  There are challenges faced in today's world in terms of crime analysis when
it comes to graphical visualization of crime patterns. Geographical
representation of crime scenes and crime types become very important in
gathering intelligence about crimes. This provides a very dynamic and easy way
of monitoring criminal activities and analyzing them as well as producing
effective countermeasures and preventive measures in solving them. But we need
effective computer tools and intelligent systems that are automated to analyze
and interpret criminal data in real time effectively and efficiently. These
current computer systems should have the capability of providing intelligence
from raw data and creating a visual graph which will make it easy for new
concepts to be built and generated from crime data in order to solve,
understand and analyze crime patterns easily. This paper proposes a new method
of visualizing and analyzing crime patterns based on geographical crime data by
using Formal Concept Analysis, or Galois Lattices, a data analysis technique
grounded on Lattice Theory and Propositional Calculus. This method considered
the set of common and distinct attributes of crimes in such a way that
categorization are done based on related crime types. This will help in
building a more defined and conceptual systems for analysis of geographical
crime data that can easily be visualized and intelligently analyzed by computer
systems.
