Digital Me: Controlling and Making Sense of My Digital Footprint

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Researchers

Research units

  • Helsinki Institute for Information Technology HIIT
  • Tampere University

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.

Details

Original languageEnglish
Title of host publicationSymbiotic Interaction
Subtitle of host publication5th International Workshop, Symbiotic 2016, Padua, Italy, September 29–30, 2016, Revised Selected Papers
EditorsL. Gamberini, A. Spagnolli, G. Jacucci, B. Blankertz, J. Freeman
Publication statusPublished - 2017
MoE publication typeA4 Article in a conference publication
EventInternational Workshop on Symbiotic Interaction - Padova, Italy
Duration: 29 Sep 201630 Sep 2016
Conference number: 5

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume9961
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Workshop

WorkshopInternational Workshop on Symbiotic Interaction
Abbreviated titleSYMBIOTIC
CountryItaly
CityPadova
Period29/09/201630/09/2016

    Research areas

  • Personal data management, Human-centric personal data, Knowledge work, Text analysis, Distributed representations, Interactive machine learning

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