Diary studies are widely used in human-computer interaction research, but also in user experience research as practiced in product R&D groups. Bolger, Davis, & Rafaeli (2003) is a good review of diary research methods from a Psychology perspective. It gives practical guidance in what research questions are suited to these methods, design decisions, tools, and analysis.
Though it covers state-of-the-art technology used for these methods, I think the argument below for the taxonomy of methods used in this paper needs revision in light of new diary methods, e.g. those made possible by using context-aware devices for signaling participants. Here is the argument for the two-way taxonomy (p. 588):
Diary studies have often been classified into the three categories of interval-, signal-, and event-contingent protocols (e.g., Wheeler & Reis 1991). The interval-contingent design, the oldest method of daily event recording, requires participants to report on their experiences at regular, predetermined intervals. Signal-contingent designs rely on some signaling device to prompt participants to provide diary reports at fixed, random, or a combination of fixed and random intervals. Event-contingent studies, arguably the most distinct design strategy, require participants to provide a self-report each time the event in question occurs. This design enables the assessment of rare or specialized occurrences that would not necessarily be captured by fixed or random interval assessments.
As we see it, diary studies serve one of two major purposes: the investigation of phenomena as they unfold over time, or the focused examination of specific, and often rare, phenomena. It appears to us that the three-way classification blends this conceptual distinction with the technological issue of signaling. Instead, we incorporate interval- and signal-contingent designs into a single category, which we call time-based designs.
This argument to collapse the taxonomy does not account for methods in which participants are signaled based on factors other than time. For example, diary studies can include signaling participants to create an entry based on events that are automatically detected by the system: this occurs when the system is immediately aware of the event because it is an interaction with the system (e.g. the participant has just completed a phone call) or because it can infer an appropriate change in state (e.g. the participant has just moved from one place to another, as detected by readings from GPS).