Integrating Event Detection, Analysis and Response: The GlobeSec Approach Brian Doherty

1. Integrating Event Detection, Analysis and Response: The GlobeSec Approach Brian Doherty European Commission - Joint Research Centre Institute for the Protection and Security of the Citizen (IPSC) Global Security and Crisis Management(GlobeSEC) Unit Crisis Monitoring and Response Technologies (CRITECH) Action - http://lunar.jrc.it/critech/ via E Fermi 2749, 21027 ISPRA (VA),Italy Tel: +39 0332 785547 Fax: +39 0332 785154 e-mail: Brian.Doherty@jrc.it

3. I am here!

4. ISFEREA

5. OPTIMA

6. CriTech

7. Field Collection Tool 3 2 1

8. Ontology editing

9. KML Google Earth Shape Files GIS XML RSS

10. CriTech Platform • DotNetNuke CMS • Open Source • Modular

11. Main Portal modules • Text Module • Document Management system • Request for Information • RSS viewer • Contacts • Crisis Area Creation • Calendar • Geographical tools • Questionnaire • Search • Newsletters • SMS facilities • Wiki modules • Forum Basically, LOTS of modules!

13. Creating a new threat/crisis/incident: • Identify the modules required • How do they need to interact? • Which of them should provide information to the map? • How should the map represent the data? • Will there be sub-entities and how will they pass data ‘upwards’?

14. Encapsulate in a template • Platform generates a new environment based on a template • User supplies only the minimum information • Data moves within the new environment and upwards in any hierarchical structure without further setup required • Maps, RSS readers etc • Collaboration can begin immediately!

15. Requests for early-warning systems becoming widespread • GHSAG (Health) • CEWS – Instability, conflict • Other projects both in progress and in the pipeline

16. Normalization • Convert the inputs into a unified format (data and metadata) • Take into account the different system output characteristics • Automatically cluster similar articles and identify (to the possible extent) duplicates • Moderation • Applying human judgment the reduction of noise, redundancy and eventual false negatives • Applying human judgment to ranking of articles • Filtering • Retrieve results filtered by both categories (from the ontology) and free text keywords • Binary filtering (match vs. no match) and/or fuzzy filtering (high relevance vs. low relevance) • Display • Display the articles of information in a human-friendly manner • Relevance, ranking and overall content should be judged graphically in a quick manner

17. Processing Phases • Normalization • Convert the inputs into a unified format (data and metadata) • Take into account the different system output characteristics • Automatically cluster similar articles and identify (to the possible extent) duplicates • Moderation • Applying human judgment the reduction of noise, redundancy and eventual false negatives • Applying human judgment to ranking of articles • Filtering • Retrieve results filtered by both categories (from the ontology) and free text keywords • Binary filtering (match vs. no match) and/or fuzzy filtering (high relevance vs. low relevance) • Display • Display the articles of information in a human-friendly manner • Relevance, ranking and overall content should be judged graphically in a quick manner

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20. Current Work • Configure Optima data harvesting and analysis directly • Integrate seamlessly with analysis, crisis management and response