We discuss data symbolization as a tool for identifying temporal patterns in complex measurement signals. We describe the basic concepts involved and illustrate their application for the analysis of gas-bubble injection data. Specific issues addressed include selection of symbolization parameters, construction of symbol-sequence histograms, and statistical characterization and comparison of these histograms. We demonstrate that symbol-sequence statistics can reveal unique information about deterministic patterns. Such information may be useful for developing flow diagnostics and comparing computational models with experiments.