The Falsified Self: Complexities in Personal Data Collection
| Autor: | Alessandro Marcengo, Federica Cena, Marina Geymonat, Amon Rapp |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Self-tracking
Exploit Computer science Wearable computer Personal informatics Autoethnography 02 engineering and technology Theoretical Computer Science User experience design Human–computer interaction 0202 electrical engineering electronic engineering information engineering 0501 psychology and cognitive sciences 050107 human factors Reliability (statistics) Wearable technology Data collection Quantified self Wearable devices Computer Science (all) business.industry 05 social sciences 020207 software engineering business Personally identifiable information |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783319402499 HCI (7) |
| Popis: | Personal Informatics systems collect personal information in order to trigger self-reflection and improve self-knowledge. Users can now choose among different wearable devices for collecting these data according to their needs and desires. These tools exploit not only different shapes and physical forms, but also diverse technologies and algorithms, which may impact the effectiveness of data gathering. In this paper we explored whether there are significant differences in their reported measures and how these can impact the user experience, along with the perceived accuracy of the gathered data and the perceived reliability of the device. To this aim, we carried out an autoethnography which lasted 4 weeks, monitoring the number of steps and the distance covered during the day and the sleep period through different wearables. The results showed that there are wide differences among diverse tools and these differences greatly influence how data collected and devices used are perceived. |
| Databáze: | OpenAIRE |
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