# CONDA-PM--A Systematic Review and Framework for Concept Drift Analysis in Process Mining
## 4 Research Methodology
### Highlights after Data Extraction  
Studies investigated through the data extraction process reflect important conclusions that can highlight the shortcomings of the respective research dealing with concept drift in process mining. We aim to reach an understanding of the goals of existing approaches. Thus we begin with studying how the selected studies are distributed among different handling modes (RQ6) and themes (RQ4). According to Figure 4, 15 studies address concept drift in an offline mode, while only four studies enable online concept drift analysis (RQ6). This observation raises an issue concerning the way the existing approaches notify users about potential drifts instead of solely dealing with drifts in a reactive \begin{table}
\begin{tabular}{c} Content analysis \\ techniques \\ \end{tabular} \\ \hline \hline \end{tabular}
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Table 4: Data extraction results. mode. Moreover, it is of interest how existing approaches can yield reliable results that may be used as a basis for complementary tasks like making predictions for a running process instance, while the underlying data is experiencing a concept drift. Figure 5 shows that 14 studies deal with the flexibility of a business process at the process instance level, whereas four studies are concerned with studying concept drift at the process type level, and only one study is addressing both. This can be explained with the fact that when moving higher in the granularity level of concept drift analysis (i.e., when analysing concept drift at the process type level), different other topics (e.g., process variability, change mining) emerge whose enabling techniques may interleave with concept drift. As a result, the added value and purpose behind concept drift analysis might be missing. When studying the inputs needed by an approach to analyse concept drift and the way the variance in these inputs might affect the focus of an approach (RQ1), it can be noticed that all selected studies take an event log as input. Note that only three studies (S9, S15, and S16) take the process model as an additional input. Figure 6 shows the number of studies considering one or more process perspectives (RQ3). 12 studies solely deal with changes in the control flow perspective, while three studies consider two and four studies more than two perspectives. From this, we can infer some factors contributing to that the difference in studied process perspectives. The first is the data available in an event log, that is, whether this event log is solely recording control-flow data or also time, resources,  
Figure 4: Number of publications classified according to handling modes. Figure 5: Number of publications according to themes of handling. and other data items. Another factor is the used technique and its ability to encode a process instance execution sequence with the associated payload, for example, timestamps and resources. As an attempt to understand the types of concept drift mainly addressed by selected studies (RQ6), we plot the number of publications with respect to the concept drift types they address (cf. Figures 7 and 8). First, we are interested in whether or not the type of concept drift is stated clearly by the selected study. As can be observed from Figure 7, 11 studies do not explicitly clarify the type of concept drift that can be detected with the proposed approach. As a consequence, issues are raised regarding the clarity and maturity of an approach. However, note that the type of drift is subject to the domain an event log represents as well as to the length of the time period the event log was recorded. From Figure 8, we can observe that sudden drifts are addressed by eight studies, which gives this drift type the biggest share. Recurring and incremental drifts are addressed by three studies (S1, S2, S3) along with sudden and gradual drifts. This can be explained with the fact that S1 is building upon and adding to the work introduced in S3. In turn, multi-order drifts are solely addressed by S12 along with sudden and gradual drifts.