Context

Researchers in the growing field of sensory urbanism are developing new ways to understand how a city sounds, smells, and feels [full paper]. The idea is to investigate how non-visual information defines the character of a city and affects its livability. The strategy is to propose data collection strategies for harvesting data regarding the smell of streets or points of interest according to a classification of smells. For example, people can provide their insight about a specific street or area specifying the conditions in which they visit that urban area and during which period in the day they visit it.

Objective of the exercise

Put in practice your understanding of the V’s model characterising Big Data collections and the implications of “intersectional” data collections characteristics on their associated collection, storage and analytics strategies.
As you have probably deduced, for performing data-centred studies it is necessary to understand the relation between the data and the research question(s) to answer. For answering a given research question, several data types might be required. Conversely, having specific data collections can allow to answer several types of research questions.

To Do

For this execise, organise into groups of 5 people. If you do not feel comfortable working in group, then you can also choose to work on your own.

Propose a data collection strategy of different types of data characterised by several V’s properties of Big Data studied in the course that can contribute to build a cartography of Lyon according to the smells of its urban areas, quarters and streets (Research Question).

Build a table (four columns) specifying the type of data to collect (1) with their associated V’s (2) and discuss how they can contributed to build the smell identity of a street, an area, a quarter, and the whole city (3). Finally, in column 4, specify one or several strategies to collect data. You can also search on internet whether there are data collections available that can contribute to provide insight to address the research question.

To HandIn

Upload a PDF document no later than Friday 12th of April 23:00 in e-Campus including:

• Title of the exercise
• Full names of the members of the team
• Table
• Discussion (natural language) on how the data you identified can contribute to build the cartography, you can complete your explanation with figures if required.

N.B Remember that you can adopt a DEI aware strategy and use inclusive language, avoid discriminatory examples and bias with non glorious associations regarding gender, race, opinions, beliefs. Remain neutral despite the fact that you are dicussing social aspects in this exercise.