Funf Journal is an Android application for researchers, self-trackers, and anyone interested in collecting and exploring information related to the mobile device, its environment, and its user's behavior.
This application was originally developed by the Human Dynamics research group at the MIT Media Lab, and is currently maintained by the Behavio team. Funf Journal leverages our experience in developing and deploying social and behavioral sensing applications for mobile devices.
Important Note: Funf Journal is still in early development stages ("alpha").
This app is built to collect your personal data so that you can analyze it. An example analysis can be found at http://funf.org/journal.html
Funf Journal allows the user or researcher to configure data collection parameters for over 30 different built-in data probes, including all phone sensors, as well as additional data types and high-level probes that generate inferences and new data based on the output of sensor data. The app supports importing and exporting of probe configurations, as well as remote configurations (with user permission).
Based on the configuration, the probe data is automatically collected as the phone is used during a user’s everyday life. The data is securely stored on the phone in an encrypted format (you will be asked to select the encryption password when the app is first launched).
The data can be extracted from the phone in one of several ways - by manually exporting it via email or any other Android service that supports file transfer, by manually copying it out of the device's memory card, or by setting up a server and configuring Funf to automatically upload the data to it - and if Internet access is not available, the app will accumulate data on the device's memory card and wait until it is back online. When a server link is set up, the data collection configuration could also be performed remotely - the app will check the server for new configuration instructions for download.
Once the data is extracted from the phone, we provide a set of desktop utilities that allow decryption of the data, demonstrate some examples of visualizing and looking into the collected data, and also produce a clean database (in SQLite format) that you can use for further analyzing and exploring your data as well as for importing data into other applications or services.
Funf Journal is built using the Funf open source sensing framework, which can be extended by developers and used to quickly build new applications that make efficient use of sensor information and other data rich features.
IMPORTANT NOTE: All of the collected data is in your domain - your Android device, and wherever you might choose to export your data to. You alone have access to it and decide what is done with it. We have no access to any of the data.
Human Dynamics http://hd.media.mit.edu
- Updated to v0.4 of Funf!
- Increased security and reduced memory footprint
- Improved and more responsive UI
- Now supports full configuration available in Funf v0.4
- Several new probes (Accounts, Simple Location, Continuous Location, TimeOffset, Services, Process Statistics)
- Updated data format
- and of course, bug fixes