iMMAP Data Cube for sharing educational risk index information


A new web platform has been launched, utilizing the innovative iMMAP Data Cube to promote the exchange of information on educational risk indices. This initiative aims to facilitate strategic decision-making processes that enhance access and retention in the education field for the most vulnerable communities.

The implementation of this platform represents a significant advancement in the search for effective solutions to the challenges faced by the education sector. By providing a digital space to share up-to-date and relevant data, collaboration and coordination among diverse stakeholders, including governments, non-governmental organizations, and education experts, are expected to be fostered.


What is a data cube?



A data cube is a structured approach for analyzing and managing extensive datasets. It provides a multidimensional representation that facilitates the organization of data across various dimensions and levels of granularity. Think of it as a three-dimensional cube, where each axis corresponds to a distinct data dimension. In the context of education, these dimensions could include time, geographic location, and educational variables such as schooling level or performance metrics. Every point within this three-dimensional cube signifies a specific combination of values across each dimension. For instance, a point could represent the educational performance in a particular geographic area during a specific time period.

The key advantage of utilizing a data cube lies in its ability to enable analysis from multiple perspectives. By querying the cube, you can obtain aggregated or disaggregated results based on the chosen dimensions. For example, you could retrieve the average educational performance of a country in a specific year or compare performance across different regions and schooling levels. This flexible approach allows for insightful examinations and comparisons of data.


What can you visualize in our data cube?

  • Six key factors have been identified: social, economic, environmental, educational, risk management, and physical, which influence access to education and the risk of dropout in educational institutions.
  • The Ranking of educational sites has been determined using a multicriteria analysis method, employing a weighted numerical model based on the logic of a Fuzzy model.
  • Mathematical and statistical calculations were performed to establish areas and value ranges representing different levels of risk.
  • The educational sites were georeferenced, and their spatial relationship with at-risk areas was analyzed to determine the associated level of risk.

The objective is to provide a multidimensional and localized view of the risks, facilitating the planning of actions in the education sector.


Multidimensional Analysis of School Risk




The School Risk Index is a comprehensive statistical measure that evaluates the level of risk in educational institutions based on various environmental, social, economic, cultural, and physical factors that affect access to quality education. It provides a ranking system from high to low-risk levels to guide decision-making and interventions by relevant entities.

In a recent analysis of seven border departments in Colombia, using the Data Cube and other data sources, the report sheds light on the school risk situation. It aims to contribute to the analysis, organization, and decision-making processes for effective humanitarian response, emphasizing the border as a critical area with the potential for improving living conditions and ensuring the right to quality education.