3. Demo
•
Find and display places of interest within some distance of the
current location on a map with the data retrieved from Wikipedia
SELECT DISTINCT (str(?label) as ?label) ?lng ?lat ?abstract ?link ?
thumbnail (GROUP_CONCAT(?type; separator=',') as ?types) WHERE { ?res
<http://www.w3.org/2003/01/geo/wgs84_pos#long> ?lng. ?res <http://
www.w3.org/2003/01/geo/wgs84_pos#lat> ?lat. ?res rdfs:label ?
label . ?res foaf:isPrimaryTopicOf ?link. ?res <http://dbpedia.org/
ontology/thumbnail> ?thumbnail. ?res <http://dbpedia.org/ontology/
abstract> ?abstract. ?res rdf:type ?type_url . ?type_url rdfs:label ?
type . MINUS {?res a <http://dbpedia.org/ontology/PopulatedPlace>}.
FILTER ((?lng > 107.60059118270874 AND ?lng < 107.61589050292967
AND ?lat > -6.920153640158125 AND ?lat < -6.909630654323788) AND
LANG(?label)='en' AND LANG(?abstract)='en' AND LANG(?type)='en') }
Limit 1000
4.
5. The problem space
•
How to classify a wide range of information about something in a
way that can express the physical, conceptual and structural which
can describe the information encoded, supports different
languages, is machine readable, can be extended to express
additional information and handles a spectrum of detail.
8. Exploring connections
Data
!
Face1
Name
Linked data
!
Retrieve the Biography by searching for a
Name.
Biography
!
!
!
Face2
Name
!
!
Biography
!
Face(1):Name and Face(2):Name were at an
Event at a Location and Date.
Event Name
Event Location
Event Date
!
!
!
Copyright and attribution
!
!
Find others who were also at the Event or at the
same Location on the same Date.
10. URI
•
universal resource identifier!
•
•
•
Just like a URL, describes a document location
Adds a description of concepts
A pointer to a resource and concept
!
http://purl.org/dc/elements/1.1/date
!
http://www.w3.org/2000/01/rdf-schema#
!
http://www.w3.org/2000/01/rdf-schema#Class
!
http://dbpedia.org/ontology/Building/floorArea
11. Namespaces
•
Also known as prefixes
•
Defines a more readable form/abbreviation for a URI
http://purl.org/dc/elements/1.1/date
http://www.w3.org/2000/01/rdf-schema#Class
http://dbpedia.org/ontology/Building/floorArea
!
!
@prefix dc:
@prefix rdfs:
@prefix dbp:
<http://purl.org/dc/elements/1.1/> .
<http://www.w3.org/2000/01/rdf-schema#> .
<http://dbpedia.org/ontology/> .
!
dc:date
rdfs:Class
dbp:Building/floorArea
12. Description
Namespace
dc
Dublin Core Metadata Element
Set
dcam
Dublin Core abstract
model
dcmitype
Dublin Core Type
Vocabulary
dcterms
Dublin Core Metadata
Terms
doap
Description of a Project
(DOAP) vocabulary
foaf
Friend of a Friend (FOAF)
vocabulary
grddl
Gleaning Resource
Descriptions from Dialects of
Languages
owl
The OWL 2 Schema
vocabulary (OWL 2)
rdf
The RDF Vocabulary (RDF)
rdfs
The RDF Schema vocabulary
(RDFS)
Ontology for a few terms of the DCMI abstract model from the http://purl.org/dc/dcam/ namespace
The Description of a Project (DOAP) vocabulary, described using W3C RDF Schema and the
Web Ontology Language.
This ontology partially describes the built-in classes and properties that together form the basis of the RDF/XML syntax of
OWL 2. The content of this ontology is based on Tables 6.1 and 6.2 in Section 6.4 of the OWL 2 RDF-Based Semantics
specification, available at http://www.w3.org/TR/owl2-rdf-based-semantics/.
skos
SKOS Vocabulary
An RDF vocabulary for describing the basic structure and content of concept schemes such as thesauri, classification
schemes, subject heading lists, taxonomies, 'folksonomies', other types of controlled vocabulary, and also concept
schemes embedded in glossaries and terminologies.
vann
A vocabulary for annotating
vocabulary descriptions
Describes a vocabulary for annotating descriptions of vocabularies with examples
and usage notes.
vs
SemWeb Vocab Status
ontology
This vocabulary was created in the FOAF project, based on experience with FOAF, Dublin Core and other early RDF vocabularies. Deployment experience shows that changing
namespace URIs is expensive and unrewarding, so this vocabulary provides terms to support in-place evolution of structured data vocabularies. By indicating status at the level
of terms rather than vocabularies, dictionary-style, fine grained improvements become easier. Different organizations and parties can agree or disagree on the status of a
vocabulary term; however the status published alongside the term may deserve special attention. Future work could include patterns for citing announcements and decisions, or
using SKOS to decentralise the extension of the basic status levels.
xsd
XML Schema description
13. Finding all the pieces
•
Schema are published in a variety of forms
•
RDF/XML, Turtle, OWL, JSON, HTML
•
The location specified in the prefix typically negotiates content
•
if you use a browser you see the documentation
•
if you use a rdf tool you get RDF/XML or Turtle
•
No single canonical source
•
No global common definitions of prefixes
22. Dublin Core
•
The primary description system for most library collections
•
Two forms
•
Simple [ dc: ]
•
•
Defines the names of descriptions (called elements or fields) but no types
Qualified [ dcterms: ]
•
Defines both the names of the elements and the type of the data which
should be used. Compatible with and extends Simple.
•
Use Qualified Dublin Core when possible
23. Simple Dublin Core [ dc: ]
Title
Format
Creator
Identifier
Subject
Source
Description
Language
Publisher
Relation
Contributor
Coverage
Date
Rights
Type
24. Simple Dublin Core [ dc: ]
•
Identifying Simple and Qualified Dublin core:
•
Simple Dublin Core fields use mixed case (for example; dc:Subject,
dc:Title)
•
Qualified Dublin Core use lower case (for example; dcterms:subject,
dcterms:title but may also be seen as dc:subject and dc:title)
•
Examination of the encoding form of the data may be required
•
All fields are optional
•
All fields are repeatable
25. Qualified Dublin Core [ dcterms: ]
•
A refinement of the original Dublin Core standard to refine, qualify
and narrow the structure of the data which should be stored in each
field/element.
•
Adds a set of encoding schemes for the fields/elements which
supports:
•
Format notation and Parsing Rules which allow structured
interpretation of the data
•
Controlled Vocabularies
31. Crosswalks: Linking Data
•
Define sameAs relationships between schema classes and
properties
•
schema1:SubjectA
•
for example:
schema2:Subject2XYZ
•
dcterms:coverage.x
sameAs
•
schema:Thing.Intangible.StructuredValue.GeoCoordinates.latitude
32. Controlled Vocabularies
•
Controlled Vocabularies are a set of common definitions
•
Typically a key/value/label combination
•
May be flat or hierarchical
•
Common example is a selection list or box where you can choose from one or a
set of values
•
Many Controlled Vocabularies exist supporting the common interchange of
information through the use of a carefully selected list of terms, words or phrases
which may be broad or specific to a particular area of research or classification
•
Multilingual Controlled Vocabularies support interchange of information across
cultural and language boundaries
33. Controlled Vocabulary examples
Vocabulary
Description
MESH
The set of labeled concepts specified by the Medical Subject Headings.
DCMIType
The set of classes specified by the DCMI Type Vocabulary, used to categorize the nature or
genre of the resource.
UDC
The set of conceptual resources specified by the Universal Decimal Classification.
IMT
The set of media types specified by the Internet Assigned Numbers Authority.
NLM
The set of conceptual resources specified by the National Library of Medicine Classification.
DDC
The set of conceptual resources specified by the Dewey Decimal Classification.
LCSH
The set of labeled concepts specified by the Library of Congress Subject Headings.
TGN
The set of places specified by the Getty Thesaurus of Geographic Names.
LCC
The set of conceptual resources specified by the Library of Congress Classification.
35. How do you use it
How to describe
!
Face2
Face1
Face
Name
Biography
Institutional affiliation
!
Event
Name
Location
Name
Street Address, City, Country
Latitude and Longitude
Date
!
Image
Copyright and attribution
39. What to Describe
•
Dependant on the context of the asset
•
What information is important to describe
•
Who is the target audience
•
How could the asset be connected to other information or other
similar assets
•
What discipline or area of study is represented
41. Describing content
•
Time, Date and Location
•
Mt Fuji
•
•
Snow coverage
•
•
Geographic
Volcanic activity
Environment
•
•
•
Weather
Sea
Person
•
•
Name
Object
•
Position in image
•
Identification
Mt Fuji
42. How to describe
•
Schema selection
•
Media specific schema (exif, XMP, MP3 or other tags)
•
Use Qualified Dublin Core as the default
•
Try to choose additional well defined and common schema
•
schema.org (Google, Yahoo, Bing searches)
•
dbpedia.org (Linked Open Data)
•
Discipline specific schema
43. Derived information
•
Image metadata provides lat and lng of the
camera position
•
Mt Fuji lat and lng are known
Mt Fuji
•
Camera direction and distance from Mt
Fuji can be calculated
44. Derived information
•
Is this Face known
•
if known: Can we find other images of this Person
•
Face2
Face1
if not known: Search for a name
•
Is the Place known
•
Can an Event be generated based on knowing that People
were at a Place at the same Time
•
Can the details of the Event be found on the web
•
Can a list of People attending the Event be found
•
Search for images of each Person in the list
Mt Fuji
Face1
Face2
45. What can you do with this stuff ?
•
http://linkeddata.org
46.
47. Demo 2
•
Changing the information displayed in the map information boxes
•
Demo 1 review
•
"label", "lng", "lat", "abstract", "link", "thumbnail", “types"
•
LANG(?label)='en' AND LANG(?abstract)='en' AND LANG(?
type)='en'
