Prism: a knowledge based system for semantic integrity specification and enforcement in database systems

This paper presents a knowledge-based approach to the specification, design, implementation, and evolution of database applications The knowledge base consists of 1) facts regarding database objects that are organized into a hierarchy of models, and 2) rules that specify the behavior of objects within a model and among modelsThe model hierarchy consists of database application data, database schemas, data model definitions, and system-related objects that control the user's interaction with the system The rules governing the behavior of objects are specified as explicit constraints on those objects User goals are transformed into conjectures that the inference engine must prove are satisfiable by interpreting all applicable constraintsThe semantic architecture of the PRISM system is described, together with the syntax and semantics of the constraint language PRISM is implemented in the C programming language and runs under the UNIX ** operating system

[1]  Nancy Gail Leveson.  Applying behavioral abstraction to information system design and integrity , 1980 .

[2]  Alexander Borgida,et al.  Data and activities: Exploiting hierarchies of classes , 1981 .

[3]  E. F. Codd,et al.  Extending the database relational model to capture more meaning , 1979, ACM Trans. Database Syst..

[4]  Diane C. P. Smith,et al.  Database abstractions: aggregation and generalization , 1977, TODS.

[5]  Carlo Zaniolo,et al.  On the design of relational database schemata , 1981, TODS.

[6]  Michael Stonebraker,et al.  The design and implementation of INGRES , 1976, TODS.

[7]  Lawrence Robinson,et al.  SPECIAL - A Specification and Assertion Language. , 1976 .

[8]  John Mylopoulos,et al.  A language facility for designing database-intensive applications , 1980, TODS.

[9]  Robert A. Kowalski,et al.  Logic and semantic networks , 1979, CACM.

[10]  L. Peter Deutsch.  Constraints: A uniform model for data and control , 1981, SIGMOD 1981.

[11]  Michael L. Brodie.  Research issues in database specification , 1983, SGMD.

[12]  Randall Davis.  Content Reference: Reasoning about Rules , 1980, Artif. Intell..

[13]  Gary G. Hendrix,et al.  Encoding Knowledge in Partitioned Networks , 1979 .

[14]  Ronald Fagin,et al.  An Equivalence Between Relational Database Dependencies and a Fragment of Propositional Logic , 1981, JACM.

[15]  Carl Hewitt,et al.  PLANNER: A Language for Proving Theorems in Robots , 1969, IJCAI.

[16]  H. Levesque,et al.  A PROCEDURAL SEMANTICS FOR SEMANTIC NETWORKS , 1979 .

[17]  Lenhart K. Schubert.  Extending The Expressive Power Of Semantic Networks , 1976, IJCAI.

[18]  Dennis McLeod,et al.  A framework for data base semantic integrity , 1976, ICSE '76.

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

[20]  Raymond Reiter.  On the Integrity of Typed First Order Data Bases , 1979, Advances in Data Base Theory.

[21]  Nicholas V. Findler,et al.  Associative Networks- Representation and Use of Knowledge by Computers , 1980, CL.

[22]  Robert Balzer.  Dynamic system specification , 1981 .

[23]  Michael Lawrence Brodie.  Specification and verification of data base semantic integrity. , 1978 .

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

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

[26]  Larry Kerschberg,et al.  Data architecture and data model considerations , 1899, AFIPS '77.