This paper describes a powerful framework for analyzing data from comprehensive two-dimensional gas chromatography with mass spectrometry (GC × GC-MS).GC × GC-MS is an emerging technology that provides greater separation capacity, improved signal-to-noise ratio, and higher-dimensional chemical ordering.Innovative methods are required to analyze complex data produced by GC × GC-MS.Smart, multi-type templates provide a powerful framework for chemical identification.Templates are two-dimensional patterns defimed in the retention-time plane.Multi-type templates contain prospective peaks, geometric objects to delineate groups of peaks, and annotations such as text labels and chemical structure diagrams.Pattern matching determines a retention-time transformation that fits the template to peaks in the.target data.