2025-02-172025-02-172021Resinas Arias de Reyna, M., Río Ortega, A.d. y Ruiz Cortés, A. (2021). PPINOT computer and ppinot4py: two libraries to compute process performance indicators. En CEUR workshop proceedings. Volum. 3098 (51-52), CEUR-WS.1613-0073https://hdl.handle.net/11441/168825The ability to compute PPIs is of utmost importance for analyzing the performance of business processes. Most process mining tools support the computation of some types of PPI. However, in most cases they either just support a predefined set of metrics, which limits their usefulness in many scenarios, or the computation results are not designed to be used outside the tool platform and integrated with other tools or workflows. PPINOT Computer and ppinot4py are two libraries that were developed to overcome these limitations. Both libraries share the same approach to compute PPIs but serve two different purposes: one library has been designed to be integrated into custom solutions for process monitoring whereas the other has been designed to be part of data analysis and exploration workflows. The libraries have been successfully deployed in two different organizations and are used in several process management courses.application/pdf2 p.engAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/openAccess