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Remote Collaborative Knowledge Discovery for Better Understanding of Self-tracking Data

Tuovinen, Lauri orcid logoORCID: 0000-0002-7916-0255 and Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389 (2019) Remote Collaborative Knowledge Discovery for Better Understanding of Self-tracking Data. In: 25th Conference of Open Innovations Association FRUCT, 5-8 Nov 2019, Helsinki, Finland. ISBN 978-952-69244-0-3

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.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:knowledge discovery; data mining; collaborative systems; personal data; wearable devices
Subjects:Computer Science > Artificial intelligence
Computer Science > Computer software
Computer Science > Interactive computer systems
Computer Science > Visualization
Computer Science > Lifelog
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Institutes and Centres > INSIGHT Centre for Data Analytics
Published in: Proceedings of the 25th Conference of Open Innovations Association FRUCT. . FRUCT Oy. ISBN 978-952-69244-0-3
Publisher:FRUCT Oy
Official URL:https://www.fruct.org/publications/fruct25/files/T...
Copyright Information:© 2019 The Authors
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:EU Horizon 2020 - Marie Skłodowska-Curie, grant No. 746837, Science Foundation Ireland, Research Centres Programme. Grant No. 12/RC/2289
ID Code:23919
Deposited On:11 Nov 2019 12:46 by Lauri Tuovinen . Last Modified 27 Apr 2020 13:12
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