Semantic Web (SW) techniques, such as ontologies, are used in Information Systems (IS) to
cope with the growing need for sharing and reusing data and knowledge in various research …

A key challenge in current Business Analytics (BA) is the selection of suitable indicators for
business objectives. This requires the exploration of business data through data-driven …

Digitalization of agricultural technology has led to the emergence of precision dairy farming,
which strives for the simultaneous improvement of productivity as well as animal well-being …

In order to create better decisions for business analytics, organizations increasingly use
external structured, semi-structured, and unstructured data in addition to the (mostly …

This paper proposes an approach to tackle the problem of querying large volume of
statistical RDF data. Our approach relies on pre-aggregation strategies to better manage the …

In order to create better decisions for business analytics, organizations increasingly use
external data, structured, semi-structured and unstructured, in addition to the (mostly …

During recent years, more and more data has been published as native RDF datasets. In
this setup, both the size of the datasets and the need to process aggregate queries …

Business Intelligence (BI) tools provide fundamental support for analyzing large volumes of
information. Data Warehouses (DW) and Online Analytical Processing (OLAP) tools are …

The popularity of the Semantic Web (SW) encourages organizations to organize and publish
semantic data using the RDF model. This growth poses new requirements to Business …

A knowledge graph (KG) represents real-world entities and their relationships. The
represented knowledge is often context-dependent, leading to the construction of …