Big Data Systems (BDSs) are an emerging class of scalable software technologies whereby
massive amounts of heterogeneous data are gathered from multiple sources, managed …

Data lakes are a fundamental building block for many industrial data analysis solutions and
becoming increasingly popular in research. Often associated with big data use cases, data …

As the challenge of our time, Big Data still has many research hassles, especially the variety
of data. The high diversity of data sources often results in information silos, a collection of …

Data lakes are becoming increasingly prevalent for Big Data management and data
analytics. In contrast to traditional 'schema-on-write'approaches such as data warehouses …

Monitoring of the state, performance, quality of operations and other parameters of
equipment and production processes, which is typically referred to as condition monitoring …

This report documents the program and the outcomes of Dagstuhl Seminar 19391``Data
Ecosystems: Sovereign Data Exchange among Organizations''. The goal of the seminar was …

In the automotive industry, welding is a critical process of automated manufacturing and its
quality monitoring is important. IoT technologies behind automated factories enable …

The ability to cross data from multiple sources represents a competitive advantage for
organizations. Yet, the governance of the data lifecycle, from the data sources into valuable …

Data lakes enable flexible knowledge discovery and reduce the overhead of materialized
data integration. Albeit effective for data storage, query execution over data lakes may be …

Big Data architectures allow to flexibly store and process heterogeneous data, from multiple
sources, in their original format. The structure of those data, commonly supplied by means of …