RDF RULES FOR XML DATA CONVERSION TO

OWL ONTOLOGY

Christophe Cruz and Christophe Nicolle

Laboratory Le2i, Université de Bourgogne, B.P. 47870, 21078, Dijon Cedex, France

Keywords: Ontology population, Ontology enrichment, OWL ontology, XML data, RDF rules.

Abstract: The paper presents a flexible method to enrich and populate an existing OWL ontology from XML data

based on RDF rules. Theses rules are defined in order to populate automatically the new version of the

OWL ontology. Basic rules are defined to identify elements in XML schemas and an OWL schema.

Advanced mapping rules are based on basic rules in order to define the mapping between XML schemas

elements and OWL schema elements. In addition, this flexible method allows users to reuse rules for other

conversions and populations.

1 INTRODUCTION

The knowledge defined in ontologies is used as an

index to retrieve specific data (García, 2005), to

infer new knowledge (Ha, 2005), to semantically

annotate multimedia data (Castano, 2007), to find

out Web Services automatically (Martin, 2007), or to

match knowledge with other knowledge for a more

general purpose.

XML schemas contain the knowledge of a

domain that was specified by the author. This

specification is only syntactic without any semantic

definition. This is due to the fact, that XML data are

used to exchange data between processes that were

developed for this data. In order to permit the

exploitation of the knowledge contained in XML

schemas and instances, we propose an ontology

enrichment and an automatic population process

from XML data based on a manual mapping of

XML schemas. The result of this process allows the

use of a SPARQL engine to request data on the

resulting OWL ontology, and allows the use of an

inference engine in order to deduce new knowledge.

In addition, multiple XML schemas and XML

documents are integrated in the OWL ontology

giving a single view on data.

Ontology enrichment is the activity of extending

an ontology by adding new elements (e.g. concepts,

relations, properties, axioms) (Castano, 2007). The

enrichment process consists in annotating

knowledge contained in XML schemas in order to

convert it into an OWL schema (Faatz, 2004). The

annotation process is manual. This is done by the

user who is the only one who knows which part of

the XML schema will be required in future

processes. However, Schema matching is a

manipulation process on schemas that takes two

heterogeneous schemas as input and produces as

output a set of mapping that identifies relations

between the elements of the two schemas (Thang,

2008). An automatic matching process is of value in

order to help in a semi-automatic way the annotation

of XML schemas and for rough enrichment.

The ontology population process is the activity

of adding new instances to an ontology (Castano,

2007). Presently, the data in XML document are

converted in OWL instances automatically with

rules generated from the previous “XML schema

annotation” process.

The following section discusses about previous

work done on this subject. Section three presents the

principles of our method which is based on formal

languages. Section three shows our method to enrich

the ontology by matching schemas and to populate

an ontology by an automatic process. A complete

background concerning XML Data conversion to

OWL ontology is described in (Cruz, 2008).

2 PRINCIPLE

The principle of our solution consists in making

RDF stand-off annotations and RDF links between

the schematic level of an OWL schema and the

111

Cruz C. and Nicolle C.

RDF RULES FOR XML DATA CONVERSION TO OWL ONTOLOGY.

DOI: 10.5220/0001843401110114

In Proceedings of the Fifth International Conference on Web Information Systems and Technologies (WEBIST 2009), page

ISBN: 978-989-8111-81-4

schematic level of several XML schemas. As a

consequence, the enriched ontology makes it

possible to link the concepts of several XML

schemas by amalgamating the attributes of common

concepts. This process has also to check the

consistency of the schema ontology in order to not

define several identical concepts and to not allow the

definition of cyclic “rdfs:subClassOf” graphs.

Figure 1: Principle of our “XSD to OWL” method.

The annotations and the links are used in a

second time to defined rules in order to

automatically populate the OWL within instances

from XML instances from XML schemas annotated.

The population has to follow some rules such as the

imitation of attribute cardinalities and unique

instances. Consequently, “advanced” rules have to

model and specify restriction on attributes. This

principle will be described in the next section.

The figure 1 presents the principle of our method

to (E)nrichment and (P)opulation of an existing

ontology. (E) is the process of enriching an ontology

and (P) is the process of populating the ontology.

These two processes use an RDF graph as rules to

enrich and to populate the ontology. The rules in

RDF are defined during the mapping process by

referring elements of XML schemas elements and

the OWL schema. In order to specify the relevant

elements of an XML schema for the enrichment

process, it is necessary to identify and mark these

elements. These marks are called “schematic marks”

and are external RDF annotations of XML

structures. These “schematic marks” are stand-off

annotations or external annotations.

The following section presents a brief

formalization of schematic marks.

2.1 Schematic Marks on XML Schema

The properties of Dyck’s languages were the subject

of studies undertaken by J. Berstel (Berstel, 2000).

According to the corollary 3.4, for each XML

language L there is only one reduced XML grammar

generating L. A reduced grammar does not have any

useless non terminal vocabulary. An XML schema

does not contain unnecessary tags, so an XML

schema does not use unnecessary non terminal

vocabulary. Consequently, an XML grammar is

necessarily its own reduced grammar. In addition, it

means that only one production rule in the XML

schema (tag <xsd:element name=”myTag” >) is

define for a tag in a XML document validated by the

XML schema. This proposal makes it possible to

introduce the concept of schematic mark.

Definition. A “schematic mark” is a mark on an

XML schema that identifies a production rule. Each

tag of an XML instance which has the same name

was produced by the same production rules.

These marks are used by the RDF rules to

identify the production rules which are the tags used

to define XML schemas. These marks are specified

with the help of the language XPath.

2.2 Schematic Marks and Semantic

An OWL grammar is also an XML grammar which

can be marked as an XML schema. However, an

ambiguous point has to be underlined. In figures 1

and 2, the OWL schema concerns the schema part of

the ontology. Indeed, the language OWL has an

XML schema in order to validate OWL documents

(http://www.w3.org/2007/OWL/wiki/OWL_XML_S

chema). In this section we focus on the OWL

schema part in an OWL document. The “semantic

marks”, which are used by the RDF rules to identify

the production rules in a XML schema, use the

language XPath to identify element of the OWL

schema.

OWL uses most of the built-in XML schema

data types. References to these data types are by

means of the URI reference for the data type,

http://www.w3.org/2001/XMLSchema.

3 ENRICHMENT

AND POPULATION METHOD

This section describes how the enrichment and the

population of an OWL ontology are managed from

XML schemas. The method is based on the

definition of schematic marks, basic mapping rules

and advanced mapping rules (e.g. fig. 2). The first

part describes the schema marking in order to

annotate the element of XML schemas. It relates to

the XML schema but also to the OWL XML

XML

Schemas

XML

Instances

OWL

Schema

OWL

Instances

RDF

Rules

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schema. The second part presents the mapping step

which is composed of the conversion rules, the

ontology enrichment process and the ontology

population process.

3.1 Schema Marking

An RDF graph is used to annotate each XML

schema. These marks are specified to keep all

information in a graph that is required during the

mapping with the OWL schematic mark step.

Figure 2: Principle of the RDF Rules definition.

In this figure, the processes (E) and (P) are here to

show the relationships established with the RDF

rules. In fact, the main objective of the figure is to

describe the components of the RDF rules. They are

composed of the schematic marks on XML schemas

and on an OWL schema. These marks are used to

identify elements required for the mapping process.

• Basic mapping rules define the schematic marks

on XML schema and OWL schema. The “bmr”

name space is used to identify the rule elements.

In addition, “bmr:xpath” defines an element in

the XML schema as does “bmr:xpathId” with

the addition that the latter acts as an identifier.

A unique property on an XML element is

welcome to define an identifier.

• Advanced mapping rules use basic mapping

rules in order to define the mapping between

XML schemas and OWL. In addition, these

rules allow to define new elements in the OWL

ontology for the enrichment process and for the

population process. The name space “amr”

represents the “advanced mapping rules”

elements.

The TriG Syntax (http://www4.wiwiss.fu-

berlin.de/bizer/TriG/) is used to ease the

explanations of how we employ schematic marks

with XML schemas.

3.2 Mapping Steps

This step consists in defining a new RDF graph in

order to define relationships between XML schema

marks and OWL marks.

Conversion Rules. The conversion rules consist in

defining rules in order to convert properties that are

different from the type of the property in the

ontology and that cannot be directly copied to the

ontology “datatypeProperty”. The first kind of

conversion is simple because it is the conversion of a

simple type into another simple type. The second

kind of conversion is complex because it is the

conversion of a sub tree from the schema into a

simple type into the OWL ontology.

The conversion of complex data can also be

found in a semi-structured data. For instance, a date

can be defined in a text format and could have to be

converted in month, day and year format in the

ontology.

Ontology Enrichment. The enrichment consists in

defining relationships between XML schematic

marks and OWL schematic marks. In order to enrich

the ontology, the RDF mapping graph has to contain

information about new entities in the ontology that

have to be. The name space “amr” represents the

“advanced mapping rules” elements.

Ontology Population. In order to generate the

population of the ontology, the RDF mapping has to

be defined. To achieve this, relationships have to be

created between the RDF graph of the XML schema

marks, the RDF graph of the OWL schematic marks

and the RDF graph of the conversion rules.

The population of the ontology is an automatic

process based on the mapping graphs. To realize this

process, we have defined an algorithm that takes into

account the type bmr:dpId in order to avoid

duplicated instances of the ontology. First, it

determines all classes that have to be populated.

Second, all “datatypeProperty” of each class is

provided to the instances. In the example given in

this paper no references are given to the

management of restriction on the properties. Some

rules can be defined in order to specify which

constraints have to be verified. If those rules are not

defined then no check on restriction is applied.

RDF Rules

Basic Mapping Rules

XML

schemas

OWL

schema

Schematic

marks

Advanced Mapping Rules

Schematic

marks

E P

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4 CONCLUSIONS

We have presented a flexible method to enrich and

populate an OWL ontology for the integration of

XML data. Basic mapping rules and advanced

mapping rules are defined by users and can be

reused for other conversions and populations of

ontologies. This conversion is the first part of our

work. The second part consists in improving the

process and in giving some proposition to the user in

order to facilitate the mapping. The RDF rules can

be used to automatically extract from XML schemas

some elements that can be converted in order to help

users during the mapping. For instance, a string that

contains a date can be detected automatically to

guide the user during the conversion.

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