Semantic Web and Emergency ResponseGetting ready for the unexpected!

Workshop on Semantics and Analytics for Emergency Response (SAFE2015)

Bart van Leeuwen ●

@semanticfire ● #safe2015 ● #iscram2015

@semanticfire

3

my fear

4 MINUTES

Reality

The Issue with

Models

Linked Data uses the

concepts and technologies of

the Web to describe the

world. (no acronyms, no tech

terms, one tweet)@philarcher1

4 MINUTES

The lazy organ

25

Visual oriented

26

Pattern Matching

27

Situational Awareness Barriers

• Pre Arrival Lens

– Based on models construct a image of

the scene before arrival

• Confirmation Bias

– Try to find confirmation of your model at

the scene, regardless of the reality

• Tunnel Vision

– Relentlessly stick to model

28

Models to

detect outliers

Triple A principle

AnybodyCan say

AnythingAbout

Any subject30

Validation

Failure!

31

Outlier detection!

Outlier detection

• Create Simple Models

• Create derivatives of simple

models

• Prevent to much constraints

• W3C Data Shapes ?

33

34

Where to

start?

v

v

v

my fear

Semantic Web and Emergency ResponseGetting ready for the unexpected!

Workshop on Semantics and Analytics for Emergency Response (SAFE2015)

Bart van Leeuwen ●

@semanticfire ● #safe2015 ● #iscram2015