[Made in Rennes] Data BZH, UX in the spotlight, and events not to be missed
Harriet Bartlett, correspondent Frenchweb: Hello Colin, you are the founder and editor-in-chief of Data BZH, can you explain to us what Data BZH is?
Colin Fay, Founder and Editor-in-Chief: Data Bzh is a collaborative data blogging platform that aims to highlight the Breton territory through its data. The objective is to simplify access to information on Brittany via open data, by analyzing and visualizing it, to make it understandable by all.
We are also working to simplify and demystify topics related to this area, in particular through the writing of popularization posts. Data BZH is also a producer of data, via data collection on APIs or by making data available from social networks.
Where did you get the idea from?
Data BZH was born from the observation that the concept ofopen data has taken an increasingly important place in recent years, both among officials and the general public. And in particular in Rennes, a city which has been a pioneer in France on the subject.
On the other hand, the citizen is not always an expert in data processing, he does not always have the keys or the technical skills to embark on the understanding of open data, and therefore is not always able to grasp the vastness of the information available – the datasets accessible in open data therefore too often remain untapped.
Data BZH wishes to offer the understanding of these data by providing the information visualized and analyzed, that is to say by bringing theopen data among citizens, by relieving it of its technical handling, processing and visualization needs. Data that is easy to understand, relevant to Brittany and accessible to all.
What is the target?
In general, anyone wishing to discover Brittany can come and consult the thematic files, and discover the Breton region through data visualizations. You can also come and shed light on a key expression of the domain by following our thematic posts.
The second target is Internet users wishing to engage in analysis and visualization themselves. Indeed, on the site, a library of books to consult and tutorials are available. Also, the codes used to produce the articles are posted on GitHub, a collaborative platform for publishing the codes used in open source.
Thus, everyone can reproduce, at home, visualizations and analyzes, following step by step the process used by the members of Data BZH. Each user can then propose their data for publication on our collaborative platform, if they wish.
Since when does Data BZH exist?
I created Data BZH in January 2016.
How many are you in the community?
Today we are two regular active members (Tristan Le Dain, and myself). We also had a few guest posts, as well as several publication proposals, which should materialize in the coming weeks.
Then, we are always ready to welcome new editors, regular or one-off. The door remains open!
Data BZH in figures, what does it give?
Tuesday, October 26, Data Bzh exceeded the 10,000 cumulative visit mark since its creation. 10,000 visits in less than 9 months… that’s no small feat, especially on a specialized subject like ours. In October 2016, we received more than 3000 visits in total. On big days, we receive more than 300 visits. In view of our highly targeted theme, these figures are very encouraging, and a real proof of the Breton craze for data!
Data BZH is also a hundred articles since its creation, and today more than 1700 people subscribed to our account Twitter.
Do you have plans for 2017?
The first year was devoted to setting up the site, in order to acquire notoriety, as well as a solid visitor base. We also took advantage of 2016 to lay down our methods of collaboration, as well as the lines of work and important themes.
In a wish to continue the democratization ofopen data and data in a global way, our team is currently working on the creation of an open-access MOOC for 2017, which will allow Internet users to go even further in the discovery and understanding of open data.
We also plan to set up a cycle of events (conferences, codelab and / or hackathon) around data.