Dear friends & colleagues,
I am currently attending a 3 month course at Columbia University in New York (together with Paul Ronga from Tribune de Genève and Mathias Born, Berner Zeitung). We are currently half way into the programme. It’s basically a course for journalists (but not just journalists), to enhance their data gathering, analytic skills (learning Python, Panda libraries, SQL, combining the three, scraping with BeautifulSoup and using Selenium for automated scraping, and much more).
I thought it would be a good moment to reach out to the community and share some of the readings and stories we’ve stubbled across. The main gist is that data driven society in the US may be a little more sophisticated than in Switzerland and Europe in general. But they are actually not all that far ahead. They are dealing with very similar problems and opportunities.
This is just a random collection of readings, which some of you might find inspirational or just offer a different perspective on data and how we deal with it.
Relational and Non-Relational Models in the Entextualization of Bureaucracy by Michael Castelle
http://computationalculture.net/article/relational-and-non-relational-models-in-the-entextualization-of-bureaucracy (a dry read at times, but very rewarding)
Literature is not Data: Against the Digital Humanities by Stephen Marche
Machine Bias by Julia Angwin, Jeff Larson, Surya Mattu and Lauren Kirchner
How the Data Sausage Gets Made: A story about scraping food recalls and regular expressions
How open data saved parkers in NYC millions of dollars
NICAR-L mailing list
Hope you are all well and look forward to any feedback or comments anybody has on the readings.