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Predictive Process Monitoring is becoming more prevalent as an aid for organizations to support their operational processes. However, most software applications available today require extensive technical know-how by the operator and are therefore not suitable for most real-world scenarios. Therefore, this work presents a prototype implementation of a Predictive Process Monitoring dashboard in the form of a web application. The system is based on the PPM Camunda Plugin presented by Bartmann et al. (2021) and allows users to easily create metrics, visualizations to display these metrics, and dashboards in which visualizations can be arranged. A usability test is with test users of different computer skills is conducted to confirm the application’s user-friendliness.
Public electronic procurement (eProcurement), here electronic sourcing (eSourcing) in particular, is almost certainly on the agenda when eGovernment experts meet. Not surprisingly is eProcurement the first high-impact service to be addressed in the European Union- recent Action Plan. This is mainly dedicated to the fact that public procurement makes out almost 20% of Europe- GDP and therefore holds a huge saving potential. To some extent this potential lies in the common European market, since effective cross-boarder eSourcing solutions can open many doors, both for buyers and suppliers. To achieve this, systems and processes and tools, need to be adoptable, transferable as well as be able to communicate with each other. In one word, they need to be interoperable. In many relevant domains, interoperability has reached a very positive level, standards have been established, workflows been put in place. In other domains however, there is still a long road ahead. As a consequence it is crucial to define requirements for such interoperable eSourcing systems and to identify the progress in research and practice.
This thesis explores the possibilities of probabilistic process modelling for the Computer Supported Cooperative Work (CSCW) systems in order to predict the behaviour of the users present in the CSCW system. Toward this objective applicability, advantages, limitations and challenges of probabilistic modelling are excavated in context of CSCW systems. Finally, as a primary goal seven models are created and examined to show the feasibilities of probabilistic process discovery and predictions of the users behaviour in CSCW systems.
The industry standard Decision Model and Notation (DMN) has enabled a new way for the formalization of business rules since 2015. Here, rules are modeled in so-called decision tables, which are defined by input columns and output columns. Furthermore, decisions are arranged in a graph-like structure (DRD level), which creates dependencies between them. With a given input, the decisions now can be requested by appropriate systems. Thereby, activated rules produce output for future use. However, modeling mistakes produces erroneous models, which can occur in the decision tables as well as at the DRD level. According to the Design Science Research Methodology, this thesis introduces an implementation of a verification prototype for the detection and resolution of these errors while the modeling phase. Therefore, presented basics provide the needed theoretical foundation for the development of the tool. This thesis further presents the architecture of the tool and the implemented verification capabilities. Finally, the created prototype is evaluated.
Business rules have become an important tool to warrant compliance at their business processes. But the collection of these business rules can have various conflicting elements. This can lead to a violation of the compliance to be achieved. This conflicting elements are therefore a kind of inconsistencies, or quasi incon- sistencies in the business rule base. The target for this thesis is to investigate how those quasi inconsistencies in business rules can be detected and analyzed. To this aim, we develop a comprehensive library which allows to apply results from the scientific field of inconsistency measurement to business rule formalisms that are actually used in practice.
The status of Business Process Management (BPM) recommender systems is not quite clear as research states. The use of recommenders familiarized itself with the world during the rise of technological evolution in the past decade.Ever since then, several BPM recommender systems came about. However, not a lot of research is conducted in this field. It is not well known to what broad are the technologies used and how are they used. Moreover, this master’s thesis aims at surveying the BPM recommender systems existing. Building on this, the recommendations come in different shapes. They can be positionbased where an element is to be placed at an element’s front, back or to autocomplete a missing link. On the other hand, Recommendations can be textual, to fill the labels of the elements. Furthermore, the literature review for BPM recommender systems took place under the guides of a literature review framework. The framework suggests 5stages of consecutive stages for this sake. The first stage is defining a scope for the research. Secondly, conceptualizing the topic by choosing key terms for literature research. After that in the third stage, comes the research stage.As for the fourth stage, it suggests choosing analysis features over which the literature is to be synthesized and compared. Finally, it recommends defining the research agenda to describe the reason for the literature review. By invoking the mentioned methodology, this master’s thesis surveyed 18 BPM recommender systems. It was found as a result of the survey that there
are not many different technologies for implementing the recommenders. It was also found that the majority of the recommenders suggest nodes that are yet to come in the model, which is called forward recommending. Also, one of the results of the survey indicated the scarce use of textual recommendations to BPM labels. Finally, 18 recommenders are considered less than excepted for a developing field therefore as a result, the survey found a shortage in the number of BPM recommender systems. The results indicate several shortages in several aspects in the field of BPM recommender systems. On this basis, this master’s thesis recommends the future work on it the results.
Multi-agent systems are a mature approach to model complex software systems by means of Agent-Oriented Software Engineering (AOSE). However, their application is not widely accepted in mainstream software engineering. Parallel to this the interdisciplinary field of Agent-based Social Simulation (ABSS) finds increasing recognition beyond the purely academic realm which starts to draw attention from the mainstream of agent researchers. This work analyzes factors to improve the uptake of AOSE as well as characteristics which separate the two fields AOSE and ABSS to understand their gap. Based on the efficiency-oriented micro-agent concept of the Otago Agent Platform (OPAL) we have constructed a new modern and self-contained micro-agent platform called µ². The design takes technological trends into account and integrates representative technologies, such as the functionally-inspired JVM language Clojure (with its Transactional Memory), asynchronous message passing frameworks and the mobile application platform Android. The mobile version of the platform shows an innovative approach to allow direct interaction between Android application components and micro-agents by mapping their related internal communication mechanisms. This empowers micro-agents to exploit virtually any capability of mobile devices for intelligent agent-based applications, robotics or simply act as a distributed middleware. Additionally, relevant platform components for the support of social simulations are identified and partially implemented. To show the usability of the platform for simulation purposes an interaction-centric scenario representing group shaping processes in a multi-cultural context is provided. The scenario is based on Hofstede's concept of 'Cultural Dimensions'. It does not only confirm the applicability of the platform for simulations but also reveals interesting patterns for culturally augmented in- and out-group agents. This explorative research advocates the potential of micro-agents as a powerful general system modelling mechanism while bridging the convergence between mobile and desktop systems. The results stimulate future work on the micro-agent concept itself, the suggested platform and the deeper exploration of mechanisms for seemless interaction of micro-agents with mobile environments. Last but not least the further elaboration of the simulation model as well as its use to augment intelligent agents with cultural aspects offer promising perspectives for future research.
In this work a framework is developed that is used to create an evaluation scheme for the evaluation of text processing tools. The evaluation scheme is developed using a model-dependent software evaluation approach and the focus of the model-dependent part is the text-processing process which is derived from the Conceptual Analysis Process developed in the GLODERS project. As input data a German court document is used containing two incidents of extortion racketeering which happened in 2011 and 2012. The evaluation of six different tools shows that one tool offers great results for the given dataset when it is compared to manual results. It is able to identify and visualize relations between concepts without any additional manual work. Other tools also offer good results with minor drawbacks. The biggest drawback for some tools is the unavailability of models for the German language. They can perform automated tasks only on English documents. Nonetheless some tools can be enhanced by self-written code which allows users with development experience to apply additional methods.
The purpose of this research is to examine various existing cloud-based Internet of Things (IoT) development platforms and evaluate one platform (IBM Watson IoT) in detail using a use case scenario. Internet of Things IoT is an emerging technology that has a vision of interconnecting the virtual world (e.g. clouds, social networks) and the physical world (e.g. device, cars, fridge, people, animals) through the Internet technology. For example, the IoT concept of smart cities which has the objectives to improve the efficiency and development of business, social and cultural services in the city, can be achieved by using sensors, actuators, clouds and mobile devices (IEEE, 2015). A sensor (e.g. temperature sensor) in the building (global world) can send the real-time data to the IoT cloud platform (virtual world), where it can be monitored, stored, analysed, or used to trigger some action (e.g. turn on the cooling system in the building if temperature exceeds a threshold limit). Although, the IoT creates vast opportunities in different areas (e.g. transportation, healthcare, manufacturing industry), it also brings challenges such as standardisation, interoperability, scalability, security and privacy. In this research report, IoT concepts and related key issues are discussed.
The focus of this research is to compare various cloud-based IoT platforms in order to understand the business and technical features they offer. The cloud-based IoT platforms from IBM, Google, Microsoft, PTC and Amazon have been studied.
To design the research, the Design Science Research (DSR) methodology has been followed, and to model the real-time IoT system the IOT-A modelling approach has been used.
The comparison of different cloud based IoT development platforms shows that all of the studied platforms provide basic IoT functionalities such as connecting the IoT devices to the cloud based IoT platform, collecting data from the IoT devices, data storage and data analytics. However, the IBM’s IoT platform appears to have an edge over the other platforms studied in this research because of the integrated run-time environment which also makes it more developer friendly. Therefore, IBM Watson IoT for Bluemix is selected for further examination of its capabilities. The IBM Watson IoT for Bluemix offerings include analytics, risk management, connect and information management. A use case was implemented to assess the capabilities that IBM Watson IoT platform offers. The digital artifacts (i.e. applications) are produced to evaluate the IBM’s IoT solution. The results show that IBM offers a very scalable, developer and deployment friendly IoT platform. Its cognitive, contextual and predictive analytics provide a promising functionality that can be used to gain insights from the IoT data transmitted by the sensors and other IoT devices.
Advanced Auditing of Inconsistencies in Declarative Process Models using Clustering Algorithms
(2021)
To have a compliant business process of an organization, it is essential to ensure a onsistent process. The measure of checking if a process is consistent or not depends on the business rules of a process. If the process adheres to these business rules, then the process is compliant and efficient. For huge processes, this is quite a challenge. Having an inconsistency in a process can yield very quickly to a non-functional process, and that’s a severe problem for organizations. This thesis presents a novel auditing approach for handling inconsistencies from a post-execution perspective. The tool identifies the run-time inconsistencies and visualizes them in heatmaps. These plots aim to help modelers observe the most problematic constraints and help them make the right remodeling decisions. The modelers assisted with many variables can be set in the tool to see a different representation of heatmaps that help grasp all the perspectives of the problem. The heatmap sort and shows the run-time inconsistency patterns, so that modeler can decide which constraints are highly problematic and should address a re-model. The tool can be applied to real-life data sets in a reasonable run-time.