Process Mining scripting environment PMLAB is an interactive programming environment for (exploratory) process mining computing and/or research on top of a process-oriented language. In this language, logs, models and many other high-level objects/tasks are first-class citizens, meaning that one can compute (interactively or not) on the basis of these elements. Importantly, there can be different granularities on the view of these high-level elements, e.g., a log can be simply passed to a discovery algorithm (coarse-level view), or analyzed to derive the most frequent cases (introspective view). The following is a list of PMLAB features:

– Interactive shell: as happens in Mathematica, a shell where every object used/computed is available is provided, and process mining algorithms may be applied to these objects to create new ones. The typical session may start by importing the libraries to be used, and to continuously enrich the environment by computing new objects from the existing ones.

– Process mining elements as first-class citizens of the language: importantly, the environment offers a solid and consistent library for some of the main tasks required in process mining, e.g., importing a log in XES format. Once a log is imported into a variable, algorithms can be applied on the variable to produce new elements (e.g., a discovery algorithm to derive a BPMN model).

– Programmer friendly: the environment not only provides the necessary help for using the elements, but more importantly describes them in a way a programmer can incorporate these objects onto her/his programs.

– Extendable: new functionalities can be added by means of new library modules.

– Irredundant: to have thirty algorithms to perform the same task maybe is not the ideal situation for using that functionality. As a policy, we believe the core environment should limit the amount of redundancy in order to simplify the usage.

– Simple Programming: the syntax and semantics of the language should be easy, in order to allow for easy programming. One example of this is types in programming languages: although useful for programming and compilation, the learning curve required to master a statically-typed language is significantly higher than the one for a dynamically-typed language. This makes dynamically-typed languages as Python a good candidate.

– OS exposed: there is a good marriage between the operating system elements (files, directories, databases, etc ...) and the elements of the environment. This will easy the management and manipulation of the data within the environment.

– With support to distributed/parallel computing: it is fairly easy to distribute or parallelize the computations to take advantage of the computing resources available.

See pmlab/doc/pm_guide.pdf for detailed instructions for installation.