Cultural data hackathon with Shiny and Leaflet

CodingDaVinci is the first German open cultural data hackathon that started in Berlin 2014. They bring together both cultural heritage institutions and the hacker & designer community to develop ideas and prototypes for the cultural sector and the public. In 2016 the hackathon took place in Hamburg and ran for a total of 10 weeks. Open cultural data is usually held by cultural heritage institutions such as galleries, libraries, archives and museums (GLAMs). A list of projects from 2016 can be seen on their website.


As I was playing around with leaflet recently I wanted to take part at the hackathon and develop something around spatial data. Leaflet is one of the most popular open-source JavaScript libraries for interactive maps and there is a wonderful R package that makes it easy to integrate and control Leaflet maps in R. You can find a neat little github page that will let you get started with Leaflet easily.

In the end I took visitor data from the museums in Hamburg. The data captures group bookings from private persons, schools, universities and other educational institutions. I came up with the idea of a map which shows the amount of museum visits of schools per neighborhood. On another layer I also mapped the amount to students per neighborhood and plotted every school as a marker on the map. This way the user can find out in which areas of Hamburg the schools often visit the museums and which neighborhoods need to catch up.


I think this map is relevant because cultural education is an indispensable part of our education system, as it is essential to the dignity of a human and the free development of his personality (Article 22, UN Human Rights Charter). An important part of this is the school trip to the museum, in order to attract students to art and culture as well as to strengthen their personality formation and social competence by means of cultural education.

Make sure you try out the map. If you are interested in the code you can check out my Github.


Author: inside data blog

data analysis & visualization blog

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