Tag: Engineering Thesis

Abstract: Microservice-based systems consist of loosely coupled, independent distributed services, communicating over the network. The integration of the frontend in microservices is a central problem. In contrast to the back end services, one independent service is often used for the front end of an application. This contradicts the principle of microservice-based systems, since a central, monolithic service is responsible for the entire frontend. This thesis examines how front end user interfaces can be integrated into microservices. The existing front end architectures in a microservice context are presented and analyzed with regard to advantages, disadvantages and challenges. A structured literature analysis is carried out to collect data for theory formation. In addition, expert interviews are conducted as part of a case study with industrial partners in order to get an overview of the methods used in practice. Subsequently, in the scope of an action research study, one integration options for user interfaces in microservices is applied for a specific application. The results of the action research are evaluated and compared to the contents of the structured literature analysis. The objective of the thesis is to show the implications of the comparison with a guideline. Practitioners can use this comparison to select a suitable front end integration solution for their application. Scientists can build on this work to develop further integration solutions, refine existing ones, and extend them.

Keywords: Microservices, micro front ends, microservice UIs, JValue

PDF: Master Thesis

Reference: Pascal Vahldiek. Guidelines für die Integration von User Interfaces in Microservice-basierten Systemen. Master Thesis. Friedrich-Alexander-Universität Erlangen-Nürnberg: 2022.

Abstract: Many modern software applications and research projects depend on the ability to access high-qualitative data sources. Even though there is already a large number of openly available data sets, such data sets are often hard to (re)use due to various barriers such as incomplete documentation, wrong or missing values, and more. To address these barriers, the JValue Project has been established by the Professorship of Open Source Software at Friedrich-Alexander-Universität Erlangen-Nürnberg. The goal of the JValue Project is to “make open data easy, safe, and reliable”. In the context of the JValue Project, numerous software applications are developed which, among others, allow to explicitly define the structure and further meta information of openly available data sets. However, it is currently neither possible to collaborate with other individuals on such data source configurations, nor is it possible to retrace the historic development that led to the current state of a particular configuration. To build a basis to address these issues, a Version Control System shall be developed, which makes it possible to store, retrieve, and compare revisions of files containing data source configurations and related information. This thesis presents a concept of such a system, and evaluates this concept by implementing a prototype showing its feasibility. As a result of this thesis, it is now possible for other applications developed in the context of the JValue Project to access, create, and compare revisions in order to provide advanced collaboration and versioning features to end users.

Keywords: Version control systems, open data, collaboration

PDF: Master Thesis

Reference: Martin Buchalik. Design and Implementation of a Version Control System for Open Data Modelling Projects. Master Thesis. Friedrich-Alexander-Universität Erlangen-Nürnberg: 2022.

Abstract: Open data has been known for having data quality issues that require complex data cleansing and data transformation in order to be usable for data analysis, data visualization, training machine learning algorithms, and other data science activities. Open Data Service (ODS) is a software project that aims at creating an interface for reliable and safe consumption of open data. It does so by providing the necessary tooling and infrastructure needed for collaboration on eliminating open data usability obstacles. ODS underwent several cycles of development to better serve its purposes, which include functioning as an extract, transform, load (ETL) tool to consume open data from different sources and adapt it to different needs. In this work we evaluate and analyze ODS performance in that regard. Specifically, as part of a data pipeline supporting a real-world data science application.

PDF: Master Thesis

Reference: Shady Hegazy. Study and Analysis of the Performance of JValue Open Data Service as Part of a Data Pipeline Supporting An Online Learning Model. Master Thesis. Friedrich-Alexander-Universität Erlangen-Nürnberg: 2022.

Abstract: Nowadays the internet provides a lot of open data for public use. Those can be written in various data types and cover plenty of subjects. Because of that the absence of a standard results into the main problem. Every provider can decide for himself how the data is constructed.

The JValue project is dedicated to this problem and aims to be the central point where those open data are gathered and optimized. Currently the JValue Open- Data-Service (ODS) provides the extraction, transformation and retrieving of open data supporting numerous protocols and data formats.

However until now there is only a very generic interface for the retrieval of those open data since the system currently ignores any data structure. In addition to that any provider can alter their data structure and upload it after the adjustment process, since they are not bound to any restrictions. This can lead to major restrictions or even the loss of the data gathering process.

To counteract this behavior a process shall be introduced, which allows the ODS to structure those open data. Furthermore a schema recommendation for the data should be generated, which then will be the foundation of the remaining data gathering process.

As a consequence of the introduced data schema there is now a possibility to also derive fitting database tables from those schema. This tables should be created and filled dynamically and provide the user a fully and easy accessible interface. As an implication of the persistent structured data, the earlier mentioned problem of frequently changing data structures can now be easily solved. The schema can be used to validate those imported and transformed data. By also adding a corresponding visual state to those data configurations, the user will be able to react up on changed data structures.

Keywords: data engineering, schema recommendation, open data

PDF: Master Thesis

Reference: Alexander Mahler. Giving Structure to Open Data in the JValue ODS. Master Thesis. Friedrich-Alexander-Universität Erlangen-Nürnberg: 2021.

Abstract: The JValue project group is developing a modeling ecosystem for Extract Transform Load (ETL) processes. Part of this ecosystem is a description model for those. This thesis suggests a conversion process from the description model into an Apache Kafka runtime, described in a cloud-native format, like Docker Compose. The conversion is implemented as a library and done in a multi-phase approach as known from classical compilers. In the first step, the description language is converted into a runtime independent intermediate description and afterward in a description of a concrete runtime, in this case, Kafka. The multi-phase approach minimizes the implementation work for additional runtimes and allows runtime independent optimization and analysis. The goal for the generated runtime is to use existing Kafka components, which is only partially possible due to the complexity of the description model.

Keywords: open data, compiler, Apache Kafka

PDF: Master Thesis

Reference: Fabian Arnold. Implementing an Open Data ETL Processing Engine with Kafka. Master Thesis. Friedrich-Alexander-Universität Erlangen-Nürnberg: 2022.