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.

The underlying characteristics of blockchain can facilitate data provenance, data integrity, data security, and data management. It has the potential to transform the healthcare sector. Since the introduction of Bitcoin in the fintech industry, the blcockhain technology has been gaining a lot of traction and its purpose is not just limited to finance. This thesis highlights the inner workings of blockchain technology and its application areas with possible existing solutions. Blockchain could lay the path for a new revolution in conventional healthcare systems. We presented how individual sectors within the healthcare industry could use blockchain and what solution persists. Also, we have presented our own concept to improve the existing paper-based prescription management system which is based on Hyperledger framework. The results of this work suggest that healthcare can benefit from blockchain technology bringing in the new ways patients can be treated.

Constituent parsing attempts to extract syntactic structure from a sentence. These parsing systems are helpful in many NLP applications such as grammar checking, question answering, and information extraction. This thesis work is about implementing a constituent parser for German language using neural networks. Over the past, recurrent neural networks have been used in building a parser and also many NLP applications. In this, self-attention neural network modules are used intensively to understand sentences effectively. With multilayered self-attention networks, constituent parsing achieves 93.68% F1 score. This is improved even further by using both character and word embeddings as a representation of the input. An F1 score of 94.10% was the best achieved by constituent parser using only the dataset provided. With the help of external datasets such as German Wikipedia, pre-trained ELMo models are used along with self-attention networks achieving 95.87% F1 score.

Weiterentwicklung des Newsfeeds von InstaHub und Entwicklung einer Unterrichtsreihe zum Thema „Algorithmen in sozialen Netzwerken“ für die Sekundarstufe II

Current political issues are often reflected in social media discussions, gathering politicians and voters on common platforms. As these can affect the public perception of politics, the inner dynamics and backgrounds of such debates are of great scientific interest. This thesis takes user generated messages from an up-to-date dataset of considerable relevance as Time Series, and applies a topic-based analysis of inspiration and agenda setting to it. The Institute for Web Science and Technologies of the University Koblenz-Landau has collected Twitter data generated beforehand by candidates of the European Parliament Election 2019. This work processes and analyzes the dataset for various properties, while focusing on the influence of politicians and media on online debates. An algorithm to cluster tweets into topical threads is introduced. Subsequently, Sequential Association Rules are mined, yielding wide array of potential influence relations between both actors and topics. The elaborated methodology can be configured with different parameters and is extensible in functionality and scope of application.

Belief revision is the subarea of knowledge representation which studies the dynamics of epistemic states of an agent. In the classical AGM approach, contraction, as part of the belief revision, deals with the removal of beliefs in knowledge bases. This master's thesis presents the study and the implementation of concept contraction in the Description Logic EL. Concept contraction deals with the following situation. Given two concept C and D, assuming that C is subsumed by D, how can concept C be changed so that it is not subsumed by D anymore, but is as similar as possible to C? This approach of belief change is different from other related work because it deals with contraction in the level of concepts and not T-Boxes and A-Boxes in general. The main contribution of the thesis is the implementation of the concept contraction. The implementation provides insight into the complexity of contraction in EL, which is tractable since the main inference task in EL is also tractable. The implementation consists of the design of five algorithms that are necessary for concept contraction. The algorithms are described, illustrated with examples, and analyzed in terms of time complexity. Furthermore, we propose an new approach for a selection function, adapt for the concept contraction. The selection function uses metadata about the concepts in order to select the best from an input set. The metadata is modeled in a framework that we have designed, based on standard metadata frameworks. As an important part of the concept contraction, the selection function is responsible for selecting the best concepts that are as similar as possible to concept C. Lastly, we have successfully implemented the concept contraction in Python, and the results are promising.

Commonsense reasoning can be seen as a process of identifying dependencies amongst events and actions. Understanding the circumstances surrounding these events requires background knowledge with sufficient breadth to cover a wide variety of domains. In the recent decades, there has been a lot of work in extracting commonsense knowledge, a number of these projects provide their collected data as semantic networks such as ConceptNet and CausalNet. In this thesis, we attempt to undertake the Choice Of Plausible Alternatives (COPA) challenge, a problem set with 1000 questions written in multiple-choice format with a premise and two alternative choices for each question. Our approach differs from previous work by using shortest paths between concepts in a causal graph with the edge weight as causality metric. We use CausalNet as primary network and implement a few design choices to explore the strengths and drawbacks of this approach, and propose an extension using ConceptNet by leveraging its commonsense knowledge base.

Business Process Querying (BPQ) is a discipline in the field of Business Process Man- agement which helps experts to understand existing process models and accelerates the development of new ones. Its queries can fetch and merge these models, answer questions regarding the underlying process, and conduct compliance checking in return. Many languages have been deployed in this discipline but two language types are dominant: Logic-based languages use temporal logic to verify models as finite state machines whereas graph-based languages use pattern matching to retrieve subgraphs of model graphs directly. This thesis aims to map the features of both language types to features of the other to identify strengths and weaknesses. Exemplarily, the features of Computational Tree Logic (CTL) and The Diagramed Modeling Language (DMQL) are mapped to one another. CTL explores the valid state space and thus is better for behavioral querying. Lacking certain structural features and counting mechanisms it is not appropriate to query structural properties. In contrast, DMQL issues structural queries and its patterns can reconstruct any CTL formula. However, they do not always achieve exactly the same semantic: Patterns treat conditional flow as sequential flow by ignoring its conditions. As a result, retrieved mappings are invalid process execution sequences, i.e. false positives, in certain scenarios. DMQL can be used for behavioral querying if these are absent or acceptable. In conclusion, both language types have strengths and are specialized for different BPQ use cases but in certain scenarios graph-based languages can be applied to both. Integrating the evaluation of conditions would remove the need for logic-based languages in BPQ completely.

Clubs, such as Scouts, rely on the work of their volunteer members, who have a variety of tasks to accomplish. Often there are sudden changes in their organization teams and offices, whereby planning steps are lost and inexperience in planning occurs. Since the special requirements are not covered by already existing tools, ScOuT, a planning tool for the organization administration, is designed and developed in this work to support clubs with regard to the mentioned problems. The focus was on identifying and using various suitable guidelines and heuristic methods to create a usable interface. The developed product was evaluated empirically by a user survey in terms of usability. The result of this study shows that already a high degree of the desired goal could be reached by the inclusion of the guidelines and methods. From this it can be concluded that with the help of user-specific concept ideas and the application of suitable guidelines and methods, a suitable basis for a usable application to support clubs can be created.

The erosion of the closed innovation paradigm in conjunction with increasing competitive pressure has boosted the interest of both researchers and organizations in open innovation. Despite such rising interest, several companies remain reluctant to open their organizational boundaries to practice open innovation. Among the many reasons for such reservation are the pertinent complexity of transitioning toward open innovation and a lack of understanding of the procedures required for such endeavors. Hence, this thesis sets out to investigate how organizations can open their boundaries to successfully transition from closed to open innovation by analyzing the current literature on open innovation. In doing so, the transitional procedures are structured and classified into a model comprising three phases, namely unfreezing, moving, and institutionalizing of changes. Procedures of the unfreezing phase lay the foundation for a successful transition to open innovation, while procedures of the moving phase depict how the change occurs. Finally, procedures of the institutionalizing phase contribute to the sustainability of the transition by employing governance mechanisms and performance measures. Additionally, the individual procedures are characterized along with their corresponding barriers and critical success factors. As a result of this structured depiction of the transition process, a guideline is derived. This guideline includes the commonly employed actions of successful practitioners of open innovation, which may serve as a baseline for interested parties of the paradigm. With the derivation of the guideline and concise depiction of the individual transitional phases, this thesis consequently reduces the overall complexity and increases the comprehensibility of the transition and its implications for organizations.

Data flow models in the literature are often very fine-grained, which transfers to the data flow analysis performed on them and thus leads to a decrease in the analysis' understandability. Since a data flow model, which abstracts from the majority of implementation details of the program modeled, allows for potentially easier to understand data flow analyses, this master thesis deals with the specification and construction of a highly abstracted data flow model and the application of data flow analyses on this model. The model and the analyses performed on it have been developed in a test-driven manner, so that a wide range of possible data flow scenarios could be covered. As a concrete data flow analysis, a static security check in the form of a detection of insufficient user input sanitization has been performed. To date, there's no data flow model on a similarly high level of abstraction. The proposed solution is therefore unique and facilitates developers without expertise in data flow analysis to perform such analyses.

In dieser Arbeit wird eine Unterrichtsreihe beschrieben, welche aus den drei Bereichen „mathematische Relationen“, „Datenbanken in Sozialen Netzwerken“ und „Datenschutz“ zusammengesetzt ist. Zu jedem Bereich wird ein eigener Unterrichtsentwurf präsentiert. Außerdem wurde im Rahmen der vorliegenden Arbeit ein Programm zur Visualisierung der Relationen des Sozialen Netzwerks Instahub entworfen, welches im Anschluss an die Beschreibung der Unterrichtsreihe aufgeführt wird.

The Internet of Things (IoT) is a fast-growing, technological concept, which aims to integrate various physical and virtual objects into a global network to enable interaction and communication between those objects (Atzori, Iera and Morabito, 2010). The application possibilities are manifold and may transform society and economy similarly to the usage of the internet (Chase, 2013). Furthermore, the Internet of Things occupies a central role for the realisation of visionary future concepts, for example, Smart City or Smart Healthcare. In addition, the utilisation of this technology promises opportunities for the enhancement of various sustainability aspects, and thus for the transformation to a smarter, more efficient and more conscious dealing with natural resources (Maksimovic, 2017). The action principle of sustainability increasingly gains attention in the societal and academical discourse. This is reasoned by the partly harmful consumption and production patterns of the last century (Mcwilliams et al., 2016). Relating to sustainability, the advancing application of IoT technology also poses risks. Following the precautionary principle, these risks should be considered early (Harremoës et al., 2001). Risks of IoT for sustainability include the massive amounts of energy and raw materials which are required for the manufacturing and operation of IoT objects and furthermore, the disposal of those objects (Birkel et al., 2019). The exact relations in the context of IoT and sustainability are insufficiently explored to this point and do not constitute a central element within the discussion of this technology (Behrendt, 2019). Therefore, this thesis aims to develop a comprehensive overview of the relations between IoT and sustainability. To achieve this aim, this thesis utilises the methodology of Grounded Theory in combination with a comprehensive literature review. The analysed literature primarily consists of research contributions in the field of Information Technology (IT). Based on this literature, aspects, solution approaches, effects and challenges in the context of IoT and sustainability were elaborated. The analysis revealed two central perspectives in this context. IoT for Sustainability (IoT4Sus) describes the utilisation and usage of IoT-generated information to enhance sustainability aspects. In contrast, Sustainability for IoT (Sus4IoT) fo-cuses on sustainability aspects of the applied technology and highlights methods to reduce negative impacts, which are associated with the manufacturing and operation of IoT. Elaborated aspects and relations were illustrated in the comprehensive CCIS Framework. This framework represents a tool for the capturing of relevant aspects and relations in this context and thus supports the awareness of the link between IoT and sustainability. Furthermore, the framework suggests an action principle to optimise the performance of IoT systems regarding sustainability. The central contribution of this thesis is represented by the providence of the CCIS Framework and the contained information regarding the aspects and relations of IoT and sustainability.

In order to plan the interior of a room, various programs for computers, smart phones or head-mounted displays are available. The transfer to the real environment is a difficult task. Therefore an augmented reality approach is developed to illustrate the planning in the real room. If several people want to contribute their ideas, conventional systems require to work on one device together. The aim of this master thesis is to design and develop a collaborative spatial planning application in augmented reality. The application is developed in Unity with ARCore and C#.

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.

Eine didaktisch-methodische Ausarbeitung einer Unterrichtsreihe zur Online-Plattform InstaHub mit dem Themenschwerpunkt Datenschutz. Die Unterrichtsreihe ist für die Klassenstufe 5-6 (und höher) eines Gymnasiums geeignet. Weiterhin werden Anregungen für Datenschutz im Unterricht gegeben.

A gonioreflectometer is a device to measure the reflection properties of arbitrary materials. In this work, such an apparatus is being built from easily obtainable parts. Therefore three stepper-motors and 809 light-emitting diodes are controlled by an Arduino microcontroller. RGB-images are captured with an industrial camera which serve as refelction data. Furthermore, a control software with several capture programs and a renderer for displaying the measured materials are implemented. These allow capturing and rendering entire bidirectional reflection distribution functions (BRDFs) by which also complex anisotropic material properties can be represented. Although the quality of the results has some artifacts due to shadows of the camera, these artifacts can be largely removed by using special algorithms like inpainting. In addition, the goniorefelctometer is applied to other use cases. One can perform 3D scans, light field capturing and light staging without altering the construction. The quality of these processes also meet the expectations in a positive way. Thus, the gonioreflectometer built in this work can be seen as a widely applicable and economical alternative to other publications.

Tracking is an integral part of many modern applications, especially in areas like autonomous systems and Augmented Reality. For performing tracking there are a wide array of approaches. One that has become a subject of research just recently is the utilization of Neural Networks. In the scope of this master thesis an application will be developed which uses such a Neural Network for the tracking process. This also requires the creation of training data as well as the creation and training of a Neural Network. Subsequently the usage of Neural Networks for tracking will be analyzed and evaluated. This includes several aspects. The quality of the tracking for different degrees of freedom will be checked as well as the the impact of the Neural Network on the applications performance. Additionally the amount of required training data is investigated, the influence of the network architecture and the importance of providing depth data as part of the networks input. This should provide an insight into how relevant this approach could be for its adoption in future products.

Die im Rahmen dieser Masterarbeit durchgeführte Analyse von Ernährungsumstellungen auf die vegane Ernährung in Form von vier Portraits lotet mit ihrer interdisziplinären Perspektive aus Gastrosophie, Ethnologie und Leibphilosophie die soziokulturellen Aspekte dieser Transmissionsprozesse aus. Dazu gehören der zivilisatorisch erlernte Umgang mit Nahrung, das Umsetzen und Reflektieren sinnlicher Wahrnehmungen im Ernährungsprozess und die Prägung von Relationen zwischen Essendem und Zu-Essendem. Geleitet wird die Analyse dabei von der Forschungsfrage: „Welche leiblich sinnlichen Wahrnehmungen geben den Anstoß zu einer Ernährungsumstellung und wie begleiten diese den Prozess der Umstellung?“. Damit gibt die Frage den Fokus auf das (leibliche) Wahrnehmungsvermögen des Menschen vor und begrenzt Ernährung bewusst nicht auf ihre physiologische Funktion der Energiegewinnung. Dadurch flicht sie sich in den Diskurs um den cultural turn in der Ernährungswissenschaft ein und zielt weg von der metabolischen Durchmessung des Essens, hin auf das Verständnis von Ernährung als Praxis des Sich-Einverleibens-von-Anderem – Essen als Vollzug von Beziehungen. Das Sich-Ernähren wird damit als sozial geprägter und leiblich vermittelter Erfahrungsvorgang sichtbar, der über das Geschmackserlebnis hinaus durch Betroffenheitserfahrung konstituiert wird. Durch das Zusammenbringen philosophischer Perspektiven, wie die der Gastrosophie Harald Lemkes, die Essen u. a. auch als Selbstbestimmung denkt, und soziologischen Theorien, wie die des Habitus-Konzepts nach Pierre Bourdieu, wird deutlich, wie die Wahrnehmungspraxis und -fähigkeit des Menschen, in ihrem leiblichsinnlichen Aspekt, die Verhaltensbestimmung im Umgang mit Nahrung und deren Quellen beeinflusst. Die vier Portraits entstanden während einer sechsmonatigen ethnographischen Feldforschung und stellen anonymisiert die Motivation, den Verlauf und das Konfliktthema der jeweiligen Ernährungsumstellung dar. Die Portraits sind sehr individuell und zeigen auf, wie und warum beispielsweise die gesundheitliche Selbstsorge oder das empathische Mitleiden mit Nutztieren Veränderungen oder Tabuisierungen im Ernährungshandeln anstoßen.

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.

Our work finds the fine grained edits in context of neighbouring tokens in Wikipedia articles. We cluster those edits according to similar neighbouring context. We encode neighbouring context into vector space using word vectors. We evaluate clusters returned by our algorithm on extrinsic and intrinsic metric and compare it with previous work. We analyse the relation between extrinsic and intrinsic measurements of fine grained edit tokens.

The purpose of this thesis is to explore the sentiment distributions of Wikipedia concepts. We analyse the sentiment of the entire English Wikipedia corpus, which includes 5,669,867 articles and 1,906,375 talks, by using a lexicon-based method with four different lexicons. Also, we explore the sentiment distributions from a time perspective using the sentiment scores obtained from our selected corpus. The results obtained have been compared not only between articles and talks but also among four lexicons: OL, MPQA, LIWC, and ANEW. Our findings show that among the four lexicons, MPQA has the highest sensitivity and ANEW has the lowest sensitivity to emotional expressions. Wikipedia articles show more sentiments than talks according to OL, MPQA, and LIWC, whereas Wikipedia talks show more sentiments than articles according to ANEW. Besides, the sentiment has a trend regarding time series, and each lexicon has its own bias regarding text describing different things. Moreover, our research provides three interactive widgets for visualising sentiment distributions for Wikipedia concepts regarding the time and geolocation attributes of concepts.

We examine the systematic underrecognition of female scientists (Matilda effect) by exploring the citation network of papers published in the American Physical Society (APS) journals. Our analysis shows that articles written by men (first author, last author and dominant gender of authors) receive more citations than similar articles written by women (first author, last author and dominant gender of authors) after controlling for the journal of publication, year of publication and content of the publication. Statistical significance of the overlap between the lists of references was considered as the measure of similarity between articles in our analysis. In addition, we found that men are less likely to cite articles written by women and women are less likely to cite articles written by men. This pattern leads to receiving more citations by articles written by men than similar articles written by women because the majority of authors who published in APS journals are male (85%). We also observed Matilda effect reduces when articles are published in journals with the highest impact factors. In other words, people’s evaluation of articles published in these journals is not affected by the gender of authors significantly. Finally, we suggested a method that can be applied by editors in academic journals to reduce the evaluation bias to some extent. Editors can identify missing citations using our proposed method to complete bibliographies. This policy can reduce the evaluation bias because we observed papers written by female scholars (first author, last author, the dominant gender of authors) miss more citations than articles written by male scholars (first author, last author, the dominant gender of authors).

Knowledge-based authentication methods are vulnerable to Shoulder surfing phenomenon. The widespread usage of these methods and not addressing the limitations it has could result in the user’s information to be compromised. User authentication method ought to be effortless to use and efficient, nevertheless secure. The problem that we face concerning the security of PIN (Personal Identification Number) or password entry is shoulder surfing, in which a direct or indirect malicious observer could identify the user sensitive information. To tackle this issue we present TouchGaze which combines gaze signals and touch capabilities, as an input method for entering user’s credentials. Gaze signals will be primarily used to enhance targeting and touch for selecting. In this work, we have designed three different PIN entry method which they all have similar interfaces. For the evaluation, these methods were compared based on efficiency, accuracy, and usability. The results uncovered that despite the fact that gaze-based methods require extra time for the user to get familiar with yet it is considered more secure. In regards to efficiency, it has the similar error margin to the traditional PIN entry methods.

Im Rahmen der Masterarbeit wird die kompetenzgestützte Weiterbildungssuche analysiert und am Beispiel des Weiterbildungsvergleichsportales EDUfittery dargestellt. Die Umsetzung und Integration eines Kompetenzmessverfahrens in ein Vergleichsportal für Weiterbildungen war das Ziel dieser Arbeit. Des Weiteren sollte anhand des Kompetenzmessverfahrens ein sogenanntes „Matching“ zwischen Kompetenz und Weiterbildung erarbeitet werden. Beim „Matching“ werden dementsprechend die vom Kunden eingegebenen Kompetenzen mit passenden Weiterbildungsvorschlägen verbunden. Somit wird ein individuelles Kundenerlebnis in der Weiterbildungssuche erreicht. Um dies zu ermöglichen, wird zu Beginn der Arbeit ein theoretisches Kompetenzschema analysiert, sodass Aussagen über Erhebungsverfahren und Auswertungsstrategien getroffen werden können, um diese, besonders in Bezug auf ein web-gestütztes Messinstrument, kritisch zu hinterfragen. Aufbauend auf der Analyse verschiedener Kompetenzmessverfahren im Online-Segment, kann gezeigt werden, dass die Kompetenzdiagnostik zwar einige Verfahren zur Verfügung stellt, doch nur wenige sind praktikabel und in der Lage tätigkeitsbezogene Handlungskompetenzen zu bewerten. Folglich wurde das Instrument der Selbsteinschätzung von Kompetenzen als am besten zutreffendes Verfahren für EDUfittery gewählt. Im Zuge der Arbeit wurden zwei Online-Umfragen und ein Experteninterview durchgeführt. Dabei wurden zum einen Mitarbeiter, als auch Personaler in Bezug auf Weiterbildungen befragt. Als Experte konnte Herr Korn, von der IHK Akademie Koblenz gewonnen werden. Anhand der Umfrageergebnisse und weiterer Recherchen konnte ein umfangreicher Business Case für EDUfittery angefertigt und mit Prozessdiagrammen veranschaulicht werden. Es wird ersichtlich, dass das Thema Kompetenzanalysen in Unternehmen bisher kaum Anwendung findet. Bei genauerer Betrachtung der aktuellen Marktsituation wird zusätzlich klar, dass es derzeitig noch keine Plattform gibt, die Kompetenzen mit Weiterbildungen erfolgreich in Zusammenhang bringt, um dem Kunden individuelle Weiterbildungslösungen anbieten zu können. Als Ergebnis der Arbeit kann demnach festgehalten werden, dass eine Integration von Kompetenzanalysen im Bereich Weiterbildungssuche durchaus sinnvoll ist. EDUfittery könnte sich bei erfolgreicher Umsetzung als hilfreiches Tool im Bereich Weiterbildung und Kompetenz etablieren und somit Unternehmen grundlegend bei der Abbildung, Analyse und Weiterentwicklung von Kompetenzen unterstützen.