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admireADMIRE (Advanced Data Mining and Integration Research for Europe) is motivated by the difficulty of extracting meaningful information of data from multiple heterogeneous and distributed large-scale data resources.The project has proposed an architecture for large-scale data mining and integration, which is focused on separating concerns between domain experts, data analysis experts and data-intensive engineers, a language (DISPEL) that can be used to express those data mining and integration workflows across those user profiles, and the necessary tools and platforms to use this language according to the architecture.

For a more detailed description about the project, visit the following link or the project website.

UPM's Role in the Project

UPM has been involved in the creation of ontologies to create semantic descriptions of data sources and data-intensive processes, and in the provision o technologies that are make use of those semantic descriptions in order to support data-intensive processes, namely a semantic registry that holds descriptions of processing elements, functions and types. This includes the generation of ontologies about data mining and about datatypes commonly used in data mining applications, together with the provision of an RDF-enabled OGSA-DAI-compliant registry that is able to handle SPARQL requests about the data-intensive processing elements available in the platform and provide added-value functionalities such as the finding of processing elements that can replace existing ones in data-intensive workflows.


The members of OEG involved in the development of ADMIRE project are:

Publications and other results

There will be soon a book published, which summarises all the results of the project and provides a visionary view on the next challenges for data-intensive research. In the meantime, you can check the ADMIRE project library: link

The most important publication is:

Additional information

  • Start date: 03/01/2008
  • End date: 31/05/2011
  • Global budget: 4.346.077 €


Created under Creative Commons License - 2015 OEG.