#8 Quantified Self Dashboards

Here are some dashboards that I came across:

Advertised as “OS for human body”, Gyroscope is a mobile app that connects to a wide range of other apps to integrate personal data. It offers three kinds of visual interfaces to the users to help them make sense of their own data, namely shareable cards, weekly reports and monthly reports, some of which are for paid users only. The founder of Gyroscope, Arnand Sharma used this app to create a dashboard of himself to share with the world (Arnand Sharma):


The data integrated in this dashboard includes:

  • Foursquare
  • Moves
  • Runkeeper
  • Strava
  • Fitbit
  • Withthings
  • Instagram
  • Twitter
  • GitHub
  • RescueTime


#6 Potential research questions

Research question

  1. Can quantifying, collating, communicating and displaying data streams for smart citizen bring benefits to a smart city?
  2. Can quantifying, collating, communicating and displaying data of an individual change how he behave?
  3. Can we encourage smart citizen’s behaviour by quantified self and gamification?



Test group: quantify-selfer

Control group: non quantify-selfers

Contribution to knowledge

New insight to smart citizens

Past academics “Quantify self” academic:

Health care – Fitness level, Asthma, personalised medicine

Gait – Walking styles

Gamification of quantified self

Safety issue in quantifying self

Existing quantified self papers:


#4 Collating personal data

Currently, personal data is generated and kept in various apps and devices. Although each app may has its own interface for data visualisation or even has an API for data extraction, there are relatively limited tools to collate and connect personal data in different tools.

IF This Then That (IFTTT)

For most app business runners, it is not common to develop apps that relies on other products due to reliability issues. IFTTT Inc, however, offers a free web-based service (If This Then That) that people use to create chains of simple conditional statements, called applets. IFTTT aims to help people do more with all their apps and devices.

#3 FitBit Charge 2

Today I received the FitBit Charge 2 wristband. This wristband is a main data source for physical activities data in the research. This lovely product from Fitbit features heart rate and sleep monitoring in addition to the usual steps tracking.

While most of the tracking is automatic, there are still some data which is relatively hard to get hold of in the Fitbit app. The food intake, for example, require logging in the food type and amount manually for any food without a proper barcode that can be scanned to get those information. The inconvenience and randomness in the logging is likely to make the tracking less consistent and accurate. As a result, the calories in and out becomes a rough estimation. Similarly, water intake is another data that require manual operation from the user. This data is easier for the user to log as most drinks are sold with volume stated on the container and people tend to drink with the same container for hygiene reasons. Researchers from Singapore Management University have taken research to address this problem. Prof. Archan Misra has programmed a smart watch with camera to automatically detect the eating gesture and take a few photos of the food. Then the backend of the system runs image recognition over the images sent back by the watch and present the best possible photo to the wearer. His study supports the hypothesis that making people aware of what they are eating with a photo of the food contributes to weight control.

fitbit screenshot

A screenshot of Fitbit Windows Desktop

The weight of the user is another feature that requires more efforts to track as it requires a smart scale as an additional sensor to the wristband or watch. Still, a smart scale is helpful in terms of keeping tracking of the personal weight data.

As for the sleep monitoring, I’m going to test this feature this evening.

#2 Available Personal Data Sources

Obviously, the fundamental element of the “data driven diary” concept is personal data. Here I keep logging any tools I find for personal data collection.

Wearable fitness tracker

Nowadays we are witnessing personal data sources emerging one after another. Fitness tracker wristband has become popular among young people.

fitbit band

Fitbit Surge Watch. Courtesy: Fitbit

For example, Fitbit was found in 2007 making fitness trackers with the same name. In 2014, Fitbit announced annual sale of 10.9 million devices. In my case, I will be wearing a Fitbit wristband to keep track of my daily physical experience including activities, exercise, food, weight and sleep. The most interesting bit is the data collected by the tracker can work seamlessly with Google Sheets with the IFTTT as the bridge to connect the two apps. An IFTTT recipe syncing FitBit tracker can be found to make this happen in a click. This is a perfect example of how the data driven diary concept can be turned into reality effortlessly. With IFTTT as the hub of sync and gathering data from different apps, we can create a dashboard visualisation to summary almost all aspects of our daily life. The advantage of doing the collection is obvious – keeping everything at a glance is much more user-friendly and time-saving than viewing summaries from several apps, Twitter, Fitbit, Facebook, Linkedin, Uber, just to name a few.


An IFTTT recipe for syncing Fitbit tracker data. courtesy: IFTTT

Jawbone UP, one of the competitors of Fitbit, features food tracking and weight losing with an app where users log their meals and the app scores the food according to the nutritional value so as to help users make healthier food choice. Fitbit also has similar functions. In addition, Fitbit allows users to set up a food plan and estimate their calorie consumption and intake. Logging food intake is made easy as any food with a barcode can be scanned directly. The Fitbit app even produce a macronutrients dashboard to show a breakdown of the overall nutrition.


Jawbone Up mobile app showing nutrition value of food. Courtesy: Jawbone Up

Intelligent Personal Assistant (voice based)

The idea of Intelligent Personal Assistant (IPA) was first presented to the general public during the 1962 Seattle World’s Fair by IBM with a computer capable of speed recognition. After being developed for more than half a century, IPA starts to become affordable and popular in the market. Amazon Alexa Echo is a most popular IPA which is constantly listening to the requests and performing tasks upon request. In this project, I plan to turn Alexa into a speech collector and capture my own voice data.


Amazon Alexa Echo IPA. Courtesy: Digital Trends 

Chronos – turn your passively collected data in smartphone into actionable insights.

Different from other mobile phone calendar apps, Chronos takes record of how the user spends his time while running quietly, even without lifting a finger. The founders hope users can live in a more intentional way by reviewing our activities. It more or less looks like a diary full of photos, resembling Facebook/Twitter timelines in some sense.


A screenshot of Chronos app. Courtesy: Chronos

Quantified Self / Lifelogging project

While looking for the tools to collect personal data, I came across several projects which collecting all sorts of quantitative and qualitative data about “yourself”.

Google Chrome Browser Plugins

For monitoring the pattern of my online activities, I found some useful Chrome browser plugins to tracking the websites I visit and the time I spent on them. The advantage of the plugins is that they can be used cross-platform on any devices – tablets, mobile phones, desktops, anything that has Chrome browser. This will allow me to track almost all my online activities. Still, any time spend in a particular apps or in-app browser won’t get tracked by these plugins.

  • Youtube Stats
  • TimeStats – Chrome browser plugin to track the time spent on any website


Psychology Care


Mood Logging

Active OS

Dashboard and Integration of Personal Data Collection, formerly known as TRAQS – case study Porsche Macan Driver Heartrate data and location.


Biometric information, continuous and personalized insights into their body chemistry


Apart from fitness trackers, there are other tools for tracking our daily activities:

  • Smart home – Smart Things,
  • Traffic – Uber, Google Maps, CityMapper
  • Social media – Twitter, Facebook, Linkedin, Google Plus, Instagram
  • Photos – iOS Photos
  • Calendar and performance – Google Calendar
  • Shopping – Discount and sample sale website notification / email alerts
  • Browser history


#1 Welcome to Data Driven Diary


This is the experimental site of my triple D concept – Data Driven Diary.

This idea comes to me after reading the shocking fire disaster of Grenfell Tower in London. As I live in a similar ex-council block to that big block, I start to worry if I suddenly die in such an accident, I will be eliminated from the world like a USB memory stick being formatted. After searching my name in both Google and Baidu (biggest search engine in Chinese language), I’m convinced that I haven’t yet done anything great enough for adding my name as an entry in Wikipedia or anything alike.

So what is the mark I left to the world about “me”? Apparently, there is some presence on the public presence on Facebook, Twitter, Sina Weibo, Wechat and Instagram, Linkedin etc like most people have. but how about other things like height, weight, hobbies, dream, emotion, achievements, fitness, places I’ve been to etc.? Unless we upload it to a network drive (either cloud storage or social media), these information will be lost forever. Fort the most influential people, there are journalists like Stefan Zweig who try to collect every piece of information and write a biography for them in his book Decisive Moments in History. The ordinary people, however, won’t have such privilege. For most of the victims of Grenfell, sadly we don’t even have any official records to confirm who are missing, not mention how they lived their life.

Posters show images of people missing after the Grenfell Tower fire. There is frustration that there is no official database of survivors. Photograph: Paul Ellis/AFP/Getty Images, Courtesy: Guardian

I start to think if there is an effortless automated way of  keeping a diary of  anyone who wishes to do so. Fortunately, with the advance of technology, the trace of how we lived every day is turned into data which is easy to upload and store. With sensors and browsers constant keeps track of us, there is a widespread privacy concern but it also offers us a new opportunity to review our activities without having to spend a few minutes a day to write a diary. For example, if we combines the location data, the calendar data, the photo album data, the electronic receipt, the Oyster card data altogether, we pretty much get a picture of how we spent last 24 hours. Certainly, we can add fitness data, browser data and other stuff on top of that.

The idea of Data Driven Diary (DDD) is to create an automated process of tracking, displaying and sharing how we lived our life, which serves as a diary for the person being recorded to review his activities and as a biography for others to get to know this guy. Even if no one bothers to read, the DDD by itself is a proof of a life ever on this planet. The challenge of this idea is the access to the data created by us but locked up by separate apps. Fortunately, there has been efforts made by tech gurus to make the data previously locked in a single app to talk to other app, e.g. IFTTT (If This Then That). DDD is also my ongoing PhD project. Therefore, apart from the technical output, I will also write on the academic contribution to knowledge, which I have to figure out…

Diary entries for 5th – 30th January 1809, Dr Thomas Lucas of Stirling

An example of a dairy of someone who is not decisive in history: Diary entries for 5th – 30th January 1809, Dr Thomas Lucas of Stirling
The pages shown are taken from the diaries of Dr Thomas Lucas, surgeon in Stirling.  The Archive holds two of Dr Lucas’s diaries, and also a Memorandum Book.  The diaries contain everything from day to day news in the town, to comments on Dr Lucas’s friends, family and business acquaintances, to international affairs and even the state of the weather. Courtesy: Stirling Local History Society and Stirling Council Archive

All in all, I’ll use myself as the first case study of DDD, creating a automatic tool to collate all the data I can gather about myself and present in both narrative and statistics. What will happen when I have a chance to review my daily life and others have a chance to know me with DDD? We will see.