I discuss the failure of LOD and the reasons. From the lessons learned, LOD2 got launched four plus (4+) years ago and is about to the completed. What can you say about the future trend of Big Data from the lessons?

1. 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.kr
Facebook: Youngwhan Nick Lee
Twitter: nicklee002
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2. Web Evolution and Big Data

3. Internet Today
2010:
• Estimated 1011 Web pages in the World
2012:
•
•
•
Social Media: Facebook (1 Billion Monthly Active Users)
문자 발명후 2003년까지 5 엑사 바이트  2012년 현재 매일 7 엑사바이트 데이터 생성 중
Is “big data” a big pile of garbage?
1-3

4. 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 civilization 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?

6. Aggregation
데이터분석
지식구조화
큐레이션
RIF
SPARQ
L
OWL
RDF
LOD
NoSQL
MapReduce
R-DBMS
Understanding
Modified, based on Gene Bellinger, Durval Castro, Anthony Mills http://www.systems-thinking.org/dikw/dikw.htm , http://yjhyjh.egloos.com/39721

7. 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
데이터사이언스
• 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)
지식공학
• 인간의 힘 이용: 큐레이션
– 인간의 눈과 지식을 이용하여 정보를 필터하고 종합
• 예: pinterest.com, videocooki.com, storify.com, scoop.it, curated.by

8. Pareto’s Law
Longtail
Bighead

9. Longtail Phenomena in
The Long Tail by Chris Anderson (Wired, Oct. ´04) adopted to
information domains
Longtail Applications
Popularity
Mobile Apps

iPhone Apps

Android Apps
SNS Apps

Facebook Apps

Twitter Apps
LOD and Others

Medical Apps

공공 정보 활용 Apps

…
…
…
Bighead Applications
…
…

10. 지식공학에서의 접근
• 온톨로지 구축
– Cyc
– WolframAlpha
– Siri
• 데이터의 웹(Web of Data)
– LOD  LOD2

11. Old “Layercake” of Semantic Web
정보 교환

12. RDF

13. OWL2

14. OWL2

15. Linked Open Data (LOD) Principles
Linking Open Data (LOD) is to connect and to open data to public

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-related, 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 publication (2009.10)

US Whitehouse release a plan to open data in RDF (2009.11)
4 Principles
of LOD
1.
2.
3.
4.
Use URIs as names for things
Use HTTP URIs
When someone looks up a URI, provide useful information
Include links to other URIs

16. Advantages of LOD
•
•
•
•
•
•
•
•
Elegant
Expandable
Flexible
Powerful
Decentralized
Participatory
Inclusive, and
“Free” to use

17. Linked Open Data (LOD) Principles

18. Change of Web Structure
유저 인터페이스
인간을 위한
웹 페이지 연결
웹페이지 연결 버스
유저 인터페이스
인간을 위한
웹 페이지 연결
웹페이지 연결 버스
매쉬업
매쉬업
컴퓨터를 위한
웹 데이터 연결
웹데이터 연결 버스
18

19. Mar., 2008
May, 2007
Sep., 2008
July, 2009

21. SPARQL

22. SPARQL (Simple Protocol and RDF Query Language)

24. Web 3.0: Merging the two Perspectives
WWW Propoal
(1989)
Semantic
Web
Technology
Innovation
Perspective
LOD Proposal (2006)
“GGG” Proposal (2007)
Knowledge-based Semantics
Next Generation Web
Data-based Semantics
Market
Behavior
Perspective
WEB 1.0
WEB 2.0
Web 3.0
“WEB2” Proposal (2009)
Technical Proposal Phase
Practical Use Phase

25. 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 evolve
In short, “Garbage in, Garbage out” experienced

26. 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
…

27. Q: Is this technical approach for LOD good enough?
A: Business approach is
definitely needed.

28. Big Data
What did we do with big data in 2013?
What would we do with big data in 2014?

29. 빅데이터와 데이터 지상주의
End of Theory
“이론의 종말” by Chris Anderson

30. Implication
• Issue: Have and Have-not are
separated
– E. g. in marketing
• 4Ps
– Price, product, place, promotion
• STP
– Segmentation, targeting, and positioning

31. Implication
• Is Technical Approach needed?

32. Business Approach
• Data Markets
– Azure Data Marketplace
– Data.com
– Infochimps.com
– DataMarket.com
– Kaggle.com

33. Data Market: Azure Data Marketplace

34. Data Market: Data.com

35. Data Market: Infochimps.com

36. Data Market: DataMarket.com

37. Data Market: Kaggle.com

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

39. 참고문헌
• 웹3.0 세상을 바꾸고 있다.
– 이영환
• A Semantic Web Primer (Cooperative Information Systems series)
– Grigoris Antoniou, Frank van Harmelen
• Semantic Web for the Working Ontologist, Second Edition: Effective
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

40. Web sites
• Problems of Linked Data
– http://milicicvuk.com/blog/2011/07/26/problems-of-linked-data14-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/sparqlby-example#(1)
• Practical P-P-P-Problems with Linked Data
– http://www.mkbergman.com/917/practical-p-p-p-problems-withlinked-data/
• Linked-Data-Api
– https://code.google.com/p/linked-data-api/