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Informatik 5
Information Systems
Prof. Dr. M. Jarke
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Prof. Dr. M. Jarke
RWTH Aachen
Informatik 5
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D-52056 Aachen
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Running Theses


Bachelor
Reach for the Stars: Gamified Group Work in Mixed Reality
Supervised by PD Dr. Ralf Klamma, AOR; Advisor(s): Benedikt Hensen, M.Sc.
Collaboration and group work are essential parts of learning since they encourage students to exchange ideas, to learn from each other and to support each other. The ability to work as a team increases the quality and amount of results and is therefore a highly demanded soft skill. However, students who face group work in courses still encounter challenges regarding efficient coordination, motivation and communication when working on group assignments or in learning groups. This becomes evident in processes where one person does all the work. Other common examples include a lack of communication where the group accumulates their individual results only at the end of the project and the participants cannot compensate if some members failed to deliver their results on time. Mixed Reality bears the potential to provide a structured 3D environment for organization and collaboration where group tasks can be split up visually between participants in virtual meetings. Additionally, Gamification can provide means of motivation to continue with a learning task and to strengthen the unity of the team.
Bachelor
Automatic HyperGraphQL Bootstrapping for Triplestores
Supervised by Prof. Dr. Stefan Decker, Prof. Markus Strohmaier; Advisor(s): Lars Gleim, M. Sc., Dipl.-Medieninf. István Koren
In the context of this bachelor thesis, the student should employ (existing) SPARQL queries to automatically extract the data schema (Ontology) of a given RDF graph and programmatically convert it to a HyperGraphQL Schema, thus greatly simplifying the deployment of GraphQL API endpoints for RDF Triplestores.
Master
Extending the b-it Chain to execute smart contracts
Supervised by Prof. Dr. Thomas Rose; Advisor(s): Thomas Osterland
Often only noticed as a technology that enables the digital currency Bitcoin, blockchain is a novel protocol that allows the distributed and secure storing of information and untempered execution of program code in trust-less environments. Did you ever feel the intense desire to write a thesis about blockchain or do you have a slight hope that blockchain is the one-and-only topic that touches your heart? Use your chance now! We are looking forward to hear from you.
Master
Utilize Chat Interfaces for Social Bot Creation
Social Bots (software robots) are computer algorithms that automatically produce content and interact with humans on social media. This thesis will utilize chat interfaces and a social bot framework to create social bots. It will also extend the framework to support various social bot types (e.g. chatbots, crawlers, transactional bots or informational bots).
Master
Privacy Attack on Social Networks Using Network Embeddings
Supervised by Prof. Dr. Markus Strohmaier, Prof. Dr. Stefan Decker; Advisor(s): Dr. Florian Lemmerich, Dr. Michael Cochez
Abstract. A company that runs a social network trains a node embedding on the network where each account is represented by one node. One user deletes his account. Thus, the company is legally required to remove all private information of that user. This includes the node associated with the user’s account and the vector representation of that node that is generated by the embedding. The company, however, does likely not delete the vector representations of the other nodes even though the removed node was used during training of these. Is it possible to identify the neighbors of the removed node? Which kinds of neighbors can be identified best, which cannot be identified? First results suggest that the identification of neighbors works well for some kind of nodes and is more difficult for others.
Bachelor
Master
Graph-Structured Query Construction for Natural Language Questions
Supervised by Prof. Dr. Stefan Decker; Advisor(s): Dr. Michael Cochez
Graph-structured queries provide an efficient means to retrieve desired data from large-scale knowledge graphs. However, it is difficult for non-expert users to write such queries, and users prefer expressing their query intention through natural language questions. Recently, an increasing effort is being exerted to construct graph-structured queries for given natural language questions. At the core of the construction is to deduce the structure of the target query and retrieve vertices/edges of the underlying knowledge graph which constitute the query. Existing query construction methods rely on conventional graph-based algorithms and question understanding techniques, which lead to inefficient and degraded performances facing complicated natural language questions over knowledge graphs with large scales. In this thesis, we focus on this problem and propose novel construction models standing on recent knowledge graph embedding techniques. Extensive experiments were conducted on question answering benchmark datasets, and the results demonstrate that our models outperform baselines in terms of effectiveness and efficiency.
Master
A Neural Network Model for Visualization Recommendation System
A Recommendation Tool for Data Visualization using Artificial Neural Networks
Master
Machine Economy for Dynamic Configurations of Production Processes
Supervised by Prof. Dr. Thomas Rose; Advisor(s): Thomas Osterland
In the context of Industry 4.0 and the Internet of Things, the autonomization of cyber physical systems is increasingly coming to the fore. Just imagine an autonomous vehicle that offers commuter services against payment. The electric vehicle has to pay tolls, requires energy from charging stations and employs washing services from time to time. Considering all entities in this process as agents that can interact and carry wallets, one can easily envision a machine-to-machine economy. Technical agents decide what tasks to conduct regarding costs, capabilities and earnings as illustrated by the demonstrators of Smart Replenishment Box and Smart Vehicle Control1.
Master
Modeling for Street Level Crime Prediction
Supervised by Prof. Dr. Stefan Decker; Advisor(s): Dr. Michael Cochez, Cristina Kadar, Raquel Rosés Brüngger
The aim of this master thesis is to build a predictive model of crime at street level for a Swiss city, including a tool implementation for visualizing the data and results.
Bachelor, Master
Incompatible Data?! Dynamic Communication for Machine Learning in the of “Internet of Production”
Supervised by Johannes Lipp, M.Sc., Moritz Kröger; Advisor(s): Prof. Dr. Stefan Decker, LLT Prof. Constantin Häfner (RWTH)
The goal of this thesis is to extend a service-oriented architecture by semantic descriptions of the interfaces using ontologies. Finally, the dynamic exchange of a component in the machine will be demonstrated in a demo scenario.
Bachelor
LD-FUSE: A Filesystem in Userspace for the Linked Data Platform
Supervised by Prof. Dr. Stefan Decker; Advisor(s): Lars Gleim, M. Sc.
In the context of this work, the student should develop a FUSE user-space file system, allowing to interact with Linked Data Platform servers over HTTP as with a local file system.
Bachelor
Immersive 3D Presentations for Education
Supervised by PD Dr. Ralf Klamma, AOR; Advisor(s): Benedikt Hensen, M.Sc.
Lectures convey 2D content on slides that are projected onto a wall but the understanding of 3D structures is important in anatomy courses or engineering. Moreover, the legibility varies based on the position in the lecture hall due to the angle and distance of the viewer which can influence the learning efficiency. Mixed Reality has the ability to immerse the viewer in the presentation. Since participants can use their own hardware, e.g. smartphones, to view 3D presentations, content can be positioned individually at the optimal location for every person. Additionally, presentations can vary in scale, ranging from miniature 3D models that are displayed on the table of every member in the audience to above-life size close-ups. Lecturers can use the same 3D presentation for remote teaching if face-to-face lectures are not possible.
Bachelor
Dynamic Embeddings of Evolving Knowledge Graphs
Supervised by Prof. Dr. Stefan Decker; Advisor(s): Dr. Michael Cochez, Dr. Florian Lemmerich
The goal of this Bachelor thesis is the research of updating KG embeddings with new information in order to obtain a dynamic and stable embedding of the fast-evolving KG while reducing the computational effort.
Bachelor
Machine Learning for Anonymization of Unstructured Text
Supervised by Prof. Dr. Stefan Decker; Advisor(s): Dr. Michael Cochez
This thesis addresses the problem of identifying personal information in unstructured text using supervised Machine Learning (ML). The final application should be able to recognize and annotate the tokens that make up personal data in an English input text as accurately as possible. First, supervised learning methods, suitable for the task, will be identified. Then, models based on the most promising approaches will be designed and implemented. For comparison, suitable evaluation metrics have to be determined. Finally, the approaches are compared and evaluated against a baseline and each other.
Bachelor
Developing Data Quality Metrics for Power System Modeling
Supervised by Prof. Dr. Stefan Decker; Advisor(s): Dr. Oya Deniz Beyan, 660b75904e3b7e318151bbdc353d734d
Linked data is gaining new attention in the last years because of its natural connection to knowledge-based applications. The quality of decisions depends heavily on the quality of the underlying data, for reasoning such quality reports are mandatory for each decision. The W3Cs Best Practices Working Groups "Data on the Web Best Practices: Data Quality Vocabulary" defines a vocabulary to archive linking results of data quality assessments to linked data. Also, a basic set of quality dimensions and metrics based on the work of Zaveri et al. (https://dx.doi.org/10.3233/SW-150175) are presented. This thesis aims to fill the gaps between the DQV, the definitions by Zaveri et al. and the realization of linked data quality assessments, to fulfil all requirements to link data quality assessments.
Bachelor
Skill Development for Intelligent Personal Assistants: A Comparison of Different Platforms
In recent years, commercial intelligent personal assistants platforms such as Amazon Alexa or Apple Siri have gained increased momentum. The usage rate of these intelligent personal assistants is rising steadily and will most likely continue to grow in the coming years. The aim of this thesis is, on the one hand, to compare different intelligent personal assistant platforms by their characteristics, and, on the other hand, to compare the development of programs running on these platforms, so-called skills.
Master
A Visualization Recommendation Tool for Production Systems
Supervised by Prof. Dr. Christoph Quix, Günther Schuh; Advisor(s): Arnab Chakrabarti, M.Sc., Frederick Sauermann (WZL, RWTH)
Master
Patterns for Integrating Rule Based and Process Based Model Components of Computerized Clinical Guidelines
Supervised by Prof. Dr. Stefan Decker, Dr. rer. nat. Cord Spreckelsen; Advisor(s): 692050c6199c8bbfb9be2189e82ff904
Master
Collaborative Immersive Learning Analytics
Supervised by PD Dr. Ralf Klamma, AOR
Our approach is a comprehensive and evolutionary sociotechnological learning analytics and design process leading to a flexible infrastructure where professional communities can co-create their wearable enhanced learning solution.
Bachelor
Persistent Association of Virtual Objects in Mixed Reality
Supervised by PD Dr. Ralf Klamma, AOR; Advisor(s): Benedikt Hensen, M.Sc.
A mixed reality environment immerses users in a three-dimensional space. This allows them to organize digital content in the entire room, e.g. task cards in immersive project management. A natural way to sort related objects is by placing them close to each other. However, this kind of spatial co-location of objects is not enough to stress their relation to each other. If another user who is unaware of the association moves one of the objects, the spatial connection is lost. Hence, lines in 3D space are required which establish a visual and persistent connection between the objects. In a previous project, an initial system was implemented which uses straight lines to connect the objects. However, straight lines have some shortcomings since they intersect with obstacles between the two endpoints. A better connection system can use 3D curves to avoid the obstacles in an efficient way.
Bachelor
Chat Assessments with Social Bots
Social Bots (software robots) are computer algorithms that automatically produce content and interact with humans on social media. This thesis will utilize chat interfaces, a social bot framework and learning management systems to conduct assessments for learning content of a lecture with the help of a social bot.
Bachelor, Master
Versioning and Access Management in Web-Based Collaborative Model-Driven Web Engineering
Modern collaborative development practices use agile principles to structure and organize the development process. The tool support for this includes source code management, with the large majority of development teams using Git. While collaboration patterns and access management of cooperation on source code is studied quite well, for MDWE (Model-Driven Web Engineering) processes, where collaboration happens on models instead of (only) source code, this is not yet the case. The thesis should investigate possibilities of versioning and access management for an existing MDWE platform.
Master
An Extensible Web Interface for Linked Data Platform Servers
The Linked Data Platform (LDP) is a simple, standardized REST API that allows for the hierarchical organization of Linked Data, similar to a classical file system. While the standard is rather simple, manual interaction with the file system is tiresome and error prone. To simplify the interaction with the LDP server, a suitable web-based user interface for browsing, editing and visualizing LDP data with suitable Web Components should be developed in this work.
Bachelor
Automatic Provenance Generation for Serverless Computing
Supervised by Prof. Dr. Stefan Decker; Advisor(s): Lars Gleim, M. Sc.
In the context of this work, the student should extend the Function-as-a-Service (FaaS) paradigm of serverless computing with concepts for the automatic tracking of provenance information or data lineage (information about data origins, uses, actors and involved processes over time, similar to a GIT revision history for data) and implement a corresponding framework using a readily available FaaS platform, such as Kubeless, OpenFaaS or the Fn Project, as well as the existing factlib.js library for semi-automatic provenance tracking, that was developed as a result of previous work.
Bachelor, Master
Blockchain-based Verification of Learning Analytics Data
The goal of this thesis is to make collected Learning Analytics data, extracted from various Learning Management Systems, traceable and verifiable by keeping a reference to the monitored data on the las2peer Blockchain. The thesis should investigate related work in the domain of educational usage of Blockchain technology. The developed extension should integrate into the existing project's infrastructure and provide learners and their mentors/tutors with a tool to explore when and what kind of data was collected. By improving this traceability, we hope to increase the trust in the data collection (and its usage) from both learners and mentors.
Bachelor
Immersive Curriculum and Learning Plan Visualizations in Mixed Reality
Supervised by PD Dr. Ralf Klamma, AOR; Advisor(s): Benedikt Hensen, M.Sc.
The creation of learning plans is a complex and important task. There are dependencies between the different topics, e.g. an advanced subject can only be understood if the underlying basic theories have been considered. Learning plans contain short-term, mid-term and long-term goals which should ideally be synchronized to each other. Additionally, learning plans bear a strategic component by identifying aspects which are most beneficial for the student’s future. There are also collaborative considerations. Members of learning groups want to adapt their learning plans to each other so that they can either learn topics together simultaneously or so that one group member who is already familiar with the topic is able to support the other group members. A framework for creating learning plans is given by Learning Design which defines clear learning outcomes, activities, times and required resources. Since learning plans are abstract, they are rarely visualized. However, such a visualization can act as a persistent overview that allows students but also lecturers to create consistent learning plans where short-term tasks work towards long-term learning outcomes. To grasp the complex nature of learning plans, a promising solution is the immersive creation of visualizations in 3D using Mixed Reality technology.
Bachelor
A Distributed Data Revisioning System for the Internet of Production
Supervised by Prof. Dr. Stefan Decker, Prof. Dr.-Ing. Klaus Wehrle; Advisor(s): Lars Gleim, M. Sc., Jan Pennekamp
In the context of this thesis, the student should implement a distributed data revisioning system, enabling interorganizational data reuse and extension in the Internet of Production and Internet of Things.
Bachelor, Master
Secure and User-friendly Authentication for a Decentralized Service Platform
The goal of this thesis is the development of a secure and user-friendly authentication system for las2peer. Conceptually, it should be build on / support the aforementioned existing features of las2peer, namely the blockchain-based verification system and the OpenId Connect standard. Technically, these two systems should be integrated within a modern Web authentication flow, supporting the WebAuthn standard and integrating Decentralized Identifiers. The resulting implementation should be fully compatible with existing authentication scenarios of las2peer and provide users with an optional extra layer of security.
Bachelor, Master
Authenticity, Integrity and Trust for Data Reuse in Resource Oriented Architectures
Supervised by Lars Gleim, M. Sc., Jan Pennekamp; Advisor(s): Prof. Dr. Stefan Decker, Prof. Dr.-Ing. Klaus Wehrle
Development of a content security model for authenticity and integrity in resource oriented architectures, based on content signing (public-key cryptography) and hash-chaining/Merkle trees (incorporating the hash/signature of previous revisions and referenced existing resources).
Bachelor
Development of a WebApp for the User-friendly Tracking of Manufacturing Processes
Supervised by Lars Gleim, M. Sc., Thomas Schemmer, Florian Brillowski; Advisor(s): Prof. Dr. Stefan Decker, Prof. Dr. Martina Ziefle
In the context of this thesis, the student should develop a web application (primarily to be used on tablet computers) in order to easily document manufacturing process steps and related information, as they are taking place in real time.
Bachelor
A Mixed Reality-Based Card Game for Formal and Informal Education
Supervised by PD Dr. Ralf Klamma, AOR; Advisor(s): Benedikt Hensen, M.Sc.
A challenge of existing educational Mixed Reality applications concerns the difficult accessibility of technology for students. Many applications require expensive head-mounted displays or high-end smartphones which can only be tried by students at the university for a limited amount of time. However, Mixed Reality content can also be shown on a broader range of devices using marker-based technology. Here, a marker is used as an anchor to show a 3D model above it. If the marker is filmed by a smartphone, it can calculate the view angle and render the 3D model from the same perspective. A challenge of marker-based applications is to find a meaningful integration of the markers into the environment. The markers should be easily recognizable but also need to give the user an idea about the 3D model that they can show.
Bachelor
Component Crawler for Mixed Reality Projects
Supervised by PD Dr. Ralf Klamma, AOR; Advisor(s): Benedikt Hensen, M.Sc.
For mixed reality applications, developers usually choose a modular development approach where the application-logic is segmented into separate components which only realize one feature. In well-designed projects, the components are reusable in different contexts within the project but also outside of it. Additionally, code from these projects can be used to find examples how to use APIs or libraries. However, many elementary features of mixed reality applications are re-implemented in new projects, instead of leveraging components from existing open-source projects.