT48121.2019.8981506
Host publication: Proceedings of the FRUCT’25, Helsinki, Finland, 5-8 November 2019
Host publication editor: Balandin, S.
Niemi, V.
Tuytina, T.
Conference: Conference of Open Innovations Association FRUCT
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Subjects:
Copyright information: © The Authors 2019.