Linked Open Data - Seminar 25.04.12

Open

Linked^ Data

Rajendra Akerkar
rak@vestforsk.no

Outline
 Web evolution
 Semantic Web
 Why we need it?
 Linked Data Paradigm
 Tools
 JSON-LD

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Web Evolution

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From Gopher to Super-Mashups

http://reegle.info/countries

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Why do we want to add meaning
to data ?

 When a computer understands what
data means, it can do
 search,
 reasoning and
 combining

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Meaning is about understanding

To understand we need a language

A language starts with words

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Things mean something in words

Online, we describe things with XML

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Look at my coin collection

The first coin is called “Silver Tram” and is
from Armenia. It was made in 1246-47 AD.

The second coin is called “Gold Stater of
Lahor” and is from India. It was made in 127-151
AD.

< ... etc >

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<?xml version="1.0" encoding="ISO-8859-1"?>
<collection name=”My coin collection">
<coin>
<title>Silver Tram</title>
<country>Armenia</country>
<year>1246-47 AD</year>
</coin>
<coin>
<title>Gold Stater of Lahor</title>
<country>India</country>
<year>127-151 AD</year>
</coin>
</collection>

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We can’t understand words alone.
We also need grammar

Online grammar is RDF
(Resource Description Framework)

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This coin is from India

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predicate

subject object

This coin is from India

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With RDF Schema we can define
concepts and make simple
relations between them

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This coin is from India, hence
from South Asia

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But, RDF schema is limited

A language needs more expression and logic to
make good reasoning possible

That’s why OWL (The Web Ontology Language)
was invented

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Next, to reason you need rules

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I got this coin from my grandfather.

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son of father
I mother or father

The rule for calling someone my grandfather is
that one of my parents has a father

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Rules are formulated in Rule Language

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<ruleml:imp>
<ruleml:_rlab ruleml:href="#example1"/>
<ruleml:_body>
<swrlx:individualPropertyAtom
swrlx:property="hasParent">
<ruleml:var>x1</ruleml:var> <ruleml:_head>
<ruleml:var>x2</ruleml:var> <swrlx:individualPropertyAtom
</swrlx:individualPropertyAtom> swrlx:property="hasGrandfather"
<swrlx:individualPropertyAtom >
swrlx:property="hasFather"> <ruleml:var>x1</ruleml:var>
<ruleml:var>x2</ruleml:var> <ruleml:var>x3</ruleml:var>
<ruleml:var>x3</ruleml:var>
</swrlx:individualPropertyAtom> </swrlx:individualPropertyAtom>
</ruleml:_body> </ruleml:_head>
</ruleml:imp>

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So,

Words in XML
Grammar in RDF (schema) and OWL
Rules in RL
There are a lot of things, that can be described
using standard formats

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Suppose, I want to search for a specific coin

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“I want all the golden coins, designed
in Asia, but used in the Europe,
between 1958 and 1989”

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We can use SPARQL
(Protocol and RDF Query Language)

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Because the Web is decentralized and data is in
many places, not only language is important

Exchange of data between different
DB for knowledge creation is an
ultimate goal

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To make a connection a machine needs a source

For this, we use resource identifiers

Best known resource identifier is the URI
which consists of a name (urn) and
a location (url)

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URI

URL
URN
http://www.mycollection.in/
Gold Stater of Lahor goldStater

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With all this background
we are capable of using
the power of all
different
data resources on
the Web
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Linked Data vs. Semantic Web

 The Semantic Web, or the Web of
Data, is the ultimate goal

 Linked Data provides the means to
reach that goal

 Linked Data helps build the Web of
Data that later can be exploited by
more advanced technologies such
as intelligent agents

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Linked Data vs. Linked Open Data

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Databases store data to answer questions (1)

•How old is Rajendra? •When was VF founded?
•Where does Rajendra work? •Where is VF located?
•What is Rajendra interested •What can VF do for me?
in?

Persons Organisations

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Databases store data to answer questions (2)

•Rajendra is .. years old. •VF was founded 27 years ago.
•Rajendra works in Sogndal. •VF is located in Norway.
•Rajendra is interested in the •VF offers IT-Consulting &
Linked Data. Research.

name date_birth work_place interests
organisation date_founded location services

Rajendra 08-08 Sogndal Linked Data
VF 1985 Norway IT-Consulting
& Research
Svein …. …. ….
nLink …. …. ….


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Data from Databases can be exposed to the Web via HTML


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Data from Databases can be accessed via APIs

<workPlace>Sogndal</workPlace> <location>Norway</location>

getWorkplace(„Rajendra“) getLocation(„VF“)


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(Some) Information on the Web can be found via search engines

Questions won t be
Google answered necessarily

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But how to get answers on complex questions? (1)
Who is interested in „Linked Data“ and is working in the same country
as VF is located?

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But how to get answers on complex questions? (2)
Who is interested in „Linked Data“ and is working in the same country as
VF is located?

work_place same thing? location
Sogndal same country? Norway
name date_birth work_place interests organisation date_founded location services

Rajendra 08-08 Sogndal Linked Data VF 1985 Norway IT-Consulting &
Research
Svein …. …. ….
nLink …. …. ….

Still no answer

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Is Mapping the solution?
Mapped!
work_place location
same country?
Sogndal Norway

Still not clear

And what, if we need to add another database?

name date_birth university course
What, if DB-owners
Rajendra 08-08 NTNU Computer
Science can t agree on a
Students Svein …. …. ….
common model?

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Mapping is no solution
for a
distributed
Web of data

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Before I come up with a
solution ,

let us understand four
simple things
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Resources
place type Norway

isA
isA type partOf

work_place Sogndal

location

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URIs & Namespaces
rdf:type
umbel:place dbpedia:Norway

rdfs:subClassOf
p:subdivisionName
rdf:type
rdfs:subClassOf
geo:point
dbpedia:Sogndal

geonames:country

dbpedia:Sogndal = http://dbpedia.org/resource/Sogndal

rdfs:subClassOf = http://www.w3.org/2000/01/rdf-schema#subClassOf

A namespace is an abstract container or environment created to hold a logical
grouping of unique identifier or symbols.
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Ontologies
place type Norway

isA
isA type partOf

work_place Sogndal

location
has
has

Person worksFor
Organisation

isA
studiesAt

University

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What, if each
resource (classes
and individuals) had a
URI?
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Expose data from databases as resources & triples on the Web
dbpedia:Sogndal dbpedia:Norway

foaf:based_near foaf:based_near

persons:Rajendra orgs:VF

foaf:name foaf:birthday foaf:based_near foaf:topic_interest foaf:name foaf:birthday foaf:based_near orgs:services
persons:Rajendra
Rajendra 08-08 dbpedia:Sogndal dbpedia:LinkedData orgs:VF VF 1985 dbpedia:Norway IT-Consulting &
Research
persons:Svein Svein …. …. …. orgs:nLink
nLink …. …. ….


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Link data and do queries all over the Web
dbpedia:Sogndal p:subdivisionName dbpedia:Norway



foaf:topic_interest

dbpedia:LinkedData

Who is interested in „Linked Data“ and
is working in the same country as VF is located?

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Link data from more than 40 datasets

Make use of more
http://esw.w3.org/topic/SweoIG/TaskForces/CommunityProjects/LinkingOpenData
than 2 Billion triples!

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The Linking Open Data cloud diagram
Link data from more
than 295 datasets
Last updated: 2011-09-19

http://richard.cyganiak.de/2007/10/lod/

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How to get answers on really complex questions?

dbpedia:Sogndal p:subdivisionName dbpedia:Norway owl:sameAs Scandinavia:Norge


3.6

foaf:topic_interest
Scandenavia:unemployment_rate_total

dbpedia:LinkedData
Who is interested in „Linked Data“ and is working in a country
where the unemployment rate is lower than 4%?

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New way to get knowledge and answers —
not by searching the web, but by doing dynamic computations based
on a vast collection of data, algorithms, and methods

http://www.wolframalpha.com/

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Comprehensive Knowledge Archive Network

Open Knowledge Foundation http://no.ckan.net/
Licensed under the Open Database
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A collaboration between: Norwegian Press Association,
Association of Norwegian Editors, Norwegian Union of
Journalists, and Department of Journalism

http://www.offentlighet.no/Registeroffentlighet/Alle-registre

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Linked data ...

publishing data on the Web ...

... to enable integration, linking and reuse
across silos

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Six Steps to Publishing Linked Data
1. Understand the Principles
2. Model Your Data
3. Choose URIs for Things in your Data
4. Setup Your Infrastructure
5. Link to other Data Sets
6. Describe and Publicise your Data

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Can’t we just publish data as files?
pdf
 easy to read and publish 

Excel
 allows further processing and analysis 

csv
 processing without need for proprietary tools 

But ...
 structure of data not explained
 no connection between different data sets, silos
 static and fixed – can’t retrieve just slices relevant to problem

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Linked data
Apply the principles of the Web to publication of data

The Web:
 is a global network of pages
 each identified by a URL
 fetching a URL gives a document
 pages connected by links
 open, anyone can say anything about anything else

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Linked data
Apply the principles to the web to publication of data

The linked data web:
 is a global network of things

 each identified by a URI
 fetching a URI gives a set of statements
 things connected by typed links 
 open, anyone can say anything about anything else

Linked data is “data you can click on”

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Linked Data - Paradigm
 Use URIs as names for things

 Use HTTP URIs so that people can look up those
names.

 When someone looks up a URI, provide useful
information.

 Include links to other URIs. so that they can discover
more things.

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LOD Benefits
 other humans and applications can
 easily access your data using Web technologies
 follow the links in order to obtain further
contextual information

 links to your data and search engine indices
can increase the visibility of your data

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JSON-LD - JSON for Linking Data

 JSON-LD (JavaScript Object Notation for Linking Data) is a
lightweight Linked Data format that gives your data context.
 It is easy for humans to read and write. It is easy for machines to parse
and generate.
 It is based on the already successful JSON format and provides a way
to help JSON data interoperate at Web-scale.
 If you are already familiar with JSON, writing JSON-LD is very easy.
 These properties make JSON-LD an ideal Linked Data interchange
language for JavaScript environments, Web service, and unstructured
databases such as CouchDB and MongoDB.

http://json-ld.org/spec/latest/json-ld-syntax/
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 This RDF model in standard XML notation

 <rdf:RDF
xmlns:rdf="http://www.w3.org/1999/02/22-
rdf-syntax-ns#"
xmlns:dc="http://purl.org/dc/elements/1.1
/"> <rdf:Description
rdf:about="/wiki/Tony_Benn">
<dc:title>Tony Benn</dc:title>
<dc:publisher>Wikipedia</dc:publisher>
</rdf:Description> </rdf:RDF>

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 written in JSON-LD like this:

 { "@context": { "title":
"http://purl.org/dc/elements/1.1/title",
"publisher":
"http://purl.org/dc/elements/1.1/publishe
r" }, "@id": "/wiki/Tony_Benn", "title":
"Tony Benn", "publisher": "Wikipedia" }

 A context is used to allow developers to use aliases
for IRIs.

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JSON-LD object
 An Internationalized Resource Identifier (IRI)
 is a mechanism for representing unique identifiers on
the web.
 In Linked Data, IRIs (or URI references) are commonly
used for describing entities and properties.

 { "a": "Person", "name": "Manu Sporny",
"homepage": "http://manu.sporny.org/"
"avatar":
"http://twitter.com/account/profile_image/m
anusporny" }

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Unambiguous Identifiers for JSON
 If a set of terms, like Person, name, and homepage,
are defined in a context, and that context is used to
resolve the names in JSON objects, machines could
automatically expand the terms to something
meaningful and unambiguous

 { "http://www.w3.org/1999/02/22-rdf-syntax-
ns#type": "http://xmlns.com/foaf/0.1/Person",
"http://xmlns.com/foaf/0.1/name": "Manu Sporny",
"http://xmlns.com/foaf/0.1/homepage":
"http://manu.sporny.org"
"http://rdfs.org/sioc/ns#avatar":
"http://twitter.com/account/profile_image/manusporn
y" }

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JSON-LD Example
 Let's start by building up a fictitious bike store called
"Links Bike Shop". We've already got our bike store
setup athttp://store.example.com/ and are using
linked data principles.
 Here's some of the URLs:
 http://store.example.com/: The home page of the store.

 http://store.example.com/products/links-swift-chain: A
chain product.

 http://store.example.com/products/links-speedy-lube: A
chain lube product.
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 We want to start creating some linked data for this
fictitious store and start with rough JSON data on
the store itself.
{
"@id": "http://store.example.com/",
"@type": "Store",
"name": "Links Bike Shop",
"description": "The most "linked" bike
store on earth!"
}

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Next let's create some rough data for
our two premier products
{
"@id":
"http://store.example.com/products/links-
swift-chain",
"@type": "Product",
"name": "Links Swift Chain",
"description": "A fine chain with many
links.",
"category":
["http://store.example.com/categories/par
ts",
"http://store.example.com/categories/chai
ns"],
"price": "10.00",
"stock": 10
}
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{
"@id":
"http://store.example.com/products/links-
speedy-lube",
"@type": "Product",
"name": "Links Speedy Lube",
"description": "Lubricant for your chain
links.",
"category":
["http://store.example.com/categories/lub
es",
"http://store.example.com/categories/chai
ns"],
"price": "5.00",
"stock": 20
}
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To make this into a full JSON-LD document
we combine the data, add a @context,
and adjust some values.
{
"@id": "http://store.example.com/",
"@type": "Store",
"name": "Links Bike Shop",
"description": "The most "linked" bike
store on earth!",
"product": [
...
...

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],
"@context": {
"Store": "http://ns.example.com/store#Store",
"Product": "http://ns.example.com/store#Product",
"product": "http://ns.example.com/store#product",
"category": {
"@id": "http://ns.example.com/store#category",
"@type": "@id"
},
"price": "http://ns.example.com/store#price",
"stock": "http://ns.example.com/store#stock",
"name": "http://purl.org/dc/terms/title",
"description":
"http://purl.org/dc/terms/description",
"p": "http://store.example.com/products/",
"cat": "http://store.example.com/category/"
}
}
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Publishing Solutions and Tools

 Triplify

 Goal: expose semantics available in RDBMS as simple as
possible

 Available for most popular Web app languages
 PHP (ready), Ruby/Python (under dev.)

 Works with most popular Web app databases
 MySQL, PHP-PDO DBs (SQLite, Oracle, DB2, MS SQL,
PostgreSQL)

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Virtuoso RDF Views
 transforms the result of SQL SELECT statements into RDF

 mapping steps
 define RDFS class IRIs for each table
 define construction of subject IRIs from primary key column values
 define construction of predicate IRIs from each non-key column

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Marrying DBs with RDF & Ontologies
Relational Databases RDF & Ontologies
Data Model Relational Triples
(tables, columns, rows) (subject, predicate, object)
Schema and data  
separation
Implicit information  

Scalability  
Schema flexibility  
Web data integration  
readiness

Using DBs for storage and querying of RDF &
ontologies

Publishing DB content as RDF

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DBpedia is a community effort to extract structured information from
Wikipedia and to make this information available on the Web. DBpedia
allows you to ask sophisticated queries against Wikipedia, and to link other
data sets on the Web to Wikipedia data.

The DBpedia knowledge base currently describes more than 2.6 million
things, including at least 213,000 persons, 328,000 places, 57,000 music
albums, 36,000 films, 20,000 companies. The knowledge base consists
of 274 million pieces of information (RDF triples).
http://dbpedia.org/

DBpedia and all other linked data is searchable with SPARQL
http://en.wikipedia.org/wiki/SPARQL

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Open Streetmap

OpenStreetMap is a free editable map of the whole world.
It is made by people like you.
OpenStreetMap allows you to view, edit and use geographical data in a
collaborative way from anywhere on Earth.
www.openstreetmap.org

GeoNames
The GeoNames geographical database is available for download
free of charge under a creative commons attribution license. It
contains over eight million geographical names and consists of
6.5 million unique features.
www.geonames.org

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Creating Open Data
 Public Domain – Only after the expiration of copyright

 Science Commons protocol for open data

 Creative Commons Zero
 Public Domain Dedication & License with Community Norms

o Avoid Technical protection measures
o Give credit where credit’s due
o Use Open formats
o Let others know!
o Share your work too!

Photo by suttonhoo @ Flickr, CC BY-NC-SA

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Examples
 http://data-gov.tw.rpi.edu/wiki
 http://dbrec.net/
 http://fanhu.bz/
 http://data.nytimes.com/schools/schools.html
 http://sig.ma
 http://visinav.deri.org/semtech2010/

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The road to open
knowledge
begins here!

Thank you !
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Linked Open Data - Seminar 25.04.12

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