  Large amounts of data are available due to low-cost and high-capacity data
storage equipments. We propose a data exploration/visualization method for
tabular multi-dimensional, time-varying datasets to present selected items in
their global context. The approach is simple and uses a rank-based
visualization and a pattern matching functionality based on temporal profiles.
Ranking categories can be specified in a flexible way and are used instead of
actual values (value reduction into bins) and plotting it over time in an
unevenly quantized representation. Patterns that emerge are matched against a
set of eight predefined temporal profiles. The graphical summarization of
large-scale temporal data is proposed and applicability is tested qualitatively
on about eight data sets and the approach is compared to classic line plots and
SAX representation
