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Lessons Learned from LOD (Linked Open Data) Failure and Big Data:

The Future Trend

Youngwhan Lee, Ph. D.전화 : 010-7997-0345

이메일 : nicklee@konkuk.ac.krFacebook: Youngwhan Nick Lee

Twitter: nicklee002

Web Evolution and Big Data

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Internet Today

2010:• Estimated 1011 Web pages in the World

2012:• Social Media: Facebook (1 Billion Monthly Active Users) • 문자 발명후 2003 년까지 5 엑사 바이트 2012 년 현재 매일 7 엑사바이트 데이터

생성 중 • Is “big data” a big pile of garbage?

Web Explosion and Big Data

• Number of Web Users (Mar. 2012): 2.3 Billion• 1011 Web pages in the World (Est. 2010)

– Since the inception of Web, there were 7000 days (i.e. 20 years). This means humans create over 10 Million pages a day.

• Digital Information Created in the year 2010: 1 zetabytes (1021)- "There was 5 exabytes of information created between the dawn of civiliza-

tion through 2003, but that much information is now created every 2 days, and the pace is increasing.“ –Eric Schmitt (2010)

- 2012, almost 7 exabytes are created everyday. - We call it “Big Data.”

• What does this mean?

Modified, based on Gene Bellinger, Durval Castro, Anthony Mills http://www.systems-thinking.org/dikw/dikw.htm , http://yjhyjh.egloos. -com/39721

R-DBMS

NoSQL

데이터분석

MapRe-duce

LOD

큐레이션 SPARQL

RDF

지식구조화

OWL

RIF

Aggregation

Understand-ing

빅데이터 / 웹에서의 정보 / 지식 추출• 정보 검색

– SEO(Search Engine Optimization) PageRank, EdgeRank

• Data Mining: 프로그램에 의한 정보 ( 지식 ) 추출 가능– 통계분석 , Rule-based Analysis, 신경망 분석– Visualization

• 지식공학 이용– RDF/OWL 사용한 온톨로지 누적 연결– Raw Data 연결하고 분석 가능하도록 개방 (Linked Open Data; LOD)– 프로그램에 의한 논리분석 가능한 지식 추출 가능

• SPARQL• RIF(Rule-based Interface Framework)

• 인간의 힘 이용 : 큐레이션– 인간의 눈과 지식을 이용하여 정보를 필터하고 종합

• 예 : pinterest.com, videocooki.com, storify.com, scoop.it, curated.by

데이터사이언스

지식공학

Pareto’s Law

Bighead

Longtail

Longtail Phenomena in

Bighead Applications

Longtail Applications

Popu

larit

y

The Long Tail by Chris Anderson (Wired, Oct. ´04) adopted to in-formation domains

… …

…

…

Mobile Apps iPhone Apps Android Apps

SNS Apps Facebook Apps Twitter Apps

LOD and Others Medical Apps 공공 정보 활용 Apps …

지식공학에서의 접근

• 온톨로지 구축– Cyc– WolframAlpha– Siri

• 데이터의 웹 (Web of Data)– LOD LOD2

Old “Layercake” of Semantic Web

정보 교환

RDF

OWL2

OWL2

Linking Open Data (LOD) is to connect and to open data to public

1. Use URIs as names for things2. Use HTTP URIs 3. When someone looks up a URI, provide useful information4. Include links to other URIs

4 Principlesof LOD

Linked Open Data (LOD) Principles

A little history of LOD Project Tim Berners-Lee proposed LOD(Linking Open Data) project (2006) Since the proposal, numerous countries and organizations participated,

caused LOD to explode in terms of the number of data Wikipedia DBpedia (www.dbpedia.org) Bio2RDF project opened in 27 fields of Biology, Genetics, Medical-re-

lated, of which the data sets are about 2.3 billions (Bio2RDF.org) (2008.10)

BBC announced to participate LOD project (www.bbc.org), now one of the institutes actively utilizing the data

US Data.gov released 5 billion data triples US Library of Congress announced to join LOD project. (http://

id.loc.gov/authorities/sh85042531#concept) NY Times ( data.nytimes.com) release their data of 150 years of publica-

tion (2009.10) US Whitehouse release a plan to open data in RDF (2009.11)

Advantages of LOD

• Elegant• Expandable• Flexible• Powerful• Decentralized• Participatory• Inclusive, and• “Free” to use

Linked Open Data (LOD) Principles

Change of Web Structure

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인간을 위한웹 페이지 연결 웹페이지 연결 버스

유저 인터페이스

웹데이터 연결 버스

매쉬업 매쉬업

인간을 위한웹 페이지 연결

컴퓨터를 위한웹 데이터 연결

웹페이지 연결 버스

유저 인터페이스

May, 2007Mar., 2008

Sep., 2008

July, 2009

SPARQL

SPARQL (Simple Protocol and RDF Query Lan-guage)

Technical Proposal Phase Practical Use Phase

Web 3.0: Merging the two Perspectives

Market Be-havior

Perspective

Technology Innovation

Perspective

WWW Propoal (1989)

Semantic Web LOD Proposal (2006)

WEB 1.0 WEB 2.0

Data-based Semantics

Knowledge-based Semantics

“GGG” Proposal (2007)

Next Generation Web

“WEB2” Proposal (2009)

Web 3.0

But no Champaign…

• Definition Unclear– Berners-Lee’s 4 principles are ambiguous

• Interpretation difficult• Inconsistent• Difficult both to learn and use• Difficult to build browsers and reasoners

• “Free” to use

Full of incomplete and inconsistent RDFs, no way to make them evolveIn short, “Garbage in, Garbage out” expe-rienced

Solution to LOD problems: LOD2

• LOD2 Stack: A Technical Approach– Linked Data Management– Enrichment and Quality Improvement– Various Tools to use

• Storage and Querying• Revision and authoring• Interlinking and fusing• Classification and enrichment• …

Q: Is this technical approach for LOD good enough?

A: Business ap-proach is definitely

needed.

Big Data

What did we do with big data in 2013?

What would we do with big data in 2014?

End of Theory

“ 이론의 종말” by Chris Anderson

빅데이터와 데이터 지상주의

Implication

• Issue: Have and Have-not are separated–E. g. in marketing

• 4Ps– Price, product, place, promotion

• STP– Segmentation, targeting, and positioning

Implication

• Is Technical Approach needed?

Business Approach

• Data Markets– Azure Data Marketplace– Data.com– Infochimps.com– DataMarket.com– Kaggle.com

Data Market: Azure Data Mar-ketplace

Data Market: Data.com

Data Market: Infochimps.com

Data Market: DataMarket.com

Data Market: Kaggle.com

Conclusion

• Positioning for Korea,– Where are we?– Where are we heading to?

참고문헌

• 웹 3.0 세상을 바꾸고 있다 .– 이영환

• A Semantic Web Primer (Cooperative Information Systems se-ries) – Grigoris Antoniou, Frank van Harmelen

• Semantic Web for the Working Ontologist, Second Edition: Effec-tive Modeling in RDFS and OWL– Dean Allemang, James Hendler

• 온톨로지 : 인터넷 진화의 열쇠– 노상규 , 박진수

• 월드와이드웹– 팀 버너스 - 리

• 큐레이션– 스티븐 로젠바움 저 , 이시은 역

Web sites

• Problems of Linked Data– http://milicicvuk.com/blog/2011/07/26/problems-of-linked-data-

14-identity/

• LOD2– http://lod2.eu/Welcome.html– http://stack.lod2.eu/blog/

• How to Define Web 3.0 – http://howtosplitanatom.com/news/how-to-define-web-30-2/

• SPARQL by Example– http://www.cambridgesemantics.com/semantic-university/spar

ql-by-example#(1)

• Practical P-P-P-Problems with Linked Data– http://www.mkbergman.com/917/practical-p-p-p-problems-with

-linked-data/

• Linked-Data-Api– https://code.google.com/p/linked-data-api/