edeaR: Extracting knowledge from process data

Play edeaR: Extracting knowledge from process data
Sign in to queue

Description

During the last decades, the logging of events in a business context has increased massively. Information concerning activities within a broad range of business processes is recorded in so-called event logs. Connecting the domains of business process management and data mining, process mining aims at extracting process-related knowledge from these event logs, in order to gain competitive advantages. Over the last years, many tools for process mining analyses have been developed, having both commercial and academic origins. Nevertheless, most of them leave little room for extensions or interactive use. Moreover, they are not able to use existing data manipulation and visualization tools. In order to meet these shortcomings, the R-package edeaR was developed to enable the creation and analysis of event logs in R. It provides functionality to read and write logs from .XES-files, the eXtensible Event Stream format, which is the generally-acknowledged format for the interchange of event log data. By using the extensive spectrum of data manipulation methods in R, edeaR provides a very convenient way to build .XES-files from raw data, which is a cumbersome task in most existing process mining tools. Furthermore, the package contains a wide set of functions to describe and select event data, thereby facilitating exploratory and descriptive analysis. Being able to handle event data in R both empowers process miners to exploit the vast area of data analysis methods in R, and invites R-users to contribute to this rapidly emerging and promising field of process mining.

Day:

1

Embed

Download

Download this episode

The Discussion

Add Your 2 Cents