A Proposal for Semantic Integration of Crime Data in Mexico City

Francisco Carrillo-Brenes, Luis M. Vilches-Blázquez, Félix Mata

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Crime is a common problem in big cities where the authorities regularly update data crime reports. In Mexico City, the crime reports are available as open data. However, other relevant data are not connected to them (e.g., socioeconomic data). Therefore, the socioeconomic and geographic data can help understand how the crime is characterized and what social indicators are related to it. In this research, we explore how data crime reports are described and how they can be associated in an Ontology with other data, such as socioeconomic and geographic data. The goal is to discover the social indicators related to a particular crime in a specific area by using SPARQL queries from a knowledge representation. Then, data sets from crime reports, socioeconomic and geographic data from 2016 were integrated to explore crime behavior in Mexico City. The work uses a NeOn methodology in which resources from existing ontologies or non-ontological resources can be mixed. Next, a set of SPARQL queries is defined to extract the knowledge from ontology and discover the associations between crime in geographic and socioeconomic domains. The results showed a set of queries where it is possible to know where a crime occurred and what other factors are associated with the crime and help to identify possible patterns among them.

Original languageEnglish
Title of host publicationGIS LATAM - 1st Conference, GIS LATAM 2020, Proceedings
EditorsMiguel Felix Mata-Rivera, Roberto Zagal-Flores, Javier Arellano Verdejo, Hugo Enrique Lazcano Hernandez
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages19
ISBN (Print)9783030598716
StatePublished - 2020
Event1st GIS LATAM Conference, GIS LATAM 2020 - Mexico City, Mexico
Duration: 28 Sep 202030 Sep 2020

Publication series

NameCommunications in Computer and Information Science
Volume1276 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937


Conference1st GIS LATAM Conference, GIS LATAM 2020
CityMexico City


  • Behavior crime data
  • Crime data
  • Mixed data
  • Ontology


Dive into the research topics of 'A Proposal for Semantic Integration of Crime Data in Mexico City'. Together they form a unique fingerprint.

Cite this