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Sonniger Start in das neue Semester (April 2023). Bildinformationen anzeigen

Sonniger Start in das neue Semester (April 2023).

Foto: Universität Paderborn, Besim Mazhiqi

Jonas Kirchhoff, M. Sc.

 Jonas Kirchhoff, M. Sc.

Software Innovation Campus Paderborn (SICP)

Wissenschaftlicher Mitarbeiter

+49 5251 60-6573
Zukunftsmeile 2
33102 Paderborn
Entscheidungsunterstützung für Energiesysteme

FlexiEnergy: Sektorübergreifende Entscheidungsunterstützung zur flexiblen Gestaltung des Energiesystems unter Unsicherheit

Prozessdigitalisierung mittels LowCode-Software

Pro-LowCode: Entwicklung und Umsetzung eines ganzheitlichen Ansatzes zur Digitalisierung von Prozessen in Industriebetrieben mittels LowCode-Software

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Anti-pattern Detection in Process-Driven Decision Support Systems

J. Kirchhoff, G. Engels, in: Software Business, Springer International Publishing, 2022, pp. 227--243

Decision makers increasingly rely on decision support systems for optimal decision making. Recently, special attention has been paid to process-driven decision support systems (PD-DSS) in which a process model prescribes the invocation sequence of software-based decision support services and the data exchange between them. Thus, it is possible to quickly combine available decision support services as needed for optimally supporting the decision making process of an individual decision maker. However, process modelers may accidentally create a process model which is technically well-formed and executable, but contains functional and behavioral flaws such as redundant or missing services. These flaws may result in inefficient computations or invalid decision recommendations when the corresponding PD-DSS is utilized by a decision maker. In this paper, we therefore propose an approach to validate functionality and behavior of a process model representing a PD-DSS. Our approach is based on expressing flaws as anti-patterns for which the process model can be automatically checked via graph matching. We prototypically implemented our approach and demonstrate its applicability in the context of decision making for energy network planning.

Detecting Data Incompatibilities in Process-Driven Decision Support Systems

J. Kirchhoff, S. Gottschalk, G. Engels, in: Lecture Notes in Business Information Processing, Springer International Publishing, 2022

Decision makers in complex business environments have different goals and constraints and therefore require tailored decision support systems (DSS). Following a low-code approach, a tailored DSS can be created by a decision maker as a process-based composition of existing, interoperable decision support services. Data incompatibilities may be introduced during the design or execution of such a process-driven DSS, e.g., when a service always generates or a decision maker selects data which violates a data constraint of a subsequent service. These incompatibilities cause interrupted or erroneous decision processes. In this paper, we contribute an approach which enables the detection of data incompatibilities in process-driven DSS during process design and execution. Our approach utilizes the JSON Schema specification to define service interfaces and associated type constraints which data produced by services or decision makers can be validated against. We demonstrate our approach in the context of decision support for energy network planning using a prototypical open-source implementation.

Decision Support Ecosystems: Definition and Platform Architecture

J. Kirchhoff, C. Weskamp, G. Engels, in: Decision Support Systems XII: Decision Support Addressing Modern Industry, Business, and Societal Needs, Springer, 2022

Decision support systems are crucial in helping decision makers to quickly identify optimal business decisions in increasingly volatile and complex business environments. However, the ideal DSS for one decision maker may not optimally address the requirements for decision support of another decision maker. This is due to differences between decision makers in business goals, regulatory restrictions or availability of resources such as data. By using a suboptimal DSS, decision makers risk implementing suboptimal decision recommendations which endanger the success of their business. This presents DSS developers with the challenge to implement a customizable DSS which can be tailored to the individual requirements for decision support of a single decision maker. In order to address this challenge, we suggest a decision support ecosystem in which DSS developers, decision makers and other domain experts collaborate using a shared platform to provide and combine reusable decision support services into a tailored DSS. The contribution of our paper is twofold: First, we define the concept of a decision support ecosystem with respect to existing digital business ecosystems and discuss expected benefits and challenges. Second, we present a reference architecture for a shared platform supporting the realization of a decision support ecosystem. We demonstrate our contributions in the example application domain of regional energy distribution network planning.

Requirements-Based Composition of Tailored Decision Support Systems

J. Kirchhoff, C. Weskamp, G. Engels, in: Human-Centered Software Engineering, Springer International Publishing, 2022, pp. 150–162

Corporate decision makers have individual requirements for decision support influenced by business goals, regulatory restrictions or access to resources such as data. Ideally, decision makers could quickly create tailored decision support systems (DSS) themselves which optimally address their individual requirements for decision support. Although service-oriented architectures have been proposed for DSS customization, they are primarily targeting trained software developers and cannot immediately be adapted by decision makers or domain experts with little to no software development knowledge. In this paper, we therefore motivate an assisted process-based service composition approach which can be used by non-developers to create tailored DSS. For assistance during service composition, we contribute a meta-model for the formalization of both decision support requirements and functionality of decision support services. Models created according to the meta-model can be used to detect mismatches between a decision maker’s requirements for decision support and services selected in the service composition representing a DSS. Furthermore, the formalizations may even be used for automated service composition given a decision maker’s decision support requirements. We demonstrate the expressiveness of our meta-model in the domain of regional energy distribution network planning.

Situational Development of Low-Code Applications in Manufacturing Companies

J. Kirchhoff, N. Weidmann, S. Sauer, G. Engels, in: Proceedings of the 25th International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings, ACM, 2022

Companies show an increasing interest in low-code development platforms to facilitate application development by domain experts without sophisticated software development knowledge. Thus, companies aim for a more efficient development of more effective applications since domain experts as so-called citizen developers are no longer limited by the availability and domain knowledge of trained software developers. Nevertheless, efficiency and effectiveness of application development is traditionally also largely influenced by the use of a suitable software development method. Domain experts are, however, not trained in software development methods. This introduces a risk of domain experts creating unusable applications or exceeding the designated time frame of a project (or both). In this paper, we therefore propose an initial version of a situational software development method which supports domain experts in manufacturing companies during the low-code development of applications. The method can be tailored based on situational factors, considering application requirements, features of the used low-code development platform, and characteristics of the development team. We also present feedback corroborating the usefulness of our method and future extension points based on expert interviews.

Low-code experimentation on software products

S. Gottschalk, R. Bhat, N. Weidmann, J. Kirchhoff, G. Engels, in: Proceedings of the 25th International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings, ACM, 2022



Extending Business Model Development Tools with Consolidated Expert Knowledge

S. Gottschalk, J. Kirchhoff, G. Engels, in: Business Modeling and Software Design, 2021

Towards a Decision Support System for Cross-Sectoral Energy Distribution Network Planning

J. Kirchhoff, S.C. Burmeister, C. Weskamp, G. Engels, in: Energy Informatics and Electro Mobility ICT, 2021

Requirements for energy distribution networks are changing fast due to the growing share of renewable energy, increasing electrification, and novel consumer and asset technologies. Since uncertainties about future developments increase planning difficulty, flexibility potentials such as synergies between the electricity, gas, heat, and transport sector often remain unused. In this paper, we therefore present a novel module-based concept for a decision support system that helps distribution network planners to identify cross-sectoral synergies and to select optimal network assets such as transformers, cables, pipes, energy storage systems or energy conversion technology. The concept enables long-term transformation plans and supports distribution network planners in designing reliable, sustainable and cost-efficient distribution networks for future demands.


Specifying Web Interfaces for Command-line Applications Based on OpenAPI

D. Wolters, J. Kirchhoff, G. Engels, in: Service-Oriented Computing – ICSOC 2019 Workshops, Springer, 2019, pp. 30-41



Semantic Data Mediator: Linking Services to Websites

D. Wolters, S. Heindorf, J. Kirchhoff, G. Engels, in: Service-Oriented Computing -- ICSOC 2017 Workshops, Springer International Publishing, 2018, pp. 388-392

Many websites offer links to social media sites for convenient content sharing. Unfortunately, those sharing capabilities are quite restricted and it is seldom possible to share content with other services, like those provided by a user's favorite applications or smart devices. In this paper, we present Semantic Data Mediator (SDM) --- a flexible middleware linking a vast number of services to millions of websites. Based on reusable repositories of service descriptions defined by the crowd, users can easily fill a personal registry with their favorite services, which can then be linked to websites by SDM. For this, SDM leverages semantic data, which is already available on millions of websites due to search engine optimization. Further support for our approach from website or service developers is not required. To enable the use of a broad range of services, data conversion services are automatically composed by SDM to transform data according to the needs of the different services. In addition to linking web services, various service adapters allow services of applications and smart devices to be linked as well. We have fully implemented our approach and present a real-world case study demonstrating its feasibility and usefulness.


XDAI-A: Framework for Enabling Cross-Device Integration of Android Apps

D. Wolters, J. Kirchhoff, C. Gerth, G. Engels, in: Service-Oriented Computing -- ICSOC 2016 Workshops, Springer International Publishing, 2017, pp. 203-206

A lot of people are managing multiple computing devices suited for different purposes, like private and work devices. Integrating applications running on different devices is often a problem, because the services provided by those applications are not meant to be integrated. In this demonstration, we present our XDAI-A framework which enables cross-device integration of services provided by Android apps. The framework uses adapters to convert Android-internal service interfaces of existing apps into external services with a platform-independent interface that can be accessed from applications on other devices and even other platforms. Our ready-to-use framework does not require to alter existing Android apps, since the adapters are installed separately. For the convenient specification of adapters, our framework comes with a domain-specific language (DSL). Additionally, we provide an infrastructure to find and integrate devices and their applications' services.

Linking Services to Websites by Leveraging Semantic Data

D. Wolters, S. Heindorf, J. Kirchhoff, G. Engels, in: 2017 IEEE International Conference on Web Services (ICWS), IEEE, 2017

Websites increasingly embed semantic data for search engine optimization. The most common ontology for semantic data,, is supported by all major search engines and describes over 500 data types, including calendar events, recipes, products, and TV shows. As of today, users wishing to pass this data to their favorite applications, e.g., their calendars, cookbooks, price comparison applications or even smart devices such as TV receivers, rely on cumbersome and error-prone workarounds such as reentering the data or a series of copy and paste operations. In this paper, we present Semantic Data Mediator (SDM), an approach that allows the easy transfer of semantic data to a multitude of services, ranging from web services to applications installed on different devices. SDM extracts semantic data from the currently displayed web page on the client-side, offers suitable services to the user, and by the press of a button, forwards this data to the desired service while doing all the necessary data conversion and service interface adaptation in between. To realize this, we built a reusable repository of service descriptions, data converters, and service adapters, which can be extended by the crowd. Our approach for linking services to websites relies solely on semantic data and does not require any additional support by either website or service developers. We have fully implemented our approach and present a real-world case study demonstrating its feasibility and usefulness.


Cross-Device Integration of Android Apps

D. Wolters, J. Kirchhoff, C. Gerth, G. Engels, in: Service-Oriented Computing, Springer International Publishing, 2016, pp. 171-185

Integrating apps on mobile devices into applications running on other devices is usually difficult. For instance, using a messenger on a smartphone to share a text written on a desktop computer often ends up in a cumbersome solution to transfer the text, because many applications are not designed for such scenarios. In this paper, we present an approach enabling the integration of apps running on Android devices into applications running on other devices and even other platforms. This is achieved by specifying adapters for Android apps, which map their services to a platform-independent service interface. For this purpose, we have developed a domain-specific language to ease the specification of such mappings. Our approach is applicable without the need to modify the existing Android apps providing the service. We analyzed its feasibility by implementing our approach and by specifying mappings for several popular Android apps, e.g., phone book, camera, and file explorer.

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