Localization and value creation

“Helping Local Businesses Reach More Customers”:

→ https://www.facebook.com/business/learn/facebook-create-ad-reach-ads

“Using computer vision to analyze real life activity”:

→ https://www.placemeter.com/

→ Making data open to foster innovation for citizens and businesses

→ Includes many datasets with geographical relevance

Similar initiatives in large cities:

The visual metaphor of the map is widely understood. It makes exploration easy: all is visible at once, while zoom allows for details as well. Multiple information cues (colors, symbols, shapes, layers, etc.) help display information. To keep in mind: maps always an interpretative layer on the territory they display. Watch this extract from the TV series "The West Wing“, Season 2, Episode 16:

(source: http://code.waag.org/buildings/)

Data is traditionally stored in tables in relational databases, taking this form:

A table can have millions of rows. How to retrieve information such as "get all customers living in Rotterdam"? "SQL" (Structured Query Language) is a system to express these kinds of queries. In the table shown above, a query written in SQL look in the "Address" column and inspect all the text to find if "Rotterdam" is present or not. This is highly inefficient (slow), and more complex queries would not work. For example, the table above could not be queried for "get all customers living in a 10 miles radius around Rotterdam". So how to store geospatial data in a way that makes it easy to retrieve?

Even if SQL does not perform well on geospatial data "out of the box", extra modules have been developed to deal with it. Microsoft SQL server since 2008:

Since ~ 2005, new types of databases have been developed, which don’t follow a table structure in order to facilitate the query of special kinds of data, like geospatial data or network data.

These new databases are called "NoSQL databases"

Carto (ex CartoDB): specializing in geospatial data + mapping.

Neo4J Spatial enables to mix the logics of networks with places in the data, so that you can make such queries on your data:

"Select all streets in the Municipality of NYC where at least 2 of my friends are walking right now."

GeoJSon and TopoJSon: 2 data formats to represent geometric and geographic data developed for Javascript applications – and beyond.

and yet…​ the logic of territories is shaping data: there is a geography of data. Representations with a supposedly universal and transparent coordinate system blinds us to this fact. This argument is made by Frederic Martel in his book "Smart": Internet does not flatten everything into one big model. There are several Internets with their geography, politics and sociology.

Here are a few dimensions on which geography plays a strong role:

It shows that the dream of "data and the web" erasing distances and geographical disparities is just a dream, social geography remains a strong factor in the structuring of remote workers.

The libertarian dream of the cypher-punks: individuals transact without consideration for their nationality, currency, legal system, political regime. Organizations, banking, voting systems, … any aggregated human activity could emerge without reference to local territories or institutions. Just groups of individuals transacting voluntarily and securely, without a notion of place or distance.