Real data challenges have helped shape the ADMIRE architecture. Here are a few of them so far.
With genetic sequencing techniques moving into the next generation, genetic data volumes are set to increase at an astonishing rate.
ADMIRE has been used to automate the process of annotating gene-expression images of developing mouse embryos with anatomical terms.
Environmental modelling and disaster prediction are increasingly important and increasingly data-driven.
ADMIRE has been used to extend flood forecast simulations in Slovakia using new data sources and new data mining tools.
Increasing choice in consumer markets like mobile telecoms is placing increasing importance on effective customer relationship management (CRM) and driving interest in the more effective use of customer data.
ADMIRE has been used as a framework to integrate customer data in the mobile telecoms sector and as an experimental platform to explore new data mining approaches to terabytes of call data in a new approach to large-scale analytical CRM.
Hunting for quasars
As digital telescopes increase in resolution the quantities of data they produce is, well, astronomical. Hunting for distant, deep-sky objects like quasars is a major data processing challenge.
ADMIRE has been used to provide a seamless way to run astronomy queries across multiple very large, distributed databases.
Listening to the Earth
Seismologists today collect terabytes of data per year from automated sensors which monitor every shiver and twitch of the Earth's crust. Extracting useful information from these data is a mammoth task, involving the cross-correlation of sensor readings from across the globe, but is vital in the quest to provide better warning of earthquakes, or volcanic eruptions.
ADMIRE has been used to create the first prototypes of a powerful, flexible data assimilation framework for broadband seismology.