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Reflections on Ubiquitous Visualization
Published in Bongshin Lee, Raimund Dachselt, Petra Isenberg, Eun Kyoung Choe, Mobile Data Visualization, 2021
Jo Vermeulen, Christopher Collins, Raimund Dachselt, Pourang Irani, Alark Joshi
Personal informatics is a major theme where information about an individual is crucial to the individual and is provided in a contextualized form. The Quantified Self movement consists of individuals who are passionate about collecting high-resolution data about their health, exercise, energy consumption, shopping habits, and so on. For example, a device such as a smartwatch not only captures the data regarding an individual's health, but also allows them to explore it either on the watch itself or on a mobile phone. Mundane tasks such as brushing your teeth, drinking coffee, or shopping could be scenarios in which we may see innovations with respect to ubiquitous visualization. Rather than experiencing visual representations only on a watch/phone, we may see representations on a toothbrush, or a coffee cup, or the handle of a shopping cart. Here one may experience “serendipitous decision-making” rather than conduct detailed analytics that would be performed on a desktop or in a collaborative setting.
Data Protection and Privacy Issues of the Internet of Things
Published in Stavros Shiaeles, Nicholas Kolokotronis, Internet of Things, Threats, Landscape, and Countermeasures, 2021
As for the definitions, wearables are devices that often look similar to their nonconnected predecessors and can be used in everyday life, such as fitness trackers, smart watches, clothes with sensors, smart glasses, and so forth [9, p. 5]. The Quantified self refers to applications and devices “designed to be regularly carried by individuals who want to record information about their own habits and lifestyles,” for instance, sleep trackers or personal assets trackers [9, p. 5]. Domotics refer to the so-called smart home automation appliances, such as smart lamps, smart plugs, home security, digital assistants, smoke alarms and smart locks [9, p. 5]. As seen, the IoT devices can be equipped with sensors, which can be understood similarly to the human senses: tools that can detect changes in real time and deliver digital or analog output about the physical environment, for example, changes in weather or light conditions [18, p. 69].
Lightbulb concrete
Published in Massimo Ragnedda, Giuseppe Destefanis, Blockchain and Web 3.0, 2019
In terms of expressive interactions, the more meaningful those mediated actions or choices are within that context, the more “agency” (Murray 2001: 394) that users are said to enjoy. But what sorts of meaningful agency exists in automated collaborations, “characterized by the fact that their core capability is algorithmic coordination” (Roio and Jelincic 2017), such as data sharing and proof of work? For some, agency is only possible when there is also some sense of personal control over that data. For example, the quantified self-movement embraces personal data-monitoring practices such as behaviour monitoring, location tracking, medical self-diagnostics and personal genome sequencing as a form of self-knowledge (Wolf 2010; Swan 2013). For others, agency equates to the chance or challenge to game the system and make the numbers work to personal advantage. For instance, the appeal of big data for corporate advantage could be classified as the appeal of uncovering the hidden laws or patterns in play and responding accordingly. Both of these aspects need to be considered in the design of any data-sharing application.
Healthier Life with Digital Companions: Effects of Reflection-Level and Statement-Type of Messages on Behavior Change via a Perceived Companion
Published in International Journal of Human–Computer Interaction, 2020
The quantified self is referred to as a movement to incorporate technology into data acquisition on aspects of personal daily life in terms of environmental factors (e.g., food consumed, quality of surrounding air), biological states (e.g., mood, arousal, blood oxygen levels), and performance (mental and physical). These kinds of daily data support a user’s self-knowledge accumulation. In particular, a common way to obtain self-knowledge is to collect data, including on one’s behaviors, habits, and thoughts, and reflect on one’s daily life (Li, 2011). Computing devices can facilitate this activity because of advances in sensor technologies, the ubiquity of access to information through wireless networks, and improvements in visualization. Through quantified-self behavior, people who seek knowledge about their own behaviors, habits, and thoughts can obtain more detailed self-knowledge with the help of various devices and sensors (Rivera–Pelayo, Zacharias, Müller, & Braun, 2012).
Towards understanding the mechanism through which reward and punishment motivate or demotivate behaviours
Published in Behaviour & Information Technology, 2023
Rita Orji, Alaa Alslaity, Gerry Chan
A major barrier to adopting healthy behaviour is the boredom often associated with it and the lack of immediate reward. Therefore, we recommend persuasive gamified systems designers can strategically implement reward and punishment to make the task of adopting behaviour fun. Virtual rewards and punishment share the characteristics of making behaviours fun, propelling users to thrive. The Persuasive System Design (PSD model states that rewarding target behaviour reinforces the behaviour and may increase the persuasiveness of a system. Consistent with previous research showing that virtual rewards can increase the fun and enjoyment in digital games [Berkovsky et al. 2010; Zuckerman and Gal-Oz 2014]), our study adds to the existing literature by finding that punishment can also be thought of as being fun. For example, ‘A system that penalizes you in some way for not reaching your daily goals is an awesome way to control yourself in a fun and entertaining way’ [P1663]. Moreover, the experience of loss can further motivate users to devote more effort working harder to maintain their points as one participant said, ‘I would feel like I'm doing something wrong and try to work harder to further reduce the amount of alcohol I ingest’ [P1133], and another participant commented: ‘Losing accrued points like that would disappoint me, and I would probably work harder in the future to avoid that disappointment’ [P191]. Besides, when a user’s performance is connected to a virtual character, the appearance of the user’s virtual character can offer a sense of self for the user to reflect on and promote changes to their behaviours. One participant explained that ‘I think it's fun to take care of a virtual representation of myself and have to work to be able to make it better’ [P733]. This is called ‘quantified-self’ (Whitson 2013), and it can help the user realise and become more aware of their habits through virtual representation of themselves. Rewarding users through their quantified self-incentivising them to engage in health-related behaviours (Hamari et al. 2018; Meyer et al. 2014; Stepanovic 2020). However, some users see that virtual characters alone are not enough to maintain the desired behaviour; one participant explained that ‘Avatars in comparison to controlling alcohol intake would not likely help me much in the long run. It's an okay feature to start with’ [P10]. Thus, it will be important to consider various forms of rewards to provoke further motivation. Use Reward and Punishment in interventions targeting long-term and continuous behaviours.