IEEE XES Standard
Why do we need the XES Standard?
The goal of the eXtensible Event Stream (XES) Standard is to standardize a language to transport, store, and exchange (possibly large volumes of) event data (e.g., for process mining).
The spectacular growth of the digital universe, summarized by the overhyped term “Big Data,” makes it possible to record, derive, and analyze events. Events may take place inside a machine (e.g., an X-ray machine, an ATM, or baggage handling system), inside an enterprise information system (e.g., an order placed by a customer or the submission of a tax declaration), inside a hospital (e.g., the analysis of a blood sample), inside a social network (e.g., exchanging e-mails or twitter messages), inside a transportation system (e.g., checking in, buying a ticket, or passing through a toll booth), etc. Events may be “life events,” “machine events,” or “organization events.” The term Internet of Events (IoE), refers to all event data available. The IoE is composed of:
- The Internet of Content (IoC): all information created by humans to increase knowledge on particular subjects. The IoC includes traditional web pages, articles, encyclopedia like Wikipedia, YouTube, e-books, news-feeds, etc.
- The Internet of People (IoP): all data related to social interaction. The IoP includes e-mail, Facebook, Twitter, forums, LinkedIn, etc.
- The Internet of Things (IoT): all physical objects connected to the network. The IoT includes all things that have a unique id and a presence in an Internet-like structure.
- The Internet of Locations (IoL): refers to all data that have a geographical or geospatial dimension. With the uptake of mobile devices (e.g. smartphones), more and more events have location or movement attributes.
Note that the IoC, the IoP, the IoT, and the IoL are overlapping. For example, a place name on a webpage or the location from which a tweet was sent. Process mining aims to exploit event data in a meaningful way, for example, to provide insights, identify bottlenecks, anticipate problems, record policy violations, recommend countermeasures, and streamline processes. This explains our focus on event data.
Process mining is an emerging discipline providing comprehensive sets of tools to provide fact-based insights and to support process improvements. This new discipline builds on process model-driven approaches and data mining. Process mining provides a generic collection of techniques to turn event data into valuable insights, improvement ideas, predictions, and recommendations. The starting point for any process mining effort is a collection of events commonly referred to as an event log (although events can also be stored in a database and may be only available as an event stream). A wide range of process mining techniques is available to extract value and actionable information from event data. Process discovery techniques take an event log or event stream as input and produce a process model without using any a-priori information. Conformance checking can be used to check if reality, reflected by the event data, conforms to a predefined process model and vice versa. Process mining can also be used to extend process models with performance-related information, e.g., bottlenecks, waste, and costs. It is event possible to predict problems and suggest actions.
Currently, there are over 25 commercial process mining tools. In fact, the adoption of process mining has been accelerating in recent years. Tools like Disco (Fluxicon), Celonis Process Mining, ProcessGold Enterprise Platform, Minit, myInvenio, Signavio Process Intelligence, QPR ProcessAnalyzer, LANA Process Mining, Rialto Process, Icris Process Mining Factory, Worksoft Analyze & Process Mining for SAP, SNP Business Process Analysis, web-Methods Process Performance Manager, and Perceptive Process Mining are now available. Moreover, open source tools like ProM, ProM Lite, and RapidProM are widely used. It is vital that event data can be exchanged between these tools. Several of these tools already support XES. For example, it is easy to exchange XES data between Disco, Celonis, ProM, Rialto Process, minit, and SNP.