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OGLM 2130 - Open data for Urban Research

Type d'enseignement : Elective

Semester : Autumn 2018-2019

Number of hours : 12

Language of tuition : English

Pre-requisite

None

Course Description

This workshop offers a critical analysis of how urban-level data are produced, interpreted, and, increasingly, released to the public. Students will learn to assess the quality of existing open data resources, critically discuss their political implications, and produce their own catalogue of real-world public datasets. In order to gain a better understanding of the pitfalls of any open data project, we will follow the School of Data pipeline and learn to use tools such as the Open Data Census.
Additional requested information: (eg mainly theoretical or mainly practical or a mixture of the two): This course mixes theory and practice, and is complementary to the Advanced Quantitative Methods course taught in the same year of the program.

Teachers

  • BRIATTE, François (PhD Candidate - University of Grenoble)
  • GOETA, Samuel (Phd Student, Télécom ParisTech)
  • GOMBIN, Joel (PhD Candidate in political science, Université de Picardie Jules Verne)

Pedagogical format

1 field visit + 3 lectures and practical workshops. 4 session x 3 hours.

Course validation

Collaborative work on a practical assignment to be determined in class.

Workload

This course requires intensive personal research for its final assignment.

Required reading

  • Espeland, Wendy N. and Mitchell L. Stevens. 2008. “A Sociology of Quantification.” European Journal of Sociology / Archives européennes de sociologie 49(3): 401–436.
  • Raman, Nithya V. 2012. “Collecting Data in Chennai City and the Limits of Openness.” Journal of Community Informatics 8(2).
  • Sassen, Saskia. 2012. “Urbanising Technology.” In: Burdett, Ricky and Wolfgang Nowak (eds), The Electric City, London, LSE Cities, pp. 12–4.

Additional required reading

  • Severino Ribecca, "The Data Visualization Catalogue" datavizcatalogue.com
  • Financial Times, "Visual Vocabulary. Designing with Data" ft-interactive.github.io/visual-vocabulary