With so many quantified self tools and ways to track a life, it can be a bit confusing. A mind map can help.

A mind map is a graphical, visualization technique that is intended to help with structuring, organizing and understanding information as well as facilitate creative thinking. It’s is also one of the best ways to synthesize and understand information in general.

Here’s my mind map of the quantified self and self-tracking space. The intention is to help you conceptualize the overall tracking technologies space as well as hopefully enable you to better track different aspects of your own life and, in turn, engage with your personal data accordingly.

In the rest of this post, I want to explain the motivation behind the project and briefly walk through why I’ve categorized things accordingly.

One of the principal points I want to make is the division I make between tracking or data collection AND data engagement or being data-driven. While we might obsess about how to track an area, we often fail to take the time to engage with the data we are collecting. For me, one of the key motivations for self-tracking is not data collection but using data to provide a feedback loop towards what I’m trying to understand or a goal I’m trying to reach. This is really only possible if you engage with whatever you are tracking.

Motivation Behind QS Mind Map

As someone who has been tracking, writing, thinking and building in the personal data space for several years, I often meet people confused by these ideas but also looking for ways to get started with self-tracking and data-driven self-improvement. I often get asked:

What should I track? What’s the most beneficial area you’ve found for tracking? What have you learned or changed in your life since tracking? How can I track my time and productive? What should I use to monitor my health or fitness? What wearable do you recommend?

For anyone getting started with tracking or quantified self, my go-to recommendation is Awesome Quantified Self. This is an open source and curated list of the best resources, devices, apps, wearables, and tools for self-tracking (Confession: I’m a contributor and maintainer on this project). For new and experienced alike, this list is a great place to find tools for tracking different areas, like health, time, productivity and more.

Unfortunately the list of option can still be a bit intimidating, especially for a beginner. There are a lot of big categories and multiple tools and apps you might use in each. Choosing the right one can be hard. The list also doesn’t really offer a way to conceptualize and frame the overall quantified self and self-tracking space.

To remedy this, I created my own mind map of quantified self and self-tracking tools and technologies.

You can find the code and complete editable description here: https://github.com/markwk/qs_mind_map.

An interactive and editable version is available at https://coggle.it/diagram/WzGmNxN_zxZw9MbF/t/quantified-self-self-tracking.

A Quantified Self and Self-Tracking Mind Map: Three Core Areas

While there are various definitions out there, I define the quantified self and self-tracking as:

measuring or documenting something about your self to gain meaning or make improvements

In short the objective is to not just track and collect data but to use data towards goals, like better self-understanding or optimizing your self-improvement. This separation of tracking and engagement lies at a key distinction I made in mind map.

Personally, I divide the quantified self technologies space into three core areas:

1. Tracking Tech: Health Tracking, Digital Life Tracking, Wearables and Sensors
2. Data Collection and Data Analysis: Ways to aggregate and engage with your data.
3. FutureTech

Leaving aside FutureTech, by which I mean a rather open space for biotech, infotech, biohacking, cyborgs, etc., the key point is the difference between the way we track and the way we use that tracking data towards what we want to acheive. In fact, without engagement you really can’t expect much benefit or changes by tracking alone.

Remember: Data and tracking is most effective with data engagement

For me (and my mind map of the quantified self), there is an operational distinction between 1. methods that help us track and collect data and and 2. ways that enable us to engage and use that data.

This distinction is not insignificant since I often hear people complain that having a wearable or using a tracking tool didn’t change their life. There are also academic studies that report to show that wearables were inffective by themselves at changing health outcomes and human behavior. To be honest it’s not really suprising that a wearable alone doesn’t lead to much in the way of health or behavior change. It’s just a tool.

The reality is that wearables and tracking tech doesn’t and likely shouldn’t work without a certain amount of engagement. Much like just buying books on a topic doesn’t result in you becoming an expert or PhD doctorate on that subject, owning a wearable doesn’t magically make you healthier, more productive, etc. A wearable is an opportunity to better understand and improve an area; but you still have to do the work.

For tracking tech to work you need to be engaged. For data to be meaningful, actionable, and life changing, you need to be actively involved.

As such, data and tracking is most effective with data engagement, and a wearable or tracking app is best utilized as a tool to help and support you in pursuit of that goal or life change. Tracking data provides feedback on the area you are trying to understand or improve.

In fact, as a recent study on wearables showed (Stiglbauer, 2019), it’s not whether you had a wearable or not that improved health consciousness, but whether you engaged with that steps data through the app. Health consciousness improved not as a function of having a wearable but in whether you looked at the data in the app.

For me this shows how significant data engagement, data analysis and data visualization can be to an effective data-driven life. While I don’t think or expect that everyone needs to become a data scientist, it’s important to go beyond tracking and engage with your data. Even using a spreadsheet can be a great start.

With that distinction in mind, let’s now look at a few of these branches in more detail.

From Tracking to Data Engagement: An Outline of Quantified Self and Self-Tracking Tools

NOTE: The intention of this section is not to provide a comprehensive list of tools. For that purpose, I recommend you check out Awesome Quantified Self on Github. Instead, I will do a high-level walkthrough of going from tracking to data engagement with some links to specific posts I’ve written additional guides on.)

It bares repeating: If you expect self-tracking to help you, you need to be engaged.

Whether you want more objective self-understanding, data-driven personal development or a way to optimize goal pursuits, self-tracking should be coupled with a form of data engagement. For example, this might involve looking at an app that aggregates and contextualizes the data or it might involve collecting the data yourself and looking at it in a separate program or tool.

1. Tracking Tech: Health Tracking, Digital Life Tracking, Wearables and Sensors

The options and technologies for the tracking a life is nearly endless, and it seems like almost everyday there is a new way to collect data about yourself. For me the primary way I divide up ways to track is like this:

Health and Fitness Tracking

These are basically ways to monitor your body. Health tracking can often be separated between ways you track your health status, like medical tests, and methods to measure your health activity and fitness, like activity and sports tracking. Some key areas are:

• DNA, Genetics, Microbiome: I got my DNA sequenced using 23andMe many years ago and have yet to see much benefit, besides knowing my caffeine metabolism type.
• Blood Testing and Biomarkers: I believe blood testing is one of the best metrics of tracking your health status and I’ve written a lot on the topic A good starting point is [Know Thy Blood: Common Questions and Answers about Blood and Blood Testing]](http://www.markwk.com/blood-test-faq.html). I’ve also created an open source directory on blood testing biomarkers too.
• Body composition and weight
• Heart: It’s easy to track your heart and heart health with a wearable. Personally I’m a huge believer in Heart Rate Variablility as a biomarker into my chronic stress and training adaption. I also think the ease of Blood Pressure Tracking makes this something good to check periodically.
• Sleep: If I had to recommend a single health area to track with know health and cognitive benefits, it would be sleep. It’s quite easy to track too, and I’ve also written a short sleep tracking guide too.
• Diet, Food and Fasting (as well as glucose and metabolism): I find food tracking to be one of the harder areas to track regularly. I’ve done a few experiments with food tracking, especially with just tracking food on a high-level (healthy vs. unhealthy meal, etc.). It appears that fasting or modifying your eating window shows promise for your health too.
• Fitness and Activity Tracking: Activity and fitness tracking is arguably the most popular way people track their lives. Whether you use an Apple Watch to Self-Track or some other wearable, running, cycling, sports, lifting and even mobility can all be tracked. Personally I use an AI coach to manage my marathon run training.
• Mood: I’m hopeful that one day we might find a way to automatically detect our moods. I even did a mood tracking experiment myself.
• Meditation and Mindfulness: I’m currently experimenting with the Muse Brain Sensing Headband to track and provide real-time feedback on my meditation. It’s also an interesting device to potentially understand my brainwaves too. In the past, I’ve used a number of meditation apps, including Calm and Insight Meditation to track my meditation sessions as a habit.
• Mind and Cognition: The best tool I’ve found here is quantified-mind.com, which provides a free platform to A/B test your cognitive enhancement self-experiments using research-backed psychology tests of your reaction time and memory.

Digital Life Tracking

For me, basically everything that doesn’t include quantifying your body is covered under the rubic of life tracking. Typically it involves platforms that automatically digitalize aspects of your life, like time, finances, movements, etc. or tools that help you do or organize your work while also provide usage logs and statistics.

• Time: I’m a huge fan of time tracking using RescueTime and Toggl as well as keeping a log of my mobile phone screentime and YouTube watching. I wrote a guide on creating a time dashboard with RescueTime, IFTTT and Google Sheets.
• Productive Activity: Besides time, I find it’s a good idea (and easy) to track my organizational processes too. This means my tasks, goals, projects, calendar, habits, etc. I’ve used Todoist to track my tasks for sometime, and it’s a great overall GTD tool with multiple ways to get your data. In terms of habit trackers, I’ve used several over the years, including Habitica. My current habit tracker is Productive on iOS, since it’s simple and reliable. When it comes to goal tracking, there are a lot of different ways you might do this. I currently using AirTable to track and manage my goals and long-term projects.
• Digital Logs, i.e. Email, Facebook and Google usage logs, etc.
• Media Consumption: I track my book reading with Goodreads and Kindle Highlights (here is my write-up). For articles, I use Instapaper and especially like the ability to export my highlights. Last.fm lets me track the soundtrack of my life and I suspect I could even use it to guage my mood too. I log podcast listens using PodcastTracker.com.
• Money and finances: I use Mint and a manual spreadsheet to track my finances.
• Location, movement and places, i.e. GPS: I previously loved and used Moves as GPS location logger, but since that service was canceled a few years ago, I no longer have a go-to location and movement tracker.
• Tally and life logger tools: For lifelogging and ad-hoc tracking experiments, I’ve used tools like Nomie, Hindsight and Reporter. Google Forms is also a good way to track too.

Wearables and Sensors

Wearables and sensors are essential bridges between our bodies and environments and digital information. Increasingly wearables provide a one-stop shop for digitalizing what goes on in our body, like sleep, movement and even mood. In turn, home sensors help you know about the ambiant conditions around you.

• Wearables (ex. Fitbit, Miband, Apple Watch, Garmin, Oura Ring)
• Environmental Sensors (ex. weather, temperature, air quality, etc.)

I currently use an (Apple Watch as my primary Self-Tracking tool)[http://www.markwk.com/apple-watch-for-self-trackers.html]. I’ve had success with Fitbit and especially find it easy to get a reach data set from their API. Xiami MiBand is a great option and cheap, though it isn’t easy to get data from it without sending data first to either Apple Health or Google Fit. Oura Ring appears to be a great and popular option among biohacker, though I’ve found the Oura API to be a bit limited due to how it stores timestamped data.

In any case, most any wearable should work to track activity, steps, heart rate, and sleep. Wearables that use Heart Rate Variability can be great to know more about your health, wellness and stress.

2. Data Collection and Data Analysis

One of the key aspects of self-tracking that gets neglected is engaging with what you are tracking. While it’s a lot of fun getting a wearable or setting up a new way to track, that’s really just the start of the journey in turning self-tracking into self-transformation.

If it’s a new area, this might involve an initial period of tracking, followed by some data exploration. Oftentimes this will result in setting some kind of goal. You, in turn, use your tracking data to get feedback on your goal pursuit.

Similarly, you might use an array of personal tracking to provide an overview of your health, productive and more. This can then be used in your weekly review or goal tracking.

While there are a lot of ways to collect and do data analysis in the quantified self space, three areas are worth emphasizing:

• Automation (i.e. data connectors and integrations): It can be a challenge linking together services and collecting data between services. Fortunately, automation tool IFTTT can be combined with many tracking tools to make it easy to aggregate data. For example, I personally use it to pool my Fitbit, Todoist Tasks and Strava activities into Google Sheets.
• Aggregators & Dashboards: Several apps and websites exist to help you see all of your data into one place, like Gyroscope, BetterSelf or Exist.io. There are also open source tools and code, like QS Ledger, can facilitating data collection and data visualization. For example, I used QS Ledger to create my year in data.
• Data-Driven Tools and Bots: There are a few tools today that take tracking data and apply it to actual advice and engagement. For example, Lark is an activity chatbot and TrainAsOne is an AI running plan coach. As technology advances, I expect to see more tools and services that leverage data towards targetted coaching and personalized health.

Beyond these cookie-cutter approaches, there is a lot of power and potential in do-it-yourself solutions. You don’t need to be a programmer or data scientists to do it either. IFTTT can be used to pull data into Google Sheets from different tracking services.

You can then use a spreadsheet app to create a simple dashboards or use more advanced data dashboard tools like Google Data Studio or Tableau. Furthermore, if you have basic python data science skills, my open source project QS Ledger provides a number of starter notebooks for data collection and visualization too.

Whatever method you choose, if you want to make your self-tracking most effective, find a way to regularly engage with your data. It’s arguably the best way to transform self-tracking into data-driven self-improvement.

3. FutureTech

While I think it’s a topic left for a future post, in my conception of the quantified self space I leave open a third core thread for FutureTech. For me, this is where science fiction meets reality. I separate this from existing data tracking tech and data analysis tools, because it is in many ways a fusion of the two and a new thing onto itself.

Some examples might include Biotech / Infotech, New Sensors on the body and in the environment, Neurofeedback, New Data Usage (like using Siri or Alexa data to detect mood), Shared and Collaborative Data (like taking group data to provide collective insights and trends), Biosensing (tools that create new sensory awareness) and Biohacking (where you use data and human augmentation tech to go beyond current human capacities).

Overall, this is an exciting area but still too early to say what it will become. Thus, I’m calling it FutureTech!

Conclusion: Ask a Question, Find a Tracker, and Engage

In this post we looked at my organization and conceptual of the Quantified Self space using a mind map. For me the key distinction is between tools to track and collect data and ways to engage and use that data.

For me, the core of the quantified self movement and idea is nothing new. It goes back to early Greek thinkers and philosophers and the quest to “know thy self.” The major change is we have tools and technologies that help us to do that in new and interesting ways.

Personally, I find the most beneficial way to use these tools and technologies is through an on-going process. First, I find or ask a question. I then do research and use tracking tools to collect some data. After awhile I then look at my data to better understand myself. Where am I at? What and how am I do? Finally, I set a goal and start a process of self-improvement with data-driven feedback. Throughout the process I engage and learn and, ultimately grow.

Best of luck on your journey and happy tracking!

Sources:

• Quantified Self Mind Map, available online at https://github.com/markwk/qs_mind_map.
• Awesome Quantified Self, available online at https://github.com/woop/awesome-quantified-self.
• Stiglbauer, B., Weber, S., & Batinic, B. (2019). Does your health really benefit from using a self-tracking device? Evidence from a longitudinal randomized control trial. Computers in Human Behavior.