Index
[MA] Implementation of a Track and Trace solution within Supply Chain Management at adidas AG
Start: 01.04.2021
End: 31.07.2021
Type: Master thesis
Student: Lukas Wittmann
Supervisor: Prof. Dr. Andreas Harth, Matthias Farnbauer-Schmidt
Abstract: A transparent supply chain is key for companies in the B2C business. Tracking goods movement between the factory, distribution centers and stores allows firms to integrate Omnichannel distributions such as Ship from Store and Click and Collect.
However, the variety of software solutions across the supply chain causes challenges in data synchronization between operational systems. Thereby, it leads to customer orders not being fulfilled in time or even cancelled.
The thesis focuses on designing and implementing a Track and Trace solution that consolidates RFID read event data centrally. Multiple data processing, data storage and data management systems are examined and incorporated into the solution.
[MA] Knowledge Extraction Solution with Natural Language Processing and Knowledge Graphs
Start: 15.12.2020
End: 13.07.2021
Type: Master thesis
Student: Kiara Marnitt Ascencion Arevalo
Supervisor: Prof. Dr. Andreas Harth, Andreas Belger
Abstract: Organizations have a wide variety of available data coming from different sources. To generate value, it is essential for companies to exploit all this information and convert it into knowledge. However, the different data sets are rarely interoperable as the data varies greatly between sources in terms of type, scope, and structure. For example, an organization’s context information is often provided as unstructured texts like analyst reports, public tenders, or press mentions. This thesis aims to create a solution to extract information from unstructured texts with the support of state-of-the-art NLP methods and represent it in a structured form through the application of Knowledge Graphs and Ontologies.
[MA] Text2Turtle (T2T) -The transformation of Wikipedia texts into a Knowledge Graph
Start: 01.12.2020
End: 29.06.2021
Type: Master thesis
Student: Christian Klose
Supervisor: Prof. Dr. Andreas Harth, Zhou Gui
Abstract: With the rise of voice assistants and semantic search comes a need for Knowledge Graphs as they are the fundamental building block enabling these technologies. This thesis deals with the automated Knowledge Graph Construction (KGC) from unstructured data. Predominantly, the focus is on Open Information Extraction (Open IE), an unsupervised learning approach that attempts to extract triples from text independent of their domain and, hence, it is the first step towards automated Knowledge Graph Construction. Previous work mainly applied Open IE Systems to English texts. In this thesis, the focus is on German texts. Due to the lack of German Open Information Extraction datasets, a dataset will be created. Two novel Open Information Extraction Systems for German will be introduced. A naive attempt to create a Knowledge Graph from the extracted triples is described. The performance of the systems is evaluated. Finally, the results of the evaluation as well as for the transformation process will be reported.
[MA] A Knowledge Graph from Financial Reports
Start: 11.01.2021
End: 02.08.2021
Type: Master thesis
Student: Pornchana Kveeyan
Supervisor: Prof. Dr. Andreas Harth, Daniel Schraudner
Abstract: XBRL or eXtensible Business Reporting Language is an XML-based language that organizations use to exchange business information. While XBRL is readable by machine, iXBRL or inline XBRL has been further developed to enable both machine and human readabilities.
An objective of this thesis is to use an RDF Mapping Language tool and transform such iXBRL-formatted financial reports and other information into an RDF presentation. Subtle business and industry insights can be discovered through a knowledge graph creation. In doing this, it would allow us to further connect the graph to other existing knowledge graphs in the market. The graph can continuously generate knowledge and grow over time. The data used in this thesis is extracted from Companies House.
[MA] Verification of Systems-of-Systems using Model Checking
Start: 01.10.2020
End: 20.05.2021
Type: Master thesis
Student: Max Kitzing
Supervisor: Prof. Dr. Andreas Harth, Dr. rer. nat. Victor Charpenay
Abstract: The thesis explores the possibility of verifying software with the well-known TLA+ model checker on a complex information system made of of independent component systems, each with its own development schedule and objectives. Specifically, the thesis addresses two research questions: (1) How can low-level implementation code be transformed to a TLA+ specification? (2) How can TLA+ specifications theoretically be abstracted, to prevent scalability issues from arising? The results of the thesis will be tested on elements of the DATEV software code base.
[MA] An Interactive Hypertext-based Linked Data Browser
Start: 01.09.2020
End: 19.04.2021
Type: Master thesis
Student: Kian Schmalenbach
Supervisor: Prof. Dr. Andreas Harth
Abstract: According to the Linked Data Principles, RDF documents published on the Web should include links to other Linked Data sources, just like HTML documents include links to other Web pages. While traditional Web browsers are capable of rendering Web pages and support hypertext, browsing the Web of Data is difficult due to the lack of readability and of browser support for RDF documents. Hence, this thesis aims at designing and implementing a piece of software in order to turn a classical Web browser into a Linked Data user agent that can retrieve, display, inspect, and modify Linked Data resources based on HTML-like hypertext markup.
[MA] Identifikation von IIoT Anwendungen und deren Beschreibung in der Literatur für den Aufbau einer Anwendungsdatenbank
End Date: 22.09.2020
Type: Master Thesis
Student: Simon Robert Kieweg
Die digitale Transformation erfolgreich zu meistern, stellt Unternehmen vor einer Vielzahl an Herausforderungen. Es gilt gleichzeitig relevante Marktentwicklungen im Blick zu behalten, aus einer Vielzahl an Möglichkeiten für das Unternehmen passende Lösungen zu identifizieren und im Fall von neuen Services diese im richtigen Moment und mit den richtigen Partnern auf den Markt zu bringen.
Die digitale Transformation im industriellen Kontext wird oftmals durch Anwendungsbeispiele inspiriert, veranschaulicht und diskutiert. Konkrete Nutzungspotentiale, die Abwägung von alternativ einsetzbaren Technologien, der entsprechende Kontext, aber auch notwendige Voraussetzungen und Ressourcen fließen dabei, oftmals mangels fehlender Information, nicht mit ein. Eine Übersicht über existierende Anwendungsfälle, ähnliche Problemstellungen oder ähnliche Rahmenbedingungensind dabei oft der erste Anknüpfungspunkt für potenzielle Anwender, um tiefer in die Notwendigkeit der Entwicklung eigener digitalisierter Wertschöpfungsansätze einzusteigen.
Ziel dieser Masterarbeit ist es ein solche Übersicht über IIoT-Anwendungen und ein dazugehöriges Kategorisierungsschema zu entwickeln, welches anschließend für die Entwicklung einer webbasierten Anwendungsdatenbank genutzt werden kann (webbasierte Anwendungsdatenbank nicht Teil der Abschlussarbeit).
Hierfür sollen im Rahmen einer strukturierten Literaturanalyse auf Basis von bisherigen Veröffentlichungen vielfältigster Art (wissenschaftliche Journalpaper, Monografien, Studien) der bisherige Stand der Forschung erarbeitet werden, ein geeignetes Framework zur Beschreibung von IIoT-Anwendungen identifiziert (z.B. Boyes, Hallaq, Cunningham & Watson, 2018) und mit Hilfe von Experteninterviews evaluiert werden.
Adressaten:
- Masterstudierende der Wirtschaftswissenschaften
- Gute Englischkenntnisse von Vorteil
- Bearbeitung in englischer oder deutscher Sprache möglich
Bearbeitungsbeginn und -formalien:
- Bearbeitung im Wintersemester 2019/2020
- Bearbeitung kann auf Englisch oder Deutsch erfolgen
In Zusammenarbeit mit der Fraunhofer Arbeitsgruppe für Supply Chain Services (SCS)
Luxshiya Ariyanayagam
luxshiya.ariyanayagam@scs.fraunhofer.de
[MA] REST Principles and IoT Protocols
Start: 01.10.2020
End: 29.04.2021
Type: Master thesis
Student: Guannan Chen
Supervisor: Dr. rer. nat. Victor Charpenay
Abstract: The architecture principles behind Web interfaces, commonly known as the Representational State Transfer (REST) principles, are often perceived among Web developers as tightly coupled with HTTP. However, it is theoretically possible to apply REST principles to any communication protocol designed to exchange application data. In particular, MQTT, a protocol designed for low-power IoT devices, may have all the necessary components to design RESTful interfaces.
The thesis should provide an evaluation of the level of compatibility between MQTT and REST and extend this evaluation to other IoT protocols. An implementation of a RESTful management layer on top of an MQTT broker may be included in the thesis as well.