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A domain ontology and software platform for collaborative personal data analytics

Tuovinen, Lauri orcid logoORCID: 0000-0002-7916-0255 and Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389 (2019) A domain ontology and software platform for collaborative personal data analytics. In: 16th International Conference on Cooperative Design, Visualization and Engineering (CDVE2019 ), 6-9 Oct 2019, Mallorca, Spain.

Abstract
Collaborative knowledge discovery is a promising approach by which people with no data analytics expertise could benefit from an analysis of their own personal data by experts. To facilitate effective collaboration between data owners and knowledge discovery experts, we have developed a software platform that uses a domain ontology to represent knowledge relevant to the execution of the collaborative knowledge discovery process. The ontology provides classes representing the main elements of collaborations: collaborators and datasets. Furthermore, the ontology enables the specification of privacy constraints that determine the precise extent to which a given dataset of personal data is shared with a given collaborator. We have developed a client-server software platform that enables users to initiate collaborations, invite experts to join them, create datasets and share them with experts, and create visualisations of data. The collaborations are mediated through the creation, modification and deletion of individuals in the underlying ontology and the propagation of ontology changes to each client connected to the server.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:wearables; sleep
Subjects:Computer Science > Artificial intelligence
Computer Science > Multimedia systems
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: CDVE 2019: Cooperative Design, Visualization, and Engineering. Lecture Notes in Computer Science (LNCS) 11792. Springer.
Publisher:Springer
Official URL:https://doi.org/10.1007/978-3-030-30949-7_1
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:Lauri Tuovinen is funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Sk lodowska-Curie grant agreement number 746837, Science Foundation Ireland under grant number SFI/12/RC/2289, and is co-funded under the European Regional Development Fund.
ID Code:23918
Deposited On:11 Nov 2019 09:50 by Alan Smeaton . Last Modified 11 Nov 2019 09:50
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