Genk's Economic Shift - From Mining Coal to Mining Data

As part of the second international Autumn School of TRADERS, themed “On the role of participatory art and design in the reconfiguration of work (in Genk)”, I hosted a workshop on data mining titled ‘Genk’s economic shift: From mining coal to mining data‘.

Type:

Workshop

Role:

Host/Organiser

Event:

TRADERS Autumn School Nov 2015

Location:

Genk, Belgium

Workhop outcomes:

In order to familiarise the participants of this working table to the context and the topic of the workshop we started our session with two introductions. The first introduction was given by Liesbeth Huybrechts, in which she explained our case study: the Kolenspoor project. Following this, I gave an introduction on the theme of this working table.

First, the participants were asked to share their conceptions of, and experience with, Big Data, data mining and algorithms. Following up on their contribution, I introduced my main research aim and my approach to data mining. Here, I emphasised on the difference between traditional data analysis and data mining in the ‘Big Data era’, and elaborated on where the essence of the data-driven approach lies in my research and therefore also in the workshop. This introduction opened up some interesting paths for the workshop for us to discuss. 

One of the outcomes of this discussion was the idea of crowdsourcing data collection on the Kolenspoor project. We talked about how we could approach this systematically, and I explained that in a ‘Big Data approach’ metadata is of equal importance as the data aimed at collecting. As a result of this discussion we explored what data we could gather when taking photos of the site, and decided to focus on geo-location to be able to automatically map photos (data) that we would collect. After altering some camera settings in our smartphones to capture geo-data for photos, we went outside to visit one of the sites along the Kolenspoor track. Here we all took pictures and uploaded these to our shared database.

Read further here.