Database Interoperability Through State Based Logical Data Independence

Computer supported cooperative work (CSCW) involving business-to-business transactions depends more and more upon database interoperability. The design of interbusiness CSCW when the businesses are already operating independent systems depends either upon effective reverse engineering (to properly discover the semantics underlying each organisation's systems and through that to develop appropriate matches for interbusiness software), or upon sufficiently rich semantic models and good database management system support for logical data independence (to allow database updating through a logical view). This paper takes the second approach, presenting a rich semantic data model that the authors have been developing and have used successfully in a number of major consultancies, and a new approach to logical data independence and view up datability based on that model. We show how these approaches support database interoperability for business-to-business transactions and, for CSCW within an organisation, how they support federated databases.

[1]  Joseph A. Goguen,et al.  Initial Algebra Semantics and Continuous Algebras , 1977, J. ACM.

[2]  Jeffrey D. Ullman,et al.  Principles of database and knowledge-base systems, Vol. I , 1988 .

[3]  S. Lane Categories for the Working Mathematician , 1971 .

[4]  Michael Johnson,et al.  On the Value of Commutative Diagrams in Information Modelling , 1993, AMAST.

[5]  C. J. Date An Introduction to Database Systems , 1975 .

[6]  David W. Shipman,et al.  The functional data model and the data languages DAPLEX , 1981, TODS.

[7]  David W. Shipman The functional data model and the data language DAPLEX , 1979, SIGMOD '79.

[8]  John Mylopoulos On knowledge base management systems , 1986 .

[9]  Michael Johnson,et al.  View updates in a semantic data modelling paradigm , 2001, Proceedings 12th Australasian Database Conference. ADC 2001.

[10]  ChenPeter Pin-Shan The entity-relationship modeltoward a unified view of data , 1976 .

[11]  Frank Piessens,et al.  Selective Attribute Elimination for Categorial Data Specifications , 1997, AMAST.

[12]  Michael Barr,et al.  Category theory for computing science (2. ed.) , 1995, Prentice Hall international series in computer science.

[13]  John Mylopoulos Next generation database systems won't work without semantics! (panel) , 1998, SIGMOD '98.

[14]  Giuseppe Longo,et al.  Categories, types and structures - an introduction to category theory for the working computer scientist , 1991, Foundations of computing.

[15]  Chris Sauer,et al.  Lessons from a failed information systems initiative: issues for complex organisations , 1999, Int. J. Medical Informatics.

[16]  Christopher N. G. Dampney,et al.  An illustrated mathematical foundation for ERA , 1992 .

[17]  Michael L. Brodie On knowledge base management systems: integrating artificial intelligence and database technologies , 2011, Topics in information systems.

[18]  R. F. C. Walters,et al.  Categories and computer science , 1992, Cambridge computer science texts.

[19]  Dana S. Scott,et al.  Some Domain Theory and Denotational Semantics in Coq , 2009, TPHOLs.

[20]  Ivar Jacobson,et al.  The unified modeling language reference manual , 2010 .

[21]  Zinovy Diskin,et al.  Algebraic Graph-Based Approach to Management of Multidatabase Systems , 1995, NGITS.

[22]  Peter P. Chen The entity-relationship model: toward a unified view of data , 1975, VLDB '75.

[23]  Frank Piessens,et al.  Categorical data-specifications , 1995 .

[24]  Michael Barr,et al.  Category theory for computing science , 1995, Prentice Hall International Series in Computer Science.

[25]  E. F. Codd,et al.  A relational model of data for large shared data banks , 1970, CACM.

[26]  Jeffrey D. Ullman,et al.  Principles Of Database And Knowledge-Base Systems , 1979 .