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A domain ontology and software platform for collaborative personal data analytics |
Tuovinen, Lauri; Smeaton, Alan F.
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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.
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Keyword(s):
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Artificial intelligence; Multimedia systems; Lifelog; wearables; sleep |
Publication Date:
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2019 |
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Type:
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Other |
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Peer-Reviewed:
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Unknown |
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Language(s):
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English |
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Institution:
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Dublin City University |
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Citation(s):
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Tuovinen, Lauri ORCID: 0000-0002-7916-0255 <https://orcid.org/0000-0002-7916-0255> and Smeaton, Alan F. ORCID: 0000-0003-1028-8389 <https://orcid.org/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. |
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Publisher(s):
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Springer |
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File Format(s):
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application/pdf |
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Related Link(s):
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http://doras.dcu.ie/23918/1/Domain_Ontology_and_Software_Platform_for_Collaborative_Personal_Analytics%281%29.pdf,
https://doi.org/10.1007/978-3-030-30949-7_1 |
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First Indexed:
2019-11-12 06:38:38 Last Updated:
2019-11-12 06:38:38 |
