Digital Me

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en Sjöberg, Mats Chen, Hung-Han Floreen, Patrik Koskela, Markus Kuikkaniemi, Kai Lehtiniemi, Tuukka Peltonen, Jaakko
dc.contributor.editor Gamberini, Luciano
dc.contributor.editor Spagnolli, Anna
dc.contributor.editor Jacucci, Giulio
dc.contributor.editor Blankertz, Benjamin
dc.contributor.editor Freeman, Jonathan 2017-05-11T09:10:23Z 2017-05-11T09:10:23Z 2017
dc.identifier.citation Sjöberg , M , Chen , H-H , Floreen , P , Koskela , M , Kuikkaniemi , K , Lehtiniemi , T & Peltonen , J 2017 , Digital Me : Controlling and Making Sense of My Digital Footprint . in L Gamberini , A Spagnolli , G Jacucci , B Blankertz & J Freeman (eds) , Symbiotic Interaction : 5th International Workshop, Symbiotic 2016, Padua, Italy, September 29–30, 2016, Revised Selected Papers . Lecture Notes in Computer Science , vol. 9961 , SPRINGER , pp. 155-167 , International Workshop on Symbiotic Interaction , Padova , Italy , 29-30 September . DOI: 10.1007/978-3-319-57753-1_14 en
dc.identifier.isbn 978-3-319-57752-4
dc.identifier.isbn 978-3-319-57753-1
dc.identifier.issn 0302-9743
dc.identifier.issn 1611-3349
dc.identifier.other PURE UUID: e1641ae4-fcd3-4b73-ac58-c0e1a86da9f6
dc.identifier.other PURE ITEMURL:
dc.identifier.other PURE FILEURL:
dc.description.abstract Our lives are getting increasingly digital; much of our personal interactions are digitally mediated. A side effect of this is a growing digital footprint, as every action is logged and stored. This data can be very powerful, e.g., a person’s actions can be predicted, and deeply personal information mined. Hence, the question of who controls the digital footprint is becoming a pressing technological and social issue. We believe that the solution lies in human-centric personal data, i.e., the individuals themselves should control their own data. We claim that in order for human-centric data management to work, the individual must be supported in understanding their data. This paper introduces a personal data storage system Digital Me (DiMe). We describe the design and implementation of DiMe, and how we use state-of-the-art machine learning for visualisation and interactive modelling of the personal data. We outline several applications that can be built on top of DiMe. en
dc.format.extent 155-167
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Springer
dc.relation.ispartof International Workshop on Symbiotic Interaction en
dc.relation.ispartofseries Symbiotic Interaction en
dc.relation.ispartofseries Lecture Notes in Computer Science en
dc.relation.ispartofseries Volume 9961 en
dc.rights openAccess en
dc.subject.other 113 Computer and information sciences en
dc.title Digital Me en
dc.type A4 Artikkeli konferenssijulkaisussa fi
dc.description.version Peer reviewed en
dc.contributor.department University of Helsinki
dc.contributor.department Department of Media
dc.contributor.department Professorship Myllymäki P. (HIIT Director)
dc.contributor.department Helsinki Institute for Information Technology HIIT
dc.contributor.department Department of Computer Science
dc.contributor.department Centre of Excellence in Computational Inference, COIN
dc.contributor.department Professorship Kaski S.
dc.subject.keyword Personal data management
dc.subject.keyword Human-centric personal data
dc.subject.keyword Knowledge work
dc.subject.keyword Text analysis
dc.subject.keyword Distributed representations
dc.subject.keyword Interactive machine learning
dc.subject.keyword 113 Computer and information sciences
dc.identifier.urn URN:NBN:fi:aalto-201705114295
dc.identifier.doi 10.1007/978-3-319-57753-1_14
dc.type.version publishedVersion

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