Inference: a somewhat skewed survey
On knowledge base management systems: integrating artificial intelligence and d atabase technologies
Computer
Implementation of a compiler for a semantic data model: Experiences with taxis
SIGMOD '87 Proceedings of the 1987 ACM SIGMOD international conference on Management of data
Types and persistence in database programming languages
ACM Computing Surveys (CSUR)
Rule management and evaluation: an active DBMS perspective
ACM SIGMOD Record
PARDES: a data-driven oriented active database model
ACM SIGMOD Record
Representation of highly-complex knowledge in a database
Journal of Intelligent Information Systems - Special issue on next generation information technologies
Active interdatabase dependencies
Information Sciences: an International Journal
CACTIS: a database system for specifying functionally-defined data
OODS '86 Proceedings on the 1986 international workshop on Object-oriented database systems
Implementation of logiclal query languages for databases (abstract only)
SIGMOD '85 Proceedings of the 1985 ACM SIGMOD international conference on Management of data
Constraint Equations: Declarative Expression of Constraints With Automatic Enforcement
VLDB '84 Proceedings of the 10th International Conference on Very Large Data Bases
A Multiagent Update Process in a Database with Temporal Data Dependencies and Schema Versioning
IEEE Transactions on Knowledge and Data Engineering
A relational database model of program execution and software components
ACM-SE 38 Proceedings of the 38th annual on Southeast regional conference
Active database systems for monitoring and surveillance
ISI'03 Proceedings of the 1st NSF/NIJ conference on Intelligence and security informatics
| Hi-index | 4.10 |
A new model with invariant-based language effectively handles data-driven rules in databases and uses the rules' inherent semantic properties and supporting mechanisms to meet high-level language requirements. It is an extension of the basic PARDES model developed by Opher Etzion in 1990 to support derivations and integrity constraints in databases. The model's invariant-based language, unlike other programming languages, can follow data- driven rules' semantic properties. Such rules are activated by modifications of data items in a database, and they play an important role in many applications that maintain complex relationships between data items or interdependencies between parts of the database. Applications include expert systems, real- time databases, simulations, and decision-support systems. The authors present requirements for choosing an adequate programming style that uses data-driven rules. These requirements are based on software-engineering criteria such as compatibility with a high-level language and verifiability of the rule language. The authors show that contemporary database programming styles fail to meet these requirements, and they present the invariant- based language as a viable solution.