=Paper=
{{Paper
|id=Vol-125/paper-7
|storemode=property
|title=Ontology-based Interoperability for Interorganizational Applications
|pdfUrl=https://ceur-ws.org/Vol-125/paper4.pdf
|volume=Vol-125
|authors=V. De Antonellis,M. Melchiori,D. Bianchini
}}
==Ontology-based Interoperability for Interorganizational Applications==
https://ceur-ws.org/Vol-125/paper4.pdf
Ontology-based Interoperability for
Interorganizational Applications ?
D. Bianchini, V. De Antonellis, M. Melchiori
Università di Brescia
Dip. Elettronica per l’Automazione
Via Branze, 38
25123 Brescia - Italy
bianchin|deantone|melchior@ing.unibs.it
Abstract. In this paper we present an ontology-based approach to sup-
port interoperability in interorganizational applications. The ontology
contains knowledge, coming from several organizations, structured in
different layers to support its effective use and communication. The pro-
posed approach has been experimented in the framework of the Italian
VISPO (Virtual district Internet-based Service PlatfOrm) project.
1 Introduction
In recent years, organizations are increasingly looking for opportunities to ex-
ploit innovative technologies that use Internet, mobile and wireless devices to
enhance communication and cooperation in providing information and services.
Modern inter- and intra-organizational applications specifically need to support
understanding of shared knowledge.
In literature, different approaches address the problem of interoperability in
distributed dinamically evolving environments and propose ontologies as a suit-
able solution [2, 11]. Several proposals involve the design of enterprise ontolo-
gies and many research groups are studying and developing methods and tools
for the definition and use of ontologies (http://ontoweb.aifb.uni-karlsruhe.de/).
The OntoWeb network [11] main goal is to bypass communication bottlenecks
among various and heterogeneous research groups and organizations. Ontolo-
gies are considered essential part in supporting information exchange processes
and business transactions, providing on-line unified access to large volumes of
information and knowledge based on machine-processable semantics of data.
Tool-supported methodologies for ontology design and several infrastructures
for search and reuse of distributed ontologies are proposed in [10, 14, 12]. In [9, 3]
the focus is on ontology-based integration of datasources. An open issue regards
effective users support to identify knowledge assets. Many research activities are
devoted to study the problems of providing different visions of the same realm
by different organizations, taking into consideration semantical aspects of the
involved datasources.
In this paper, we propose an ontology-based approach to support interop-
erability in interorganizational applications according to a three-layer ontology
?
This work has been partially supported by the Italian MIUR VISPO (Virtual district
Internet-based Service PlatfOrm [15]) project and the European EU NoE INTEROP.
architecture. The ontology acts as an informative infrastructure to aggregate in-
formation exchanged among organizations that cooperate for business purposes
giving rise to a virtual district. The ontology provides an access point to informa-
tion at local level and supports service aggregation and distribution. In particu-
lar, we discuss the use of a three-layer ontology in the virtual district scenario by
presenting some results of our research and development activity in the Italian
VISPO (Virtual district Internet-based PlatfOrm) project [7, 15]. Starting from
heterogeneous XML-based and XML-compliant datasources, a domain ontology
is designed in a semi-automated way with the support of the artemis tool envi-
ronment [1]. Knowledge in the ontology is organized intro three layers by means
of: clusters of similar concepts coming from different sources (semantic mapping
layer); unified global concepts and semantical relationships between them (me-
diation layer); subject categories derived from available standard taxonomies
(categorization layer). In particular, we focus on ontology use and deployment.
This paper is organized as follows: Section 2 presents the considered con-
text and provides motivations for the proposed approach; Section 3 presents
the ontology design approach; Section 4 shows different modalities to exploit
the interorganizational knowledge represented in the domain ontology; Section 5
presents concluding remarks.
2 Ontology support to interoperability and
communication intra- and inter-organizations
The availability of methodologies to construct ontologies is a critical issue in
supporting the communication and cooperation among different organizations.
In fact, the explicit and shared representation of interorganizational knowledge
is a main prerequisite for exchanging information and services. According to the
experience gained in the VISPO Project [15], that studied the definition of meth-
ods and architectures to support the activities of a virtual district, we illustrate
two application profiles for ontologies that match some relevant requirements
on knowledge representation that we collected in the two considered virtual
districts. In the following sections, we describe the ontology architecture, the
related design methodology and the deployment primitives that support these
application profiles. The requirement analysis developed in the VISPO Project
confirmed that various services and tools that support the business activities of
the district are to be based on shared knowledge representations that can be
usefully organized as ontologies. In particular, this need arises in the applica-
tion profiles we present: (i) service for the analysis of purchase requests, and (ii)
e-procurement service with aggregation of purchase requests. In the first case,
we describe the knowledge requirements for the design of services that support
the analysis of purchase requests generated into a single company. In the other
case, we analyze the requirements of interorganizational knowledge for design-
ing an e-procurement service devoted to companies that would like to aggregate
their purchase orders regarding the same products for the purpose of obtaining
a commercial advantage and therefore lower prices from suppliers. The context
of developing a support for the analysis of purchase requests leads to identify
an intra-organizational use of our methodology for ontology construction, while
the context of e-procurement services design leads to a inter-organizational use
of the methodology.
2.1 An intra-organizational use of three-layer ontology in a Virtual
District
In this considered context, we address the use of ontology in the analysis of in-
ternal purchase orders, that is, a set of auditing activities to analyze and control
the sources, the flows and the volumes of the orders made from the depart-
ments of a company. In this case, the employees of each department usually
formulates purchase requests according to a terminology and descriptions that
are not completely normalized, but vary from department to department and
often from employee to employee. The requests are directed and processed from
the Purchase Department of the company that is responsible to collect the pur-
chase requests and to send the orders to the suppliers. From the perspective
of the analysis of internal purchase orders, the problem is to identify all the
requests referred to the same product or to the same product category, since
they can be possibly described differently in the various requests and purchase
transactions. The main requirement, in this case, is the need for an internal cat-
alog that provides standardized descriptions for the purchase requests. In this
way, in fact, it is possible to evaluate the ordered amounts of a given prod-
uct that results uniquely identified. The internal catalog can be constructed by
integrating the terminology and the descriptions of products contained in the
purchase requests. In the experimentation of our methodology in the context
of the VISPO Project, an internal catalog has been constructed according to
the three-layer ontology, presented in Section 3, by integrating the description
of purchase requests extracted from the ERP of a selected company and the
product descriptions obtained from two public industrial catalogs. The appli-
cation of our methodology and, in particular, the integration with descriptions
from industrial catalogs provide the following benefits: (i) the descriptions and
the terms identifying products are made homogeneous and are better standard-
ized, (ii) the descriptions of products are enriched on the basis of the industrial
catalog descriptions. The internal catalog can be exploited to formulate a new
purchase request in terms of the global concepts the catalog contains (for in-
stance, an hexagonal-head screwdriver - 4mm diameter) and, in this case,
the tree-layer architecture is followed in a top down way, that is the ontology
is browsed from the categorization layer down to the mediation layer until the
desired product is identified. If a specific product is required (for instance, an
exagonal-head screwdriver of given brand and model) the architecture is used
bottom-up to classify the product in the associated global concept. The Figure 1
shows schematically the process of standardization of the internal catalog.
2.2 An inter-organizational use of three-layer ontology in a Virtual
District
The relevant issue in developing the e-procurement service is that the differ-
ent purchase requests have to be aggregated into a single order from the e-
procurement service to the supplier that provides the better conditions for the
ordered items. It is supposed that the e-procurement service relies on different
suppliers, each of ones has its own catalog, so from the e-procurement perspec-
tive the problem is: (i) to provide a unified supplier catalog from which the
client companies can decide their orders and (ii) to map the product descrip-
tion of the unified catalog onto the suppliers’ ones. This scenario corresponds
Analysis
of internal Internal catalog
purchase
orders
Service
Integration
and standardization
Purchase Public
Catalog Public
requests Catalog
descriptions
Fig. 1. The internal catalog standardization process
to the well known problem of catalog integration that we analyze with respect
to an inter-organizational use of our ontology construction methodology. In gen-
eral, to enable the integration of more catalogs that list products in overlapping
domains, we need to identify correspondences among similar concepts and to
construct unified representations of them that maintain references to the origi-
nal catalogs. This allows one to search for a given product in the unified catalog
and, after the product is found, accessing to the associated products listed in the
supplier catalogs. The identification of correspondences is required at different
levels:
– different catalogs use different product taxonomies as tables of contents; we
need to establish mappings among the taxonomies since, in general, they use
different terminology and have different organizations (see Fig. 2);
– we need to mediate and to establish correspondences among different repre-
sentations of similar products adopted from different catalogs and possibly
to map them into standardized representations.
A unified catalog represented as three-layer ontology that satisfies the pre-
sented requirements can be constructed as illustrated in the next sections, where
in particular the products are represented as global concepts in the ontology. On
the basis of this ontology, an e-procurement service can be designed to support
the aggregation of purchase requests from the companies of the virtual district.
In fact, if the requests are referred to products chosen in the unified catalog, the
e-procurement service can classify the ordered products of different purchase
requests, aggregate the requests related to homogeneous products into single
purchasing transactions that will regard bigger quantities, so obtaining greater
discounts from suppliers. In this scenario, our thee-layer ontology can be used
according to a top-down perspective, where the e-service browses the ontology
Catalog 1 Screwdriver
Hexagonal- Phillips-
Slot-head
head head
4mm 5mm 6mm 4mm 5mm 6mm 4mm 5mm 6mm
Catalog 2 Screwdriver
4mm 5mm 6mm
Hexagonal- Phillips- Hexagonal- Phillips- Hexagonal- Phillips-
Slot-head Slot-head Slot-head
head head head head head head
Fig. 2. Heterogeneities in taxonomies of product catalogs
starting from the global concepts and reformulates a purchase request made in
terms of global concepts into one referring products in a supplier catalog. The
application of ontology to this context is schematically shown in the Figure 3.
VIRTUAL DISTRICT
COMPANIES
Supplier A
purchase
Company A requests
Catalog A
Company B purchase
requests
e-Procurement aggregated Supplier B
purchase
service transactions
Catalog B
Company … purchase
requests
Unified Supplier …
Catalog
Catalog …
Fig. 3. Tree-layer ontology use in a context of e-procurement
3 Ontology design
To support interoperability and communication in a virtual district scenario,
we proposed a three-layer ontology architecture which provides a unified seman-
tic representation of interorganizational knowledge in the considered domain by
means of ontological concepts and semantic relationships between them [6]. The
ontology is composed by a set of concepts and relationships (inter-layer and
intra-layer links) between them.
Ontological concepts. The three layers of the ontology architecture orga-
nize interorganizational knowledge through three main kinds of concepts:
– XClasses, that are conceptual elements of the original datasources expressed
using a common formalism, the X-Formalism, presented in [4] (semantic
mapping layer);
– global concepts, that are global XClasses obtained by unification of similar
XClasses in different datasources (mediation layer);
– subject categories, belonging to available standard taxonomies (categoriza-
tion layer).
These different kinds of concepts are specified as follows. We assume that in-
formation in the considered datasources is expressed using XML-based or XML-
compliant schema languages. An XClass is thus described by a name, a set
of properties or attributes (with simple or built-in data types, such as string,
NMTOKEN or integer, and some cardinality constraints) and a set of references to
other XClasses (with cardinality constraints). A global XClass is associated to a
cluster of XClasses, that are grouped on the basis of their semantic similarity [5,
9]. A global XClass results from the unification of similar XClasses by means of
rules for the reconciliation of names, types and cardinality constraints of prop-
erties and referenced XClasses. Each global XClass defines a global concept. To
provide topic-based view of underlying layers, global concepts are related to sub-
ject categories relevant to the domain of interest, as provided in several standard
taxonomies. There are several proposals for standard classifications in literature.
In particular, in our work we considered the UNSPSC taxonomy [8].
Figure 4 shows a portion of three-layer ontology built in the VISPO project
to support e-procurement services in a virtual district operating in the indus-
trial supply market. We have considered two on-line industrial catalogs, the
Beta1 and Usag2 catalogs, containing detailed descriptions of their products,
and a third catalog provided by a company of the virtual district with less
detailed product descriptions. From each catalog, we extracted the product
descriptions, represented through XClasses, and we grouped them into clus-
ters on the basis of their similarity in the semantic mapping layer (for ex-
ample, the XClasses Toggle joint shears for sheet-steel and Shears for
sheet-steel). Then, we unified descriptions belonging to the same clusters into
global concepts in the mediation layer (for example, the concept Shears), find-
ing semantic relationships between them (e.g., generalization relationships
between Shears and Blades). Finally, global concepts have been related to sub-
ject categories of the UNSPSC taxonomy in the categorization layer.
Intra-layer and inter-layer links. XClasses, global concepts and subject
categories at different levels of abstraction are related by means of inter-layer
1
“http://www.beta-tools.com/”
2
“http://www.usag.it/”
Tool and General Machinery Categorization
layer
Hand Tools Hydraulic machinery
and equipment
GENERALISATION Forming Wrenches Cutting and crimping
EQUIVALENCE tools and drivers and punching tools
DISJUNCTION
ASSOCIATION Mediation
LINK layer
WEB LINK
Blades
SUBJECT CATEGORY
ONTOLOGICAL Screwdriver
CONCEPT Shears
CLUSTER
Ontological Semantic
concept Mapping
Toggle
Toggle joint
joint shears
shears for
for sheet−
sheet−steel
steel (S1)
(S1)
Shears layer
Shears forfor sheet−
sheet−steel
steel (S2)
(S2)
Global class
Screwdriver
Screwdriver with
with plastic
plastic handle
handle (S1)
(S1) Blades
Blades (S3)
(S3)
Screwdriver
Screwdriver with
with wooden
wooden handle
handle (S1)
(S1)
Screwholding
Screwholding screwdriver (S2)
screwdriver (S2)
Interchangeable
Interchangeable blade
blade screwdriver
screwdriver (S2)
(S2)
Screwdriver
Screwdriver (S3)
(S3)
Web Web
source source
Catalogue S1 Catalogue S2 Catalogue S3
Fig. 4. A portion of three-layer ontology.
and intra-layer links that can be used to browse the three-layer ontology as
explained in Section 4. In the semantic mapping layer, local XClasses belonging
to the same cluster are related each other by means of similar-to relationships,
obtained through the evaluation of their structural and name affinity [5]. Clusters
of XClasses are connected to corresponding global XClasses (global concepts) in
the mediation layer through association links.
Global concepts in the mediation layer are organized by means of semantic
relationships. We consider three kinds of relationships: (i) generalization, a con-
cept α generalizes another concept β if the set of instances of α includes the set
of instances of β; (ii) disjunction, two concepts α and β are disjoint if the sets of
their instances are disjoint; (iii) equivalence, two concepts α and β are equivalent
if the sets of their instances coincide.
Finally, association links are maintained between global concepts and sub-
ject categories in the categorization layer. Subject categories are organized in a
generalization taxonomy.
Ontological elements and intra/inter-layer links are represented in a common
manner by means of the frame structure shown in Table 1, that can be easily
exploited by a software agent for the ontology deployment (see Section 4), apart
from the logical language used to implement the ontology. Note that not all
the fields of the frame structure are always mandatory for every ontological
element. Source links for a global concept are obtained by means of the union
of source links for local XClasses in the associated cluster; in the same manner,
source links for subject categories are the union of source links for associated
global concepts (in the case of leaf subject categories) or of source links for the
specialized subject categories (otherwise in the taxonomy).
Property Description
Name Name of the ontological element
Type XClass, global concept or subject category
Property List of properties of the global concept or XClass, with associated
types and cardinality constraints; empty for subject categories
Kind-of Names of elements that generalize the current one (generaliza-
tion relationship in the mediation and categorization layer)
Equivalent-to Names of ontological elements that are related to the current
one through an equivalence relationship between global
concepts in the mediation layer and a similar-to relationship
between local XClasses in the semantic mapping layer
Disjunction Names of elements that are disjoint from the current one, in the
case of global concepts in the mediation layer
Association Names of elements that are related to the current one by means
of an association link (inter-layer links)
SourceLinks Links to the datasources to which the current element is related
Table 1. The common frame structure for ontological elements.
In [6] we presented a methodology for the construction of the three-layer
ontology, articulated into four main steps:
1. data analysis and conceptualization, to extract XClasses from datasources
and to cluster similar XClasses;
2. integration, to unify similar XClasses into the global XClasses;
3. synthesis and categorization, (i) to define global concepts and semantic re-
lationships between them starting from global XClasses; (ii) to relate global
concepts to subject categories;
4. implementation, to formally represent the ontology and to iteratively refine
and test the ontology concepts.
The construction of the three-layer ontology is supported by artemis [1], a
semi-automated tool environment which supports the domain expert in extract-
ing information from datasources, integrating global concepts, identifying the
semantic relationships and querying the ontology contents. Figure 5 shows the
artemis architecture.
4 Ontology deployment
Domain knowledge ontology is a very useful tool to provide an access point to
the interorganizational information within the virtual district and support dis-
covery of information for business purposes. Several searching modalities can be
exploited in the three-layer ontology, taking into consideration all different levels
of abstraction, experience of user in the considered domain and the kind of the
Wrappers ARTEMIS
Name Affinity
NameAffinity
Affinity Mediator
evaluation evaluation
evaluation
ODL 3
ODLII3 Clustering
Clustering
Structural
Structural Global
Global
XXformalism Affinity
Affinity Affinity
Affinity
formalism evaluation evaluation
totoODL 3
ODLI 3 evaluation evaluation
I
Unification
Unification
XML Extensional
XMLtoto Terminological
Terminological Extensional
Affinity
XXformalism
formalism Relationships
Relationships Affinity
evaluation
evaluation
ARTEMIS
ARTEMISGUI
GUI
Ontology Serching ODL 3
ODLI I3toto
Keyword
Keyworddriven
driven Query
Query extended
search Composition extended
search Composition XXformalism
formalism
Subject Categories
GUI
GUI wrapper
wrapper
Description Query
Querydriven
driven
search
search
CORBA object
Domain
DomainOntology
OntologyGenerator
Generator
CORBA interaction
Access to External Data
Fig. 5. The artemis tool environment architecture.
user: human or software agent. The different searching modalities rely on a set
of primitives that permit to software agents or applications to exploit ontology
searching capabilities and that are listed in Table 2.
Category-driven navigation. The taxonomy of subject categories can be
browsed to find the desired one and visit datasources directly connected to it; it
is also possible to reach ontological concepts associated to that category and use
other searching modalities. According to the portion of ontology shown in Fig-
ure 4, the user can browse the UNSPSC taxonomy from the Tool and General
Machinery category to the Wrenches and drivers category and visualize all
the datasources associated to the second one; the underlying tool environment
supports the user executing the primitives (1) and (2) to browse the taxonomy
and the primitive (7) to visualize datasources.
Concept-driven navigation. Global concepts of the mediation layer are
exploited as starting points to build queries on the global concepts in the con-
sidered domain, propagating these queries towards each involved datasources; in
this manner, only one query is requested on the global concepts describing the
domain, instead of multiple queries submitted to all datasources; moreover, it
is not necessary to know location, terminology and content for each datasource;
results of the queries are obtained exploiting association links between global
concepts and local XClasses and are combined to obtain the query answer to
be presented to the user; we consider a query language proposed by ODMG-93
standard [13], OQL (Object Query Language), a superset of SQL’92 query lan-
guage; in particular, a subset of OQL-like queries is used:
Primitive Description
(1) {Category} generalizationOf (sc) Returns all super-categories of a
category sc
(2) {Category} specializationOf (sc) Returns all sub-categories of a
category sc
(3) {OntologicalElement} elementF rom (t) Returns all ontological elements
whose names contain the term t
(4) “N U LL00 ∪ relT ype getRelationBetween (ci , cj ) Returns the relation type, if exists,
between global concepts ci and cj
(5) { < attrN ame, attrT ype > } attributeOf (ci ) Returns all the attribute names and
types of the global concept ci
(6) { < Concept, relT ype > } relationsOf (ci ) Returns all the concepts that are related
to the concept ci with the corresponding
relation type
(7) { Sources } getSourcesOf (ej ) Returns all the sources related to the
ontological element ei
Table 2. Primitives for ontology deployment.
query ::= select *
from concept 1{, concept 2,...}
[where condition]
This query contains a set of global concepts, a boolean condition on the at-
tributes of them and returns the instances of concepts involved in the query
that satisfy the condition. To perform query reformulation and merging of the
answers obtained from the datasources, we exploit the mapping rules defined in
the mediation scheme, where correspondences between global and local features
are represented. In the considered example, suppose that the user retrieves the
ontological concept Blades through one of the different searching modalities; at
this point, he searches for other ontological concepts that are related to Blades
by means of semantic relationships (the system uses the primitives (4) and (7))
and chooses the concepts related to the current one by the generalization
relationship (in the example, only the concept Shears); finally, he requires data-
sources related to all visited ontological concepts by means of the primitive (7).
Keyword-driven search. A traditional keyword-driven search can be used
to find desired ontological concepts (both at global and at local level of ab-
straction); users can specify one or more keywords and these terms are matched
against the ontology, comparing them with names of ontological elements: (i)
in case of names of global concepts, sources related to the matching concept
and to its specializations are considered and the list of URL of these sources is
presented to the user; (ii) in case of names of subject categories, sources related
to the matching category and to its subcategories are considered and the list of
URL of these sources is presented to the user. When more than one keyword is
specified, the search is repeated for each keyword; in particular, if the keywords
are concatenated by the AND operator, we consider the intersection of results
obtained for single keywords, while if the keywords are concatenated by the OR
operator, we consider the union of the results. As an example, the user speci-
fies the keyword Screwdriver; the system visualizes all ontological elements that
contain the word screwdriver or its synonyms using the primitive (3); the result
of the search is the ontological concept Screwdriver and local XClasses belong-
ing to the associated cluster; the system visualizes the corresponding datasources
using the primitive (7).
Experience of the user about the considered domain and the ontology struc-
ture influences the choice of the searching modality: users with less experience
generally prefer the category-driven or the keyword-driven search, while the
concept-driven search requires more knowledge about query formulation (even
if graphical interfaces are used to support this task) and about use of SQL-like
query languages. An ontology-based search engine (for which we propose an ar-
chitecture, described in Figure 6) provides users with an overview of categories,
concepts and relevant relationships in the considered domain, supporting them
in determining the information that better matches their needs. This kind of
search engine can be considered to be complementary to traditional Web search
engines which are based only on keyword occurences.
Query Keyword
Navigation
composition insertion
interface
interface interface
Query−driven Keyword−driven
Navigation
search search
module
module module
Ontology−based
search engine
Search results
Fig. 6. Architecture of an ontology-based search engine.
5 Conclusions and future work
In this paper we have proposed an ontology-based approach to support interop-
erability and communication in interorganizational applications, where different
organizations cooperate and share information to expand their market possibil-
ities. Our approach organizes ontologies in three abstraction levels to represent
the interorganizational knowledge, providing a global view on heterogeneous
datasources, where the same information can be represented in different ways.
Several searching modalities to exploit the proposed ontological representation of
knowledge are provided. A semi-automated tool environment both for ontology
design and for searching support is being completed.
Future activities are devoted to the refinement of the representation language
to express ontological concepts and semantical relationships at each level of the
ontology and to the study of methods and technologies for domain ontology
test, reuse and consistency checking, also in the framework of the European
INTEROP network of excellence.
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