  The exponential growth of astronomical data collected by both ground based
and space borne instruments has fostered the growth of Astroinformatics: a new
discipline laying at the intersection between astronomy, applied computer
science, and information and computation (ICT) technologies. At the very heart
of Astroinformatics is a complex set of methodologies usually called Data
Mining (DM) or Knowledge Discovery in Data Bases (KDD). In the astronomical
domain, DM/KDD are still in a very early usage stage, even though new methods
and tools are being continuously deployed in order to cope with the Massive
Data Sets (MDS) that can only grow in the future. In this paper, we briefly
outline some general problems encountered when applying DM/KDD methods to
astrophysical problems, and describe the DAME (DAta Mining & Exploration) web
application. While specifically tailored to work on MDS, DAME can be
effectively applied also to smaller data sets. As an illustration, we describe
two application of DAME to two different problems: the identification of
candidate globular clusters in external galaxies, and the classification of
active galactic nuclei (AGN). We believe that tools and services of this nature
will become increasingly necessary for the data-intensive astronomy (and indeed
all sciences) in the 21st century.
