[last update:  2011-04-07]

The SDT tool set is designed and built as an (Eclipse) perspective for the DOGMA studio framework. It is a group decision making system that is embedded with modern ontology engineering technologies. It supports the approaches to semantic decision tables. The SDT perspective is designed, constructed and implemented as a collection of loosely coupled (Eclipse) plug-ins.

The SDT tool set communicates with the DOGMA Server, which is an advanced J2EE application running in a JBoss server and which efficiently stores Lexons and Commitments in a PostgreSQL Database, in order to get full engineering supports concerning community-based ontology creation. ontology versioning, visualization, querying, reasoning and publishing.

The SDT perspective supports reasoning the decision rules in semantic decision tables, constructing semantic decision tables, managing domain ontologies, annotating decision tables, validate decision tables using domain ontologies.

SDT Perspective

The current SDT perspective contains the following plug-ins:

Basic plug-ins

• decision table constructor (the first version was released before Oct. 2009). It guides a non-technical end user to create decision tables in an easy and step-wise way.
• decision table annotator (the first version was released before Oct. 2009). It supports the ontological annotation of decision tables. It includes a viewer for formal ontological relations in order to facilitate the annotation.
• domain ontology manager (the first version was released before 2008). It support the communication between the local SDT perspective and remote DOGMA server.
• DECOL editor (the first version was released before Oct. 2009, the second in September 2010). Users write SDT commitments (meta-rules of a decision table) in the form of DECOL. In the second version, users can use it for the natural language verbalization and model commitments based on examples.The verbalization in this version is for the constraints of mandatory, uniqueness and frequency. And so do the examples.
• SDRule-L editor (the first version was released in 2008. It was disabled since early 2009). It supports the graphical visualization of SDRule-L (Semantic Decision Rule Language).
• decision item bag/context manager (the first version was released in September 2010; the second version was released in April, 2011). It is used to collect and group condition and action candidates in a domain, and supports necessary functions for different types of decision makers in a hierarchical organization.
• Concept definition visualizer (the first version was released in 2008, replaced by WordNet+Domain dictionary viewer since December, 2010). It provides definitions in natural language for decision conditions, actions and the concepts in the domain ontologies. The textual definitions are retrieved from domain dictionary (glossary and thesaurus) and WordNet.
• Domain Dictionary + WordNet viewer (the first version was released in December 2010). It is used to show the definitions of atomic concepts in an SDT (or decision table), or in an ontology. The definitions are stored in WordNet and domain dictionaries. It also supports users with the searching function. 

Advanced Plug-ins (SDT applications)

• GRASIM (the first version was released in 2009). It uses SDTs for ontology-based data matching.
• Transaction tester (the first version was released in July 2010). It uses SDTs to test transaction rules with parameters in the conditions.
• Rule auditor (the first version was released in September 2010). It uses SDTs to audit decision rules in a tabular format.

Ongoing work

• SDT Analyzer
• SDT dependency visualizer
• SDT Mapper

Background of Semantic Decision Tables

Researchers have been investigating the study of decision tables for more than fifty years. As an important tool to support Information System Management, decision tables have many outstanding advantages, i.e. they are easily learned, readable and understandable by non-technical people. Seeing the advantages, the interest of decision tables has been rising steadily. However, often the definition of concepts, variables and hidden (or meta-) decision rules that underlie remain implicit. When decision tables get larger, ambiguities, content inconsistencies and conceptual reasoning difficulties arise. The situation gets naturally worse when a group of decision makers need to build decision tables in a collaborative environment. Thus, the concept of Semantic Decision Table (SDT) is proposed.

SDT provides a means to capture and examine decision makers’ concepts, as well as a tool for refining their knowledge and facilitating knowledge sharing in a scalable manner. An SDT is the result of annotating a (set of) decision table(s) (or any well structured decision resources) with (domain) ontologies. It is modeled based on the framework of Developing Ontology-Grounded Methods and Applications (DOGMA). We have designed a methodology to assist a decision group to create SDTs. With regard to the technical issues of SDT, Semantic Decision Rule Language (SDRule-L/SDRule-ML) and Decision Commitment Language (DECOL) are designed and implemented to model, store, reason and publish SDT rules.

In order to justify the theoretical part of SDT, we have applied SDT in several interesting applications. One application is to use it as self-organizing and automatically reorganizing decision tables when users’ requirements are updated. An algorithm called SOAR (adaptive self-organization and automatic reorganization algorithm) has been developed and evaluated. The other applications show the possibilities of using SDT to monitor processes and present semantically rich decision rules to non-technical persons.

Support Readings

1. Yan Tang, Semantic Decision Tables - A New, Promising and Practical Way of Organizing Your Business Semantics with Existing Decision Making Tools , ISBN 978-3-8383-3791-3, LAP LAMBERT Academic Publishing AG & Co. KG, Saarbrücken, Germany, 2010 
2. http://en.wikipedia.org/wiki/Semantic_decision_table