Flexible Integration and Efficient Analysis of Multidimensional Datasets from the Web

If numeric data from the Web are brought together, natural scientists can compare climate measurements with estimations, financial analysts can evaluate companies based on balance sheets and daily stock market values, and citizens can explore the GDP per capita from several data sources. However, heterogeneities and size of data remain a problem. This work presents methods to query a uniform view - the Global Cube - of available datasets from the Web and builds on Linked Data query approaches

Data Mart Reconciliation in Virtual Innovation Factories

The present paper deals with the problem of collaboration at strategic level in innovation-oriented Virtual Enterprises. The problem is taken from the perspective of sharing a special kind of data, Key Performance Indicators, that are measures adopted to monitor the achievement of certain strategic goals. We discuss the main conflicts that can arise in measures coming from autonomous enterprises, adopting the conceptual multidimensional cube model. Then we propose a novel semantic model to deal with conflicts related to the structure of a measure, that arise when the “same” KPI is calculated in different ways by different enterprises. Finally, conflict reconciliation strategies enabled by the semantic model are discussed

Flexible Integration and Efficient Analysis of Multidimensional Datasets from the Web

If numeric data from the Web are brought together, natural scientists can compare climate measurements with estimations, financial analysts can evaluate companies based on balance sheets and daily stock market values, and citizens can explore the GDP per capita from several data sources. However, heterogeneities and size of data remain a problem. This work presents methods to query a uniform view - the Global Cube - of available datasets from the Web and builds on Linked Data query approaches