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© Copyright 2010 Dieter Fensel and Ioan Toma, updated by Anna Fensel in 2016‐2018
Semantic Web Services
SS 2018
Web Science
Anna Fensel
12.03.2018
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Where are we?
# Title
1 Introduction
2 Web Science + Cathy O’Neil’s talk: “Weapons of Math Destruction”
3 Service Science
4 Web services
5 Web2.0 services
6 Semantic Web
7 Semantic Web Service Stack (WSMO, WSML, WSMX)
8 OWL-S and the others
9 Semantic Services as a Part of the Future Internet and Big Data Technology
10 Lightweight Annotations
11 Linked Services
12 Applications
13 Mobile Services

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Outline
• Motivation
• Web Science
• Web Evolution
– Web 1.0 – Traditional Web
– Web 2.0 – Social Web
• Major breakthroughs of Web 2.0
– Web 3.0 – Semantic Web
• What Web Science could be
– The computer science of the 21st century
– Extension to Data Science
• Summary
• References
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MOTIVATION

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Motivation
http://www.youtube.com/watch?v=6gmP4nk0EOE
The Web Today
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Motivation
“[…] As the Web has grown in complexity and the
number and types of interactions that take place have
ballooned, it remains the case that we know more about
some complex natural phenomena (the obvious example
is the human genome) than we do about this particular
engineered one.”
A Framework for Web Science
T. Berners-Lee and W. Hall and J. A. Hendler and K. O'Hara and N.
Shadbolt and D. J. Weitzner Foundations and Trends® in Web
Science 1 (2006)
A new science that studies the complex phenomena called Web is needed!!

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WEB SCIENCE
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Web Science definition
A new science that focuses on how huge decentralized
Web systems work.
“The Web isn’t about what you can do with computers. It’s people and, yes,
they are connected by computers. But computer science, as the study of
what happens in a computer, doesn’t tell you about what happens on the
Web.”
Tim Berners-Lee
“A new field of science that involves a multi-disciplinary study and
inquiry for the understanding of the Web and its relationships to us”
Bebo White, SLAC, Stanford University
Shift from how a single computer works to how huge
decentralized Web systems work

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Endorsements for Web Science
“Web science represents a pretty big next step in the evolution of
information. This kind of research likely to have a lot of influence on
the next generation of researchers, scientists and, most importantly,
the next generation of entrepreneurs who will build new companies
from this.”
Eric E. Schmidt, CEO Google (2011-2015)
“Web science research is a prerequisite to designing and building
the kinds of complex, human-oriented systems that we are after in
services science.”
Irving Wladawsky-Berger, IBM
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Web science – multi-disciplinary approach
http://webscience.org/images/collide.jpg

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• To understand what the Web is
• To engineer the Web’s future and providing
infrastructure
• To ensure the Web’s social benefit
The Goals of Web Science
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Scientific method
• Natural Sciences such as physics, chemistry, etc. are
analytic disciplines that aim to find laws that generate or
explain observed phenomena
• Computer Science on the other hand is synthetic. It is
about creating formalisms and algorithms in order to
support particular desired behaviour.
• Web science scientific method has to be a combination
of these two paradigms

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What Could Scientific Theories for the
Web Look Like?
• Some simple examples:
– Every page on the Web can be reached by following less than 10
links
– The average number of words per search query is greater than 3
– Web page download times follow a lognormal distribution function
(Huberman)
– The Web is a “scale-free” graph
• Can these statements be easily validated? Are they good
theories? What constitutes good theories about the
Web?
http://webcast.bibalex.org/Presentations/Bebo91108.ppt
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Electricity : 1800 Electricity Now
What are the analogies for Web Science and Design? Is
our understanding of the Web like that of 1800 electricity?
http://webcast.bibalex.org/Presentations/Bebo91108.ppt
Food For Thought

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In the rest of this lecture
• Web Evolution
– Web 1.0 - Traditional Web
– Web 2.0 – Social Web
– Web 3.0 - Semantic Web
• Future steps to realize Web science
– Large scale reasoning
– Rethinking Computer Science for the 21st century
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WEB 1.0 – TRADITIONAL WEB

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More than a 2 billion users
more than 50 billion pages
Static
WWW
URI, HTML, HTTP
Web 1.0
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• The World Wide Web ("WWW" or simply the
"Web") is a system of interlinked, hypertext
documents that runs over the Internet. With a
Web browser, a user views Web pages that may
contain text, images, and other multimedia and
navigates between them using hyperlinks. -
wikipedia
• The Web was created around 1990 by Tim
Berners-Lee working at CERN in Geneva,
Switzerland.
Web 1.0

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• A distributed document delivery system implemented
using application-level protocols on the Internet
• A tool for collaborative writing and community building
• A framework of protocols that support e-commerce
• A network of co-operating computers interoperating using
HTTP and related protocols to form a ‘subnet’ of the
Internet
• A large, cyclical, directed graph made up of Web pages
and links
Web 1.0
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WWW Components
• Structural Components
– Clients/browsers – to dominant implementations
– Servers – run on sophisticated hardware
– Caches – many interesting implementations
– Internet – the global infrastructure which facilitates data
transfer
• Language and Protocol Components
– Uniform Resource Identifiers (URIs)
– Hyper Text Transfer Protocol (HTTP)
– Hyper Text Markup Language (HTML)

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Uniform Resource Identifiers (URIs)
• Uniform Resource Identifiers (URIs) are used
to name/identify resources on the Web
• URIs are pointers to resources to which
request methods can be applied to generate
potentially different responses
• Resource can reside anywhere on the
Internet
• Most popular form of a URI is the Uniform
Resource Locator (URL)
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Hypertext Transfer Protocol (HTTP)
• Protocol for client/server communication
– The heart of the Web
– Very simple request/response protocol
• Client sends request message, server replies with response
message
– Provide a way to publish and retrieve HTML pages
– Stateless
– Relies on URI naming mechanism

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HTTP Request Messages
• GET – retrieve document specified by URL
• PUT – store specified document under given URL
• HEAD – retrieve info. about document specified by URL
• OPTIONS – retrieve information about available options
• POST – give information (eg. annotation) to the server
• DELETE – remove document specified by URL
• TRACE – loopback request message
• CONNECT – for use by caches
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HTML
• Hyper-Text Markup Language
– A subset of Standardized General Markup
Language (SGML)
– Facilitates a hyper-media environment
• Documents use elements to “mark up” or identify sections
of text for different purposes or display characteristics
• Mark up elements are not seen by the user when page is
displayed
• Documents are rendered by browsers

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HTML
HTML markup consists of several types of entities,
including: elements, attributes, data types and character
references
– DTD (Document Type Definition)
• <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN" "http://www.w3.org/TR/html4/strict.dtd">
– Element (such as document (<html>…</html>), head elements
(<title>…</title>)
– Attribute: <span id='anId' class='aClass' style='color:red;'
title='HyperText Markup Language'>HTML</span>
– Data type: CDATA, URIs, Dates, Link types, language code,
color, text string, etc.
– Character references: for referring to rarely used characters:
• "&#x6C34;" (in hexadecimal) represents the Chinese character for
water
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WEB 2.0

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Web 2.0
“Web 2.0is a
notion for a row of
interactive and
collaborative
systems of the
internet“
http://widgets-gadgets.com/2006_10_01_archive.html
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Web 2.0
• Web 2.0 is a vaguely defined phrase referring to
various topics such as social networking sites,
wikis, communication tools, and folksonomies.
• Tim O'Reilly provided a definition of Web 2.0 in
2006: "Web 2.0 is the business revolution in the
computer industry caused by the move to the
internet as platform, and an attempt to
understand the rules for success on that new
platform. Chief among those rules is this: Build
applications that harness network effects to get
better the more people use them.”

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People, Services, Technologies
Web 2.0
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Consumers  Prosumers
Web 1.0 Web 2.0 improvement
DoubleClick Google AdSense personalized
Ofoto Flickr tagging, community
Britannica Online Wikipedia community, free
content
Web sites blogging dialogue
publishing participation
CMS wikis flexibility, freedom
directories tagging community
taxonomy folksonomy
What is the web 2.0? „Definition“ by O‘Reilly

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• Gmail
• Google Notebooks (Collaborative Notepad in the Web)
• Wikis
• Wikipedia
– Worlds biggest encyclopedia, Top 30 web site, 100
langueges
• Del.icio.us (Social Tagging for Bookmarks)
• Flickr (Photo Sharing and Tagging)
• Blogs, RSS, Blogger.com
• Programmableweb.com: 150 web-APIs
What is the Web 2.0? - Examples
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• Easy usable user interfaces to
update contents
• Easy organization of contents
• Easy usage of contents
• Easy publishing of comments
• Social: collaborative (single
users but strongly
connected)
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Blogs

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• Wiki  invented by Ward Cunningham
• Collection of HTML sites: read and edit
• Most famous and biggest Wiki: Wikipedia (MediaWiki)
– But: Also often used in Intranets (i. e. our group)
• Problems solved socially instead of technically
• Flexible structure
• Background algorithms + human intelligence
• No new technologies
• social: collaborative (nobody owns contents)
Wikis
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Source: http://c2.com/cgi/wiki?WikiDesignPrinciples
• Open
Should a page be found to be incomplete or poorly organized, any
reader can edit it as they see fit.
• Incremental
Pages can cite other pages, including pages that have not been
written yet.
• Organic
The structure and text content of the site are open to editing and
evolution.
• Mundane
A small number of (irregular) text conventions will provide access to
the most useful page markup.
• Universal
The mechanisms of editing and organizing are the same as those of
writing so that any writer is automatically an editor and organizer.
• Overt
The formatted (and printed) output will suggest the input required to
reproduce it.
Wikis: Design Principles
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Source: http://c2.com/cgi/wiki?WikiDesignPrinciples
• Unified
Page names will be drawn from a flat space so that no
additional context is required to interpret them.
• Precise
Pages will be titled with sufficient precision to avoid most
name clashes, typically by forming noun phrases.
• Tolerant
Interpretable (even if undesirable) behavior is preferred
to error messages.
• Observable
Activity within the site can be watched and reviewed by
any other visitor to the site.
• Convergent
Duplication can be discouraged or removed by finding
and citing similar or related content.
Wikis: Design Principles
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• Idea: Enrich contents by user chosen keywords
• Replace folder based structure by a organisation using tags
• New: Simple user interfaces for tagging and tag based search
• First steps to Semantic Web?
• Technically: user interfaces
• Social: collaborative (own contents, shared tags)
Social Tagging

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Collaborative Tagging
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Collaborative Tagging: Delicious
• Browser plug-ins available from http://del.icio.us
• Allows the tagging of bookmarks
• Community aspect:
– Suggestion of tags that were used by other users
– Availability of tag clouds for bookmarks of the whole community
– Possibility to browse related bookmarks based on tags

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Tagging: Flickr.com
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User
Tag Resource
Resource
Resource
Resource
Resource
Tag
Tag
Tag
Tag
User
User
Mary tags www.wikipedia.org with wiki wikipedia encyclopedia
Data created by tagging, knowledge structures
Folksonomies

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Size of Tags:
count of usage
Orientation in
Information Set
Browsing
replaces
Searching
Different meaning
for different users
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Tag Clouds
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Major breakthroughs of Web 2.0
The four major breakthroughs of Web 2.0 are:
1. Blurring the distinction between content
consumers and content providers.
2. Moving from media for individuals towards
media for communities.
3. Blurring the distinction between service
consumers and service providers.
4. Integrating human and machine computing
in a new way.

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Blurring the distinction between content
consumers and providers
Interactive Web applications through asynchronous
JavaScript and XML (AJAX)
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Blurring the distinction between content
consumers and providers
Interactive Web applications through asynchronous
JavaScript and XML (AJAX)

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Blurring the distinction between content
consumers and providers:
Weblogs or Blogs, Wikis
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Blurring the distinction between content
consumers and providers:
Flickr, YouTube

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Blurring the distinction between content
consumers and providers
Tagging – del.icio.us, shazam.com
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Blurring the distinction between content
consumers and providers
RDFA, micro formats

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Moving from a media for individuals towards a
media for communities
Folksomonies, FOAF
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Moving from a media for individuals towards a
media for communities
Community pages (friend-of-a-friend, flickr, LinkedIn,
myspace, Facebook…)

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Moving from a media for individuals towards a
media for communities
Second Life
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Moving from a media for individuals towards a
media for communities
Wikipedia

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Moving from a media for individuals towards a
media for communities
Wikipedia
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Blurring the distinction between service
consumers and service providers
RSS feeds

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Blurring the distinction between service
consumers and service providers
Yahoo pipes allow people to connect internet data sources,
process them, and redirect the output.
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Blurring the distinction between service
consumers and service providers
Widgets, gadgets, and mashups.

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Integrating human and machine computing in
a new way
Amazon Mechanical turk
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SEMANTIC WEB

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Static
WWW
URI, HTML, HTTP
Semantic Web
RDF, RDF(S), OWL
From Web to Semantic Web
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• If the Web is about the global networking of data through URL,
HTML, and HTTP…
• … the Semantic Web is about the global networking of
knowledge through URI, RDF, and SPARQL
• This knowledge can be an annotation of Web data (this picture
depicts Innsbruck) or just for knowledge‘s sake (Innsbruck is a city
in Austria)
Semantic Web

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• URIs are used to identify resources, not just things that exists on
the Web, e.g. Sir Tim Berners-Lee
• RDF is used to make statements about resources in the form of
triples
<entity, property, value>
• With RDFS, resources can belong to classes (my Mercedes
belongs to the class of cars) and classes can be subclasses or
superclasses of other classes (vehicles are a superclass of cars,
cabriolets are a subclass of cars)
Semantic Web
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• Give URIs to concepts - Each URI
identifies one concept.
• Share these symbols between many
languages
• Support URI lookup
Semantic Web Architecture

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The Semantic Web layer cake
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• Uniform Resource Identifier (URI) is the dual of
URL on Semantic Web
– It’s purpose is to indentify resources
• eXtensible Markup Language (XML) is a markup
language used to structure information
– Fundament of data representation on the Semantic Web
– Tags do not convey semantic information
URI and XML

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• Resource Description Framework (RDF) is the
dual of HTML in the Semantic Web
– Simple way to describe resources on the Web
– Sort of simple ontology language (RDF-S)
– Based on triples (subject; predicate; object)
– Serialization is XML based
• Ontology Web Language (OWL) a layered
language based on DL
– More complex ontology language
– Overcome some RDF(S) limitations
RDF and OWL
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• SPARQL
– Query language for RDF triples
– A protocol for querying RDF data over the Web
• Rule languages (e.g. SWRL)
– Extend basic predicates in ontology languages with
proprietary predicates
– Based on different logics
• Description Logic
• Logic Programming
SPARQL and Rule languages

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Annotated Content
• KIM Browser Plugin
Web content is annotated using
ontologies
Content can be searched and
browsed intelligently
Semantic Web
Select one or more concepts
from the ontology…
… send the currently loaded
web page to the Annotation
Server
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Dereferencable
URI
Disco Hyperdata Browser
navigating the Semantic Web as an
unbound set of data sources
Semantic Web

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Faceted DBLP
uses the keywords provided in
metadata annotations to
automatically create light-weight
topic categorization
Semantic Web
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Semantic Web

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WEB EVOLUTION - SUMMARY
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Web Evolution - summary
Web 1.0 Web 2.0 Semantic Web
Personal Websites Blogs Semantic Blogs: semiBlog, Haystack, Semblog,
Structured Blogging
Content Management Systems,
Britannica Online
Wikis, Wikipedia Semantic Wikis: Semantic MediaWiki, SemperWiki,
Platypus, dbpedia, Rhizome
Altavista, Google Google Personalised,
DumbFind, Hakia
Semantic Search: SWSE, Swoogle, Intellidimension
CiteSeer, Project Gutenberg Google Scholar, Book Search Semantic Digital Libraries: JeromeDL, BRICKS,
Longwell
Message Boards Community Portals Semantic Forums and Community Portals: SIOC,
OpenLink DataSpaces
Buddy Lists, Address Books Online Social Networks Semantic Social Networks: FOAF, PeopleAggregator
… … Semantic Social Information Spaces: Nepomuk,
Gnowsis

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Web Evolution - summary
• Traditional Web (Web1.0)
– Normal User: browsing
– Communication style: one-direction communication (e.g. reading a book)
– Data: web data (string and syntactic format)
– Data contributor: webmaster or experienced user
– How to add data: compose HTML pages
• Social Web (Web2.0)
– Normal User: browsing + publishing and organizing web data
– Communication style: human-human (sharing)
– Data: web data + tags
– Data contributor: normal user – revolution!
– How to add data: tagging
• Semantic Web
– Normal User: interacting (human-machine)
– Communication style: humanmachine
– Data: web data + tags + metadata (in SW Language)
– Data contributor: normal user, machine
– How to add data: machine generate or user publish
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WHAT WEB SCIENCE COULD BE

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Web principles
In the context of the traditional Web (Web 1.0)
a set of principles were proposed:
• Web resource are identified by URI
(Universal Resource Identifier)
• Namespaces should be used to denote
consistent information spaces
• Make use of HTML, XML and other W3C
Web technology recommendations, as well
as the decentralization of resources
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• The traditional Web represents information using
– natural language (English, German, Italian,…)
– graphics, multimedia, page layout
• Humans can process this easily
– can deduce facts from partial information
– can create mental associations
– are used to various sensory information
Web 1.0 + semantics = Semantic Web

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• However…. Machines are ignorant!
– partial information is unusable
– difficult to make sense from, e.g., an image
– drawing analogies automatically is difficult
– difficult to combine information automatically
• is <foo:creator> same as <bar:author>?
• how to combine different XML hierarchies?
– …
Web 1.0 + semantics = Semantic Web
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Semantic Web
• Semantic Web is about applying semantics to
the tradition Web, Web 1.0
• Some of the benefits of Semantic Web:
– More precise queries
– Smarter apps with less work
– Share & link data between apps
– Information has machine-processable and
machine-understandable semantics

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• The principal limits of describing large, heterogeneous,
and distributed systems
• The principal limits of self representation and self
reflection
 Necessitates incompleteness and incorrectness of
semantic descriptions.
Limitations of applying semantics to
traditional Web
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Limitations of applying semantics to
traditional Web
The principal limits of describing large, heterogeneous, and distributed systems

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The principal limits of self representation and self reflection
Limitations of applying semantics to
traditional Web
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The principal limits of self representation and self reflection
Limitations of applying semantics to
traditional Web

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Object Layer
(encodes possible complete reasoning
knowledge for the problem)
Meta Layer
(encodes heuristics, i.e. strategic knowledge)
Introspection Reflection
The principal limits of self representation and self reflection
Limitations of applying semantics to
traditional Web
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• The meta layer should apply heuristics that may help
– Speed up the overall reasoning process.
– Increase its flexibility.
• Therefore, it needs to be incomplete in various aspects
and resemble important aspects of our consciousness.
– Introspection
– Reflection
• Unbounded rationality, constrained rationality, limited
rationality.
Limitations of applying semantics to
traditional Web

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• Description of data by metadata or programs by
metaprograms
– Always larger (even infinitely large) …
– … or always an approximation
Limitations of applying semantics to
traditional Web
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• In a large, distributed, and heterogeneous environment,
classical ACID (Atomicity, Consistency, Isolation,
Durability) guarantees of the database world no longer
scale in any sense.
• Even a simple read operation in an environment such as
the Web, a peer-to-peer storage network, a set of
distributed repositories, or a space, cannot guarantee
completeness in the sense of assuming that if data was
not returned, then it was not there.
• Similarly, a write can also not guarantee a consistent
state that it is immediately replicated to all the storage
facilities at once.
Data look-up on the Web

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• Modern information retrieval applies the same
principles
– In information retrieval, the notion of
completeness (recall) becomes more and more
meaningless in the context of Web scale
information infrastructures.
– It is very unlikely that a user requests all the
information relevant to a certain topic that exists
on a worldwide scale, since this could easily go
far beyond the amount of information processing
he or she is investing in achieving a certain goal.
– Therefore, instead of investigating the full space
of precision and recall, information retrieval is
starting to focus more around improving
precision and proper ranking of results.
Information retrieval on the Web
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• What holds for a simple data look-up holds in an even
stronger sense for reasoning on Web scale.
• The notion of 100% completeness and correctness as
usually assumed in logic-based reasoning does not even
make sense anymore since the underlying fact base is
changing faster than any reasoning process can process
it.
• Therefore, we have to develop a notion of usability of
inferred results and relate them with the resources that
are requested for it.
Reasoning on the Web

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precision
(soundness)
recall (completeness)
Logic
IR
Semantic Web
Reasoning on the Web
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• LarKC – The Large Knowledge Collider
http://larkc.sti2.at/
• An open source, modular, and distributed platform for
inference on the Web that makes use of new reasoning
techniques
• A plug-in architecture that supports cooperation between
distributed, heterogeneous, cooperating modules enabling
research into new and different reasoning techniques
LarKC – The Large Knowledge Collider

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LarKC – The Large Knowledge Collider
• A platform for infinitely scalable
reasoning on the data-web
• First real attempt at Reasoning at a
Web scale
• Not just adding a Web syntax to
reasoning, but reflecting on the
underlying assumptions of reasoning
and the Web
– Bringing Web principles to reasoning
– Bringing reasoning to the Web
• Thus LarKC is true Web Science
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92
LarKC – The Large Knowledge Collider
• A number of broken assumptions of reasoning and logic in a Web
context:
– The Web is small
– The Web does not change
– The Web does not contradict itself
• In fact:
– The Web is huge
– The Web changes faster than we can reason over it
– The Web contains contradictions and different points of view
• The essence of the web (search) must be included into the reasoning
process, generating something new called reasearch
• After 4000 years of separation LarKC merges induction and deduction

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WEB SCIENCE – THE COMPUTER
SCIENCE OF THE 21st CENTURY
94
• With the Web we have an open, heterogeneous, distributed, and fast
changing computing environment.
• Therefore we need computing to be understood as
– A goal driven approach where the solution process
is only partially determined and actually decided
during runtime, based on available data and services.
– A heuristic approach that gives up on absolute
notion of completeness and correctness in order to
gain scalability.
• The times of 100% complete and correct solutions are gone.
Web Science – The Computer Science of the
21st Century

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The Need for Trade-offs:
• In all areas one has to define the trade-off between the
guarantees one provides in terms of service level
agreements. Completeness and correctness are just
examples of some very strong guarantees and what this
requires in terms of assumptions, and computational
complexity.
• Different heuristic problem solving approaches are just
different combinations of these three factors.
Web Science – The Computer Science of the
21st Century
96
• Service level agreements (or goals) define what has to
be provided as result of solving a problem.
• Do we request an optimal solution, a semi-optimal
solution, or just any solution?
Web Science – The Computer Science of the
21st Century

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• Assumptions describe the generality of the problem
solving approach:
– Assuming that there is only one solution allows stopping the
search for an optimum immediately after a solution has been
found.
– Instead of a global optimization method, a much simpler heuristic
search method can be used in this case, which would still deliver
a global optimum.
• Computational complexity (scalability) or the resources
that are required to fill the gap between the assumptions
and the goals.
Web Science – The Computer Science of the
21st Century
98
Web Science – The Computer Science of the
21st Century
• Computer science in the 20th century was about perfect
solutions in closed domains and applications.
• Web science, the new computer science of the 21st
century, will be about approximate solutions and
frameworks that capture the relationships of partial
solutions and requirements in terms of computational
costs, i.e., the proper balance of their ratio.

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• This shift is comparable to the transition in physics, from classical
physics to relativity theory and quantum mechanics,
• ...where the notion of absolute space and time is replaced by
relativistic notions and the principle limits of precision.
• the more precisely we know about the location of a particle in space,
the less we know about its movement in time and vice versa.
?
?
?
?
Web Science – The Computer Science of the
21st Century
100
Data Science
• As the Web gets to consist primarily of (structured) data, Data Science
gets to take some functions of Web Science.
• “Data science, also known as data-driven science, is an
interdisciplinary field of scientific methods, processes, algorithms and
systems to extract knowledge or insights from data in various forms,
either structured or unstructured, similar to data mining.” - Wikipedia

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Data science process flowchart from "Doing
Data Science", Cathy O'Neil and Rachel
Schutt, 2013
102
Current Data Science Challenges…
• …include human bias in design of algorithms, insufficient transparency,
non-compliance to laws and ethics in algorithms, leading to
semantically wrong decisions, often with massive negative impacts.
• See more details and examples at:
• https://www.youtube.com/watch?v=TQHs8SA1qpk

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Summary
• The Web is a in an extending success story with over more than a 2
billion users more than 50 billion pages. (*)
• There is a need for a new science that focuses on how huge
decentralized Web systems work - Web Science.
• Semantics will play a central role in the future development of the
Web.
• However there are limitations of applying semantics to traditional Web
due to the principal limits of self representation and self reflection.
• Limitations should be addressed by considering 2 levels: meta layer
and object layer.
• Meta layer should apply heuristics that may help speed up the overall
reasoning process and increase its flexibility.
• Introspection and Reflection can be used to move from one layer to
the other.
(*) Rough estimate, source: Shroff, G. (2013). The Intelligent Web: Search, smart
algorithms, and big data. OUP Oxford.
104
References
• Mandatory reading:
– T. Berners-Lee, W. Hall, J. Hendler, N. Shadbolt, D. Weitzner
(2006): Creating a science of the Web.
http://eprints.ecs.soton.ac.uk/12615/
– T. Berners-Lee, W. Hall, J. Hendler, K. O’Hara, N. Shadbolt, D.
Weitzner (2006): A Framework for Web Science.
http://eprints.ecs.soton.ac.uk/13347/
– D. Fensel, Dieter F. van Harmelen. Unifying Reasoning and
Search to Web Scale, IEEE Internet Computing, 11(2), 2007
– D. Fensel, D. Wolf: The Scientific Role of Computer Science in
the 21st Century. In Proceedings of the third International
Workshop on Philosophy and Informatics (WSPI 2006),
Saarbruecken, Germany, May 3-4, 2006.
– Cathy O’Neil: “Weapons of Math Destruction” (2016):
https://www.youtube.com/watch?v=TQHs8SA1qpk

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References
• Further reading:
– D. Fensel, F. van Harmelen, B. Andersson, P. Brennan, H.
Cunningham E. Della Valle, F. Fischer, Z. Huang, A. Kiryakov
and T. Kyung-il Lee, L. School,V. Tresp, S. Wesner, M. Witbrock
and N. Zhong, Towards LarKC: a Platform for Web-scale
ReasoningIEEE Computer Society Press Los Alamitos, CA,
USA, 2008.
– F. Fischer, G. Unel, B. Bishop and D. Fensel, Towards a
scalable, pragmatic Knowledge Representation Language for the
Web, 2009.
106
References
• Wikipedia and other links:
– http://en.wikipedia.org/wiki/Web_of_Science
– http://en.wikipedia.org/wiki/Web_2.0
– http://en.wikipedia.org/wiki/Semantic_Web
– Web Science Research Initiative http://webscience.org/
– LarKC: http://larkc.sti2.at
– Linked Data Benchmark Council: http://www.ldbcouncil.org/
– https://de.wikipedia.org/wiki/Data_Science

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Next Lecture
# Title
1 Introduction
2 Web Science + Cathy O’Neil’s talk: “Weapons of Math Destruction”
3 Service Science
4 Web services
5 Web2.0 services
6 Semantic Web
7 Semantic Web Service Stack (WSMO, WSML, WSMX)
8 OWL-S and the others
9 Semantic Services as a Part of the Future Internet and Big Data Technology
10 Lightweight Annotations
11 Linked Services
12 Applications
13 Mobile Services
108
Questions?