SWRL Rule Editor

A Web Application as Rich as Desktop Business Rule Editors

João Paulo Orlando

, Adriano Rívolli

, Saeed Hassanpour

, Martin J. O'Connor

Amar Das

and Dilvan A. Moreira

Dept. of Computer Science, ICMC - Universidade de São Paulo, Campus de São Carlos,

Caixa Postal 668, 13560-970, São Carlos, SP, Brazil

Stanford Center for Biomedical Informatics Research, Stanford, CA, U.S.A.

Keywords: SWRL Tool, SWRL API, Rule Tool, Rule SWRL, Rule Visualization, Rule Composition, Semantic Web,

SWRL.

Abstract: The Semantic Web Rule Language (SWRL) allows the combination of rules and ontology terms, defined

using the Web Ontology Language (OWL), to increase the expressiveness of both. However, as rule sets

grow, they become difficult to understand and error prone, especially when used and maintained by more

than one person. If SWRL is to become a true web standard, it has to be able to handle big rule sets. To find

answers to this problem, we first surveyed business rule systems and found the key features and interfaces

they used and then, based on our finds, we proposed techniques and tools that use new visual

representations to edit rules in a web application. They allow error detection, rule similarity analysis, rule

clustering visualization and atom reuse between rules. These tools are implemented in the SWRL Editor, an

open source plug-in for Web-Protégé (a web-based ontology editor) that leverages Web-Protégé’s

collaborative tools to allow groups of users to not only view and edit rules but also comment and discuss

about them. We evaluated our solution comparing it to the only two SWRL editor implementations openly

available and showed that it implements more of the key features present in traditional rule systems.

1 INTRODUCTION

The Semantic Web has the goal of making the

content available on the Web not only understood by

people but also by machines (Berners-Lee, Hendler,

and Lassila, 2011). To this end, it uses ontologies for

knowledge representation and for the generation of

semantically annotated data.

The Web Ontology Language (OWL) is the

W3C standard language for Semantic Web

ontologies (McGuinness and van Harmelen, 2004).

It is a powerful language for building ontologies to

specify high-level descriptions of web content.

These ontologies are built using class hierarchies

representing domain concepts and their related

properties. OWL also provides a powerful set of

axioms to define precisely how to interpret concepts

in an ontology and infer information from these

concepts.

However, the expressiveness of OWL is not

always sufficient for modeling all kinds of problems.

To overcome this deficiency, the SWRL (Semantic

Web Rule Language) was created. It extends the set

of OWL axioms to include Horn-like rules. It thus

enables Horn-like rules to be combined with an

OWL knowledge base to create assertions in the

form of rules, using concepts defined in OWL to

represent, organize and share specific domain

knowledge by means of conditional statements

(World Wide Web Consortium [W3C], 2004).

As the complexity of systems modeled using

SWRL grows, developers face difficulties in

managing the resulting rule set properly. A system

with a large rule number becomes difficult to

understand and error prone, especially when used

and maintained by more than one person

(Hassanpour, O’Connor, and Das, 2009). But SWRL

lacks a rule-editing tool that is little more than a

simple text editor and that incorporates the best

techniques in rule creation/management tools to

support users in creating and managing large rule

sets. That is the problem we wanted to alleviate.

Research in rule management and development

happens in several areas, such as databases, business

systems, etc. So, to begin with, we conducted an

258

Paulo Orlando J., Rívolli A., Hassanpour S., J. O’Connor M., Das A. and A. Moreira D..

SWRL Rule Editor - A Web Application as Rich as Desktop Business Rule Editors.

DOI: 10.5220/0003999402580263

In Proceedings of the 14th International Conference on Enterprise Information Systems (ICEIS-2012), pages 258-263

ISBN: 978-989-8565-11-2

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

extensive survey on this kind of business rule

systems (which are generally rule-based systems

used by large corporations) and found the key

features and interfaces found on them. After that, we

proposed new features and interfaces to recreate/

adapt the ones we have found, in the business

sytems, for use in a web application environment

tailored for SWRL (all the tools studied were for

desktop use). Finally, we implemented an editor, the

SWRL Editor, to use these proposed features and

interfaces to offer the SWRL community a rule

editor with the same capability as the best editors

available to other communities (mainly the business

rule community).

In this paper, we present the SWRL Editor. It

includes new or adapted visual representations and

techniques to enhance the viewing and composition

of rules. It aims to help Semantic Web developers in

the process of creating, viewing and managing

SWRL rules. It allows:

 Knowledge acquisition with less

inconsistencies, ambiguities and duplicated

rules;

 A better viewing experience for rules and rule

sets to facilitate the understanding, knowledge

and manipulation of them;

2 SWRL

SWRL is an expressive rule language that combines

Horn clauses with concepts defined in OWL and can

be used to increase the capacity of inference about

individuals in a knowledge base in OWL (W3C,

2004). SWRL rules are composed by two parts: the

antecedent (body) and consequent (head). Each rule

is an implication between the body and head that can

be understood as if the body conditions are true then

make the conditions of the head also true. Both parts

consist of a conjunction of zero or more atoms, not

allowing disjunctions or denial.

Atoms, on the one hand, are formed by a

predicate and one or more arguments (the number

and type of arguments are determined by the atom

type). Although the W3C specification defines seven

atom types, in this paper, we adopt the convention

used in (Hassanpour et al., 2009) that considers

SameAs and DifferentFrom as having the same type

because they are syntactically identical, even though

they have different semantics (what leaves us with

six types).

The six types of atoms are: the Class, Object

property and Data valued property types correspond

to elements (concepts) defined in the ontology. Data

range type corresponds to the data types used in the

ontology. The type Same/Different is used to explain

the equality or difference between two individuals,

as OWL needs to work with the open-world

paradigm. Finally, Built-ins are types that

encapsulate utility functions and can even be

extended by users. Although SWRL rules can be

represented in more than one format, the human-

readable format is adopted in this paper. The arrow

(→) is used to separate body and head, the caret (^)

represents the conjunction of atoms and the question

mark (?) distinguishes variable names from

individuals. Using this syntax, a rule that states that

the brother of the father of an individual is his uncle

can be written as follows:

hasParent(?x,?y) ^ hasBrother(?y,?z) →

hasUncle(?x,?z)

3 RELATED WORK

Before developing the SWRL Editor, we conducted

an extensive research on tools to edit rules in general

(not only SWRL rules), as well as general-purpose

tools for SWRL rules (a total of 16 tools were

reviewed). We were interested in their key features

and interfaces adopted (Rivolli, Orlando and

Moreira, 2011). In this section, two of these tools,

the SWRL Tab and Axiomé, are briefly presented.

They are directly related to our SWRL Editor and

were the only two openly available tools we found to

edit SWRL. We also discuss some of the key

features found in tools for creating business rule

systems (which are rule-based systems used by large

corporations).

The SWRL Tab (SWRLTab, 2012) is a plug-in

for the Protégé ontology editor and its main purpose

is to allow editing and management of SWRL rules.

The rules are presented in tabular format, so they

can be edited directly where they are displayed or in

an editor. The tool performs the identification of

syntax errors, using the SWRL specification (W3C,

2004), and validates the correct use of ontology

terms. In addition, a set of Application Programming

Interfaces (APIs) is available, allowing, for example,

rule inference and syntax validation. On the other

hand, the tool does not offer any facilities to

organize or group the rules.

Axiomé (Hassanpour et al., 2009) is also a plug-

in for Protégé and uses the APIs provided by the

SWRL Tab tool. From the user perspective, Axiomé

offers more tools to organize and view rules and also

allows rule edition using templates that are

generated based on the structure of the rules. The

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main technical tools offered are: Automatic rule

grouping; Visualization of dependences between

rules; Rule Paraphrase (a dynamically generated

textual explanation of a rule); and Templates for

editing and acquiring rules.

There are a number of techniques and tools

related to the creation of business rules that may be

reused for the improvement or creation of new

techniques related to SWRL rules (Rivolli et al.,

2011). Although tools related to the creation of

business rules are still evolving (Zacharias, 2008),

their current development stage is far ahead

compared to SWRL tools.

The analysis of these tools shows different forms

of user interaction with rules, for example, decision

trees and tables, templates for editing rules, natural

language interfaces, automatic term suggestion, error

correction, visualization diagrams and integrated

editors that use grouping techniques.

4 SWRL EDITOR

4.1 Infrastructure and Architecture

The SWRL Editor was developed as a plug-in for

Web-Protégé, the web version of the ontology editor

Protégé (Tudorache, Vendetti and Noy, 2008a).

Protégé is a free, extensible, open source, ontology

editor developed by the Stanford Center for

Biomedical Informatics Research (Stanford

University). Web-Protégé uses the Google Web

Toolkit (GWT) to provide a desktop-like user

experience on the web, actually similar to the

desktop version of Protégé. The architecture, based

on plug-ins, is one of the main Protégé/Web-Protégé

features. The extension mechanism allows new

features to be added gradually, what made the

Protégé/Web-Protégé a flexible but yet solid

platform for developing semantic technologies

(Tudorache, Noy, and Musen, 2008b). Web-Protégé

plugins make it possible to add new tabs containing

one or more portlets, reusable graphic components.

As a Web-Protégé plugin, the SWRL Editor uses

the Java language and the GWT development tool. It

consists of a tab and a portlet that interact, over the

network, with the Protégé API allowing the

manipulation of SWRL rules in a friendlier way

using a higher abstraction level of representation

than the SWRL language.

Unlike the SWRL Tab and Axiomé tools, which

are very coupled to the Protégé tool, the SWRL

Editor was developed applying appropriate design

patterns (such as MVP) to make it reusable and

decoupled from the Web-Protégé platform.

At the Web-Protégé side, the server allows

access to its services through the Ontology API, to

read/write ontologies, and the Collaboration API, to

support collaboration services, such as ontology

term annotation and change control (Tudorache et

al., 2008a). SWRL Editor users can apply these

collaboration services to annotate components used

in their rules. The CHAO (Changes and Annotations

Ontology) (Noy, Chugh, Liu, and Musen, 2006) has

classes to define different annotation types, such as

comments, or changes, such as class created

(Tudorache et al., 2008a).

In the Web-Protégé client side, there are the user

GUI, a ontology model and a RPC module (to

communicate with the server). The ontology model

has a partial representation of the server ontology

that is updated as needed by the client.

The SWRL Editor plug-in has its own rule

representation model, generated by the SWRL

Manager from the SWRL rules it gets using the

Ontology API. It also has the SWRL Collaboration

module to manage the versioning of rule changes

and the Plug-in Manager to load code (in jar files)

with different algorithms for rule Grouping and

Decision Tree view generation. The client side has a

MVP (Model-view-presenter) architecture that is

similar to the Protégé client.

4.2 Visualization

The solutions created to enhance visualization and

rule understanding consist of visual representations

for rules (Figure 1, 2 and 3), organization techniques

and resources to present rule sets. Lets use a rule set

form the Ontology for Breast Cancer Grading

(Bulzan, 2010) to show our tool features. This rule

set is composed of 12 rules, which are used to assign

a note to a tumor from the three criteria from NGS

(Next-Generation Sequencing). We show the same

rule using three different visual representations:

 The SWRL highlight visual representation

(Figure 1) displays the rule atoms and adds

color to the arguments according to their type;

Figure 1: Visual representations for rules - Highlight.

 The hierarchical view (Figure 2) abstracts rule

syntax and presents rules in a hierarchical tree

related to their meaning and type of atoms;

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Figure 2: Visual representations for SWRL rules - Hierarchical View.

Figure 3: Visual representations for SWRL rules - View in Paraphrase.

Figure 4: Family Ontology (Peace, 2008) – (A) SWRL Editor with textual Highlight; (B) Hierarchical SWRL Editor.

 Paraphrase visualization (Figure 3) shows a

paraphrase of the rule axioms using a technique

developed for Axiomé (Hassanpour et al.,

2009). We added bold characters to mark

connection terms;

All three representations make the rule

presentation clearer and enrich its meaning with

colors and symbols.

These visualization techniques allow the user to

better manage and understand the rule sets.

In addition, the tool has the following features:

 Automatic procedures for extracting

information and generating views for each

visual representation, without user intervention;

 The capability of listing rules in any of the

visual representations: there is a tab for each

representation and users can switch them at

will;

These features add functionality for the use of

rule developers, allowing them to easily locate and

understand specific rules.

4.3 Rule Creation and Edition

The SWRL Editor has two rule edition modes to

assist users:

 Editor with textual Highlight (Figure 4 (A));

 SWRL hierarchical editor (Figure 4 (B));

The textual editor with highlight is similar to the

standard type of editor normally used in tools, such

as Eclipse or Netbeans, to edit C or Java programs.

Its color scheme is related to the syntactic elements

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and can be changed by users (antecedents and

consequents are also separated).

The SWRL hierarchical graphic editor, shown in

figure 4 (B), has boxes that change according to the

selected atoms and icons to separate different atom

types. It has separate boxes for consequents and

antecedents. The editor also suggests terms from the

ontologies being used, based on atom types and

position.

Users can freely switch between the two editors,

what can be a very good tool to teach rule structure

to novices. In addition, both editors offer the

following features:

 Detection of lexical and syntactic errors;

 Identification of similar rules;

 Hierarchical navigation into otology classes,

properties and bultins using a tree (on the editor

left side), with the possibility of their inclusion

in a new rule.

5 TOOLS COMPARISON

In this section, we present a comparison between the

features of the SWRL Tab, Axiomé and our tool,

SWRL Editor, as the other tools in the review do not

work with SWRL. The Axiomé and SWRL Tab

tools have resources coupled to the Protégé 3 API.

They are also not available for the Web-Protégé

version (only the desktop version) and, for that

reason, cannot benefit of some of the collaboration

tools available for the web. The SWRL Editor

manipulates rules using an internal logical

representation that can be easily mapped to other

APIs, such as the OWL-API (and, in the future, even

to SPARQL Rules).

To make this comparison, we used the main

features that we found in more traditional rule based

desktop tools (developed mainly for business users)

(Rivolli et al., 2011) and (Zacharias, 2008). Table 1

shows the comparison between the three tools:

We can see that the SWRL Editor has an

overwhelming advantage over the other tools as it

implements most of the traditional rule based tools

features.

Compared to the SWRL Editor, the other two

tools either lack most of its capabilities or have a

more restricted implementation. The SWRL Editor

is an evolution of them. We determined, after input

from some users, that a more sophisticated usability

test, comparing the three tools, would not be very

informative due to the lack of features to compare.

We tested the tool using three ontologies (with

SWRL rule sets). When using the Autism ontology,

we were able to easily find problems, like repeated

rules, that had escaped their developers using the

other two tools.

Table 1: Comparing the features of the tools.

Feature SWRL

Editor

SWRL

Tab

Axiomé

Platform

Web

Desktop Desktop

Decision tables

U U

Decision trees

U U

Graphic diagram

Text editor

9 9

Text editor with

Highlight

U U

Rule templates

Natural language

Partially

Visual representation

Grouping

Term suggestions

Error Detection

Better

Coverage

9 9

Filter

9 9

Customization Tool

U U

Add new algorithms

U U

It is also important to mention the fact that the

SWRL Editor is available on the Web and integrates

its various resources (and enhancements) with Web-

Protégé collaboration features into a single tool.

Users can annotate components used in their rules,

adding comments, proposals etc, and discuss online

(in real time) about them using the Notes and

Discussion Tab. As big rule sets are likely to be

developed by groups of distributed users, that

resulting single tool can more effectively support the

work of these groups. That is one of SWRL Editor

important contributions as none of the tools in the

literature (including more general tools for rule

editing) support that.

6 FINAL CONSIDERATIONS

Rule sets in SWRL have the fundamental role of

being the inference engine to create new knowledge

inside the Semantic Web. But SWRL lacked a rule-

editing tool that was more than a simple text editor

and incorporated the best techniques for rule

creation/management, available in tools for other

rule domains.

After we conducted an extensive survey of

business rule systems and compiled their most

important features and interfaces, we designed the

SWRL Editor tool to use, what we considered, the

key features to offer a SWRL rule editor with the

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same capabilities as the best editors available to

other communities.

But we went a step further and implemented this

tool as a Web-Protégé plugin (using GWT/AJAX

technology) to create a desktop like tool running on

the web, so we could add to it: zero footprint

installation, automatic updates, easy cooperation

among user groups, operating system independency,

and other well known advantages of web

applications.

The SWRL Editor uses three approaches for

visualizing rules:

1. The SWRL Text Highlight.

2. The Hierarchical View.

3. Paraphrase Visualization.

For rule composition we created two editing tools:

1. Text Editor with Syntax Highlight

2. Hierarchical SWRL Editor

Both editors have error detection, warnings,

search (for similar rules), self-completion and

hierarchical navigation of terms in the ontology.

Our main contribution is to show, using the

SWRL Editor, that it is possible to make a tool for

SWRL rule edition that have the equivalent key

features and interfaces of more traditional rule based

desktop tools (developed mainly for business users)

as a “desktop like” web application. That would not

be possible a year ago; it is only possible now due to

new internet technologies, such as HTML 5. Such a

tool is far more advanced than the current state-of-

the-art for SWRL edition.

We also show that it is possible to add

collaboration to this tool by leveraging the fact that

it runs distributed over the web, it keeps information

about rule versioning and uses Web-Protégé tools

for cooperation. No other tools described in the

literature have such feature but that is important, as

big rule sets are likely to be developed by groups of

distributed users.

As future work, we intend to develop tools to

target redundancy errors, highlight relevant rules

(given some criteria) and ways to establish

connections among rules (so if you modify one the

others in the set are highlighted).

ACKNOWLEDGEMENTS

This work has been a collaborative project between

the Intermídia Lab – ICMC – University of São

Paulo and the Stanford Center for Biomedical

Informatics Research (BMIR) – Stanford University.

This project has been funded by the National

Institutes of Health, under grant R01MH87756. It

has also been funded by grants from the National

Council for Scientific and Technological

Development - CNPq, a Brazilian research agency.

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