Compact and field portable infrared spectrometers have been increasingly used over the past few years by an exploration industry constantly searching for a technological edge and the ability to more accurately and rapidly assess project areas. In particular, this technology allows large amounts of data to be rapidly collected on-site and sample mineralogy, mineral crystallinity and mineral composition to be quickly assessed. In recent years, short wave infrared (SWIR) reflectance spectroscopy has proved useful in a wide range of geological environments and at various stages of exploration programs, from grass roots reconnaissance through drilling programs and resource evaluation. Unfortunately these data have frequently been analysed and interpreted in isolation using time consuming data analysis techniques removed from the realities of a fast moving exploration industry. This paper presents new analysis techniques which allow these data to be efficiently integrated in the exploration program. Although SWIR data contain a wealth of mineral information it is impractical to use this information in its raw form. A more effective approach involves the extraction of key characteristics of these data (ie mineralogy, mineral composition and crystallinity) as numerical values, and the integration of this digital mineralogy' with more conventional exploration datasets (eg geochemistry, coordinate data, etc). This paper demonstrates that the integrated analysis of sound geological observations, geochemical, spatial and spectral data can quickly lead to a greater understanding of the nature and distribution of target mineralisation. As a first step, software driven pattern matching routines enable the identification of the major clay mineral species in a series of samples (eg kaolinite, montmorillonite and sericite). This allows the major alteration facies and their spatial distribution to be identified. Quantification of diagnostic absorption feature characteristics then allows more accurate determinations of mineralogy to be made (eg mineral composition and crystallinity). Examples of the application of SWIR analysis for alteration mapping from selected porphyry and epithermal systems from around the Pacific Rim are discussed. The data presented are derived from a variety of locations and sample types including drill core, ridge and spur rock chip samples, soil samples and geochemical pulps. In these large alteration systems, the spectral data can be used to describe and map the distribution of various alteration facies as many of these are characterised by clay and phyllosilicate mineral assemblages and are detected by SWIR analysis (eg smectite, chlorite, biotite, illite, muscovite, kaolinite, dickite, pyrophyllite, alunite, etc). In addition, the ability to evaluate even subtle trends in mineral crystallinity and composition is often vital in these systems when looking for vectors towards higher temperature parts of the system. In addition to detailed evaluation of mineralogy, the integration of digital mineralogy data with geochemical data leads to the ability to describe not only geochemically anomalous intersections or regions but also to recognise associations between subtle changes in mineralogy and target mineralisation. This is often important because understanding these mineralogical associations can lead to more accurate targeting and rapid assessment of the project.