Abstract: This paper presents a framework for implementing data mining techniques for extracting hidden
knowledge from a large amount of industrial safety data. Data mining is an emerging area of computational
intelligence that offers theories, techniques, and tools for processing and analyzing large data sets. Its
application in industrial safety data can provide significant benefits to the users such as government
agencies who are in charge industrial safety law and regulations, and various industrial organizations. A
framework, consisting of general concepts, data requirement, types of knowledge that can be discovered,
the mining processes and algorithms, potential benefits and limitations, and how data mining can be applied
to industrial safety data, will be discussed.