During the interview participants were asked to scroll through, present and reflect on their data. In the main, this was a task of rapidly making sense of the data by relating it to themselves and their everyday lives, past and present. But beyond sense-making, and achieving a settled record of the past, there are clearly elements of this record that could hold a wider personal value to participants, or provide the basis for reconstructing the past with some relevance to the present. Clearly, what this data will mean to any participant is situated and dynamic; the findings here only speak of the meaning and identities
participants presented at interview. Selected examples from individuals’ experiences are presented here thematically to demonstrate the range of possible meaning and value quantified data can develop as a form of personal record.
Remarking on Changes in One’s Life
In different ways, all participants remarked upon transitions and things that had changed in their lives. Old houses and neighbourhoods; improved fitness; changed diet; forgotten places; moving in with a partner; weight loss; teen music tastes; recovering from injury; leaving university. Leaning on Radley’s terms once again, “these objects become
interesting because they are displaced from their time” (p.51). The data, in various ways - through maps, graphs, peaks and troughs, absences – offered a highly legible reflection of these life changes, no matter the metric recorded.
Change was also a way to navigate through the data and anchor a narrative. Browsing through extensive records, change or exception was often more evident than the routine
and humdrum. Well known routines and patterns – regular routes, commutes, lunches etc. – were ways of gathering data together, and describing it as belonging to a certain period of time, or way of life.
“All of those days that I basically did home, school, Pret again, and then going back home. By itself that doesn't really tell me anything, it's not very interesting, it just shows how boring some days are. […] Maybe they are not as similar as I think they are. Don't know.” (Becky, Moves)
This phenomenon is reminiscent of the way people browse thousands of SenseCam images. Lindley et al. (2009) describe people ‘compressing the everyday’ as they move past the humdrum, and instead become attentive to changes in their images. “One watches in anticipation of change rather than pausing to reflect upon a fixed moment.” (pp 9, Lindley et al., 2009)
Remembering Moments and Periods of Life
Data was variously approached as an index to remembering in broad strokes, distinct periods of their life, as well as specific moments and events. Lulls or gaps in activity- related data were revealing of periods of injury, illness or busyness. Routine and
consistent data tracking might also reflect a settled period of time. The scale, visualisation and granularity of the data could mediate these different temporal perspectives. Running charted over a month in Nike+21 would prompt a wider focus than the detailed breakdown of one cycle ride in Strava for example.
“It was my first 5k, July or August, I think it was July, because August I train a lot, because September I train a lot, it was the second one, so July was the 10k but what happened was that in April I twisted my ankle. I had to stop for a month, that is why
May is sort of a phantom here.” (Tanya, Nike+)
Details, perhaps a top speed, the elevation, and especially locations might focus remembering on specific events.
“Oh actually this is one to Wylam. This is one I did with my girlfriend, and I was obviously just using it at the time, I don't think we were going very fast.” (Ivan, Endomodo)
Alternatively, the mass of data was sometimes oriented to by memorable events -
birthdays, sightseeing, races, long bike rides. The data around these special occasions was held up as “another layer” (Darren, last.fm). In an exceptional example, Suzanne
described recording the route of her honeymoon - US road trip.
“So we've got it on Google Maps and then because you go with the little man, and drop him at places, so places that we didn't necessarily take photos of, like where we stopped and had a picnic one day which was just like, you know a picnic bench in the middle of nowhere but you can look at it on GoogleMaps and you can look around.”
Following this experience, Suzanne intends to use Moves to map routes in upcoming sightseeing holidays in Prague and Budapest. In such a way, the data became a way for participants to orient personal remembering, even within a public record such as Google Maps. And Suzanne now anticipates using Moves in a documentary fashion to explicitly support this.
Vivid Recollection and Inferring the Past
During narratives, the participants clearly engaged both in vivid recollection as well as inferring the past through a kind of personal detective work, relating recognizable
features of the data to remembered experience, routines and known facts about one’s life. “And I remember running down there, and thinking bloody hell this is miles, I really wish I could cut across but coming across the fence, and then it being rough terrain. Isn't that funny, I actually remember that really distinctly.” (Tony, Sportstracker) Tony is pointing out a specific part of the map here, an unusual squiggle, which prompts him to remember, vividly, the effort and frustration of the terrain. Remembering vivid
memories such as these was evidently surprising and pleasurable. Often, with the passage of time, data could be reduced to “just numbers” (Peter, Strava). However, there was also a satisfaction to working out one’s past, being able to account for it, to put it in order and tell a coherent story.
"I must have went to boot camp... yeah. So and then I've even put my water
consumption in, which I never track so I must have been messing around with what I could track …Yeah... must have been... I guess it was January so it would be people having silly selection boxes of sweets. Bring them in don't they to get rid of them…" (Colette, MFP)
This example also highlights the very live sense-making process interacting with one’s data, and the desire to resolve and explain it.
Reminiscence, Nostalgia and Emotion
A feature of several interviews, participants would occasionally reminisce about their past and the changes in their life, which were sometimes a fleeting source of nostalgia. Tim reminisced about a music festival with an older group of university friends. Lily missed ‘proper lunches’ since starting a diet. Joanne recalled an especially satisfying triathlon victory. Tanya recalls beginning to run just as she moved to the UK.
“I think this period is really good. It was autumn here, and I'd never experienced that because they don't have leaves falling and brown things, so it was beautiful in the park. I remember feeling all of that... Like it was a different thing from running in the same track, seeing the same people, that I usually done... here it is like watching… I dunno nature more... more trees. [sic]” (Tanya, Nike+)
Tanya was sentimental as she recounted her data in this case. For her, the data represents some of the best of her running activity, especially in contrast to periods of injury, or slow running; but it also remarkable for being a novel, and more aesthetic experience. Not all participants reacted emotionally towards their data in this way however.
“I don't feel nostalgic about this data... It's kind of an interesting sort of marker of time, but I don't.” (Tony, SportsTracker)
Tony’s comment reflects a curiosity with his data, frequently described as ‘interesting’ without being as emotive an experience as perhaps, looking back through a photo album. At interview, participants were directly prompted to compare remembering with
photographs to remembering with their data. The majority of participants, like Tony, described photos as being somehow more evocative or having a “warmth of feeling” (Suzanne, Runkeeper) in terms of remembering. However, some participants also described their data as being more personal, private and intimate – something they were much less likely to share.
Other participants suggested that their data sometimes lacked details that would evoke specific memories of an experience in the way that photographs taken at a time and place “pick out particular moments and episodes” (Lily, Misfit Shine). An activity tracker is just always on, and hence rarely turned and focused on a particular event the way a camera might be. The way such moments and episodes are captured and represented by data seems almost incidental by comparison. Put bluntly by Darren (last.fm), data, colder and more abstract, rarely achieved the same emotive value as an image:
“When it comes to photographs, it can be funny sometimes to see how you used to look when you were a lot younger it doesn't really trigger, the same emotion, because this is just kind of a chart.” (Darren, LastFm)
A photo of how he used to look, therefore seems more emotionally resonant than a data double (Lupton, 2014; Ruckenstein, 2015) of how Darren used to listen to music. On reflection, data seems to act best as a “condensed symbol” (Radley, 1990) to
“punctualise experience” (Middleton and Brown, 2005) and structure remembering. This resonates somewhat with Thiry et al.’s (2013) description of a timeline as “a framework for authoring” rather than an evocative mirror of the past.
Becoming a possession
Throughout, almost regardless of its emotive value, or the extent to which participants had previously looked back on their data, data was conceived of as a personal possession.
“This data is very personal to me, it's my data and my numbers and my figures. And it feels a lot more mine.” (Lily, MFP/Misfit Shine)
Many felt they had worked to create their data, even when passively tracked, and were keen “not to mess up the history of it” (Tim, last.fm). For others, the data represented a desired identity or facet of their life, seeing themselves and their lives reflected in it.
“It sounds ludicrous but you get a personal attachment to… you. Because that's what you did.” (Aaron, MoneyLover)
Aaron identifies with his data here, because it portrays how he has carefully managed his money through several bank accounts, reflecting how he already saw himself, as someone shrewd. Hence, nearly all participants were reluctant to lose their data; even those like Peter who felt more clinical about their data suggested there were “certain stats” that would endure and remain meaningful in the future.
For others, the accumulation of their data maintained a motivation for tracking. As such, many participants saw their records as valued possessions, which they would be reticent to lose, even if they had not set out to accumulate such a record, and struggled to
articulate a clear future purpose for them. No editing, curating or deleting data
Interestingly, despite these claims about the importance of some of their data, few participants took any steps to retrospectively edit, manage or curate their data by, for example, deleting data, gathering important data together, or adding comments or annotation. At most, curation involved sharing data between different apps. Participants like Leanne did combine calorie data from her Fitbit with MyFitnessPal, but this
happened automatically, without her input. As a rare example, Brianna imported her Moves data into a journaling app, Momento (momentoapp.com) along with other media, giving her a place to annotate and reflect on different streams of personal data together. Curation might otherwise occur by hazard, through the occasional sharing of data to social media. Lily explained “on the days when I had massively beaten my goal I have
taken a screenshot of it and put it on Twitter”. In this way, her ‘best’ days of activity recorded with her Misfit Shine have become marked out and put aside, elevated to being worth posting publicly a representation that will persist beyond the original application. Notably however, no one in the study admitted to deleting or even editing any of their data. Even though some data was deliberately avoided during the interview, the only data that was missing was lost hazard, for example through changing devices. To selectively edit their data would potentially undermine it as an objective record, even while they acknowledged the inaccuracies in that record.
Nevertheless, with the exception of importing data into journaling tools, or exporting ‘raw’ data (often a non-trivial technical process), there appear few opportunities to personally curate one’s data. Like much curation, these seem effortful processes. Therefore, curating data and changing its presentation was overwhelmingly system- driven. Features such as dashboards (Figure 4, p.98), records, achievements, ‘recent activity’ and graphs over time, offered participants different ‘visual cuts’ (Epstein et al., 2014) of their data. Yet, cases such as Lily extending the graph of her weight loss, to emphasise her past success, hint at the potential meaning gained in curating or editing at least the presentation of one’s data. In broad terms, this attitude reflects Marshall’s description of ‘benign neglect’, common to other digital possessions. Yet, the success of filters applied to selfies in apps like Instagram and Snapchat point to the way photographs can be tailored and ameliorated in a way that data currently cannot.
Mixed meanings of sharing
Finally, the analysis revealed occasions for the participants to find occasional meaning in sharing their data. In line with other studies, there were few examples of participants shared data on social media, and certainly not past data, perhaps as sites like Facebook tend to be ‘in the now’ (Harper et al., 2012). However, tracking did occasionally encompass shared experiences, such as a cycle ride (Ivan), birthday meal (Leanne) or honeymoon (Suzanne. In these cases, participants described selectively sharing their data with friends. In Ivan’s case, historical data of a joint achievement was seen as a resource for both shared reminiscence, and to motivate doing something together again.
“I kind of thought it would be nice to say to him in five years’ time, do you want to go out and do the Coast to Coast [cycle ride] again, and see if we can beat the record? And I can send him a graph or something.” (Ivan, Endomodo)
Ivan anticipates that having a record would be a hook for remembering their ride in the future, towards the practical aim of motivating the ride again.
Nonetheless, the prevailing feeling from participants was that one’s own data was most likely quite uninteresting to anyone else. Some protested they were being boring at points in the interview, as they felt they were speaking about the most mundane concerns. For many, even if their data was public, it was so personal – "because it’s just me” – that to share it with someone would be “very selfish in that way” (Leanne, MFP). Data by default reflects on oneself more than anyone else, and so perhaps demands a degree of humility or modesty, at least publicly.