APE 2012: Semantic Publishing - Just a Buzzword?

Semantic Publishing –
Just a Buzzword?
The current state of the Semantic Web and
a hands-on example of multidimensional microcontent

Prof. Dr. Felix Sasaki Michael Dreusicke (CEO)
W3C German-Austrian Office / DFKI PAUX Technologies GmbH
felix.sasaki@dfki.de md@paux.de
www.w3c.de www.paux.de

1. Why the Semantic Web?

© W3C German-Austrian Office & PAUX Technologies, APE 2012

Bridge the gap between what humans
see and what a browser “sees”

© W3C German-Austrian Office & PAUX Technologies, APE 2012 3

Give Uniqueness to concepts –
example “bank”

✔ ✔
✔ ✔

✔
✔

http://dbpedia.org/page/Bank ✔
© W3C German-Austrian Office & PAUX Technologies, APE 2012

Provide access to lot’s of interlinked
data – in a standardized manner


Allow for new ways to access the Web

• People who were born in Berlin before 1900
• Part of one answer from dbpedia (= Semantic Web version of
Wikipedia):
“Alexander Gottlieb Baumgarten”
born “1714-07-17”
died “1762-05-26”


2. Semantic Web in a Nutshell


Identify things (“resources”) using
URIs (Unique Resource Identifiers)

“Eric Miller” =
http://www.w3.org/People/EM/contact#me


Make statements about resources

• For humans: “Eric Miller has the email address em@w3.org”
• For machines: triples consisting of Subject, Predicate, Object
• http://www.w3.org/People/EM/contact#me
• http://www.w3.org/2000/10/swap/pim/contact#mailbox
• mailto:em@w3.org


Statements are like links
in the human Web

Consisting of source (subject),
target (object),
type of link (predicate)

http://www.w3.org/People/EM/contact#me

http://www.w3.org/2000/10/swap/pim/contact#mailbox

mailto:em@w3.org


Main technologies
in the Semantic Web

• RDF: Describe Resources
• “Eric Miller has the email address …”
• RDF Schema: Describe kinds of resources
• “Eric Miller is a person”
• OWL: Richer descriptions (“ontologies”)
• SPARLQ: Query RDF
• “Find me all persons who have an email address”
• “Find people who were born in Berlin before 1900”


3. Trends in Semantic Web


TREND: Linked Open Data

• Provide masses of data following the “5 stars of open linked
data”
• More and more communities
• Health Care & Life Sciences
• dbpedia in many languages
• Libraries
• eGovernment
• News provider
• …


TREND: Integrating Semantic Web
into Web pages: RDFa

All content on this site is licensed under
<a rel="license" href="http://creativecommons.org/licenses/by/3.0/">
a Creative Commons License
</a>.


TREND: Build bridges to other
approaches for metadata on the Web

• Example: schema.org
• Metadata vocabulary
• Used by Bing, Google, Yahoo! for presenting Web search results
• Can solve the ambiguity problem (“what is a bank?”)


A bank at schema.org


schema.org

One
vocabulary

Written as Written as
RDFa Microdata


schema.org

One
vocabulary

RDFa Microdata
Bridge towards
Semantic Web


schema.org

One
vocabulary

RDFa Microdata
Bridge towards Used at
Semantic Web schema.org


schema.org

One
vocabulary
Most
important!

RDFa Microdata
Bridge towards Used at
Semantic Web schema.org


TREND: build bridges among (Semantic
Web) vocabularies for the Web


Overview

• Advanced hypertext functionality
• Modular text
• Multiple links
• Rated links
• Examples

• Use cases
• Search
• Context-sensitive help
• Personalized content
• e-Learning
• Annotation + sharing + back channel
• Search engine optimization
• New business model

Advanced Hypertext Functionality

1"#

1"#
"n"

"n"
• Modular text
"
"m
n"#
"
"m
n"#

1"#
"n"

• Multiple links

• Rated links


Modular text

control
only over

1"#

1"#
"n"
container

"n"
reusable

"
"m
n"#
reusable n"#
"
"m

Control
over
content

1"#
"n"

Multiple Links

Pictures

Media Videos

Documents
Aggregation
Articles

references Textbooks

Aggregation
Commentary

Aggregation

Aggregation

Aggregation


Rated links
User Group
Previous Knowledge

Rating Difficulty
Rating Paragraph
Relevancy

e#
Quality

Pag

g
t in
Ra
Re f
e re
nce

Article
n-m

Rating Rating

e
er e nc
Re f Pag
e#
Ra
t in
g

Sentence

Examples for modular text


Text model


Everything has an ID/URI

ID

ID
ID
ID ID ID ID ID
ID

ID
ID ID ID ID ID
ID


Why an URI for everything?

• Metadata
• Multiple and rated links
• €


Example: Textbook „Statistic“

© W3C Germany/Austria & PAUX Technologies, APE 2012 31

Categories + icons for sentences


Use case 1: Search


Proposals


Number of hits


Search results: Single information


Search results: Sorted by category


Use case 2: context-sensitive help


Example: Help for a word ...


... opens popup


Popup shows linked content


For example a definition


... and some more topics (clickable)


Help for words in help texts


Help for help


...


Model: Text as linked data


Help for a word


Example: Sentence


Example: Paragraph


@sentence


persons@sentence


hyperlinks@sentence


pictures@sentence


...@paragraph


Person has an ID
and therefore context

ID


Example: Role for word

Editor


Example: Role for sentence

Contact


Example: Role for paragraph

Translator


Role has an ID

ID
Translator


Example: Persons within a role

Translator


Use case 3: Personalized content


Different surface


Different background


Use case 4: e-Learning


Example: Multiple choice test


Use case 5: Comment, share, discuss


Example: Liquid books


Further Books


Embedded content


Cross selling: Purchase further books


Cross selling: Popups as teasers


Advertising in the content ...


... or in the popups


Monitoring for each content object


Sharing


For example: Annotation of sentence


Rating and comment


Example: Facebook


Content object and annotation to Facebook


Comments and likes for comment at Facebook


Back channel


Aggregation at the book


In short

• RDF-Triple
• e-Learning
• SEO
• Microsites
• RDFa


Use case 6: Search engine optimization


Microsites of every content object
(text and relations)


Pages

http://www.


Paragraphs

http://www.

http://www.

http://www.


Sentences

http://www.

http://www.

http://www.

http://www.

http://www.

http://www.

http://www.

http://www.


Words (+relations +annotations)

ww. w.
http //www.

http //www.

http //www.
http ://ww
http w.

http w.

http w.

ww.
http://www. http://www.

w

w

w
://w

://w

://w

://w

://w
:

:

:
http

http
http://www. http://www. http://www.
http://www.
http://www.
http://www.
http://www.

http://www.
http://www.
http://www.
http://www.
http://www.
http://www.
http://www.
http://www.
ww. w.
http //www.

http //www.

http //www.
http ://ww
http w.

http w.

http w.

ww.
w

w

w
://w

://w

://w

://w

://w
:

:

:
http
http


Use case 7: New business model
Pr ic
eP
On l
i ne

e
Paragraph

n li n
Price P Print

t
rin
AO

l
obi
AP
ce P

AM
ce P
Pr i

Pr i

ce P
e
PO n li n
r ic e

Pr i
P
Re f
e re
nce
e
O n li n
Pr i ce A
Price SP Online

Article
n-m

Price SP Print Price A Print

Price SP Mobil
Pr ic
eA
Mo b
il

ce
e re n
Re f
Pr i
ce S
Pr i
Pr i

AO
ce S
ce S

n li n
AP

Sentence
AM

rin

e
t
obi
l


Summary

• Semantic Web
• Why we need it
• The technical bits
• What comes next
• Semantic Microcontent
• Concrete Advantages


Thank you for your attention.
Questions?

Prof. Dr. Felix Sasaki Michael Dreusicke (CEO)
W3C German-Austrian Office / PAUX Technologies GmbH
DFKI md@paux.de
felix.sasaki@dfki.de www.paux.de
www.w3c.de


APE 2012: Semantic Publishing - Just a Buzzword?

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