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 …

This paper describes the convergence of some of the most influential technologies in the last
few years, namely data warehousing (DW), on-line analytical processing (OLAP), and the …

Collaboration at strategic level entails the sharing of Performance Indicators (PIs) to
measure the achievement of common objectives and evaluate performances. PIs are …

Intelligence, Data Warehouse and OLAP have been widely used to identify, collect, process,
integrate and analyze information for decision making, thus promoting business …

Performance measurement is the subject of interdisciplinary research on information
systems, organizational modeling and decision support systems. The data cube model is …

This paper describes the main functionalities of an ontology-based data explorer for Key
Performance Indicators (KPI), aimed to support users in the extraction of KPI values from a …

The rapidly increasing number of online service users made the performance and scalability
of computer systems a high priority. Most systems are expected to exhibit a soft-realtime …

Measurement and comparison of performances in networked organisations is particularly
critical because of heterogeneity and sparsity of data. In particular, each organization is …

A multi-dimensional ontology (MDO) enriches an OLAP cube with concepts that represent
business terms in the context of data analysis. The formal representation of the meaning of …

NoSQL solutions are started to be increasingly used in modern days' Data Warehouses
(DW). However, business analysts face challenges when performing On Line Analytical …