Data Acquisition: Depending on the information source type, different acquisition patterns will be applied to ensure acquired information is the richest possible and has a suitable format for analysis.
Information Analysis: Each analysis module is geared towards a specific content type, i.e. Text, Image, Video, Audio and Speech or Biometric data. These modules interact with the ‘Semantic mash-up’ component, to link Semantic Web data.
Information and Reference Repositories: source data and mined information will be stored in these repositories, separated by content type. Repositories will also store the reference images, text, keywords, biometric data etc. of interest to the LEAs,
Interoperability and Management Application: This is the end users’ workbench., built on a web based collaborative platform. It will allow LEAs to create and configure their monitoring requests and analysis petitions.
Visual Analytics (VA) and Data Mining (DM): VA and DM will provide the intelligence necessary to support the output of the system. They will allow LEAs to effectively mine processed data both from Closed and Open information sources, and to further relate it to Semantic Web sources when required.