Marko Niinimäki

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On-Line Analytical Processing (OLAP) is a powerful method for analysing large data warehouse data. Typically, the data for an OLAP database is collected from a set of data repositories such as e.g. operational databases. This data set is often huge, and it may not be known in advance what data is required and when to perform the desired data analysis tasks.(More)
On-Line Analytical Processing (OLAP) is a powerful method for analysing large warehouse data. Typically, the data for an OLAP database is collected from a set of data repositories such as e.g. operational databases. This data set is often huge, and it may not be known in advance what data are required and when to perform the desired data analysis tasks.(More)
Summarizability, i.e. the correctness of aggregation operations, is essential for OLAP analysis. Summarizability has commonly been studied in the context of dimension hierarchies, but the role of semantics of measure attributes and aggregation functions (sum, avg, min, max, count) has received less research interest. In this paper, we focus on the(More)
This paper describes the European Data Grid's (EDG's) java security system and Spitfire database access system giving special emphasis on the virtual organization technologies. These technologies create a feasible framework for authentication and authorization in distributed Grid applications. A virtual organization (VO) is a collection of people in the(More)
Medical image processing is known as a computationally expensive and data intensive domain. It is thus well-suited for Grid computing. However, Grid computing usually requires the applications to be designed for parallel processing, which is a challenge for medical imaging researchers in hospitals that are most often not used to this. Making parallel(More)