Post on 18-Dec-2014
description
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Integrating and Publishing Public Safety Data Using Semantic Technologies
Alvaro Gravesalvaro@graves.cl
Tetherless World
Constellation
Department of Cognitive Science
Outline
Motivations
Implementation
Challenges and next steps
Conclusions
<Motivation>
<Research>
Research Motivation
Lots of “human computational power” An example:
– 9 billion human-hours of solitaire were played in 2003 (in red)
– Building Panama canal took 20 million human-hours (in blue)
Interesting, but...
… How can we use this cognitive and computational processing power...
… to solve difficult problems....
… (Ideally) without much effort from the users?
Social Machines
• Social Machines are mechanisms where:
– Humans do the creative work
– Machines do the administrative work
What are we good at?
Humans MachinesPattern Discovery Good BadCreative Thinking Good BadInformation Management Bad GoodData Communication Bad Good
Example 1: reCAPTCHA
Example 2: GalaxyZoo
Example 3: Threadless
How to study Social Machines?
Limitations Access to information (logs, database) Privacy concerns Lack of flexibility
Solution: Create framework for Social Machines Incentives are important
</Research>
<Practical>
Troy, NY
Segmented city– Downtown
– RPI
– North/South
High risk zones
Unlike big cities– Hard to have
centralized data
– Resources are scarce
How can... Citizens to be aware of their environment?
– How risky is to park in this street between 1AM and 3AM?
Policy-makers make right decisions?– Is a specific crime increasing over time?
Law enforcers be more transparent in their work?
– How to show our work to the community?
What can we do?
Idea: Let's build....
… a platform for integrating public safety information
… a framework for studying Social Machines– Understand behavior of users in front of
data– Run experiments (ex: provenance => trust)
</Practical></Motivation>
<Implementation>
Architecture
<SemanticWeb>
Semantic Technologies
Based on the Web– Don't need to create special platform
Domain agnostic– Can express different domains
Dynamically coupled– Easy to mix different data sources
(Also: Interoperable, distributed, extensible, etc.)
Semantic Web: Example
Most basic “language”: RDF (Resource Description Framework)
Set of assertions (triples)
My name is Alvaro Graveshttp://graves.cl#me foaf:name “Alvaro
Graves”
Add more triples
</SemanticWeb>
<DataIntegration>
Different sources...
RPI Public Safety PDF files available on the Web Different formats depending on which
year Not easy to extract data
Troy Police Department Excel files upon request Less information (date/time, event type,
geographical references) Only certain crime types
...Similar Problems
Unclear geographical references (“Dining Hall”, “15th and Peoples ave.”)
Not only crimes but other events (fires, medical emergencies, etc.)
Our Taxonomy
</DataIntegration>
<Curation+Persistance>
Existing data is not enough
Lack of geolocation Use Google Maps as a Web Service
for obtaining latitude and longitude Typos
Manual correction Ambiguity
“Event occurred Off campus” (!) Approximate to the best we could
An example
Persistence
Use of semantic technologies for persistence
Pros: Easy to setup Works with MySQL+PHP
Cons: Not very scalable Queries cannot be too complex
</Curation+Persistance>
<Visualization+Publishing>
Data in multiple ways Citizens
At home/office On the street
Decision makers Statistics Potential correlations?
Machines Create notifications Display in other platform Reuse data
PublicSafetyMap.org
PublicSafetyMap.org
m.PublicSafetyMap.org
Only data around your location
Still in development!
PublicSafetyMap.org/feeds.php
Latest data Current search
RDF RSS KML
</Visualization+Publishing></Implementation>
<Challenges>
More than technical problems
Hard to convince decision makers
Trust issues
“Social entry barriers”
Next steps
Connect with well-known social networks (Facebook, Twitter, etc.) Geolocate anything (Bicycling route, pizza delivery area)
– Geoinferencing Add more dataset (Weather, real estate, Fire dept.)Annotation on events (Establishing trust measures, explanations, etc.)
Next steps
</Challenges>
<Conclusions>
Research: Studying Social Machines
Don't compete with Google
Opening data so others can use it for their own applications
But most important: A Framework where we can study Social Machines
Being able to run experiments
From Practical:Public Safety Information
User can visualize their neighborhood.
Policy-makers can manage data in a useful way.
Law enforcers can show their efforts.
</Conclusions><mailto:alvaro@graves.cl/>