ORM 2010 : ORM

P:03 Real-time Integration of Geo-data in ORM

Ken Evans — Sun, 31 Oct 2010 10:48:00 GMT

Real-time Integration of Geo-data in ORM

Herman Balsters, University of Groningen (The Netherlands)
Chris Klaver, University of Groningen (The Netherlands)
George Huitema, University of Groningen, and TNO (The Netherlands)

Abstract. Geographic information (geo-data; i.e., data with a spatial component.) is being used for civil, political, and commercial applications. Modeling geo-data can be involved due to its often very complex structure, hence placing high demands on the modeling language employed. Many geo-applications would greatly benefit from the possibility of integrating existing geo-databases. Data integration is a notoriously hard problem, and integrating geo-databases in practice often adds the extra requirement that the integration should result in a real-time system.

This paper provides a case study and a design method for real-time integration of geo-databases based on the ORM modeling language. We will show that the use of ORM is superior to competing approaches, and that the so-called ORM federation procedure will yield correct design of integrated geo-databases.

Paper published October 2010 in: Springer LNCS 6428, pp. 436-446.

Note: This is a PowerPoint presentation in standard Zip format

P:12 Subtyping and Derivation Rules in Fact-Based Modeling

Ken Evans — Fri, 29 Oct 2010 15:11:56 GMT

Subtyping and Derivation Rules in Fact-Based Modeling

Peter Bollen, Maastricht University (The Netherlands)

Abstract. In this paper we will reflect on the derivation rule modeling concept and we will investigate how the definition of derivation rules is related to the subtypes and the subtype defining fact types in a conceptual schema.

We propose the concept of ‘derivation-logic induced' classifying fact types and what advantages this can have in terms of the creation and maintainability of conceptual schemas.

Paper available in: Springer LNCS 6428, pp. 514-521

Note: This is a PowerPoint presentation in standard Zip format

P:11 Mapping ORM To Datalog - an Overview

Ken Evans — Fri, 29 Oct 2010 15:07:52 GMT

Mapping ORM to Datalog: An Overview

Terry Halpin, LogicBlox (Australia) and INTI International University (Malaysia)
Matthew Curland, LogicBlox (USA)
Kurt Stirewalt, LogicBlox (USA)
Navin Viswanath, LogicBlox (USA)
Matthew McGill, LogicBlox (USA)
Steven Beck, LogicBlox (USA)

Abstract. Optimization of modern businesses is becoming increasingly dependent on business intelligence and rule-based software to perform predictive analytics over massive data sets and enforce complex business rules. This has led to a resurgence of interest in datalog, because of its powerful capability for processing complex rules, especially those involving recursion, and the exploitation of novel data structures that provide performance advantages over relational database systems.

ORM 2 is a conceptual approach for fact oriented modeling that provides a high level graphical and textual syntax to facilitate validation of data models and complex rules with nontechnical domain experts. Datalog^LB is an extended form of typed datalog that exploits fact-oriented data structures to provide deep and highly performant support for complex rules with guaranteed decidability. This paper provides an overview of recent research and development efforts to extend the Natural ORM Architect (NORMA) software tool to map ORM models to Datalog^LB.

Paper available in: Springer LNCS 6428, pp. 504-513

Note: This is a PowerPoint presentation in standard Zip format