The main principles and the algorithm of a density-based clustering approach, OPTICS, are described, and its unique properties, such as the ability to reveal clusters of arbitrary shapes and different densities, are illustrated on simulated and real spectral and chromatographic data sets. A "reachability plot" visualizing density fluctuations of data in multivariate space and a "color map" relating the original and/or descriptive features with data clustering allow a deeper insight into the data structure and its interpretation in chemical terms.