Lecture 4: Handling Heterogeneity with Information Resource Dictionary Systems

1. Lecture 4: Handling Heterogeneity with Information Resource Dictionary Systems Nick Rossiter, Computing Science, Newcastle University, England B.N.Rossiter@newcastle.ac.uk http://www.cs.ncl.ac.uk/people/b.n.rossiter/

2. Introduction • Looking at multi-level architecture for information systems • Need to handle higher levels than intension • Take object work two levels higher • Example with dates • Composition of functors and natural transformations

3. Approach • Principles of Information Resource Dictionary System (IRDS) • Benefits in General • Assistance for Cross-Platform Operation • Search for Sound Theoretical Basis

4. IRDS/Reference Model • Based on ISO/IEC Standards • 10027 1990 Information Res. Dict. Sys. (IRDS) • 10032 1993 Reference Model • 10728 1993 IRDS - System Interfaces; • 9075 1992 SQL

5. Extract IRDS Standard Framework

6. Outline IRDS • Introduces concept of meta-meta data • Four-level approach

7. Example of Dates • IRDDS concepts is some measure of time • IRDD is constructs available -- light years, years since various events, months, days, carbon dates, etc • IRD is formats available -- yyyy, mm/dd/yyyy, dd/mm/yyyy, etc • APP is values -- 195, 05/30/1967, 30/05/1967

8. Relating Extension to Intension levelexample • Application data Supplier(1,’Smith’) extension -direct addressing • Schema data Supplier (supp_no, name) intension - addressing by name level pair:

9. Relating Intension to Constructs • Schema data Supplier (supp_no, name) intension - addressing by name • Meta data Table(supplier) data dictionary - addressing by concepts, constructs.

10. Relating Constructs to Abstractions • Meta data Table(Supplier) data dictionary - addressing by concepts, constructs. • Meta meta data Aggregation(Table) real-world abstractions - addressing by abstractions

11. Level-pairs are the Critical Dictionary Entries • Meta is: mapping from schema names (intension) to constructs available as 2-tuple: <intension_entry, construction> e.g. <student<id,name>, table> • MetaMeta is: mapping from construct available to abstraction as 2-tuple: <construction, abstraction> e.g. <table, aggregation>

12. Examples of Levels and Level-pairs: Intension/Extension • Extension (APP): Student<1234, ‘John James’, ‘15 Montford Road’> • Intension (IRD): Student<id, name, address> • APP IRD by: Name: Student<1234, ‘John James’, ‘15 Montford Road’> Student<id, name, address>

13. Examples of Levels and Level-pairs: Constructs/Intension • Intension (IRD): Student<id, name, address> • Constructs (IRDD): Table • IRD IRDD by Meta: Student<id, name, address> Table

14. Examples of Levels and Level-pairs: Abstractions/Constructs • Constructs (IRDD): Table • Abstractions (IRDDS): Aggregation • IRDD IRDDS by MetaMeta: Table Aggregation

15. Interpretation of IRDS in Schematic form • concepts mission • MetaMeta Policy • constructs management • Meta Organize • intension enterprise • Name Data • extension information Information Resource Dictionary Definition Schema (IRDDS) Information Resource Dictionary Definition (IRDD) Information Resource Dictionary (IRD) Information Resource Data (APP)

16. Overall Mappings • Can write: System = MetaMeta o Meta o Name (APP) to represent composition. • System(APP) = IRDDS • Also the dual: Model = Data o Organize o Policy

17. IRDS Enables Heterogeneous Systems to be Related • Only one IRDDS in principle but extensible IRDDS covers all paradigms • For relational database, can use mapping: System : APP IRDDS • Comparison of System for each paradigm enables in principle: • completely different approaches to be related • heterogeneous systems to be run in integrated fashion

18. Formalization of IRDS Approach • Quality enhanced by formalization • Can know more confidently the limits and behaviour of a system • Which formalism is best-suited?

19. Category Theory? • Need relations to represent level-pairs • Multi-level construction (higher-order) • Category theory seems appropriate: - categories for basic structures - functors relate categories - natural transformations relate functors

20. IRDS Levels in Functorial Terms MetaMeta • IRDDSIRDD SystemPolicy Model Meta Data Organize • APPIRD Name

21. Dates Revisited Concept (IRDDS) date Policy MetaMeta Constructs (IRDD) giga years days,months,years (years days, months, years (years AD) Muslim) Organize Universe American Euroopean Muslim Meta Format (IRD) g.f x 109 mm/dd/yyyy dd/mm/yyyy dd/mm/yyyy Data Name Values 4.2 05/19/2000 19/05/2000 14/03/1350 (APP)

22. Connections between levels are Adjunctions • For two categories A and B, an adjunction between them involves two functors: • a free functor F: A B adding structure to A • an underlying functor G: B A forgetting structure in B • Organize: IRDD IRD and • Meta: IRD IRDD are a pair of adjunctions

23. Date Comparison as Natural Transformation • Take composition of adjuntions: Model_US: date 05/19/00 Model_Eur: date 19/05/00 Then have natural transformation: Amer_Eur_Date_Compare: Model_US Model_Eur

24. Further Reading • Information technology - Information Resource Dictionary System (IRDS) framework, Standard ISO/IEC 10027 (1990); 10728 (1993). • Constructing Standards for Cross-Platform Operation, Heather, M A, & Rossiter, B N, Constructing Standards for Cross-Platform Operation, Software Quality Management VI, British Computer Society, Amsterdam, April 1998, 218-229 (1998).

25. Concluding Remarks • Lecture 1 -- Interoperability -- showed problems of handling heterogeneous data • Lecture 2 -- Introduction to Category Theory -- described categories as a basis for thinking about information systems • Lecture 3 -- Objects as Categories -- described how the intension/extension could be represented by categories, functors and natural transformations

26. Finale • Lecture 4 -- IRDS -- showed how all four levels of an information system can be described formally with categories, perhaps giving a better understanding of problems.