@OpenAustin WERE ON A MISSION Were building the most meaningful , - - PowerPoint PPT Presentation

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@OpenAustin

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WE’RE ON A MISSION

We’re building the most meaningful, collabora.ve, and abundant data resource in the world by dismantling the barriers between data and people.

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A NEW KIND OF COMPANY

Benefit Corpora.on

Notable Benefit Corpora.ons

• Expanded purpose includes public benefit
• Requires considera6on of shareholders and stakeholders
• Flexibility to weigh public benefit in sale & IPO decisions

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OUR PRODUCT

A data plaIorm that helps people work together to solve problems faster by creaMng new ways to discover, prep, and collaborate.

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Jonathan Or6z

September 19, 2016

OPEN DATA WANTS TO BE LINKED DATA

Because data is a social animal, too.

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HUGE

There are a

OPEN DATA SETS

NUMBER

• f

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TOO MUCH OF DATA’S GROWTH IS HAPPENING IN SILOS.

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DOWNLOADABLE

Only available as DOCUMENTS

DOWNLOADABLE DOWNLOADABLE

SLIDE 9 CSV TSV XLS

XML

KML GML

“JSON”

“GeoJSON” “TopoJSON” BINARY Shapefiles NetCDF

OPEN DATA EXISTS IN MANY FORMATS

XML

KML GML

CSV TSV XLS BINARY Shapefiles NetCDF “ J S O N ” “GeoJSON” “TopoJSON”

XML

KML G M L

CSV T S V XLS BINARY S h a p e fi l e s NetCDF “ J S O N ” “ G e

• J

S O N ” “ T

• p
• J

S O N ”

XML

GML

CSV XLS B I N A R Y S h a p e fi l e s N e t C D F “TopoJSON”

XML

KML GML

CSV T S V XLS B I N A R Y “JSON” “GeoJSON”

XML

CSV Shapefiles NetCDF “ T

• p
• J

S O N ”

KML

“JSON” “GeoJSON”

XML

CSV BINARY S h a p e fi l e s NetCDF “TopoJSON”

XML

C S V B I N A R Y Shapefiles N e t C D F “TopoJSON”

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Few formats convey MEANING about the contents in a way that can be

SHARED and EXTENDED.

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APIs

Some datasets are available via

But those APIs don’t generally have consistent interfaces

• r pa+erns…

SLIDE 12 JSON X M L CSV J S O N XML CSV JSON XML CSV

THEY LOAD IT IN

JSON

XML

CSV

JSON X M L CSV J S O N XML J S O N J S O N X M L C S V J S O N

XML

CSV

JSON X M L C S V JSON X M L CSV J S O N XML C S V

YOU PULL IT OUT

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EXISTS

GREAT

It is that this open data

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OPEN DATA FOR ALTERNATIVE RISK MODELS = $2B IN LOANS ACROSS 700+ INDUSTRIES

SLIDE 15 https://www.one.org/international/follow-the-money/case-studies/access-to-oil-and-mining-data-leads-to-doubling-of-education-and-health-budgets/

PIURA

AREQUIPA

OIL AND MINING DATA IMPROVES REVENUE FORECASTING = 2X SPENT ON EDUCATION AND HEALTH

SLIDE 16 http://iquantny.tumblr.com/post/144197004989/the-nypd-was-systematically-ticketing-legally

AN OPEN DATA BLOGGER IN NYC USED PUBLIC DATA TO PROVE THE NYPD ISSUED 1000’S OF PARKING TICKETS IN ERROR

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• Mr. Wellington’s analysis idenJfied errors the department made in issuing parking summonses. It

appears to be a misunderstanding by officers on patrol of a recent, abstruse change in the parking

• rules. We appreciate Mr. Wellington bringing this anomaly to our aNenJon.

The department’s internal analysis found that patrol officers who are unfamiliar with the change have

• bserved vehicles parked in front of pedestrian ramps and issued a summons in error. When the rule

changed in 2009 to allow for certain pedestrian ramps to be blocked by parked vehicles, the department focused training on traffic agents, who write the majority of summonses. Yet, the majority of summonses wriNen for this code violaJon were wriNen by police officers. As a result, the department sent a training message to all officers clarifying the rule change and has communicated to commanders of precincts with the highest number of summonses, informing them of the issues within their command.

Thanks to this analysis and the availability of this open data, the department is also taking steps to digitally monitor these types

• f summonses to ensure that they are being issued correctly.”

“ ”

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I was speechless. THIS is what the future of government could look like one day. THIS is what Open Data is all about. THIS was coming from the NYPD, who is not generally celebrated for its transparency, and yet it’s the most open and honest response I have received from any New York City agency to date. Imagine a city where all agencies embrace this sort of analysis instead of deflect and hide from it.

” “

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JUST IMAGINE WHAT PEOPLE ARE GOING TO DO WITH ALL THOSE DATA SETS

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JUST IMAGINE WHAT MACHINES ARE GOING TO DO WITH ALL THOSE DATA SETS

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it

UNDERSTANDING

But it and it can be a challenge

FINDING USING

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AND OVER AGAIN

This process happens as each data user does it individually

AND OVER OVER

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XML Data Science

So much HUMAN

SAME DATA

EFFORT

is wasted on the

WORKING & REWORKING

• f the

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The End

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LINKED DATA

What is

?

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IMAGINE RELEARNING WEB BROWSING FOR EACH NEW SITE YOU VISIT.

That's what it's like when data isn't linked.

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SAME

WWW

It’s applying the architecture as the

• f linked documents to…

DATA

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DATA

First, break into ATOMIC FACTS

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SUBJECT, PREDICATE, OBJECT

( )

(Turkey, "is a", Country) (Ankara, "is a", City) (Ankara, "is the capital of", Turkey)

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SUBJECT, PREDICATE, OBJECT

( )

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Turkey Country

"is a"

Ankara City

"is a" "is the capital of"

THE TRIPLE

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ENTITIES

Refer to and RELATIONSHIPS via URIs so theirMEANINGS can be discussed

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SUBJECT, PREDICATE, OBJECT

( )

hNp:/ /subject hNp:/ /predicate hNp:/ /object

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Turkey Country

"is a"

Ankara City

"is a" "is the capital of"

(dbpedia:Ankara, rdf:type, dbo:City) (dbpedia:Turkey, rdf:type, dbo:Country) (dbpedia:Ankara, dbo:capital, dbpedia:Turkey)

PUTTING IT TOGETHER

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Turkey Turkey

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(dbpedia:Turkey, rdf:type, dbo:Country) (dbpedia:Turkey_(bird), rdf:type, dbo:Bird) (dbpedia:Turkey, foaf:name, "Turkey") (dbpedia:Turkey_(bird), foaf:name, "Turkey")

TURKEY vs TURKEY

dbpedia:Turkey dbpedia:Turkey_(bird) dbo:Country “Turkey” dbo:Bird

rdf:type foaf:name foaf:name rdf:type

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“AAA” Principal

Can say

ANYONE ANYTHING

About

ANY TOPIC

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Triples are a universal format for represenMng facts - Any structured data can be mechanically transformed into triples.

CSV TSV XLS XML KML GML “JSON” “GeoJSON” “TopoJSON” BINARY Shapefiles NetCDF

YEA TRIPLES!

CSV “TopoJSON” XLS “TopoJSON” “GeoJSON” CSV GML XLS XLS “TopoJSON” “TopoJSON” Shapefiles

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TABULAR DATA AS A GRAPH

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LINKED

Why should you make your open data

?

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DISCOVERY

To make

• f your data easier

INTEROPERABLE

To make your data To help the machines learn FASTER

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The End ?

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“NETWORK EFFECT”

Data can enjoy a

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Each dataset that is added to the network

INCREASES the incrementalVALUE

• f every data set in the network

SLIDE 45 NETWORK EFFECT

DATA NETWORK

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UNIVERSAL IDENTIFIERS

is about publishing data as

LINKED DATA ATOMIC FACTS

and using to refer to concepts and relaJonships, so we can agree upon the

SEMANTIC MEANING

• f data.

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LINKED DATA

Your

OPEN DATA

wants to be

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So the PEOPLE and MACHINES who are using that data to solve HUMANITIES BIGGEST PROBLEMS can leverage the sum of accumulated knowledge as effectively as possible.

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OPEN DATA

The Jme to make your accessible as

LINKED DATA

is

NOW!

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The End

for real