Ciudata Segura
OPAL
DNP

About the Project

Latin America and the Caribbean (LAC) remains the most violent region on the planet, accounting for over a third of homicides in the world. Increasingly, data and information are being promoted as a powerful tool to understand and prevent crime and violence.
However, there are two key questions that remain largely unanswered:
1) Why is crime clustering in certain neighborhoods?
2) Why do certain individuals turn to crime and not others?

Leveraging traditional (official statistics, surveys, interviews) and new data sources (big data, i.e CDRs and open source GIS), Ciudata Segura aims to build a granular spatio-temporal tool to diagnose crime factors in cities and better inform security policy-making.


Pilot in Colombia


The pilot phase is currently being deployed in six Colombian cities presenting a diversity of contexts, both in terms of socioeconomic and political characteristics and crime prevalence: Bogotá, Medellín, Barranquilla, Montería, Valledupar, and Tumaco. Preliminary results will be shared with our local partners by the end of 2018.


A CLOSER LOOK

The big data models used in this study have been previously tested in three cities, including Boston, Los Angeles and Chicago. The models include the following variables:

  Physical characteristics of the city,
  (such as land use, size of blocks, age of buildings, population density, vacuums)

  Socioeconomic characteristics,
 (such as unemployment and income inequality)


1) Why is crime clustering in certain neighborhoods?
2) Why do certain individuals turn to crime and not others?Mobility patterns of individuals

Overall, results have shown that a comprehensive model including all variable above is the best better predictor of crime, but also that crime dynamics cannot be explained to the same extent in all cities.

Want to learn more about using big data for crime prediction?
Here are some resources:
Webinar 'Leveraging (Mobile) Data to Predict and Prevent Crime’ by Dr. Nuria Oliver.
Moves on the Street: Classifying Crime Hotspots Using Aggregated Anonymized Data on People Dynamics Andrey Bogomolov, Bruno Lepri, Jacopo Staiano, Emmanuel Letouzé, Nuria Oliver, Fabio Pianesi, and Alex Pentland, 2015.
Using Big Data to stop crime: six Colombian cities will show us how IDB blog


Who We Are


For more information about Ciudata Segura, please contact Julie Ricard: jricard@datapopalliance.org

About the Project

OPAL (for "Open Algorithms") is a non-profit socio-technological innovation developed by a group of partners around the MIT Media Lab, Imperial College London, Orange, the World Economic Forum and Data-Pop Alliance, aiming to unlock the potential of private sector data for public good purposes by “sending the code to the data” in a safe, participatory, and sustainable manner. It is designed to provide a far better picture of human reality to official statisticians, policymakers, businesses, and citizens, while fostering inclusion and inputs of all on the kinds and uses of analysis performed on data about them.

To date, using ‘big data’ sources collected by private companies (such as “Call Detail Records” by telecom operators) for research and policy purposes has been a conundrum, for legitimate ethical and commercial reasons. There is ample evidence that computational analyses of these fine-grained datasets can shed light on socio-economic outcomes and processes at levels of granularities and degrees of complexities never seen before, and inform better decisions to fight poverty, inequality, diseases, crime, urban congestion, and more. But there are no systems and standards developed to do this at scale, ethically. OPAL aims to do just that.

OPAL combines a state-of-the-art privacy-preserving technology and a participatory governance system with an ethical oversight body and capacity building activities. It started in 2017 with pilots in Colombia and Senegal in partnership with their governments and 2 major telecom operators, Orange-Sonatel and Telefónica Colombia, with funding from the French Development Agency (AFD). It ambitions to expand to other industries and geographies in 2019 and beyond, as a key milestone towards a vision where data is at the heart of fairer societal development around the globe.

FOR MORE INFORMATION


  1. View the OPAL Website HERE
  2. Read the full OPAL vision note HERE

Coming Soon.