-Ontologies are commonly used to represent formal semantics in a computer system, usually capturing them in the form of concepts, relationships and axioms. Axioms convey asserted knowledge and support inferring new knowledge through logical reasoning. For complex systems, the process of creating ontologies manually can be tedious and error-prone. Many automated methods of knowledge discovery are based on mining domain text corpus, but current state-of-the-art methods using this approach fail to consider properly semantic data embedded in XML schemata in complex systems. This paper proposes a mapping method for identifying relevant semantic data in XML schemata, automatically structuring and representing it in the form of a draft ontology. Concepts, concept hierarchy and domain relationships from XML schema are mapped to relevant parts of an OWL ontology. A part-ofspeech tagging method extracts domain relationships from schema annotations. This mapping method can be applied to any system that has a well-annotated XML schema. We illustrate our process with the preliminary results obtained when creating a command and control to simulation (C2SIM) draft ontology from an XML schema.
Keywords—OWL, XML Schema, Part of Speech tagging, Command and Control, Interoperability
I. INTRODUCTION
Knowledge discovery is essentially the process of
extracting semantic concepts and relationships from domain
resources within a particular domain. Ontologies are the de
facto standard for representing knowledge of a system [
Although ontologies are valuable assets in system
modeling, testing and analysis, the process of manually creating an
ontology for a complex system is inherently tedious and
error prone. Existing methods of knowledge discovery and
ontology creation usually are based on text mining of a data
corpus for that domain. XML-based systems capture the
structure and syntax of all necessary and meaningful
elements in a XML schema, which therefore is a useful starting
point for semantic analysis. In such systems, XML schemata
have been shown to be a valuable resource of semantic data
[
XML often is used as the exchange mechanism in the
command and control domain [
Most existing work on mapping a XML Schema to an
ontology (e.g. [
Bohring et al. [
Existing work ignores semantic information pertaining to domain relationships that are present in well-annotated XML schema annotations. By design, the purpose of XML annotations is to capture description of elements, which are often described in relation to other elements. For instance, consider the XSD annotation for the element <xs:EventStatus> of the C2 domain in Figure 1.
This pattern of linking elements in annotations is common in domains with well-annotated XML schemata. Our approach leverages this pattern by employing a mapping from xs:element to owl:class and uses Part of Speech tagging of XSD annotations to extract domain relationships.
The mapping process takes as input a sufficiently annotated XML schema, which we define as any XML schema that contains the following: a) The schema provides annotations for most elements using descriptive domain terminology b) Annotations referencing elements defined in the schema use a consistent naming convention.
As an example of the latter, if the schema defines an element as “ReporterWho” then any annotation referring to this element must do so in a consistent way, i.e., the reference can be extracted by simple operations (e.g., removing spaces, pruning special characters, etc.)
The system components and relationships between the components are illustrated in Figure 2 below.
Pre-processing the XML schema: Our approach maps the ontological concept name to the name of the element in the XML schema. XML schemata allow for multiple elements to have the same name. More often than not, the same name is used (e.g. <xs:element name=”ID”/>),specially when defining identifiers and other common elements. Even though the same name may exist in different element definitions, as long as their context is different they are semantically different concepts. In order to disambiguate between elements with the same name, we propose a preprocessing step that concatenates the parent complex type name to the name of the element using a delimiter. For elements that do not have a parent complex type, an iterating place-holder name can be used (e.g. “Parenti”) Because XML schema rules require that all xs:complexType have unique names in the schema, this pre-processing step ensures that element names (and therefore concept names in the ontology) are unique in the XML schema. The preprocessing step performs the disambiguation technique to all elements, and not only to the redundant elements. This is specifically convenient because capturing the schema structure in the ontology could be useful to other ontological processes (e.g. ontology matching that uses XML schema structure). The pre-processing step is illustrated in Figures 3 and 4 below. After pre-processing, the following mappings are established while parsing through the XML schema:
Mapping 1: 'xs:element’ to owl:class:
Commonly, each definition of an element contains a name and an
associated complex type. An owl:class is created with
the class name equal to the name of the element. Attribute
definitions for the element are mapped to the
owl:datatype property. Cardinality of concepts is
defined according to the xs:minOccurs and
xs:MaxOccurs in the XML schema as explained in [
Mapping 2: Element hierarchy to concept hierarchy:
Nayak and Wina [
Mapping 3: Schemata composition to ‘partOf’ and ‘kindOf’ relationships: In XML schemata an element defined as a complex type is composed of other elements. Elements can be composed using ‘All’, ‘Sequence’ and ‘Choice’ indicators. All elements in ‘All’ and ‘Sequence’ groupings are mapped to a ‘isPartOf’ OWL object property and all elements in the ‘Choice’ composition are mapped to a ‘isKindOf’ OWL object property. The following two examples illustrate the mapping from schema composition to OWL object properties. <xs:complexType name=”taskType”> <xs:sequence>
<xs:element <xs:element <xs:element </xs:sequence> </xs:complexType>
Example 1 - Consider the definition of a Task below: <xs:element name=”Task” type=”taskType”>
The definition of ‘taskType’ is composed of other elements as follows:
In the definition above, the element ‘Task’ is composed of ‘Who’, ‘When’ and ‘Where’ using the sequence composition. The mapping proposed in the paper will leverage the sequence composition to establish the following properties: • ‘Who’ isPartOf ‘Task’ • ‘When’ isPartOf ‘Task’ • ‘Where’ isPartOf ‘Task’ Example 2 - Consider the definition of a Where below: name=”Who” type=”whoType”/> name=”When” type=”whenType”/> name=”Where” type=”whereType”/> name=”AtWhere” type=”AtWhereType”/> name=”RouteWhere” type=”routeType”/>
Mapping 4: Mining XSD annotations for domain
relationships: Annotations in XML schemata are designed to
provide documentation in the form of free text for elements
being defined. It is common in the C2 domain to have
annotations in XML schemata describing an element often in
relationship to other elements. Existing published research
in XML schemata to ontology mapping does not check for
semantic relationships in XSD annotations. We propose the
novel use of Part of Speech (POS) tagging to extract domain
relationships from XSD annotations. Part of Speech tagging
is a well-developed natural language technique that parses
text and determines the part of speech for each word in the
text. The common process is to determine the tag based on a
probabilistic modeling of the word and its context
(preceding and succeeding words). The current standard involves
use of the Penn Treebank tokenization that categorizes into
thirty-six possible parts of speech [
Step1: Identifying all concepts in the annotation: This is done by identifying all words tagged as nouns or proper nouns (NN, NNS, NNP, NNPS) by the POS tagger. The concepts are added to a vector as follows:
V concepts = {Ci | Ci is the ith concept in the annotation} Step 2: Identifying predicates for the relationship: Starting at the beginning of the annotation, a concatenation of adjectives (JJ), Pronouns (WP), and prepositions (IN) is created until concept Ci is encountered. This concatenation forms the predicate of the domain relationship. These predicates are added into the vector as:
V predicates = {predi | predi is the concatenated predicate before the ith concept in the annotation}
Each concept Ci will now have an accompanying predicate. If predi has only one word and is a coordinating conjunction (e.g. “and”) then predi-1 is assigned to predi. This is due to the presence of a coordinating conjunction between <xs:element name=”Where” type=”whereType> <xs:complexType name=”whereType”> <xs:choice>
<xs:element <xs:element </xs:choice> </xs:complexType> The element ‘Where’ is composed of ‘AtWhere’ and ‘RouteWhere’ using the choice composition. The mapping proposed in this paper will leverage the choice composition to establish the following properties: • ‘AtWhere’ isaKindOf ‘Where’ • ‘RouteWhere’ isaKindOf ‘Where’ two concept names C1 and C2, meaning that whatever predicate applied to C1 also applies to C2.
Step 3: Creating the domain relationship: If the annotation is for element E1, then for each concept in Vconcepts the following domain relationship (owl:objectProperty) is created: <subject, predicate, object> = < Ci, str_concat(hasAs,predi), E1 > Fig 5. AAns eaxnamepxlae mscphelemacoelnesmiednetrwtihtheafnonloltoawtioinng annotation:
Based on the technique described above, the following domain relationship is created: <Task hasAsReferenceTask TaskWhatRef> Note: For the sake of clarity of illustration the schema as it appears before pre-processing is shown in Figure 5.
The mappings described in the steps above are illustrated in Figure 6.
IV. APPLICATION TO C2SIM.
C2-to-simulation interoperability (C2SIM) is a standard
under development by the Simulation Interoperability
Standards Organization (SISO) to facilitate interoperability
between C2 and simulation systems [
In order to provide interoperability on the semantic level,
C2SIM will require ontological support for formalizing
semantics and for the design and analysis of networked C2
and simulation systems. Early work on the need for and
future of semantic C2SIM is described in [
A software prototype was built, based on the proposed
method using OWL-API [
FUTURE WORK
The proposed method extracts domain concepts and
relationships from well-annotated XML schema. Potential
approaches to improve the quality and resolution of the
resulting ontology include the use of domain synonym tables as a
means to support identifying concept names in schema
annotations. We believe this can account for variants of a
name that may be used in the schema annotation. Future
work improving our methodology also includes capturing
C2 doctrine in the form of axioms, as well as evaluating the
use of reasoning to both infer and hypothesize knowledge.
In ongoing work [