1. Peter P. ChenInformation Modeling Past, Present, Future of Data/Information Modeling Foster Distinguished Chair Professor Computer Science Dept. Louisiana State University Baton Rouge, LA 70803, USA pchen@lsu.edu http://www.csc.lsu.edu/~chen

2. Peter P. ChenInformation Modeling 2 Overview Historical Background – How Entity-Relationship Model (ERM) was Developed Last Twenty-Five Years – ER Conferences, IDEF, ANSI/IRDS, CASE Methodologies/tools The Present – OO, Data Mining, UML The Future – Discovering „Links/Relationships“ – Validity/Credibility of Data, Machine Learning/Reasoning – Natural Languages and Data/Information Modeling – Modeling for XML/Semantic Web Conclusions

3. Peter P. ChenInformation Modeling 3 The Needs of the DB Community in the Early 70‘s For Software/Hardware Vendors – Integration of Various File and DB Formats – Incorporating More „Data Semantics“ For User Organizations – A Unified Methodology for File and DB design for Various File and DBMS‘s – Incorporating More Business Rules

4. Peter P. ChenInformation Modeling 4 How the ERM was Developed -- Right Place at the Right Time (I)? I Got Ph.D. From Harvard in 1973 – Thesis Title: Optimal File Allocation Worked for Honeywell from 73 to 74 – In a 10-person Architecture Team for Next Generation Distributed System – Many Team Members Were DB Experts & 20 Years Older: – Charles Bachman, Henry Leftkovitz, John Lyon

5. Peter P. ChenInformation Modeling 5 Right Place at the Right Time (II)? Joined MIT Management School Faculty in 74 – Interacted with User Organizations – They wanted a unified modeling and design methodology – Completed the ERM Paper – Most other faculty members were busy implementing DBMS prototypes

6. Peter P. ChenInformation Modeling 6 Concepts of Entity and Relationship Figure 2

7. Peter P. ChenInformation Modeling 7 An Example of ER Diagram Figure 2

8. Peter P. ChenInformation Modeling 8 Theoretical Foundations of ER Model Set Theory Modern Algebra Logic Lattice Theory

9. Peter P. ChenInformation Modeling 9 Defining ER Concepts using Set Figure 2

10. Peter P. ChenInformation Modeling 10 Relationship as an Ordered Tuple Figure 2

11. Peter P. ChenInformation Modeling 11 First ER Paper & Initial Reactions (I) Published in ACM Transactions on DBMS, Vol. 1, No.1, pp. 9-36, March 76

12. Peter P. ChenInformation Modeling 12 First ER Paper & Initial Reactions (II) The Situation then – Most People were in Religious War – I was a „New Kid on the Block“ The Advices I got: – Dropped the ER Model – Joined one of the Religious Camps

13. Peter P. ChenInformation Modeling 13 The First Five Years (I) Persistence with the ER Model – Continue to Write Papers on ERM – Organized First ER Conference in 1979 at UCLA – 2nd ER Conference Two Years Later – Now, an Annual Conference – November 2001 in Japan – 2002 in Finland – 2003 in Chicago – 2004 in Shanghai, China

14. Peter P. ChenInformation Modeling 14 The First Five Years (II) Some Academic People Started to Develop Semantics-Richer Data Models – Mike Hammer of EECS, MIT, now a guru in „reverse-engineering“ US-AF ICAM/IDEF Project – Served as a consultant – The ERM Became the Basis of IDEF More Companies Started to Experiment ERM

15. Peter P. ChenInformation Modeling 15 Related Developments in Next 20 Years Codd‘s RM/T Model added ER Concepts Bachman‘s Partnership Model, too. ANSI/IRDS Standard of Information Resource Directory Systems (IRDS) – Adopted ERM CASE (Computer-Aided Software Engineering) – First Major CASE Symposium in Atlanta, 1987, Keynote speaker – IBM AD Cycle – Based on ERM – IBM DB2 Repository Mgr – ERM – Oracle Desinger/200 -- ERM

16. Peter P. ChenInformation Modeling 16 The Present Status of Data/Information Modeling (I) ER Modeling is the „most widely used methodology“ in the business DB application development world – more than 85% of the FORTUNE 3,000 companies and major organizations are using it More advanced ER concepts are proposed and used UML, which is a specific language syntax, reinforces the ER concepts

17. Peter P. ChenInformation Modeling 17 The Present Status of Information Modeling (II) OO Modeling incorporates many concepts of ERM – Object is an implementation concept – Current OO methodologies deed more general concepts of relationship What is „Data Mining“? – Discover hidden „relationships“, Discover the embedded ER Models

18. Peter P. ChenInformation Modeling 18 Future (I) Discovering Links/Relationships from Data in Various Sources (such as DARPA‘s EELD Program) Validity/Credibility Analysis and Integration of Data; Machine Learning/Reasoning Natural Languages vs. Data/Info Modeling. ER Modeling Concepts are Similar to – Chinese Character Composition Methods – Ancient Egyptian Hieroglyph – English Sentence Grammar Structure

19. Peter P. ChenInformation Modeling 19 The Future (II) ERM and the Fundamental Principles of Systems Architecture ER Model is closely related to – XML – Semantic Web

20. Peter P. ChenInformation Modeling 20 Information Validity/Credibility Analysis A Paper was published in InfoFusion 2001, Montreal Algorithm was developed Prototype developed Also, developed machine learning algorithm

21. Peter P. ChenInformation Modeling 21 ER Modeling & English  First presented the ideas (abstract of a paper) in 2nd ER Conference in Washington, D.C. 1981  Paper was published in Information Sciences, 1983  Adopted as a standard systems analysis technique by some large consulting firms  Recently, OO Analysis re-discovered some of the basic concepts  Also, the research community started to use, modify, or extend the concepts

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25. Peter P. ChenInformation Modeling 25 Chinese Characters as Models of Real World Entities Figure 2

26. Peter P. ChenInformation Modeling 26 Ancient Egyptian Hieroglyph Figure 2

27. Peter P. ChenInformation Modeling 27 Various Components of XML XML has many components: – XML (language part) – XSL – DOM – DTD – XLink and XPointer – RDF – XML Schema – etc. Not all are compatible with each other

28. Peter P. ChenInformation Modeling 28 What is RDF? Acronym for “Resource Description Framework” As a way to specify metadata Two parts: – Model and Syntax – Schema The “RDF Schema” is not a W3C recommended specification, yet http://www.w3.org/TR/REC-rdf-syntax

29. Peter P. ChenInformation Modeling 29 W3C Pays Attention to ERM The Cambridge Communiqué ( http://www.w3.org/TR/schema-arch) states: – RDF can be viewed as a member of the Entity-Relationship Model Family In several articles, Tim Berners- Lee discusses the similarity and differences between ERM and RDF.

30. Peter P. ChenInformation Modeling 30 RDF vs. ER Model RDF can be viewed as a version of binary ER model ( but at a lower and more detailed level ) RDF’s dependence on sentence analysis is similar to a series of work done in the correspondence between the ER model and English (and several other natural languages). – Reference: Chen, P.P., “Entity-Relationship Diagram and English Sentence Structure,” Information Science, 1983, Academic Press. – Major concepts: – Noun --> Entity, Verb --> Relationship – Adjective --> Attribute of Entity, Adverb --> Attribute of Relationship – Gerund --> Relationship-converted Entity – Etc.

31. Peter P. ChenInformation Modeling 31 Real World Modeling & Fundamental Principles of Systems Architecture Entity Lattice and Other Mathematical Structures and Operations Fundamental Principles of Systems Architecture – Starting from Info System Architecture, and then extends to all kinds of systems – Fundamental Questions on – Representation/Understanding – Operations – Costs/Benefits/Optimization

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33. Peter P. ChenInformation Modeling 33 Conclusions (I) ER Modeling was triggered by the needs – Unifying data views from top-down and bottom-up perspectives – For vendors & user organizations – Incorporating more sematics Entity and relationship are fundamental concepts for – Data/Knowledge Representation – Database design – Software engineering – Information system development – And others (data mining,...)

34. Peter P. ChenInformation Modeling 34 Conclusions (II) Future: – Discovering Missing/Intended/Un-intended Relationship from data – Prediction of the Validity of data and data model; Machine Learning/Reasonsing – Natual Languages and ERM – Multi-language Information Extraction and Understanding – Culture-based Modeling Methodology – Modeling & Design of Web  Theory of Web, Semantic Web – Fundamental Principles of Systems Architecture

35. Peter P. ChenInformation Modeling 35 References ER and other Conferences – ER2002 (Finland), ER2003 (Chicago), ER2004 (Shanghai) – http://www.conceptualmodeling.org Chen’s papers online: – http://www.csc.lsu.edu/~chen XML Schema: – Primer: http://www.w3c.org/TR/xmlschema-0/ – Structure: http://www.w3c.org/TR/xmlschema-1/ – Data Types: http://www.w3c.org/TR/xmlschema-2/ XML XLink & XPointer: – http://www.w3c.org/XML/Linking RDF – http://www.w3c.org/RDF/