Ralph Bergmann

Universität Trier · Department of Computer Studies / Business Informatics

This paper presents a novel approach to the operator-based adapta- tion of workflows, which is a specific type of transformational adaptation. We introduce the notion of workflow adaptation operators which are partial functions transforming a workflow into a successor workflow, specified by workflow frac- tions to be inserted and/or deleted. The ad...

Social workflows pervade peoples׳ everyday life. Whenever a group of persons works together on a challenging or multifaceted task, a social workflow begins. Unlike traditional business workflows, such social workflows aim at supporting processes that contain personal tasks and data. In this work, we envision a social workflow service as part of a s...

The Collaborative Agile Knowledge Engine (CAKE) is a prototypical generic software system for integrated process and knowledge management. CAKE integrates recent re-search results on agile workflows, process-oriented case-based reasoning, and web technologies into a common platform that can be configured to different application domains and needs....

In the recent years, the use of workflows has significantly expanded from its original domain of business processes towards new areas. The increasing demand for individual and more flexible workflows asks for new methods that support domain experts to create, monitor, and adapt workflows. The emergent field of process-oriented case-based reasoning...

The use of Artificial Intelligence, and especially Machine Learning methods, promise to play key roles in the development of Digital Twins due to their outstanding properties in processing large IoT data streams. However, so far, there is a lack of research on the systematisation of Machine Learning-based Digital Twins (MLDTs) as well as on their m...

Case-Based Reasoning (CBR) solves new problems by using experience represented by solved cases. The acquisition of adaptation knowledge and its subsequent application remains a classic challenge for CBR applications. In this paper, we present a novel approach for adapting semantic workflows during the reuse phase of the CBR cycle. A reinforcement l...

This paper presents a case-based approach for workflow flexibility by deviation. In previous work, a constraint-based workflow model and engine have been developed that allow for flexible deviations from predefined workflow models during run-time. When encountering deviations, domain-independent strategies can be applied for a resolution in order t...

Modeling similarity measures in Case-Based Reasoning is a knowledge-intensive, demanding, and error-prone task even for domain experts. Visualizations offer support for users, but are currently only available for certain subdomains and case representations. Currently, there are only visualizations that can be used for local attributes or specific c...

Case-Based Reasoning (CBR) is a methodology with many applications in industrial and scientific domains. Over the past decades, various frameworks have been developed to facilitate the development of CBR applications. For practitioners and researchers, it is challenging to overview the landscape of existing frameworks with their specific scope and...

To build intelligent manufacturing systems that react flexibly in case of failures or unexpected circumstances, manufacturing capabilities of production systems must be utilized as much as possible. Artificial Intelligence (AI) and, in particular, automated planning can contribute to this by enabling flexible production processes. To efficiently le...

The research area of Internet of Things (IoT) is gaining more relevance for several domains and application areas, including Case-Based Reasoning (CBR). However, IoT data is characterized by high volumes and variance of data types, making the application of CBR methods difficult. Since only few works have been published in this area so far, the int...

Digital transformation is both an opportunity and a challenge. To take advantage of this opportunity for humans and the environment, the transformation process must be understood as a design process that affects almost all areas of life. In this paper, we investigate AI-Based Self-Adaptive Cyber-Physical Process Systems (AI-CPPS) as an extension of...

Modern technologies such as the Internet of Things (IoT) are becoming increasingly important in various fields, including business process management (BPM) research. An important area of research in BPM is process mining, which can be used to analyze event logs e.g., to check the conformance of running processes. However, the data ingested in IoT e...

Similarity-based retrieval of semantic graphs is a crucial task of Process-Oriented Case-Based Reasoning (POCBR) that is usually complex and time-consuming, as it requires some kind of inexact graph matching. Previous work tackles this problem by using Graph Neural Networks (GNNs) to learn pairwise graph similarities. In this paper, we present a no...

In Process-Oriented Case-Based Reasoning (POCBR), experiential knowledge from previous problem-solving situations is retrieved from a case base to be reused for upcoming problems. The task of retrieval is approached in previous work by using Graph Neural Networks (GNNs) to learn workflow similarities which are, in turn, used to find similar workflo...

Data and process mining techniques can be applied in many areas to gain valuable insights. For many reasons, accessibility to real-world business and medical data is severely limited. However, research, but especially the development of new methods, depends on a sufficient basis of realistic data. Due to the lack of data, this progress is hindered....

Conformance checking is a process mining technique that allows verifying the conformance of process instances to a given model. Many conformance checking algorithms provide quantitative information about the conformance of a process instance through metrics such as fitness. Fitness measures to what degree the model allows the behavior observed in t...

The Internet of Things (IoT) has been shown to be very valuable for Business Process Management (BPM), for example, to better track and control process executions. While IoT actuators can automatically trigger actions, IoT sensors can monitor the changes in the environment and the humans involved in the processes. These sensors produce large amount...

Today, it is difficult for companies to react to unforeseen events, e. g., global crises. Highly standardized manufacturing processes are particularly limited in their ability to react flexibly, creating a demand for more advanced workflow management techniques, e. g., extended by artificial intelligence methods. In this paper, we describe how Case...

Monitoring the state of currently running processes and reacting to ad-hoc situations during runtime is a key challenge in Business Process Management (BPM). This is especially the case in cyber-physical environments that are characterized by high context sensitivity. MAPE-K control loops are widely used for self-management in these environments an...

Crises, such as the COVID-19 pandemic, pose unprecedented challenges for governmental or healthcare organizations as well as for the entire industry and the service sector. For instance, shifts in business areas due to increased infection control regulations led to overburdened or underchallenged units within the organizations. Thus, the flexible a...

Conformance checking is a process mining technique that allows verifying the conformance of process instances to a given model. Thus, this technique is predestined to be used in the medical context for the comparison of treatment cases with clinical guidelines. However, medical processes are highly variable, highly dynamic, and complex. This makes...

During crises such as COVID-19, there is a need to adapt existing work processes and teams to the changing environment in a very flexible and dynamic way in many business and healthcare organizations. In this paper, we conceptualize the advances required for Process-Oriented Case-Based Reasoning to flexibly and dynamically organize human resources...

Modern technologies such as the Internet of Things (IoT) are becoming increasingly important in various domains, including Business Process Management (BPM) research. One main research area in BPM is process mining, which can be used to analyze event logs, e.g., for checking the conformance of running processes. However, there are only a few IoT-ba...

Conformance checking enables organizations to determine whether their executed processes are compliant with the intended process. However, if the processes contain recurring activities, state-of-the-art approaches unfortunately have difficulties calculating the conformance. The occurrence of complex temporal rules can further increase the complexit...

In Process-Oriented Case-Based Reasoning (POCBR), determining the similarity between cases represented as semantic graphs often requires some kind of inexact graph matching, which generally is an NP-hard problem. Heuristic search algorithms such as A* search have been successfully applied for this task, but the computational performance is still a...

The hyperparameter configuration of machine learning models has a great influence on their performance. These hyperparameters are often set either manually w. r. t. to the experience of an expert or by an Automated Hyperparameter Optimization (HPO) method. However, integrating experience knowledge into HPO methods is challenging. Therefore, we prop...

Process management and process orchestration/execution are currently hot topics; prevalent trends such as automation and Industry 4.0 require solutions which allow domain-experts to easily model and execute processes in various domains, including manufacturing and health-care. These domains, in turn, rely on a tight integration between hardware and...

In Case-Based Reasoning (CBR), knowledge gained from previously experienced problem-solving situations is stored as cases that can be used to solve similar upcoming problems. Although these cases act as independent knowledge entities, dependencies between cases are common in real-world scenarios, despite being only rarely considered during case ret...

The developments of new concepts for an increased digitization of manufacturing industries in the context of Industry 4.0 have brought about novel system architectures and frameworks for smart production systems. These range from generic frameworks for Industry 4.0 to domain-specific architectures for Industrial Internet of Things (IIoT). While mos...

Monitoring the state of currently running processes and reacting to deviations during runtime is a key challenge in Business Process Management (BPM). The MAPE-K control loop describes four phases for approaching this challenge: Monitor, Analyze, Plan, Execute. In this paper, we present the ProGAN framework, an idea of an approach for implementing...

Similarity-based retrieval of semantic graphs is a core task of Process-Oriented Case-Based Reasoning (POCBR) with applications in real-world scenarios, e.g., in smart manufacturing. The involved similarity computation is usually complex and time-consuming, as it requires some kind of inexact graph matching. To tackle these problems, we present an...

Adaptive workflow management is an important topic in recent years, as increasing dynamics due to growing customer demands and faster changing market conditions require more flexibility in workflows. This is especially the case for rigid and rather standardized production processes that cannot be easily modified, if, for example, a breakdown occurs...

The construction and completion of knowledge graphs in industrial settings has gained traction over the past years. However, modelling a specific domain is often entailed with significant cost. This can be alleviated by including other knowledge sources such as text—a challenge known as open-world knowledge graph completion. Although knowledge grap...

Currently, Deep Learning (DL) components within a Case-Based Reasoning (CBR) application often lack the comprehensive integration of available domain knowledge. The trend within machine learning towards so-called Informed machine learning can help to overcome this limitation. In this paper , we therefore investigate the potential of integrating dom...

Modeling and executing knowledge-intensive processes (KiPs) are challenging with state-of-the-art approaches, and the specific demands of KiPs are the subject of ongoing research. In this context, little attention has been paid to the ontology-driven combination of data-centric and semantic business process modeling, which finds additional motivati...

The accelerated growth of available data causes case bases of increasing sizes and thus lowers efficiency during the case retrieval phase in Case-Based Reasoning (CBR) systems. Even though, many complex and data-intensive tasks are solved by using Graphic Processing Units (GPUs), its application in CBR research has yet to advance past the early sta...

The production industry is in a transformation towards more autonomous and intelligent manufacturing. In addition to more flexible production processes to dynamically respond to changes in the environment, it is also essential that production processes are continuously monitored and completed in time. Video-based methods such as object detection sy...

The production and manufacturing industries are currently transitioning towards more autonomous and intelligent production lines within the Fourth Industrial Revolution (Industry 4.0). Learning Factories as small scale physical models of real shop floors are realistic platforms to conduct research in the smart manufacturing area without depending o...

The transition to Industry 4.0 requires smart manufacturing systems that are easily configurable and provide a high level of flexibility during manufacturing in order to achieve mass customization or to support cloud manufacturing. To realize this, Cyber-Physical Systems (CPSs) combined with Artificial Intelligence (AI) methods find their way into...

Similarity-based retrieval of semantic graphs is widely used in real-world scenarios, e. g., in the domain of business workflows. To tackle the problem of complex and time-consuming graph similarity computations during retrieval, the MAC/FAC approach is used in Process-Oriented Case-Based Reasoning (POCBR), where similar graphs are extracted from a...

The similarity assessment of graphs is a fundamental problem that is particularly challenging if efficiency is of core importance. In this paper, we focus on a similarity measure for semantically labeled graphs whose labels are composed in an object-oriented manner. The measure is based on A* search and is particularly suited for case-based reasoni...

Our objective is to develop an approach based on case-based reasoning that detects and handles unforeseen deviations that occur in flexible workflow execution. With a case-based approach we aim at supporting the continuation of a deviant workflow execution by utilizing successfully completed processes, where similar deviations emerged. As a first s...

Process Mining is a technology family for the analysis of business processes based on event logs. The methods are successfully applied in various areas, including medicine. This paper examines, using a systematic literature review, whether Process Mining is suitable for case acquisition from Hospital Information Systems in order to construct a case...

The transition to Industry 4.0 requires smart manufacturing systems that are easily configurable and provide a high level of flexibility during manufacturing in order to achieve mass customization or to support cloud manufacturing. To realize this, Cyber-Physical Systems (CPSs) combined with Artificial Intelligence (AI) methods find their way into...

Argumentation Machines search for arguments in natural language from information sources on the Web and reason with them on the knowledge level to actively support the deliberation and synthesis of arguments for a particular user query. The recap project is part of the Priority Program ratio and aims at novel contributions to and confluence of meth...

This paper targets the automated extraction of components of argumentative information and their relations from natural language text. Moreover, we address a current lack of systems to provide complete argumentative structure from arbitrary natural language text for general usage. We present an argument mining pipeline as a universally applicable a...

Research on computational argumentation is currently being intensively investigated. The goal of this community is to find the best pro and con arguments for a user given topic either to form an opinion for oneself, or to persuade others to adopt a certain standpoint. While existing argument mining methods can find appropriate arguments for a topic...

The data provided by cyber-physical production systems (CPPSs) to monitor their condition via data-driven predictive maintenance is often high dimensional and only a few fault and failure (FaF) examples are available. These FaFs can usually be detected in a (small) localized subset of data streams, whereas the use of all data streams induces noise...

Nowadays, semantic information provided by an ontology is indispensable in the context of Industry 4.0, especially when using methods from Artificial Intelligence. The currently available ontologies do not satisfy the demands of simulation environments used for research purposes. For this reason, we develop an ontology customized to Fischertechnik...

Many researchers have addressed the demands of knowledge intensive processes and often propose a data-oriented workflow approach. Others use ontologies in the periphery of workflow management systems to achieve different kind of contributions, while just a few research utilize the ontology for a semantic process definition. This paper introduces a...

This paper presents ProCAKE - the process-oriented case-based knowledge engine of the CAKE framework, which has evolved from several research projects at the University of Trier over the years. ProCAKE constitutes a domain-independent framework that can be used to implement diverse structural or process-oriented case-based reasoning applications fo...

Research on argumentation in Artificial Intelligence recently investigates new methods that contribute to the vision of developing robust argumentation machines. One line of research explores ways of reasoning with natural language arguments coming from information sources on the web as a foundation for the deliberation and synthesis of arguments i...

Argumentation is an important sub-field of Artificial Intelligence, which involves computational methods for reasoning and decision making based on argumentative structures. This paper contributes to case-based reasoning with argument graphs in the standardized Argument Interchange Format by improving the similarity-based retrieval phase. We explor...

In process-oriented case-based reasoning, similarity-based retrieval of workflow cases from large case bases is still a difficult issue due to the computationally expensive similarity assessment. The two-phase MAC/FAC (“Many are called, but few are chosen”) retrieval has been proven useful to reduce the retrieval time but comes at the cost of an ad...

This paper investigates automatic adaptation of scientific workflows in process-oriented case-based reasoning with the goal of providing modeling assistance. With regard to our previous work on the adaptation of business workflows, we discuss the differences between the workflow types and the implications for transferring the approaches to scientif...

Manufacturing systems naturally contain plenty of sensors which produce data primarily used by the control software to detect relevant status information of the actuators. In addition, sensors are included in order to monitor the health status of specific components, which enable to detect certain known, frequently occurring faults or undesired sta...

In the field of argumentation, the vision of robust argumentation machines is investigated. They explore natural language arguments from information sources on the web and reason with them on the knowledge level to actively support the deliberation and synthesis of arguments for a particular user query. We aim at combining methods from case-based re...

The concept developed during the SEMAFLEX project combines knowledge‐based document management with flexible workflow management to achieve ideal support for small‐ and medium‐sized enterprises. This paper focusses on the workflow approach that implements flexibility by deviation on the basis of constraint satisfaction problem solving. Workflow dev...

Supporting knowledge-intensive processes (KiPs) has been widely addressed so far and is still subject of discussion. In this context, little attention was paid to the ontology-driven combination of data-centric and semantic business process modeling, which finds its motivation in supporting KiPs by enabling work sharing between humans and artificia...

The increasing demand for individual and more flexible process models and workflows asks for new intelligent process-oriented information systems. Such systems should, among other things, support domain experts in the creation and adaptation of process models or workflows. For this purpose, repositories of best practice workflows are an important m...

Scientific Workflows do not seem to be broadly used today in the Digital Humanities to perform text and data analysis. Although they have become established in e-Science, modeling new workflows is usually a demanding task, especially for novice users. Case-Based Reasoning (CBR) has been applied in the past to support the development of workflows as...

This paper investigates the generation of recipes in consideration of user-defined nutrient contents. For this purpose, we extend our previous case-based reasoning approach that already covers the formulation of user queries with various dietary practices. More precisely, this work augments the domain ontology with nutritional information and intro...

Process-oriented case-based reasoning (POCBR) supports workflow modeling by retrieving and adapting workflows that have proved useful in the past. Current approaches typically require users to specify detailed queries, which can be a demanding task. Conversational case-based reasoning (CCBR) particularly addresses this problem by proposing methods...

This paper introduces a novel approach which unifies a datacentric and a constraint-based workflow principle to support the requirements of knowledge intensive business processes. By the integration of a knowledge-based system, process definition and execution relevant data coincide on an ontology-based semantic net. The data, mainly driving the proce...

This paper introduces a novel approach for flexible workflow management by applying constraint satisfaction problem solving. This enables us to support workflow deviations at runtime, react to upcoming events or unpredictable circumstances, but still support the user through worklist suggestions. The developed workflow engine is completely based on...

One of the biggest challenges in business process management is the creation of appropriate and efficient workflows. This asks for intelligent, knowledge-based systems that assist domain experts in this endeavor. In this paper we investigate workflow creation by applying Process-Oriented Case-Based Reasoning (POCBR). We introduce POCBR and describe...