Topic Archives: Uncategorized
When we decide to track one thing, we sometimes find that we are indirectly tracking something else. That is the theme of today’s talk.
When Mark Leavitt was 57, he found out that he had heart disease, a condition that runs in his family. Mark set about making some life changes. He tracked his weight while adopting a low-fat diet. His tracking showed him that he was making progress and that progress encouraged him to keep tracking. But once Mark’s weight loss stalled and then started to backslide (though he had maintained his diet) his desire to track dwindled and was then snuffed out by a major life event.
Though he was ostensibly tracking weight, this experience gave him some insight into his motivation. He began to build a mental model of his willpower. When was it strong? When was it weak? Using his background as a doctor to make assumptions on the nature of his willpower, he used the tracking of other lifestyle changes, such as movement and strength-training, to test those assumptions and better understand how to follow through on his intentions.
Watch below to see what Mark found worked for him and if you would like to see how Mark’s keeping up with his habits, you can check out his live dashboard here.
Enjoy these links, articles, and ideas from around the web.
By Whom, For Whom? Science, Startups and the Quantified Self by Whitney Erin Boesel. At our recent conference Whitney and Jakob Eg Larson helped facilitate a breakout session for attendees interested in QS and research. This great write-up explores what transpired during that hour-long session.
Confessions of a Self-Tracker by Michael Painter. A nice short piece about Michael’s experience with the assumed differences between self-trackers who are patients and those who track for athletic performance.
Measuring the Universe. A nice video piece on an Roman Ondak’s instillation at Tate St. Ives – “Through the simple action of measuring oneself, Ondak’s work doesn’t just expand on ideas of space and the universal but also the personal, creating a growing living artwork that questions just what a museum is for.” (via Carol Togan)
The Future of Quantified Self Devices by Aaron Parecki. Aaron, another QS conference attendee, explains his ideas for a possible future of the self-tracking technology ecosystem and how to put the individual at the core.
Consolidate this: Quantified Self edition by Nova Spivack. Is story-telling the future of QS? Nova makes that case that it is.
Stan James finds comfort in his daily habits.So much so, that he found that he kept adding to his routine. He started out by just using physical reminders, but found that tracking tools like Equinimity (meditation) and 750 Words (writing) added a little extra boost. In August of 2012 he started using Lift, a habit tracking mobile and web application. In this great talk, Stan explains what he’s learned from his 14 months of habit tracking. (filmed at the Bay Area QS Meetup).
This Thursday we kick off our fifth Quantified Self Conference. We’ve come a long way since our first conference in 2011 and we can’t wait to open the doors and welcome everyone to a wonderful event.
We’ll be hosting over 400 self-trackers, toolmakers, researchers, and other members of our growing QS community. We’ve planned for two amazing days of talks, breakout discussions, demos, and office hours that are sure to inform, inspire, and encourage. We treat our conference as a “carefully curated unconference.” This means that all of our talks and sessions come from our attendees. We are happy to announce that we have more than 120 separate talks and discussions planned. More than 25% of the attendees will be presenting in some way. This is program made for and by the community. Be sure to check out the program to see what will be going on.
For those of you who are not able to attend be sure to follow along on Twitter by checking out #QS13. We have also set up a Flickr group so that you can check out photos from the conference: Quantified Self Global 2013.
When you move from a small town to a big city you’re faced with a number of interesting challenges. How do you get around? Should you sell your car? When Valerie Aurora moved to San Francisco she faced these common roadblocks, but she also encountered something new: being harassed. In this great talk, filmed at the Bay Area QS Meetup, Valerie explains her rationale for tracking street harassment incidents and what she learned about herself and her new city in the process.
In this wonderful talk from the Bay Area Quantified Self Show&Tell meeting, Ashish Mukharji, author of Run Barefoot, Run Healthy, describes doing three years of continuous happiness tracking, using a single number.
This slide from Mary Meeker’s Internet Trends slide deck (link is to full deck on Slideshare) puts some numbers around what we’ve been noticing among QS Toolmakers: everybody wants to talk APIs.
What would you do if you had access to accurate galvanic skin response (GSR), skin temperature, heat flux, and 3-axis accelerometer data, as well as processed data estimating calorie burn, physical activity levels, steps, and sleep? We are holding a contest over in our QS Forum to provoke good questions that can be answered with our data. And there’s a prize.
Why do this? One of the things I’ve learned moderating Quantified Self show&tell talks over the last five years is that the most interesting and inspiring projects depend first on interesting questions. The data, visualization, and analysis is important, of course. But the meaning rests on having a good question, on personal curiosity and interest.
In conjunction with our upcoming QS Europe Conference in Amsterdam on May 11/12, our friends at BodyMedia have agreed to donate a complete personal SenseWear System (retail price $2,500), a state-of-the-art wearable sensor that allows raw data output. That’s going to be our prize. So if you have good questions, we can supply you with a way to collect the data.
To be clear: we care about your question, not your technical skills. I know that getting this much data about yourself can be intimidating. But data analysis and visualization skills are very high in the QS Community, and we can help you find technical support.
So if you have an interesting question or project that you would like to pursue, please describe it in this thread on the QS Forum. The winning idea will be chosen by QS Labs based on its ability to inspire others in the QS community. We will be having a breakout session at the upcoming conference where we discuss the projects posted to the thread.
Go here to post your proposal:
We want to better serve our community. To that end, we’ve created a short survey to to help us understand how we can use this website to support you and your Quantified Self endeavors. We have some ideas about where this website can go, but we want to hear from our community! Please take a few minutes to let us know what you think about our current website and how it could better serve your needs.
Personal Informatics in Practice: Enabling People to Capture, Manage and Control Information for Lifelong Goals
Bob Kummerfeld is an Associate Professor of Computer Science in the School of Information Technologies at the University of Sydney. Bob carries out research into system support for pervasive user models.
People’s long term, important goals are drivers for using personal informatics tools. For example, if a person’s goal is achieve and maintain good health, this is a driver to capture data such as blood pressure, exercise, activity, sleep and food eaten. Personal informatics tools aim to make it easy for people to capture such information and so that it is available for self-monitoring, so people can see how they are progressing towards their goals. It can also help people decide how to alter their behaviour and then to see if this helps them achieve their goals.
Our research aims to create a personal informatics framework for lifelong goals, by enabling people to have a new form of flexibility and control to:
- set relevant and realistic personal goals;
- link these flexibly to tools that capture relevant personal data;
- monitor their progress towards goals;
- and manage the data over the long term (update, share, delete, archive).
As one might expect, given the importance of goal setting and tracking, there are many goal setting systems, such as HealthMonth, GoalsOnTrack, stickK. While these provide a variety of valuable support for goal setting, they lack support for 2 and 4 above. We aim to address the broad challenges of enabling people to flexibly manage and control their data associated with their long term important goals.
User control over personal data during goal setting:
To help people think about the personal data that will be useful for achieving their goals, we are exploring a rich representation of goals. This should enable people to think more effectively about their goals and the kinds of personal data that could be useful. We draw on theories such as Goal-setting Theory and Social Cognitive Theory which point to the importance of aspects such as specificity, importance and difficulty of the goal, deadlines and feedback about the goal, commitment and self efficacy about being about to complete the goal. So we aim to help people think about these aspects. We explain each of these at the goal setting interface. We suggest personalised default values, and explain the reasons for those recommendations, and allow users to set their own values if they wish.
User control over personal data while linking devices to goals:
Social cognitive theory also indicates that if a person is aware of their potential resources (e.g. monitoring tools, social support) towards achieving goals, they gain insight about their own capabilities. In our system, for example, if a person acquires a step counter, they are advised to set an initial goal of using it to get a baseline, by tracking daily steps walked each day over a week. Suppose this indicates they walk an average 5,000 steps a day. Our system recommends an initial goal of 6,000 steps a day for the next week, explaining that while it is well below the recommended 10,000, it is more likely to be attainable from this person’s baseline. Thus our framework both recommends goals that are likely to be achievable and explains the reasons for the recommendation.
Personal informatics now has many different tools for monitoring health and activity. Users can choose different tools for monitoring different goals. This can create a problem which we call ‘scattered subgoals’. For example, maintaining wellbeing includes several subgoals such as “Walking 10000 steps a day”, “Do at least 30 minutes moderate activity per day”, or “Avoid more than 30 minutes of sitting in front of computer”. Users might use step counters such as Fitbit for monitoring a step goal, mobile applications for logging minutes of activity, or notifiers to remind them if they are in static posture for more than 30 minutes. In most cases, they have to visit different web sites to monitor different goals. This makes it hard to monitor goals. Available goal setting systems have not addressed this issue so far.
Our vision is to make it much more easier for people to monitor their diverse goals because our system enables them to aggregate their personal data for all their goals, extracting it from different systems and keeping it in a single store that the individual controls. Since more and more APIs are becoming available for developing mashups for personal health informatics, we can readily extract such information. The challenge still remains to ensure the person can control this aggregation and then manage the information effectively so that it serves their goals.
User access to aggregated information for goal monitoring:
An important part of our work is to enable people to see several goals together and to log salient notes about them. The example in Figure 1 shows a hypothetical user monitoring three goals:
walking 10k steps/day goal (green graph),
having 5 periods of intense activity per week (red dots)
at least 60 minutes moderate activity daily (blue graph).
The figure illustrates the user noting a quiz that interfered with achieving the goals (just as they noted that they were sick in the previous week). Theories of metacognition indicate the importance of enabling people to for log such salient life events to explain the progress achieved and make sense of long term information and trends.
User control over managing personal data:
Finally, existing systems lack support for people to manage the lifelong personal information. We have identified several important levels of control:
determining which information can be shared with others;
easy ways to remove information, for example when sensor data is wrong (such as when they allowed someone else to use their step counter);
transforming the information into compacted forms, for example, reducing fine-grained sensor data into higher level information about goals, so reducing the amount of information kept, reducing the risk to privacy it creates.
To achieve user control over goal related data, we will design and evaluate interfaces for managing goals and reflection over long term by defining goals; monitoring the social and cognitive information associated with each goal; and reviewing goals. These will enable users to connect sensors and choose the type and frequency of feedback, including e-mail, tweets, desktop notification and ambient displays. The driving design goal of our framework is to ensure user control of personal data.