LifeLogger @ BarCamp Pune 3

| July 9th, 2007

A couple of things have kept me away from blogging in the last few weeks. One of them has been about organizing BarCamp Pune 3 and the other my latest ‘weekend project’ – LifeLogger. I presented the concept behind LifeLogger along with a small demo, yesterday at the Barcamp. I received some really good feedback along with a dozen questions about the project. The audience appreciated the idea and I hope I got them thinking about how powerful their data (however trivial) could be.

This time around we crossed the 250 registrations mark at the camp. There was a considerable improvement this time in overall planning and the level of the sessions. Thankfully, technical sessions dominated the event as compared to advertising sessions in the last camp. We are definitely getting better with each event.

This event couldn’t have been successful without the help from the sponsors: ThoughtWorks for the tshirts, Persistent for the venue and hospitality, Codewalla, Bookeazy and AsianLaws.org for their support.

Coming back to the LifeLogger, here are a few screenshots of what the application looks as of today:


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The screenshot above displays the main interface for the LifeLogger UI. Along with the option to search/browse your data, it also provides a graphical representation of the system (i.e. number of searches, browse, blogs read etc for the user).


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The screenshot above displays the search results from the users data. The results are visually depicted in different colors, with each color representing one of the disparate sources (bookmarks/blog/browse URL/search) of the data.

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The screenshot above displays the date range browse feature. Various graphs help the user visualize his browsing/reading/search patterns along with the results.


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The screenshot above depicts the browse results for the given date range in the descending order of time.


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One of the cool features of LifeLogger is that when a user browses his data for the date range equivalent to a single day, LifeLogger looks back at the web history data for seven days prior and estimates which URL’s visited during that day are aberrant to the users daily browsing pattern. These results are then displayed separately as ‘Interesting picks of the day’ along with the browse results. These results summarize the key events day.

If you are still reading this post you can learn more about LifeLogger at its homepage. I would love to hear your feedback/suggestions.