IUPC: Identification and Unification of Process Constraints

Business Process Compliance (BPC) has gained significant momentum in research and practice during the last years. Although many approaches address BPC, they mostly assume the existence of some kind of unified base of process constraints and focus on their verification over the business processes. However, it remains unclear how such an inte- grated process constraint base can be built up, even though this con- stitutes the essential prerequisite for all further compliance checks. In addition, the heterogeneity of process constraints has been neglected so far. Without identification and separation of process constraints from domain rules as well as unification of process constraints, the success- ful IT support of BPC will not be possible. In this technical report we introduce a unified representation framework that enables the identifica- tion of process constraints from domain rules and their later unification within a process constraint base. Separating process constraints from domain rules can lead to significant reduction of compliance checking effort. Unification enables consistency checks and optimizations as well as maintenance and evolution of the constraint base on the other side.Comment: 13 pages, 4 figures, technical repor

Cloud Process Execution Engine - Evaluation of the Core Concepts

In this technical report we describe describe the Domain Specific Language (DSL) of the Workflow Execution Execution (WEE). Instead of interpreting an XML based workflow description language like BPEL, the WEE uses a minimized but expressive set of statements that runs directly on to of a virtual machine that supports the Ruby language.Frameworks/Virtual Machines supporting supporting this language include Java, .NET and there exists also a standalone Virtual Machine. Using a DSL gives us the advantage of maintaining a very compact code base of under 400 lines of code, as the host programming language implements all the concepts like parallelism, threads, checking for syntactic correctness. The implementation just hooks into existing statements to keep track of the workflow and deliver information about current existing context variables and state to the environment that embeds WEE

Cloud Process Execution Engine: Architecture and Interfaces

Process Execution Engines are a vital part of Business Process Management (BPM) and Manufacturing Orchestration Management (MOM), as they allow the business or manufacturing logic (expressed in a graphical notation such as BPMN) to be executed. This execution drives and supervises all interactions between humans, machines, software, and the environment. If done right, this will lead to a highly flexible, low-code, and easy to maintain solution, that allows for ad-hoc changes and functional evolution, as well as delivering a wealth of data for data-science applications. The Cloud Process Execution Engine CPEE.org implements a radically distributed scale-out architecture, together with a minimal set of interfaces, to allow for the simplest possible integration with existing services, machines, and existing data-analysis tools. Its open-source components can serve as a blueprint for future development of commercial solutions, and serves as a proven testbed for academic research, teaching, and industrial application since 2008. In this paper we present the architecture, interfaces that make CPEE.org possible, as well as discuss different lifecycle models utilized during execution to provide overarching support for a wide range of data-analysis tasks.Comment: 30 pages, 12 figures, 2 illustration

Model-Driven Engineering Method to Support the Formalization of Machine Learning using SysML

Methods: This work introduces a method supporting the collaborative definition of machine learning tasks by leveraging model-based engineering in the formalization of the systems modeling language SysML. The method supports the identification and integration of various data sources, the required definition of semantic connections between data attributes, and the definition of data processing steps within the machine learning support. Results: By consolidating the knowledge of domain and machine learning experts, a powerful tool to describe machine learning tasks by formalizing knowledge using the systems modeling language SysML is introduced. The method is evaluated based on two use cases, i.e., a smart weather system that allows to predict weather forecasts based on sensor data, and a waste prevention case for 3D printer filament that cancels the printing if the intended result cannot be achieved (image processing). Further, a user study is conducted to gather insights of potential users regarding perceived workload and usability of the elaborated method. Conclusion: Integrating machine learning-specific properties in systems engineering techniques allows non-data scientists to understand formalized knowledge and define specific aspects of a machine learning problem, document knowledge on the data, and to further support data scientists to use the formalized knowledge as input for an implementation using (semi-) automatic code generation. In this respect, this work contributes by consolidating knowledge from various domains and therefore, fosters the integration of machine learning in industry by involving several stakeholders.Comment: 43 pages, 24 figure, 3 table

Conversational Process Modelling: State of the Art, Applications, and Implications in Practice

Chatbots such as ChatGPT have caused a tremendous hype lately. For BPM applications, it is often not clear how to apply chatbots to generate business value. Hence, this work aims at the systematic analysis of existing chatbots for their support of conversational process modelling as process-oriented capability. Application scenarios are identified along the process life cycle. Then a systematic literature review on conversational process modelling is performed. The resulting taxonomy serves as input for the identification of application scenarios for conversational process modelling, including paraphrasing and improvement of process descriptions. The application scenarios are evaluated for existing chatbots based on a real-world test set from the higher education domain. It contains process descriptions as well as corresponding process models, together with an assessment of the model quality. Based on the literature and application scenario analyses, recommendations for the usage (practical implications) and further development (research directions) of conversational process modelling are derived

A Structured Marketplace for Arbitrary Services

Abstract Creating simple marketplaces with common rules, that enable the dynamic selection and consumption of functionality, is the missing link to allow small businesses to enter the cloud, not only as consumers, but also as vendors. In this paper we present the concepts behind a hybrid service and process repository that can act as the foundation for such a marketplace, as well as a prototype that allowed us to test various real-world scenarios. The advantage of a hybrid service and process repository is, that it not only holds a flat list of services, but exposes a generic set of use cases, information how specific services can be used to implement the use cases as well as information to select services at run-time according to customers goal functions

CEWebS - Cooperative Environment Web Services

Abstract: We are specifying and developing a flexible Web Service based framework that allows us to interactively combine components in order to meet the situationdependent dynamically changing requirements of blended learning. Our goal is to support instructors and students with customisable e-learning templates that are particularly close to their users and directly meet their needs in effective blended learning scenarios. Since the framework we develop is open source, everybody is welcome to share initial experiences