2. POPULATION DISTRIBUTION BY SHIP TYPE TOP 40 SHIP TYPES EXTRACTED FROM: AIS DATASET (FROM: 2013-02-12 TO: 2013-07-16) AND TOTAL 90 SHIP CATEGORIES CIRCA IN 8839 UNIQUE RECORDS

3. POPULATION DISTRIBUTION BY SHIP TYPE – PIE CHART TOP 40 SHIP TYPES EXTRACTED FROM: AIS DATASET (FROM: 2013-02-12 TO: 2013-07-16) AND TOTAL 90 SHIP CATEGORIES CIRCA IN 8839 UNIQUE RECORDS

4. LENGTH STATISTICS FOR TOP 40 SHIP TYPES (M) EXTRACTED FROM: AIS DATASET (FROM: 2013-02- 12 TO: 2013-07-16) AND TOTAL 90 SHIP CATEGORIES CIRCA IN 8839 UNIQUE RECORDS OF WHICH 6700 REPORT SHIP LENGTH

5. TOP 20 SHIP TYPES HAVING THE HIGHEST MAXIMUM LENGTH (M) EXTRACTED FROM: AIS DATASET (FROM: 2013- 02-12 TO: 2013-07-16), TOTAL 90 SHIP CATEGORIES CIRCA IN 8839 UNIQUE RECORDS

7. HISTOGRAM FOR SHIP LENGTH AIS DATA (FROM: 2013-02-12 TO: 2013-07-16)

9. SPATIAL TOOL DEVELOPMENT

10. 1 KM BOUNDARY LINE

11. 5 KM BOUNDARY LINE

12. 12 KM BOUNDARY LINE

14. HISTOGRAM FOR SHIP SPEED TO UNDERSTAND SHIP SPEED FREQUENCY BETWEEN 0 AND 2 KNOTS AIS DATA (FROM: 2013-02-12 TO: 2013-07-16), 406186 UNIQUE RECORDS

15. NAVIGATION STATUS FREQUENCIES - FOR SHIPS WITHIN THE 12KM BOUNDARY

16. PROTOTYPE SHOWING THE 1, 5 AND 12 KM BOUNDARIES AS OVERLAYS

17. USER CONTROLS TO DEFINE SHIP POSITIONS AND DATE RANGES DISPLAYED

18. USER CONTROLS TO DEFINE SHIP STATUS (ANCHORED/UNDERWAY) DISPLAYED

19. USER CONTROLS TO DEFINE SHIP TYPE CATEGORIES DISPLAYED

20. ADDING THE INFORMATION STATISTICS, SHIP POSITION WINDOW Ship Position Window Collective Information Window

21. USER SELECTION VALIDATION

22. WITHOUT GROUPING CRITERIA

23. WITH GROUPING CRITERIA

24. WITH GROUPING CRITERIA AND SHIP SPEED <=0.2 KNOTS CONSIDERED AS ANCHORED

25. PROTOTYPE: SHOWING 10,000 SHIP POSITIONS Artefact 1

26. ARTEFACT 1 AT HIGHER ZOOM Artefact 1

32. AGGRESSIVE CLUSTERING APPROACH IS ENABLED FOR GROUPS AS SMALL AS 2 POINTS OR MORE AS SEEN AT A HIGHER ZOOM LEVEL

33. CLUSTERING IS ENABLED FOR GROUPS THAT HAVE ARE MADE OF 20 POINTS OR MORE AS SEEN AT A HIGHER ZOOM LEVEL

34. LocationIs Tracker Site Online? Data Feed (Online/ Historical) Data Set Descriptors available on tracker Data Set Descriptors to be uploaded MaltaYesOnline2013-02-12 - 2014-04-07, 3797 vessels, 1298342 positions, real coordinates Not Applicable LampedusaYesHistorical2013-03-31 - 2013-12-08, 822 vessels, 110322 positions, real coordinates 2013-03-31 – 2014-03-07, 837 vessels, 127915 positions, real coordinates AugustaYesHistorical2013-05-01 - 2013-09-30, 406 vessels, 2207 positions, Single point coordinate 2013-01-15 - 2013-12-31, 2490 vessels, 2492 positions, real coordinates CataniaYesHistorical2011-01-01 - 2013-09-30, 363 vessels, 7320 positions, Single point coordinate - SiracusaNoHistorical-2013-04-10 – 2013-12-31, 352 vessels, 352 positions, real coordinates DATASET STATUS - BIODIVALUE TRACKERS

35. HIGH LEVEL PROCESS – FROM AIS ANTENNA TO BIODIVALUE TRACKER

36. SCENARIO 1 - MANUAL UPLOAD OF HISTORICAL DATASETS INTO BIODIVALUE TRACKERS SPECIFIC TO LOCATION High level requirements Collate and update data as per established CSV format and guidelines Upload and import CSV file directly to MySQL database feeding BioDiValue Tracker to refresh historical data available through web interface Benefits Most of the infrastructure is already in place Limited know how transfer is required to update the system from time to lime Limitations Requires human intervention every time to manually update BioDiValue Tracker Dataset available through BioDiValue Tracker will not be close to real time as in Scenario 2 Dataset quality is expected to vary as sources may not be automated as in scenario 2. Seperate BioDiValue Tracker for every location in Sicily No pre-processing of dataset to allow user to select vessel positions according to defined distance from coastline from BioDiValue Tracker May give rise to inconsistencies when assimilating data sources for different locations into one BioDiWare software

37. SCENARIO 2 - NEAR REAL TIME UPDATE OF BIODIVALUE TRACKERS THROUGH AIS ANTENNA FEED High level requirements Setup infrastructure as in high level process described in previous slides using software and practices that are already in function for BioDiValue Tracker – Malta Knowledge transfer from BioDiValue Tracker – Malta to implement in Sicily Benefits Automated process from data capture through AIS Antenna to BioDiValue Tracker Better opportunity provide consistent and timely datasets to BioDiValue Trackers and input to BioDiWare software. Datasets available through BioDiValue Tracker are expected to be as close to real time as can be. Dataset quality expected to be consistent throughout as AIS data feed is subject to standards. Less prone to human errors related to manually handling updates every time Depending on AIS implementation it may be possible to capture AIS data from several nearby locations in one BioDiValue Tracker Pre-processing of dataset allows user to select vessel positions according to defined distance from coastline from BioDiValue Tracker Limitations Require more infrastructure when and if more than one AIS antenna feed is to be combined (minimum 1 in Sicily depending on topology and 1 in Malta) in one BioDiValue Tracker. This complication can be avoided by developing a BioDiValue Tracker for every antenna. Combined feeds from multiple AIS Antenna’s that overlap in range require changes to the preprocessing before pushing the data onto the BioDiValue Tracker. Significant resources need to be allocated for knowledge transfer to happen and support period to ensure a smooth implementation