Overview of aggregators for Quantified Self data

written by Erik 04/26/2016
aggregators quantified self

Collecting the data mentioned in the previous post is one challenge, but another is how to aggregate all the data to one source to prepare for analyzing. For this we need an aggregator, or to create one of our own. The analytics for My quantified Mood will then most probably be done with a statistical tool such as IBM SPSS.  Lets have a look at what solutions dedicated to the task of aggregating and analyzing data that are available.

The need

The optimal thing would be an app or software that collects all the quantified self data from various sources, puts it into a nice interface and makes a mathematically correct correlation analysis on the go. Even though there are things trying to do this, turns out there isn’t one doing all this seamlessly available. So, the best solution out there seems to be to find apps that allows exporting, and then do multiple exports and collect all the data in en excel sheet.

Services that aggregate and analyze data

Many apps collect your data and make sense out of it. Lets have a look at the ones I found most interesting.


addapp aggregate data

The AddApp interface

AddApp focuses on giving you “personal tips to get healthier”. You connect your devices and apps, such as Fitbit, Apple Health and Runkeeper, and with regular interval the app presents you insights  based on your data. It’s a pretty limited service, but still really likable. AddApp have succeeded in making a simple and good-looking app doing one thing and making it fun. On the flip side, the insights I’m getting are quite repetitive and sometimes it seems like they make up facts in order to come up with something new (I don’t even own a bike at, so those bicycle insights seems pretty fake). Also the data export option is lacking, and the number of services that can be connected is quite limited.

But still, this is a keeper, not for this project in particular, but because it looks nice and presents interesting and fun facts in an appealing way.


I tried Exist in early February and back then I found it had lots of issues, but now it looks like a whole other story. Not sure if they changed a lot since then, or if I used it in the wrong way the first time around, but this time it looks great. The heart of Exist is a web

exist aggregate data

The Exist dashboard

interface where you can connect services such as Fitbit and last.fm, with both iOS and Android companion apps. They collect and show your data on a dashboard, and make correlations and – I think – recommendations. There is alos a mood tracking function in order to  make correlations with the rest of your activities. On top of that I am also allowed to export my data, in jSon format. All that sounds pretty awesome to be honest, and very close to the purpose with this blog.  The service offers a free month and then costs $6 / month or $57 / year.

I didn’t see this version of Exist last time, so I will give Exist another go and write up a proper review in a few weeks time.


Tictrac aggregate data analyze

The old TicTrac dashboard

TicTrac has been around with a neat web dashboard where you can connect and collect your data and get a nice overview. The unique feature was that they offered a huge collection of measurements to be added to that dashboard, including a calendar to add how often you have a cold, measurement of excitement and how good your posture is. Some of this data was fetched from one or more of existing services, and some you had to fill in directly into the web interface or the companion app. They also offered a one-button export function which directly took all your data and put into a Excel sheet. This seemed like the perfect data aggregating service, if only it would have been continued.

However, they are currently working on a new beta version, where they also include analytics, health challenges in parallell with the dashboard function. So far in the beta version the measurements offered are dramatically fewer than in the old version, and the data has to be fetched from existing wearables or apps. The old version is still up and running, but naturally most efforts from TicTrac are put into perfecting the new service. Some of the bugs in the original version will probably never be corrected, which is a shame on such a good service. I’ve tried the new beta version as well, and it has good potential, although is at the moment in an obvious beta state. Looking forward seeing what comes out, and I’m hoping for something similar as the old version.


And now we’ve come to a tool I really like the concept of: Zenobase. A really powerful, great and free tool, but with quite

aggregator zenobase analyze data quantified self

Regression analysis of time listened to singer-songwriters and sleep duration

bad user-friendliness . It’s a web based platform where you can use data from other apps and devices to analyze your data in the way you want. Although doing the same thing as AddApp, they are really far apart. Contrary to AddApp, Zenobase offers maximum customizability in a confusing interface.

However, after watching youtube-tutorials (still hard to really get it, but slowly I understood how I was supposed to handle it), I got a hang of how to do regression analysis. So, I now know for a fact that there’s a negative correlation between how much time i spend listening to singer-songwriters and the time I sleep the next night. Zenobase is worth the effort just for the ability to make those quirky analyses, which can be quite addictive.

Zenobase is great for projects demanding vast amount of data given that you can fetch data from a lot of services, and get a level of detail that few other services offer. Given that it’s not the most user-friendly tool, consider if you are willing to take the time to learn it. For me it’s a keeper, if nothing else so for the ability to download my last.fm-data in great detail for music listening history. IT also has a nice feeling of coming from a couple of enthusiasts who have put together an interface for everyone to use, without much interest in making a business out of it. Zenobase is free, but if you want to add a lot of data, or just support the service, there’s a $5 / month premium version.


Fluxstream aggreagtor

Fluxstream “clock” view

Similar to Zenobase, Fluxstream seems more like a service provided from some Quantified Self enthusiasts than a commercial company, which is confirmed by communicating it’s non-profit and open source profile on the web page. So it’s free, but I found it really hard to make anything out of it. I get presented some overviews of the data I fetch from other services, but it’s tricky to understand how to use it. Zenobase was also hard to use, but at least there I understood what I could achieve if I understood it, whilst with Fluxstream I don’t see how to try. Also, it seems to get stuck a lot in updating mode, so maybe there are good things under the hood that would be shown if working properly. If you have any good experiences from it, please let me know.

Services that aggregate data

If you want to analyze the data by yourself, the most helpful thing would be a service that justs aggregates data into a unified format. Except for the bundled ones in smartphones there aren’t any dedicated services for this task, but IFTTT has some functions that are useful.

Apple Health

Apple Health and Google Fit are the two obvious aggregators of health data, and being an iOS user. apple health quantified moodApple Heath has a good approach and wants to function as the aggregator of all your health data, without – at this point – making the actual analysis.

The app which comes preinstalled with iOS connects with various sources to collect and share health data. You can also export it directly, or use one of the third party tools to get it exported in a more appealing format, such as the QS Access App. The pros and cons with this, as with most other things coming from Apple: It’s good at what it does, but you can’t customize it or make it do anything it isn’t specifically designed to do. There are quite a few services that don’t export to Apple Health (why Fitbit, don’t you export to Apple Health??!!), and there are also quite som useful measurements missing.

This is still probably the best starting point for creating a quantified self dataset for analyzing. Export data from Apple Health with the QS Access App is a breeze, and then it’s quite ease to keep using the same format to fetch data from the other services that are does not export to Apple Health.


IFTTT (IF This Then That) is a really cool services allowing you to connects apps and services and then make recipes to automate your life. This could be simple things like “If forecast says

IFTTT aggregator data quantified self

IFTTT screenshot

rain tomorrow send a text to my phone” or more advanced such as “When I get close to my home, turn on the lights and start my favorite music”. Having created connections with lots of services, there is a lot of data to fetch, and luckily they have also created a connection with spreadsheets in Google Drive. So you can create recipes fetching data from various sources (such as weather, Fitbit or Spotify) with certain triggers (easiest is to just choose a set time very day) and then get that data into a spreadsheet. For people interested in quantified self you could for example use this to detect location with the app Moves, reading the weather on that location and save it into a google spreadsheet at 18:00 each day.


There are lots of services wanting to help you analyzing your data, and some of them does it really well. Apple Health is a good foundation for exporting data. I will personally also keep AddApp because it looks nice and is fun, Zenobase because of it’s exporting functions of data that is hard to get elsewhere and IFTTT due to it’s capability of capturing external events such as weather. And then I will definitely give Exist a serious try over the next couple of weeks.






You may also like

Leave a Comment