Data warehouses are databases of a specific kind that periodically collect information about
the activities being performed by an organization. This information is then accumulated over …

The MultiDim model is a conceptual multidimensional model for data warehouse and OLAP
applications. These applications require the presence of a time dimension to track changes …

The data model of the classical data warehouse (formally, dimensional model) does not offer
comprehensive support for temporal data management. The underlying reason is that it …

Temporal data warehouses (TDWs) have been developed for the management of time-
varying data in dimensions. This paper presents a new approach for the logical modelling of …

In secondary data use context, traditional data warehouse design methods don't address
many of today's challenges; particularly in the healthcare domain were semantics plays an …

In a data warehouse, real-world activities can trigger changes to dimensions and their
hierarchical structure. Eg, organizations can be reorganized over time causing changes to …

Data warehouses are repositories of electronically stored data which are designed to
support reporting and analysis. The analysis of historical data often involves aggregation …

A data warehouse (DW) is a vast collection of historical data built to support
multidimensional data analysis applications. In this context, an important problem is that of …

Data Warehouses typically are building blocks of decision support systems in companies
and public administration. The data contained in a data warehouse is analyzed by means of …

Data warehouse applications and business intelligence (BI) communities have been
increasingly feeling the need to collect temporal data for accountability and traceability …