Tag: BPMN

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Data Processing vs. Process Management?

In today’s data-driven business landscape, managing data effectively is crucial for achieving organizational goals. While data processing systems play a vital role in collecting and organizing data, it is often overlooked that data should not be managed solely for its own sake. True value lies in understanding how data can be leveraged to achieve business objectives, which is where the concept of process management comes into play.

Today we live in a world where data is everywhere and every enterprise knows about the value of data. But how do we handle data? How do we create, collect analyze it? This is the area of data processing software. And we all use databases, spread sheets and data management systems to manage all kind of data. Many software systems are build around specific data domains and we use this software to create and maintain the data.

But in this context, however, it is often overlooked that data should not be managed for its own sake. The reason why we need data in companies is that we want to achieve certain business goals. And in this context, we come to the question of how corporate goals can be achieved at all? This is the area of process management.

So what’s the difference between data processing and processes management?

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BPMN 2.0 and Jakarta EE – A Powerful Alliance

A BPMN Workflow engine based on the Jakarta EE Framework forms a powerful and effective combination for developing enterprise applications with a focus on business process management. Both, Jakarta EE and BPMN 2.0 are standardized and widely supported. The scalability of Jakarta EE provides a secure foundation for building enterprise applications with robust business process management capabilities. This enables developers to leverage the strengths of both technologies to create efficient, interoperable, and maintainable BPM solutions. In the following I will explain the aspects in more detail.

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New Version of Open-BPMN Available!

Today we released the latest Version of Open-BPMN. The new version includes a lot of enhancements and new additional features. This makes it more easy to model BPMN Diagrams:

  • Improved Layout
  • Property Panel can be opened by double click
  • BPMN Pool and Lane Design improved
  • Fixed minor layout issues

Open BPMN can be run in a Browser or installed on Microsoft VS-Code. You can install Open-BPMN form the VS–Code Marketplace.

BPMN 2.0 Extensibility Mechanism

One of the core features is the extensibility of Open BPMN. Open-BPMN enables you to customize it’s behavior and appearance by adapting the BPMN 2.0 extension mechanism. This extension mechanism can be used to adapt BPMN elements to the unique requirements of a vertical domain, and still have a valid BPMN Core. Open Source Workflow Engines like Imixs-Workflow already integrate Open BPMN into there tooling platforms.

But more important, Open-BPMN is based on the Eclipse Graphical Language Server Platform (GLSP). This platform provides a huge set of features and an API to extend and adapt the Modeler in various ways.

Find out more…

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BPMN Modelling with Eclipse GLSP

Imixs-Workflow started a new modelling project called Open-BPMN. Open-BPMN is a free BPMN 2.0 modelling platform that can be extended and customized by any BPMN 2.0 compliant execution engine. The primary goal of this project is to provide a graphical BPMN editing framework that can be extended in various ways by different solutions to create an agile and innovative community around the BPMN standard.

For this reason we build Open BPMN based on the Eclipse Graphical Language Server Platform (GLSP). GLSP is an extensible open-source framework for building custom diagram editors based on web technologies. The platform provides a language server protocol (LSP) for diagrams that allows to adapt any kind of modelling language. GLSP splits into a server part and a client part. The server part is responsible to handle the underlying model stored in a filesystem, database or microservice and provides the graphical model meta data. The client part communicates with the server and provides the graphical representation and the modelling tools to create and modify a model.

The main advantage of GLSP is its openness and extensibility. In this way it allows us to not only provide a new flexible BPMN modelling tool but also adapt the BPMN Extensions of Imixs-Workflow within this solution. Adapting the Imixs-Workflow engine within the Open-BPMN Modeller is a first proof of concept showing the flexibility and power of this platform.

Multi IDE Support and Extensibility

GLSP can be integrated into different IDEs like Microsoft VS Code, the web based Theia IDE and of course the Eclipse Platform. This allows us to use Open-BPMN in much more different ways and projects and opens the modelling tool to a broader community.

With the extensibility of GLSP, Open-BPMN can not only be extended within the extension mechanism of BPMN 2.0, but also by additional views, editors and UI elements in various ways. For example custom Form editors, Analyse-Panels or Reporting Tools can be adapted by individual projects.

The Community

There is also a strong and agile community around this project that supports us in adapting the technology into the Imixs-Workflow project. Of course Open-BPMN is free software and we invite you to participate in it. There are different ways how you can do that. Join the Open-BPMN Project on GitHub or help us to improve the project by reporting bugs or start a new discussion.

So if you plan to customize BPMN for your own software project, then join Open-BPMN and get support from an agile community. Of course, we also offer professional support for your project.

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New AI for Automated Document Import

The latest version 4.5.3 of our Business Process Management suite Imixs-Office-Workflow now includes an improved AI module. The system can import documents and automatically recognize and assign their content. For example, incoming invoices and delivery notes can be processed automatically in background. This significantly shortens throughput times in document based business workflows.

The open source module Imixs-ML is based on a machine learning approach in combination with pattern recognition. Good results are achieved even with small amounts of data. In addition, Imixs-Office-Workflow includes a self-learning AI system. This means that the system permanently improves its ability to recognize content from new documents in the background without having to import big training data.

After an automated document import – e.g. from an e-mail mailbox or an Office scanner – the user can check the data and correct it where necessary.

Model Your Business Process Quick & Easily

With the Imixs Workflow Technology, all kinds of business processes can be easily modelled with BPMN 2.0. Even complex approval processes like the 4-eyes principle are supported by the Imixs Workflow engine.

Due to its openness Imixs-Office-Workflow supports many open interfaces to various IT solutions and server systems. Thus, integration into an existing enterprise IT can be done very easily.

Through our consulting concept, we help companies to digitize their business processes. Get in touch with us and find out more!

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Imixs Workflow & SpaCy 3.1

With its latest version, the Open Source Workflow Engine Imixs-Workflow fully integrates the AI Framework SpaCy v3.1. SpaCy has become an industry standard over the last two years with a huge ecosystem. SpaCy can be combined with a variety of plugins and so called pipelines, to process any kind of data within a machine learning environment.

The Imixs Workflow project Imixs-ML follows a generic approach to combine machine learning frameworks with BPMN. The project provides a core API and a Rest Service Interface. This makes it easy to combine the workflow management platform with the AI ecosystem from spaCy. The integration is based on the Imixs Micro Kernel architecture which allows a modern model based development.

The Imixs-ML project is hosted on Gibhub.

Processing Business Documents with AI

An example of how AI can be combined with BPM, is the processing of business documents. The concepts of natural language processing (NLP) with its sub domains of entity recognition and classification allows the analysis of business documents in various ways. For example, payment information like IBAN/BIC and an payment date can be extracted from an invoice document to be processed by the Imixs Workflow engine. With the classification of documents, for example, customer orders can be automatically routed to the responsible sales department. This all is embedded into a continuous learning technology where the Imixs Workflow engine automatically refines the ML models based on the decisions made by humans actors in a specific business process. Starting from scratch is possible even if only a small training database exists.

Dynamic Classification

One new feature of SpaCy 3.1 is the new multi-label classifier. This new pipeline allows the learning of new categories within an existing ML model. For a continuous learning system like Imixs-ML this is a great feature to extract more data from a business task with the help of AI.

If you like to learn more about the BPMN and AI start a dicsussion on Github or ask our experts.

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Stream Analytics with Imixs-Workflow

The real-time processing of a continuous stream of business data and events is becoming increasingly important in modern IT architectures. This type of architecture, in which events are building the centre of data processing, is also known as a Reactive Streaming Architecture. In the following we will show how to solve some of the related challenges with the help of a workflow technology.

Let’s take a closer look at this type of architecture first. Basically, the event-based processing of data is not new and has actually been developed for decades in various specialized domains such as the financial sector. But since the last few years, new standards for processing data streams have emerged. Technologies like Apache Kafka, Storm, Flink or Spark are gaining popularity and pushing a new hype.

From industrial production systems to multiplayer computer games, so-called Streaming Architectures are used more and more frequently in order to be able to process big data in real time. Streaming architectures have developed into a central architectural element of modern technology companies. In many companies real-time streams have become the core system in their architecture.

The goal is to be able to integrate new system solutions more quickly and to connect any kind of data streams. The streaming architecture is not only found at technology giants such as Ebay, Netflix or Amazon, but today in every modern technology company that is working on the digitization of its business processes. So what are the main challenges in building such an architecture?

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Imixs-Workflow 5.2 Supports Asynchronous Events

With the new release v5.2.0, the open source workflow engine Imixs-Workflow now supports the asynchronous execution of BPMN events.

This feature is a big step forward especially in a microservice architecture. The new so called AsyncEvents make it much more easier to decouple a Rest API call from the processing life cycle of the workflow engine. In this way the request-response pattern shows better performance and allows a very clear design of complex business processes.

The AsyncEvents were already part of the Imixs-Microservice project in a pre-release and become now a core feature of the Imixs-Workflow engine. Especially in more complex architectures, the use of the so-called SAGA Pattern is an important building block. With asynchronous events Imixs-Workflow is now supporting this design pattern as a core feature. Read also our blog about building powerful microservice solutions with the SAGA Pattern.

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Microservice Saga Pattern with Imixs-Workflow

In my last blog I explained the core concepts behind the Microservice Saga Pattern. In this blog I will address the problem from a more practical perspective by demonstrating how Imixs-Workflow can be used as a Saga Orchestrator within a Microservice architecture. First, I would like to give a brief review of the main concepts of the saga pattern. Later I show some implementation examples.

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