WebTrends - Between Semantic, loss of Privacy and Personalization.

Sven.Rizzotti@useKit.com

WebTrendsWebTrends

Between Semantic loss of Privacy and Personalization.

WebTrends

Dr. Sven Rizzotti – ! University of Basel, Switzerland! useKit.com

WebTrendsWebTrends Sven.Rizzotti@useKit.com

Predictions

Popular Mechanics, forecasting the relentless march of science, 1949

"Computers in the future may weighno more than 1.5 tons."

Predictions

Thomas Watson, chairman of IBM1943

"I think there is a world market formaybe five computers."

Predictions

Ken Olson, president, chairman and founder of Digital Equipment Corp.

"There is no reason anyone wouldwant a computer in their home."

Outline• Part I

– Location-Aware Web– Mobile Web– Web of Things

• Part II– Semantic Web– Personalization– Privacy

• Practical Example: useKit

Mobile Web

Image credit: RusselBeattie.com

W3C – Mobile Web Initiative

Tim Berners-Lee, W3C

“The Mobile Web Initiative’s goal is to make browsing the Web from mobile

devices a reality”

Mobile Web

• Explosive Mobile Web Growth Worldwide– Latin America (Chile: 3200% growth in 2009)– 40% of American adults use a mobile to access the Web (2010)

RedOrbit Staff & Wire Reports

Mobile traffic expectation

0 125 250 375 500

� � �

� �

Coda Research Consultancy 2010

Peta Bytes / Month

Location based Services - (lbs)

http://www.layar.com

foursquare

http://www.foursquare.com

Location based Services - (lbs)• Mobile access demand for lbs

– Route planning– Where am I?– Where are my friends?– Point of interests

http://www.where.com

Location aware Web• Many applications use location and expose location in

the UI• Web not ready for locations yet

– Not supported in URI– Not supported in HTTP– Not supported in HTML– Mashability requires exposed application

models

Web of Things

Image credit: http://www.touchatag.com

Web of Things

Ian Rae (Twitter @irae), 6, 2008

• Frigdes, lights, toasters, washing machine• Network of internet enabled objects with web services

that interact with them• Technologies: RFID (radio frequency identification),

sensors, smartphones, gps

Pachube

http://www.pachube.com

Web of Things

Dries Buytaert

“If the graph of people is cool, imagine a graph of everything”

Semantic Web

http://www.freewebs.com

Web of Things

Rachel Lovinger

There’s no Semantic WebWithout Content and Data

Semantics• Machines are good at complex things where people

arenʼt– Computing, recalling long numbers– Compare large data sets– Search through massive amount of data records

Semantics• People are good at complex things where machines

arenʼt– Equivalence ! 14:00h / 4 pm– Inexactness! 14:00h / 4.23 pm– Splitting things! 14:01:20 / 140120

Semantics Basics for machines• Identity

– Uniqueness

• Definition• Structure

Semantics Basics for machines• Identity• Definition

– Ontology

• Structure

Semantics Basics for machines• Identity• Definition• Structure

– Web Standards (Dublin, RDF, OWL, SKOS)– Non standards (Microformats, Folksonomy)

Semantic Web – More relevant information

• Documents with computer-processable meaning

• Mass of unstructured data ➜ semantic information?– RDF (Resource Description Framework)– OWL (Web Ontology Languages)– Microformats (hCard, hCalendar)

Linked data

Richard Cyganiak and Anja Jentzsch

Linked data

• One Page Concept– URL == ID– Contains related IDʼs– Search optimized

http://en.wikipedia.org/wiki/Linked_data

Personalization• Semantic + Personalization = Relevant information

Image credit: http://puttingdotsonpaper.com

Personalization• Semantic + Personalization = Relevant information• Meeting the customer's needs more effectively and

efficiently ➜ increase satisfaction• Web Personalization: A site just for you• Real benefit: The Aha effect

Personalization• Learns what you like from your actions

(you are what you click on and what you buy)• Personalization is about data

WebTrendsWebTrends

Personalization• Collaborative filter• User profile• Data analysis tools

How to gather user data?• Forms• Web usage mining (click analysis)• Cookies• Rating• Collaborative filters

Collaborative filters• Choice of content based on like-minded people• Guessing based on previous actions• Recommendations based on profile

Privacy is …Privacy is not simply an absence of information about us in the minds of others; rather it is the control we have over information about ourselves.

Charles Fried

Image credit: http://www.arcotrasporti.it/

Privacy is not dead• … but misunderstood• Privacy: Control of how information flows• Example: Google Buzz

– opting in vs. opting out

• Example: Chatrooms– The A/S/L question

danah boyd, SXSW2010

Social networks• Personal

– Private (ex. Address book)– Public (ex. Facebook)

• Behavioral– People involved in regular communication

Private and public information• Publicly accessible ≠ Public content • Contextual integrity• Private and public is not as black and white

Helen Nissenbaum, PRIVACY AS CONTEXTUAL INTEGRITY, 2004

Privacy – Changing the rules• The default is “everybody”• Publicly available ≠ being publicized

Privacy in details• PII / PEI

– Personally Identifiable Information– Personally Embarrassing Information

Privacy and Publicity Mashup• ChatRoulette

– Entertain and be entertained– Sense of anonymity

• Blippy• Jigsaw

Privacy• "Missed the bus again."• "Attempting to figure out why the cat is hiding."• "I'm signing off."• "On bus going in to the office."• "Scanning pictures of 12-year old girls in mini skirts..."• "Going to bed now."• "Thinking about eating."• "About to start a conference call."• "I'm watching my dog chase the reflection from his tags and wish I had a laser

pointer!"• "Feeling so bored at work I'm going to die. Wonder if it is my attitude or the work."• "Washing hair. Fetching groceries."

The Twitter Curve

http://headrush.typepad.com

Subversives• Finding “Subversives” [Tom Owad]• Amazon: Wish lists of 100ʼ000 of people• Yahoo people search: name, city, state• Google maps:

http://www.applefritter.com/bannedbooks

Subversives

Past Developments• Web 2.0• Blogging and micro-blogging• Social networks• Web services

Web 2.0• Marketing term• 1999 [Darcy DiNucc], 2004 [John Battelle, Tim O'Reilly]

Web 2.0

Tim Berners-Lee, W3C

“If Web 2.0 for you is blogs and wikis,then that is people to people.

But that was what the Webwas supposed to be all along.”

WebTrendsWebTrends

commons.wikimedia.org

WebTrendsWebTrends

geek and poke

Web Sites as Web Services• From unstructured to structured information

ProgramableWeb

• Open data is a competitive advantage

Business Data

Web Sites as Web Services

Web Site

Customers

• Open data is a competitive advantage

Business Data

Web Sites as Web Services

Customers Additional Businesses

Mashups

Web Site

Business Data

Web Service API

Showcase

• Little efficient helpers ➜ Increase productivity➜ Focus

• Shareability➜ Collaboration➜ Visibility

• Contextualization➜ Semantic

Where are we going?

Web 1.0 Web 2.0 Web 3.0

Read-only45 Mio users (1996)Focus: CompaniesHome PagesOwning ContentHTML, PortalsWeb formsPage views

read-write1 Bio users (2006)Focus: CommunitiesBlogsSharing ContentXML, RSSWeb AppsCost per click

Personal mobile WebIndividualFocus: LifestreamConsol. dyn. contentSemantic WebUser behaviorPlatforms

Semantic Web Future Web

Web Social Software

Where are we going?

Social Connectivity

Summary• Digital devices always connected and networked

– Car, Radio, TV, Fridge, …

• Mobile– Dominant platform to get to the net

• Privacy– Almost none, all in the same boat

• Semantic on the way– Presumably not in a top-down manner

• Information pollution and overload

WebTrends - Between Semantic, loss of Privacy and Personalization.

Technology

Transcript of WebTrends - Between Semantic, loss of Privacy and Personalization.

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