A5025927135- Advanced Database Systems and Queries
- Semantic Web and Ontologies
- Cloud Computing and Resource Management
- Data Quality and Management
- Scientific Computing and Data Management
- Distributed systems and fault tolerance
- Data Management and Algorithms
- Software System Performance and Reliability
- Distributed and Parallel Computing Systems
- Service-Oriented Architecture and Web Services
- Web Data Mining and Analysis
- Research Data Management Practices
- Digital Rights Management and Security
- Model-Driven Software Engineering Techniques
- Digitalization, Law, and Regulation
- Machine Learning and Data Classification
- Explainable Artificial Intelligence (XAI)
- Digital Innovation in Industries
- Advanced Data Storage Technologies
- Blockchain Technology Applications and Security
- Data Visualization and Analytics
- Electronic Health Records Systems
- Peer-to-Peer Network Technologies
- Data Mining Algorithms and Applications
- Software Engineering Research
University of Regensburg
2022-2024
Leibniz Institute for Baltic Sea Research
2024
University of Illinois Urbana-Champaign
2024
University of Rostock
2013-2022
Universität Greifswald
2007
In the same way as with relational systems, schema evolution is a crucial aspect of NoSQL systems. But providing approaches and tools to support more challenging than for databases. Not only are most systems schemaless, but different data models exist without standard specification them. Moreover, recent proposals fail address some key aspects related kinds relationships between entities, definition relationship types, structural variation. this article, we present generic approach able...
NoSQL data stores are commonly schema-less, providing no means for globally defining or managing the schema. While this offers great flexibility in early stages of application development, developers soon can experience heavy burden dealing with increasingly heterogeneous data. This paper targets schema evolution stores, complex task adapting and changing implicit structure stored. We discuss recommendations developer community on handling changes, introduce a simple, declarative language....
Data accumulating in data lakes can become inaccessible the long run when its semantics are not available. The heterogeneity of formats and sheer volumes collections prohibit cleaning unifying manually. Thus, tools for automated lake analysis great interest. In this paper, we target particular problem reconstructing schema evolution history from lakes. Knowing how is structured, structure has evolved over time, enables programmatic access to lake. By deriving a sequence versions, rather than...
This paper explores scalable implementation strategies for carrying out lazy schema evolution in NoSQL data stores. For decades, has been an evergreen database research. Yet new challenges arise the context of cloud-hosted backends: With all reads and writes charged by provider, migrating entire instance eagerly into a can be prohibitively expensive. Thus, migration may more cost-efficient, as legacy entities are only migrated case they actually accessed application. Related work shown that...
Data preprocessing is an important task in machine learning which can significantly improve model outcomes. However, evaluating the impact of data often difficult. There a need for tools make it transparent to user on how certain transformations conducted affect data. Thus, we propose vision transparency system that provides insights into preparation pipelines. Our envisioned consists Python library enables users log and processed Subsequently, generates summaries was pipeline so-called...
Building applications for processing data lakes is a software engineering challenge. We present Darwin, middleware that operate on variational data. This concerns with heterogeneous structure, usually stored within schema-flexible NoSQL database. Darwin assists application developers in essential and schema curation tasks: Upon request, extracts description, discovers the history of versions, proposes mappings between these versions. Users may interactively choose which are most realistic....
We demonstrate MigCast, a tool-based advisor for exploring data migration strategies in the context of developing NoSQL-backed applications. Users MigCast can consider their options evolving model along with legacy already persisted cloud-hosted production database. They explore alternative actions as financial costs are predicted respective to cloud provider chosen. Thereby they better equipped assess potential consequences imminent decisions. To this end, maintains an internal cost model,...
Abstract When NoSQL database systems are used in an agile software development setting, data model changes occur frequently and thus, is routinely stored different versions. The management of versioned leads to overhead potentially impeding the development. Several migration strategies exist that handle legacy differently during accesses, each which can be characterized by certain advantages disadvantages. Depending on requirements for application, we evaluate compare through metrics like...
To provide good results and decisions in data-driven systems, data quality must be ensured as a primary consideration. An important aspect of this is cleaning. Although many different algorithms tools already exist for cleaning, an end-to-end solution still needed. In paper, we present our vision well-founded optimizer. contrast to studies that consider cleaning the context machine learning, approach focuses on various scenarios, such when preprocessing downstream analysis are separated. Our...
For an optimal care of patients in home healthcare, it is essential to exchange healthcare-related information with other stakeholders. Unfortunately, paper-based documentation procedures as well the heterogeneity between systems inhibit a well-regulated communication. Therefore, digital patient record introduced establish foundation for integrating information.For record, suitable integration techniques are required that store data compact way and offer flexibility robustness. this purpose,...
When NoSQL database systems are used in an agile software development setting, data model changes occur frequently and thus, is routinely stored different versions. This leads to overhead affecting the particular, management of accesses. In this context, migration strategies exist, which characterized by certain advantages disadvantages. Using exactly that strategy whose characteristics match according scenario, depends on query workload, caused schema evolution, requirements for application...
Abstract Data-driven methods and data science are important scientific in many research fields. All approaches require professional engineering components. At the moment, computer experts needed for solving these tasks. Simultaneously, scientists from fields (like natural sciences, medicine, environmental engineering) want to analyse their autonomously. The arising task is development of tools that can support an automated curation utilisable domain experts. In this article, we will...