The Tracking Self Fuad Soudah Faculty of Architecture, Design and Planning Design Lab
Fuad Soudah
Fuad Soudah
The Tracking Self
The Tracking Self
The Tracking Self Fuad Soudah Faculty of Architecture, Design and Planning Design Lab Abstract The context of self-tracking in contemporary world has metamorphosed with the progression of potency and ubiquity of devices affording the collection of accurate data encompassing a wide span of human activities making feasible for the offering of a grandeur amount of personalised contents. However, we are often not enabled to investigate our activity history in a reflective way, by how we continued to develop and how the nature of our choices has holistically shifted overtime. In this research I studied the available tools related to self-tracking by conducting an integrative review. The desired areas to be tracked and contents of a personalised dashboard were found by incorporating a focus group of 5 students with a background established in design, involving a generative and a co-design session. Quality attributes of personal dashboards were further assessed by evaluating with the original focus group a webbased extreme prototype developed by utilising a variety of visualisations generated by commercial services based on the researcher’s personal data in relation to designs created by the focus group during the co-design session. The study has showed that the digital services often restrict the use of data they collect but also allow for most activities to be seamlessly tracked except for media consumption and many of physiological nature. People are interested in tracking specifics as individuals, although as an aggregate there is nothing they would not track. Self-tracking is highly valued as a tool of discovery, especially when it creates a eureka effect or makes a person recall profound, deeply engraved memories. The qualities include information based on correlated data, accessibility of the service the information is visualised on and customisation. I conclude the paper with a discussion on most surprising discoveries made and the yet not harnessed gorgeously disruptive potential.
Table of Contents 1. Introduction p.2 2. Methodology p.3 3. Phase 1 p.4 a. Expert Interview b. Analysis 4. Phase 2 p.7 a. Focus Group b. Analysis 5. Phase 3 p.8 a. Prototyping b. Detailed Rationale c. Caveat d. User Evaluation and Analysis e. Results 6. Conclusions p.12 7. Discussion p.13 8. References p.14 9. Appendix p.17 Introduction In the contemporary world, data can be transmitted at 99.7% of the speed of light (Poletti, Wheeler and Petrovich et.al. 2013) and the number of promised functionalities increases proportionally to Moore’s Law (Buxton, 2002) in which the number of transistors in an integrated circuit roughly doubles every two years (Moore, 2006), all making possible for Ubiquitous Computing to become a reality, envisioned as computers meant to be everywhere for people to accomplish everyday tasks (Weiser, 1999), paving way for Personal Informatics, a concept in which the use of technology for data collection on a wide span of life activities is done for invoking changes to a person’s life (Rapp et al. 2015). Understanding what prompts humans to invoke change is covered by Self Determination Theory, in which the needs for competence, relatedness and autonomy drive extrinsic motivation – humans’ will to pursue goals (Ryan and Deci, 2000), magnifying the
The Tracking Self Fuad Soudah Faculty of Architecture, Design and Planning Design Lab need for personalisation to achieve which, information about the user needs to be accumulated overtime by the use of sensors (Barua, Kay and Kummerfeld, 2006). In consequence, today, we are constantly surrounded by a range of computer systems, communicating between one another at an instance, detecting how we behave and responding accordingly to what we do, often at a highly personalised manner for the benefit of individuals, with the systems becoming twice as potent with each next two years. These systems, equipped with a set of sensors create an array of affordances, for instance if it utilises a gyroscope, the device will detect its orientation change. This allows for a human action cycle in which a change in orientation of the device, will be expected to change the device’s perceived state (Norman, 2013) with each change being additionally evaluated on how it felt (Verplank, 2009). For the state change to occur, an application installed on the device needs to be programmed to react to the orientation change by monitoring and interpreting the data generated by the gyroscope. As this data can be stored, the opportunity to keep track of state changes extends onto other types of sensors to be used for monitoring a wide span of phenomena, therefore the simple interactions you make while using digital devices but it may also be associated with the music you listen to, the movies, shows and images you watch (Kay, 2015). Each interaction and state change may be tracked and the data generated has great significance, as it can be used to generate lifelong user models that can help people achieve long term goals (Tang and Kay, 2007) whether weight loss, mastering languages or pursuing hobbies; Making it a great tool for learning, as adequate materials can be delivered to us by considering our existing and preferred ways of acquiring knowledge (Kay, 2008). Data may also be used
for self-tracking as a tool of discovery instead of optimisation (Wolf as cited in Neff, 2016). Nevertheless, the provision of processed data (ie. Information) without overloading its consumers remains a challenge (Hoggenmueller, Wiethoff and Tomitsch, 2018) and the market is highly fragmented with a severe lack of tools available which would enable the users to reflect on themselves in a holistic manner (Ahmadpour and Cochrane, 2017). The purpose of this phenomenological study is to explore the tools available for self-tracking and its resonance on humans – representative of five students with a background established in design at University of Sydney’s Faculty of Architecture, Design and Planning, to showcase the current state of the market and whether the conceptual and mental models are aligned for contemporary products (Norman, 2013). Subsequently, the following research questions were devised: -
What do contemporary digital services afford us to track? What do people want to keep track of? What do the quality attributes consist of in personal dashboards? Methodology
Research on and through design were used to investigate the impact a conceptual dashboard creates on its potential users in relation to stated research questions (Dalsgaard, 2010) with each carrying a methodological phase in this primarily qualitative-oriented research. Phase 1: An integrative review (Whittemore and Knafl, 2005) of existing hardware and software applications supported by a structured interview with an expert and the creation of a mindmap (Kokotovich, 2008)
The Tracking Self Fuad Soudah Faculty of Architecture, Design and Planning Design Lab were conducted to primarily establish an answer to the first research question. Phase 2: A focus group (Tremblay, Hevner and Berndt, 2010) consisting of 5 students with a background established in design (Keller, van der Hoog and Stappers, 2004) was involved, entailing discussions, a generative session (Visser, Stappers, van der Lugt and Sanders, 2005), (Sanders, 2002) and a co-design workshop (Steen, Manschot, and De Koning, 2011) all featured in one 2-hour long sitting hosted in a laboratory environment. Aforementioned were analysed using Thematic Analysis (Braun and Clarke, 2006) and Affinity Diagramming (Holtzblatt, Wendell and Wood, 2005) to primarily establish an answer for the second research question. Phase 3: An extreme prototyping technique (Beck, 2000) (also known as rapid prototyping) was undertaken, which entailed the insights derived from the thematic analysis and the originally created designs – wireframes (Garrett, 2011) generated by the focus group in Phase 2. These were compared against existing solutions analysed in Phase 1, of which visualisations generated based on my own personal data were extracted, adapted and deployed as hyperlinked mockups (Ohshima, Kuroki, Yamamoto and Tamura, 2003) into a web-based conceptual dashboard created with HTML, CSS, Bootstrap and swiper.js frameworks, coded in Sublime, running on a localserver launched with SublimeServer on Google Chrome web browser. The prototype was evaluated with the original focus group using a scenario (Rosson and Carroll, 2009) and think-aloud protocol (Rooden, 1998), reflected on by the participants with AttrakDiff questionnaire (Hassenzahl, Burmester and Koller, 2003) and a structured interview (Doody and Noonan, 2013) to distinguish quality attributes associated with a conceptual dashboard based on personal data, with the evaluation hosted in a laboratory
environment. This was conducted to establish an answer for the third research question. Phase 1 Expert Interview Consultations and an expert interview with Jim Cook from University of Sydney’s TechLab were conducted to disambiguate the concept of self-tracking, learn of his knowledge and view on the topic and personal use of related hardware and software. A set of 27 questions were asked during the structured interview. 6 Questions were asked in relation to what Jim already self-tracks, keeps track of and would like to track that he doesn’t. Most and least desirable areas to be tracked were constituted and broader areas named that he would track. 10 Expert Questions were asked regarding what self-tracking means to Jim, what digital tools are created for this, the popularity of the concept and how it evolved in the last decade. Researchers that he knows who investigate self-tracking and whether research around the tracking of media consumption is present. Areas not feasible to be tracked were asked to be defined and whether he knows of related devices in development. The affordances and constraints of such devices, and restrictions imposed by them in terms of generated data were explored, including services with no existing market alternatives. 11 Questions were asked, touching on the tools Jim personally uses for self-tracking, the total length of use, the motivation and his likelihood of future use, for each tool. The enjoyability of each, whether they work in correlation, the advantages provided compared to if he was not in use of any, the perceived changes to have happened after he started using each, changes that he would see introduced to the tools and how insightful does he find the feedback provided by each.
The Tracking Self Fuad Soudah Faculty of Architecture, Design and Planning Design Lab The interview was transcribed, although the thematic analysis was conducted after the completion of Phase 2. Based on the preliminary analysis a set of applications were identified such as: Exist, RescueTime, Last.fm, Facebook, Twitter, Instagram. Many of the applications voiced were investigated to assess how self-tracking affordances are accommodated. Later, I have looked at the potential data that could be extracted based on the researched services. In addition, Professor Judy Kay from University of Sydney was consulted on the work conducted by the Professor on the concept of self-tracking. Analysis The expert interviewee shed light on ‘Exist’, a service which utilises a range of digital services with open APIs1 to collate data and produce a set of insights along with visualisations, all presented on a dashboard for a user to learn about themselves. I have identified direct competitors such as ‘Gyroscope’ and custom solutions being developed even by Jim himself, however, ‘Exist’ employed the widest range of services, so I decided to review it as a user. Figure 1. ‘Exist’ and the data it collected based on my personal accounts
To receive meaningful information from Exist, I decided to utilise my personal data based on the services it could link to such as: Android, Google Fit, Calendar, GitHub, Gmail, Instagram, Last.fm, Facebook and Twitter. To receive even more data, I decided to set up a RescueTime account to monitor my productivity and my mood in Exist’s native Android application. This covered most of the data the service integrates, excluding: location, finance and food (see Figure 1). Exist showcases a wide span of patterns in terms of data management, which may be broken down into the following:
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API – Application Programming Inteface
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Data collected automatically and available in detail o Location o Music ▪ Last.fm o Physical Activity and Sleep ▪ Google Fit o Productivity ▪ RescueTime Only general data may be shared such as daily aggregates of user’s activity o Email ▪ Gmail o Calendar ▪ Google Calendar
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Social Media ▪ Facebook ▪ Twitter ▪ Instagram o Productivity ▪ GitHub Data needs to be inputted manually o Health (ex. Weight) ▪ Google Fit o Mood ▪ Exist app
Some complications became apparent. While on iOS ‘Exist’ can extract health data automatically, on Samsung devices S Health will require to have the data converted via a third-party application, such as ‘Health Sync’, into ‘Google Fit’. The data will be accurate, however, it will not transfer all of it, including food intake and more detailed health-related. Interestingly, location can’t be tracked unless ‘Swarm’ is used. Spending cannot be tracked at all, along with alcohol and caffeine consumption, detailed fitness activities performed, and words written. This set me in a cognitive dissonance as coffees can be tracked in ‘Samsung Health’. Spending can be tracked with personal banking, with some applications such as ‘CommBank’ showcasing a detailed breakdown of your monthly spending. What I found as even more alarming was the almost complete disregard for the consumption tracking of media. While music can be tracked in detail with ‘Last.fm’ and articles read within an application called ‘Pocket’, books, visual novels, comics, movies, tv shows, manga, anime, video games and many more cultural entities forming a person’s cultural identity and perception of the world were left out. I argue these are imperative for self-tracking. I decided to investigate a selected range of equivalent services used by Exist, including finding out whether media-related services do exist and how they manage data with APIs.
The analysis has showcased the restrictive nature of the researched digital services which seem to have viable alternative always present. Unfortunately, each may be perceived as less valuable due to reduced popularity and the need to introduce the data manually which defies the needs portrayed in self-determination theory such as relatedness. Phase 2 Focus Group The User Research was conducted in the form of a focus group, where 5 students with a background established in design were invited to a 2-hour long co-design session due to their advanced literacy in technology, diverse backgrounds and use of tracking devices. The session was recorded in audio and video with notes taken occasionally, hosted in a casual setting as beverages and snacks were provided with funk music playing in the background. Nonetheless, it was a lab environment as no external factors interfered with the session at University of Sydney’s Faculty of Architecture, Design and Planning. A set of context-mapping tools were involved: collaging, supported by a set of 100 photos depicting random objects, sourced from my personal digital library with each 25 differentiated by its source and postprocessing level, and 100 epithets written in a variety of suiting colours and fonts sourced from ‘Google Fonts’. Spatial Circles framework was adapted on a set of A3 sheets of paper dedicated for each participant to work on. The frameworks were iterated due to feedback provided by my research coordinator and one potential focus group participant. User Research was split into four distinct parts. Each of the participants received an opening questionnaire inquiring on their background before the start of the session. In addition, participant information sheets and consent forms were provided and upon its completion
The Tracking Self Fuad Soudah Faculty of Architecture, Design and Planning Design Lab the session started with the first part entailing a 10-minute long discussion on ‘what do you use to track yourself?’ The second part was a generative session in which participants were asked to create a collage on the topic of ‘what would you like to keep track of?’ with the set of tools provided such as: pens, pencils, markers, gluesticks, scissors and the set of images, and words. The allocation of the latter was as instructed: ‘The areas you’re most interested in tracking go to the center. The areas you’re least interested in tracking go to the edges’. After 20 minutes the participants were advised ‘if there were any, would you make any connections between some activities you'd like to track? Annotate them, if so! What do they have in common?’ and after 30 minutes ‘What made you decide on choosing your most and least desired items? If there is one, shortly annotate your rationale.’ This session’s part ended after 40 minutes with a 10-minute presentation given by the participants on what they have created. The third part consisted of a co-design session in which the participants were prompted to ‘Imagine your own - personal dashboard‘ and ‘Use Supplied Tools to conceptualize your personal dashboard. Feel free to use the supplied framework or conceptualize it in however you see fit’. After 15 minutes the participants were asked to ‘Take a look at your neighbours’ work. Is there anything you'd like to add to your dashboard?’. The session concluded after 30 minutes with a 10-minute discussion on the results. After the discussion was completed, one of the participants had left due to a scheduled appointment. The forth part showcased a commercial dashboard solution of ‘Exist’ based on its advertised images on its website and the participants were advised to ‘Compare this dashboard to your design. Is there anything you find interesting? Would you adapt any feature? Which do you find better - yours or
Exist?’. The discussion was concluded with the provision of a digitally sent questionnaire in which feedback could be given on the session. Analysis All the parts and the expert interview were transcribed by listening to the collected audio material, analysed by highlighting quotes and annotated in relation to the type of insights: -
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General: My words spoken, general remarks about the given session Interesting: Insights I deducted based on my own knowledge in relation to what participants said Key: Insights directly related to the context of what participants said Paramount: Summary of insights annotated on a single page and/or perceived tacit and latent knowledge
For the focus group, a total of 116 general, 164 key, 85 interesting and 37 paramount insights were identified based on 19360 words transcribed and for the expert interview, a total of 8 general, 49 key, 16 interesting and 39 paramount insights were found on 5887 words. Grounded on an aggregate of 25247 words transcribed, 76 paramount insights were collated, based on which an affinity diagram was created in which the insights were differentiated by origin and at further step supplemented with additional key insights to test whether the general outliers have not shifted. Patterns were identified such as general Quantified Self remarks, what people track and the tools they use. Subliminal patterns and Motivation were identified, and Issues, Expectations & Needs, Reservations; all pointing towards the need for a deeply correlated personal dashboard. As individuals, each participant voiced and generated preferences in tracking some of the following: Art, Ocean, Photos, Music, Health, Events, Buildings, Food, Transport, Relationships, Thoughts, Life, Landscapes,
The Tracking Self Fuad Soudah Faculty of Architecture, Design and Planning Design Lab Hometown, Different Perspectives etc. Nobody was interested in tracking everything but as an aggregate I argue people would track everything as far as the reach of human imagination may swerve off. In addition, the participants preferred their own designs over ‘Exist’, with the latter scathed for information overload, illegibility of visualised information, lack of references to where the data is coming from, lack of its purpose and unsatisfactory delivery. The participants would have liked to see more concrete information such as ‘this is how much you spend on average over the month’ – D. In summary, participants would have wanted it to ‘Be meaningful to me and I might do something about it’ – P. Phase 3 Prototyping A conceptual dashboard was created in a week by the use of an extreme prototyping technique in which I have synthesised wireframes created by the original focus group during the co-design session and connotated them to existing visualisations generated by commercial digital services. For this prototype, I utilised the visualisations based on my personal data as hyperlinked mockups, redirecting to its original source and an infrastructure of my own personal website, in particular my digital research journal created for this research. I have appropriated my own cascading sheet style file, a customised Bootstrap framework and included interactions with swiper.js to make possible for the cohesion and stacking of modules and addressing key user needs derived from the expert interview and focus group. The prototype was meant to be fully functioning on any given device, therefore facilitating responsive web design technique. The dashboard was split into sections, entailing assets extracted from the following
commercial services based on the data collected on my personal activity recorded: -
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RescueTime: Since 10th October 2018 Exist: Since 11th October 2018 Samsung Health: Since 3rd July 2017 Facebook: Since 2010 Google Locations: Since 21st June 2013 Onedrive: Photos backed since 2001, personal photos and videos since 10th February 2008 Duolingo: Since 17th of February 2016 Filmweb: Since 4th of February 2012 Last.fm: Since 10th of April 2010
The modules were differentiated by random background gradient colours, the co-design participants’ needs for a diary reflected by the introduction of a handwritten font and were assorted accordingly due to the following: -
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Productivity, Health and Location due to preferences stated by my expert interviewee Diary, Photo Reel and Culture due to needs expressed by the co-design participants during the discussion and activities undertaken Curation due to the gap established during the background research
Detailed overview of entailed modules and sections it broke down to is as follows: -
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Productivity: o RescueTime: Scatter Chart of your productivity o RescueTime: Histogram of your weekly productivity o Exist: Doughnut Chart of how you spend your time weekly o Exist: Area chart of your productivity Health o Samsung Health: Line chart of your average heart rate o Samsung Health: Histogram and static map of your activity
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Exist: Area chart of correlations founds o Exist: Histogram of a largest set of correlations found Location: o Google Maps: Semantic Map with your current location o Facebook: Semantic Map with your memories pinned o Google Location: Static Map of your logged locations o Been: Static Map of the countries you’ve visited o Google Location: Semantic Map of where you’ve been Diary: o Onedrive: Photos stored on cloud ▪ Information listed as per the design from the co-design session Photo Reel (part of Diary) o Onedrive: Collage of automatically tagged photos o Onedrive: Collage of geotagged photos o Microsoft Photos & Onedrive: Bubbles of photos associated with detected faces Culture o Duolingo: Line chart of your language learning progress o Filmweb: The movies you’ve seen and reviewed o Filmweb: The shows you’ve seen and reviewed o Filmweb: Statistics and summary of what you’ve seen Curation: o Reel of nuancedly suggested media with pictures sourced primarily from Filmweb and Goodreads of: ▪ Movies ▪ Music ▪ TV Shows
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Anime Books Video Games
Detailed Rationale Each section entailed an image mockup of statistics extracted from appropriate web services with a short description of what it depicted, imbued with nuanced insights followed by 3 - 30 - 300 rule (“Poster tips: 3 30 - 300 seconds”, 2012). For instance, the first image in productivity featured a visualisation of my productivity mapped out compared to all other users within the same design profession. The description entailed: ‘You were quite productive this week. Facebook and Youtube distract you the most.’, providing instant insights upon discovery. ‘Here’s how you perform compared to other designers’ was hyperlinked to RescueTime, if the user preferred to learn more of where the data came from, which could also be done by hovering over the image and clicking it. Some sections were more nuanced, for instance Film in Curation consisted of 7 titles. The first one featured the 4th title in the row – Apocalypse Now (Coppola, 1979) with an official polish poster (Świerzy, 1981) and the following description: ‘You have seen Apocalypse Now on Netflix and given it 9/10. You were most compelled by the bleak atmosphere and progressive storyline. Your writing style became reflective after watching movie’. Clicking on ‘Apocalypse Now’ would take you to its ‘Netflix’ subpage, clicking on ‘given it 9/10’ would take you to your review on ‘filmweb’. The movies to the right in reel would feature 3 other related Vietnam War movies and additional nuances such as the authors of the polish posters of ‘Apocalypse Now’ and ‘Platoon’ (Stone, 1986), directors of the movies and whether the movies are covered by your current subscriptions and if applicable,
The Tracking Self Fuad Soudah Faculty of Architecture, Design and Planning Design Lab if they are covered by your subscription overseas according to ‘Unogs’ service. The reel to the left provided suggestions based on highly related titles such as: ‘Heart of Darkness’ (Conrad, 1899), a book ‘Apocalypse Now’ was based on; ‘Spec Ops: The Line’ (Yager Development, 2012), a video game based on ‘Apocalypse Now’ and ‘Heart of Darkness’; ‘Odyssey’ (Homer, VIII B.C.), a book in relevance and yet preceding the aforementioned titles (Alava, 2008). Each suggestion was briefly explained with sources attached such as ‘Metacritic’ aggregates and qualities perceived by associated communities and its availability to you on services such as ‘Netflix’, ‘Amazon Prime’, ‘Steam’, ‘Humble Bundle’. Many of the modules had contents based on self-tracking data nuancedly cross-referenced with additional details available on click, although most descriptions were generated based on the knowledge of myself, researched services, cultural nuances and social media. Caveat During the prototyping phase I have decided to not address a few key issues. The designs generated by the co-design participants were created for mobile devices, however testing the prototype on a computer would have made the documentation and observations more feasible. Furthermore, the prototype was created to be functional on mobile devices on which the interactions are primarily gesture based. These can be easily simulated on PC by using the touchscreen or a touchpad, nevertheless I expected the interactions to be relatively unknown for the wider audience. My hypothesis was that the interactions would be found cumbersome but the system would still suit the participants’ needs to some extent. My goal was to establish the extent. ‘To break a design solution requires embracing failure.’ (Tomitsch et. al., 2018)
User Evaluation and Analysis After providing an overview of what the session will entail and after the signing of the consent form, the audio recorder was launched and the participants were told: ‘Before we start: The prototype will run on my computer, feel free to interact with it by your preferred means: keyboard, trackpad, touch and/or digital pen. You’ll have 5 minutes to interact with it. I’ll let you know when to stop. During this time, I would like you to actively comment on what you’re doing, what you think you see and how you feel about it. Basically, your thought process.’ Followed by: ‘And now… Imagine a world in which all the digital services you use, have the data open for you to make use of. And there is a single service, which uses all this data for the benefit of you. Now what you’ll see is a high-fidelity prototype. It was designed and constructed based on the data of my own and you are free to make comments on that, however, I would like you, to imagine, that all the contents, that you’ll see, are all directed towards you. So to imagine, as if all the contents that are there, are actually based on all your digital activity.’ At this point, the session was being video recorded in 360 and timed by a stop-watch. A few conditionals were attached: -
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If a participant was stuck in one place for more than 45 seconds, I prompted them to check the rest of the webpage If a participant was redirected from the prototype to another webpage for more than 45 seconds, I prompt them to go back When the timer was coming 20-15 seconds close to 5-minute limit, I
The Tracking Self Fuad Soudah Faculty of Architecture, Design and Planning Design Lab
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asked if they needed more time and provided with additional 30 seconds o When they continued using the service for 5 minutes 30 seconds, I asked them to stop If the participant struggled with navigating the website, I asked how they would interact on a mobile
The questions asked during the structured interview were as following: -
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How would you describe the service you just experienced? What did you learn from this service? Did you notice anything that surprised you? Did you notice any connection between specific objects in the service and your own life? How much did you enjoy this service? What changes would you like to see introduced to this service for you to enjoy it more? If the service was based on your own personal data, what would be the likelihood of you using it in the future? Would you like to share any additional thoughts if you have any?
Figure 2. Portfolio-presentation of User Evaluation
The session was thematically analysed and based on the data, insights were generated and visualised by the use of an affinity diagram the way it was done for the co-design session with one change in which I also annotated insights which were a direct link noticed between the prototype each user was evaluating and the designs they created. Results Based on 7824 words: 44 general, 91 key, 2 interesting, 46 Paramount and 4 linking insights were derived from the transcripts. The affinity diagram showcased an equal distribution between: Figure 3. Detailed results of User Evaluation: Pragmatic, Hedonic Identity, Hedonic Stimulation, Attractiveness
The Tracking Self Fuad Soudah Faculty of Architecture, Design and Planning Design Lab The problems with the design of the website primarily due to: -
The need for Customisation Accessibility related such as reduced legibility of font and animations Ambiguity of contents Lack of source of information
And the potential of the system due to: -
Significance of a rich and personalised recommendations Reflection based on historical statistics of your activity Scalability of the system to be used on a variety of devices Linkage with what the participants generated
The participants have also expressed their likeability of the system and were surprised with how much can be done with data. ‘It’s like a digital library, personalised for yourself. (...) I never have thought that personal information can be structured that way’ – T. AttrakDiff showcased a portfolio-presentation on the verge of self-oriented and neutral (see Figure 2). On a scale from -3 to 3 the pragmatic quality was rated at 0,09 with confidence of 0,47 and hedonic quality rated at 0,99 with confidence of 0,37. This breaks down into Hedonic Identity of 1,09 and Hedonic Stimulation of 0,89, and attractiveness of 1,09. For detailed breakdown of results, see Figure 3. This can be read as surprisingly positive results, considering the cumbersomeness of the interface as predicted. However, this severely impacted the usability of the service as all participants were stuck at the productivity module for a minimum of three minutes, the module that all participants did not feel as in reflected their preferences, subsequently voicing the need for
customisation of modules and remarking at the interface being difficult to use. Nevertheless, the system was seen as moderately attractive and moreover, value and potential were seen and expressed by the participants, which could prognosticate for an improved, ‘desired’ result if only the issues were addressed with the customisation and accessibility fixed within the next cycle. In addition, 4 out of 5 participants noticed links between the co-design session and the prototype and requested for the Culture and/or Curation modules to be at the top. Conclusions The research results provide a clear answer to the original research questions: -
What do contemporary digital services afford us to track?
‘Oh, you can track everything…’ – Expert Interviewee. All your digital activities leave a footprint. Non-digital activities are often recorded as well. Most services restrict the use of data they collect but alternatives are present and most activities can be seamlessly tracked, except for the consumption of media and some physiological activities. -
What do people want to keep track of?
Everyone carries their preferences. As an aggregate, there is no single thing people would not track. Most of the time they want to discover something and highly value ‘eureka!’ moments but at times, they are peculiarly interested in recalling profound, deeply engraved memories. Such as: ‘Like I still remember like ten years ago the sunshine on my hair. Like I still feel the warmth' – S -
What do the quality attributes consist of in personal dashboards?
The Tracking Self Fuad Soudah Faculty of Architecture, Design and Planning Design Lab Customisation is paramount. Legibility and minimalism are highly regarded; However, the data needs to be clearly sourced and visualised in ways that makes sense to the users to enable reflection. Precise, nuanced correlations based on personal data are highly sought after and links to publicly available information found as interesting. ‘So maybe the system (…) knows many people’s health conditions, you know data and they analyse internally and they come up with something like oh the people live like this are like harry potter, you know? And they recommend me the latest harry potter movie’ - P. Discussion ’10 years ago if you told that I could track everything about myself I would have not believed you. Today I think it’s quite feasible and reasonable to do’ – Expert Interviewee Before I started this research, I felt that the results would not surprise me. But in the end, the devil is in the detail and in many cases, there is more than meets the eye. It was quite interesting to see how a substantial part of our lives in form of the consumption of media is left out from contemporary self-tracking tools. Despite my participants did not feature media at the forefront of their needs, in many cases they would have preferred to see cultural-related recommendations presented first in the evaluated prototype. I argue this is a firm gap in the research, recurrently verified by the services such as Exist not covering the consumption of media, consulted researchers who were not aware of work conducted in this specific area and my participants who would have liked to see personalised recommendations. The data however is restricted by contemporary services’ APIs even for personal use, therefore future research may prove challenging.
Nevertheless, with the progression of artificial intelligence, increase in performance of integrated circuits and efficacy of sensors with a progressively larger part of our lives being lead in conjunction with the digital world, the potential for establishing tools collating all our personal data and generating insights highly regarded for its usefulness and potential by individuals is possible and has the capacity to create a positive impact on human lives and radically change the way we communicate. On the other hand, considering that everything can be tracked, this may revolutionise the way we interact not just with the environment but with people altogether. ‘seeing the activities that people are engaged with and then comparing that to the mood of that I have (…) I think that’s going to be dreadfully insightful’ – Expert Interviewee Regardless; ‘Anything that can go wrong, will go wrong’ – Murphy’s Law. We are living in a world, where every single activity we do is tracked in one way or another. I argue this will lead towards systems which will know better about ourselves than we already do. Will that necessarily be a worse world to be living in, though? The participants seemed excited and after conducting this research, so am I. Embrace the change and make self-tracking not just for optimisation but also discovery. Acknowledgements I would like to acknowledge my co-design participants, my research coordinator and everyone who have contributed towards the development of this research. References Ahmadpour, N., Cochrane, K. (2017). From information to reflection: Design strategies for personal informatics. IEEE Life Sciences Conference: Multi-society perspectives on personalized healthcare and wearables 2017,
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