Decoding data visualizations: #oneSecond by Philipp Adrian

#oneSecond is a project by Philipp Andrian showing a connection between 5522 people on Twitter across the world within the same second. In this interview, he explains why he decided to start the project, where the data came form and which tools he used.

How did you come up with the project?

The project was part of a publications class at the basel school of design ( where I studied visual communication. The assignment was very open –  the only premise was to create a (printed) publication in any form, while topic and content of the publication were up to each student. For me, the fascination of books is their permanency. Once printed their content is preserved and available in the future for everyone to read. Also, after printing, the book is finished, there can’t be any changes or additions anymore. This suggests putting a lot of effort and thought into what to print in a book because whatever is printed will be preserved for the future and by that is gaining value since it has been deemed valuable enough to be put into a book. Social media on the other hand is quite the opposite, nothing that is posted, is meant to last forever. By allowing everybody from all over the world to post content without restrictions, it becomes a melting pot of different cultures that changes constantly and is so immense that nobody is able to grasp or process the whole thing. New content gets drowned by new content and everything older than a few hours (at max) gets melted together in a vast data cluster that is not really accessible in the future and a single piece of content is forgotten in the instant it leaves the screen.



The idea of my project was to combine the two opposite worlds and to use the phenomena that I observed and felt about books. I wanted to preserve a single random moment of social media and by documenting this moment into a book making it special and making it worth being put into a book. Through stopping the time and preventing the content from this second from being drowned by new data the project allows us to inspect and explore this special moment and the people that where part of it.

Please describe your workflow: how did you proceed?

I first had to find a way to get all the data of one second on Twitter and I needed to know what information I would have for each tweet in order to create a proper presentation for this data. After collecting every piece of information I was able to find for each tweet, I restructured this data into four books and designed the layout for each. I knew now what would go into each book so the next step was to create all the assets I needed for the design like QR-Codes of all the links that were part of the tweets, as well as infographics and maps with markers for each tweet. With all the assets prepared, I used InDesign scripting to fill in the data and assets into my layout. It was possible to create the whole book inclusive the index with page references to every tweet through InDesign scripting. After generating the books, some pages needed manual fine tuning before exporting them into pdf and sending them to be printed.



Which data did you work with and how did you get access to it?

Since I needed one second of twitter, I started to look for my data at the Twitter API. While it is possible to get a lot of data on one single tweet, it turned out that it wasn’t possible for all the data of a certain time period. I had to look for another way and finally found Datasift where it is possible to filter and buy publicly generated data from different social media platforms including Twitter.
Datasift offers a pay-as-you-go plan so that it is possible to buy relatively small amounts of data on affordable conditions. You can choose a source and then set different filters that define which tweets you want to buy. Since I wanted to get ALL the data during a certain timeframe I set no filter and like that got all the data I needed.I now had over 5000 tweets that were sent within the second I chose and for each one I had the tweet ID. With an easy call to the twitter API for each tweet, I was able to get all the data associated with that Tweet.
In order to normalize place information of where the tweet was sent form I used the Google Maps and Foursquare APIs to translate Place names into Coordinates.
With the coordinates I used the Askgeo API to get informations about the timezone the user was in:
These were the services I used to collect data automatically. I also went through all the data manually once to define the language of each tweet and categorize the users avatar. This whole process involved a lot of data crunching, which I did all in PHP.
Which tools did you use to visualize the data?
After knowing what data was available to me, I designed the layout and infographics of the books in InDesign. To create the QR-Codes I used a PHP-Library called PHP Qr Code ( And to create the timezone maps I used a a program called TileMill ( After creating all the assets I used InDesign scripting with some help of the basil.js library ( to fill the data into the layout and generate the infographics directly in indesign.

Interview by Natalia Karbasova for the Open Data Hack Day blog Read more about the project #oneSecond here.

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