POTENTIAL ADVANTAGES OF SEMANTIC WEB FOR
INTERNET COMMERCE
Yuxiao Zhao, Kristian Sandahl
Dept of Computer and Information Science, Linköping University, S-58183, Linköping, Sweden
Email: [email protected], [email protected]
Keywords:
Semantic Web, Internet commerce, Application
Abstract:
Past decade saw much hype in the area of information technology. The emerging of semantic Web makes us
ask if it is another hype. This paper focuses on its potential application in Internet commerce and intends to
answer the question to some degree. The contributions are: first, we find and examine twelve potential
advantages of applying semantic Web for Internet commerce; second, we conduct a case study of eprocurement in order to show its advantages for each process of e-procurement; lastly, we identify critical
research issues that may transfer the potential advantages into tangible benefits.
1 INTRODUCTION
To consume remote data, an entity has to face
two issues: (1) how to access to them; and (2) how
to understand their meanings. Humans can consume
Web data, because (1) Web provides a mechanism to
access to them; and (2) humans themselves are able
understand their meanings. Computers also could
consume Web data, because (1) they can access to
them by using the same mechanism as humans; and
(2) they could understand their meanings via
semantic Web (SW). SW is not a separate Web but
an extension of the current one, in which
information is given well defined meaning, better
enabling computers and people to work in
cooperation (Berners-Lee et al 2001). So far, no way
has been found to allow computers to simulate
humans’ capability in understanding the meanings.
However, an ontology-based method can ease the
problem to some extent. Although the method is not
explicitly new, the upcoming scale and scope of
deployment over the Web offers great potential as
well as challenges (Linden 2001).
The essential element of SW is the ontology of
concepts used in the domain. The ontology can
represent relations between concepts in taxonomies,
such as equivalence, part-of, and is-a. In addition the
ontology can represent rules for logical reasoning
about concepts. Assume, for instance, that you are
searching the Web for graduate students in
information systems. Your ontology can help expand
the search by representing the equivalence of the
terms graduate student and doctoral student. Thus
you will not miss people just because of the different
wording on the Web pages. A more advanced
example is to employ a taxonomy of university
subjects and thus noting that information systems
can be part-of departments of economics, computer
science etc. The intention is that the ontology should
be used by all actors in the field of businesses
thereby easing information exchange. As an example
of an inference rule, the university ontology knows
that every graduate student has at least one thesis
advisor. Once you find an interesting graduate
student, call him Ted, it becomes possible to search
for other graduate students of the advisor of Ted.
Currently SW is coordinated by W3C Semantic
Web working groupi and is based on XML, XML
Schema, RDF/RDFSii. The Web ontology language
(OWL)iii, the key enabling technology of SW, is
proposed and being built from the DAML+OILiv
(Hendler and McGuinness 2000; Fensel et al 2001a;
McGuinness et al 2002; Fensel 2002).
It is well known that SW can be applied in Web
annotations, software agents and Internet commerce.
For Web annotation, it has been broadly studied
(Heflin and Hendler 2001; Noy et al 2001; Nagao et
al 2001; Euzenat 2002a). It intends to: (1) develop
basic ontology syntax and tags based on
RDF/RDFS; (2) develop ontology-based rule
reasoning; (3) build a domain ontology using
ontology authoring tools; (4) create the ontologybased metadata for a Web content; and (5) find the
right information via advanced search engine.
For software agents, numerous applications have
been dreamed and/or created (Berners-Lee et al
2001; Hendler 2001). Recent publications saw the
apparent trend of combining SW and Web service,
which is a software application identified by a URI,
whose interfaces and bindings are capable of being
defined, described and discovered as XML artifacts
(Austin et al 2002). It is to develop distributed and
loosely coupled Internet computation. At least two
projects are found: DAML-S (DSC 2002) and SW
enabled Web services (Fensel et al 2002). The
former is to build DAML+OIL ontology for Web
services in the application level in order to enable
such tasks as discovery, invocation, interoperation,
composition, verification and monitoring of Web
services. The latter aims to create a Web service
modeling framework, a discovery mechanism and
some scalable mediation services.
For Internet commerce, although the applications
of SW have been paid attention and extensively
mentioned (Berners-Lee et al 2001; Hendler 2001;
Fensel et al 2001a; McIlraith et al 2001), it is still in
the initial phase and lacks convincing benefits and is
difficult to evaluate (OWS 2002). This paper
highlights the applications of SW for Internet
commerce, aiming to find its potential advantages so
as to define critical research issues for transforming
these potential advantages into real or tangible ones.
So we target those readers who try to combine SW
and Internet commerce for producing novel valueadded applications. Note that the concept of Internet
commerce here is broad, not only focusing on the
activities of electronically buying and selling but
also including its related business processes.
This paper is organized as follows: Section 2
identifies potential advantages of SW for Internet
commerce. Section 3 presents a case study for eprocurement to show the potential benefits of SW in
each business process. Section 4 provides some
research issues for SW to be applied for Internet
commerce. Section 5 concludes the paper.
2 POTENTIAL ADVANTAGES
The essence of SW is to develop ontology-based
semantics in terms of some standards, thereby
making information given formal, explicit meaning
and thus machines understandable. The semantics
can cover any structured or non-structured data and
applications, such as Web sites, Web services,
devices, flow data, databases.
Ultimately derived from semantics and standards,
twelve SW advantages over previous Web have been
identifiedv. But it is under investigation whether
these advantages can be utilized to create real ROI
(return on investment) for end users. The detailed
examinations one by one are as follows.
A1. Search
SW enhances search mechanism with respect to
exactness and amount because of the standardized
Web annotations and service descriptions. Currently
keyword searching creates the all-or-nothing results.
Ontology-based searching uses the relationships and
axioms of concepts, thus it could filter some
seemingly appropriate but unwanted results and add
some seemingly different but actually same results.
The advantage has been confirmed in the arena of
information retrieval (OWS 2002), while Schreiber
et al (2001) believe there is a long way to go to
actually prove that ontology-based search is better
(in some respects) than keyword search.
Internet commerce has to search for the right
products and services, business partners, customers
and Web services. One of hard ebXML (e-business
XML) issues is to search exactly what we need and
how to search core components that represent
business processes (Hofreiter et al 2002). Ontologybased search could help ease the difficulty.
A2. Agents
Agents are programs acting on behalf of another
person, an entity or a process. Intelligent agents are
widely known and useful for application automation
and Internet commerce (Hendler 2001; Blake 2001).
For example, Hendler (2001) indicated that
ontology-based intelligent agents could obviously
enhance application integration and thus improve
Internet commerce. Cost et al (2002) developed an
intelligent online service called ITtalks that
facilitates user and agent interaction for locating
talks on IT. Payne et al (2002) developed a semantic
calendar agent.
A3. Knowledge management (KM)
KM includes the processes of capturing,
extracting, processing and storing knowledge.
Ontology allows Web data meaningfully related
instead of existing linked Web, no matter whether
they are structured or non-structured (Heflin et al
2002). Fensel et al (2001b) addressed structuring,
standardizing, aligning and personalizing various
contents in B2B (Business-to-Business) ecommerce. Casati and Shan (2002) showed how to
improve business analysis by introducing the
semantics of business process execution data.
The advantage of KM is realized via ontology
manipulation, which needs support tools, e.g.,
ontology creating (Noy et al 2001), ontology
learning and manipulation (Staab et al 2001;
Maedche and Staab 2001). OWS (2002) categorized
the tools for ontology-based applications into five
types: ontology-related inference engines, topic
maps, content management, information retrieval
and information visualization.
A4. Integration
Integration here indicates business cooperation as
an entity, internally and externally, to achieve
business goals. Ontology can be used for specifying
the terminology of heterogeneous systems, and
ontology mappings can resolve the mismatches
between the systems, thereby realizing semantic
integration (Cui et al 2002).
SW technology could ease the messaging
between applications and foster software component
reuses and B2B automation. The combination of SW
and Web services is changing the integration
between applications internally and externally,
thereby enabling standardized, searchable and
intelligent agents on the Web. The semantic B2B
engine is emerging to allow business partners to
understand document syntax and semantics, and thus
to transfer the exchanging documents into the right
applications to process (Bussler 2001).
A5. Composition of complex systems
It is possible to compose numerous Web services
and Web contents to produce one more complex
system (Piccinelli et al 2001; Casati and Shan 2001;
Fensel 2002; Sheth et al 2002; Euzenat 2002b). The
complexity reflects that the composed system could
statically and dynamically span multiple decoupled
Web services and contents with complex workflow,
involving discovery, substitution, composition and
management. In addition, we also have the nonfunctional requirements such as availability, security
and trust (O’Sullivan et al 2002). Some scalable
mediation services are needed for direct connectivity
(Fensel et al 2002).
So far there exist two representative composition
languages: DAML-S (DSC 2002) and Business
Process Execution Language for Web Service
(BPEL4WS 2002), which is a merger of Web
Services Flow Language (Leymann 2001) from IBM
and XLANG (Thatte 2001) from Microsoft. If it
becomes realistic, the composition could create a
new software development model and a new
industry conducting software composition.
Internet commerce spans multiple organizations
and thus the composition may be very suitable for it,
especially for automatic negotiation and contracting
(Maes et al 1999; Hummer et al 2002; Ströbet 2002).
A6. Multimedia collection
A collection handles a set of non-textual objects
such as images and audio. SW via ontology offers a
way to enable semantic annotations that could be
easily organized and found (Schreiber et al 2001;
Heflin et al 2002). Nearly all e-commerce Web sites
have to handle a large amount of images and audio
of products and services.
A7. Information filtering
Information filtering occurs in the processes of
information receiving, sending and storing by
filtering unwelcome data and Web services
invocation, sending selectively to the right clients
and storing in the right place for the value-added
consumption. An enterprise always has to process a
huge amount of e-commerce data. Theoretically
filtering via semantics could be more effectively
than keyword filtering.
A8. Machine dialogue across the domains
Ontology provides formal semantics, thereby
making not only humans but also machines
understandable. In addition ontology mappings or
translation could foster the understandings between
domains so as to enable the dialogue across multiple
domains. Ontology translation could bridge them.
Internet commerce requires automatic negotiation
and contracting for all searched results. This feature
could significantly help machines process a large
amount of business partner information that humans
cannot handle, and thus save time and money.
A9. Virtual community
Some enterprises for common interests can be
tightly connected on the Web and form a virtual
enterprise, due to the mutually benefited preferences
defined in terms of ontology. Ontology also can be
used to define relationships in the community from
forming, organizing, communicating to demising
automatically.
A10. Online advertising
Online advertising can be exposed via more
easily and more exactly searched ways. It not only
waits for humans to click but also for machines to
consume. It could be found through efficient search
engines and processed by software agents, and thus
directly contribute to Internet commerce. As one of
DAML projects, the Software Agent Group of the
Robotics Institute, Carnegie Mellon University,
Nokia Research Center and German Research
Center for AI have been researching on agents and
tools for advertising and brokering.
A11. Serendipity (unexpected benefits)
The business partners normally tend to be quite
fixed, stable and long-term. Through SW techniques,
there is a higher possibility of finding unexpected
partners, customers as well as superior products and
services, and thus collecting benefits (Heflin et al
(2002). Probably serendipity service providers will
emerge to help collect the benefits.
A12. Vocabulary flexibility & standardization
Theoretically, ontology mappings and translation
allows users to flexibly choose the words they like.
Since users are diverse and it is hard to require them
to fully know the standards, this advantage could be
interesting.
In practice, Fillies et al (2002) demonstrated in a
financial group how to create a central vocabulary
within an ontological context, to standardize the
concepts, and to improve the communications
between different departments.
Flexibility and standardization seem conflicting.
In fact they reflect different developmental stages of
SW. In the initial stage, vocabulary standardization
could be prioritized, whereas with the emerging and
maturity of ontology mapping or manipulation tools
the advantage of vocabulary flexibility will show up.
3 E-PROCUREMENT AS A CASE
STUDY
To apply SW in e-procurement, there are two
possible approaches: centrally and distributed. By
centrally, the suppliers register their profiles in some
centrally distributed registries so a buyer can search
them, e.g. UDDIvi. So far nearly all e-procurement
software takes this way. By distributed, the suppliers
build their Web sites and specify the metadata in
terms of some standards that guide each buyer to
exactly find themvii. E-procurement software
normally doesn’t take this way, maybe because it
demands thoroughly elaborated data. Conversely,
knowledge management software almost takes this
way.
E-procurement software is normally built for
three cases: (1) B2C (Business-to-Consumer); (2) e-
marketplace for m suppliers and n buyers; (3)
Auction-based pricing for m suppliers and one
buyer. Our case study just focuses on (3).
For the scenario of unknown business partners, a
business partner needs to find the right partners
through registry and search mechanism. The
following automatic functions for one buyer are
necessary: (1) the buyer registers its profile and
preferences so as to let any suppliers know its
buying interests and related data such as credit
status; (2) the buyer finds a set of the right suppliers
quickly; (3) the buyer negotiates with the suppliers
one by one with the least human involvement; (4)
the buyer makes the contract with the right suppliers.
For the scenario of known business partners, the
transaction continues with the following automatic
functions for a buyer: (5) the buyer receives the
purchased products with the right quality and date;
(6) the buyer pays the supplier according to the
contract.
For each process, Table 1 shows basic tools and
agents, special tools and agents needed for Internet
commerce, and potential advantages using SW.
Table 1.
# Process
Basic Tools and Agents
1. Register a
profile
A tool to register.
2. Search
the suppliers
Search engine on the Internet
and local knowledge base;
Extract/analyze the data;
Filter the suppliers;
Receive the data of the new
suppliers.
3. Negotiate
with
suppliers
Ask the unspecified info;
Feedback to suppliers;
Find the feasible supplier(s);
Inform the suppliers.
4. Contract
with
suppliers
Send/receive the contracts;
Dynamically handle exceptions;
Build and add the knowledge
base of suppliers.
Trace the transportation;
Receive the products;
Check the quality;
Report the results.
Link the results with contracts;
Pay for the purchase;
Add the knowledge base.
5. Confirm
the
purchases
6. Pay the
suppliers
Tools and Agents for Internet
commerce
What data items to be registered;
How to certify the data integrity;
How to handle the dynamics.
Highly precise search and process
without missing the critical suppliers;
Catalogue change management;
Benchmarking is needed.
Prioritize the suppliers with quality,
delivery and past relationships;
How many rounds to negotiate;
When human intervention is needed;
How to collectively bid.
Legitimate issues;
Insurance mechanism.
Exception handling;
Quality checking.
Security and reliability;
Invoicing and statement;
Continuous improvement.
Potential Advantages
A12. Flexible vocabulary
A1. Search
A2. Agents
A3. KM
A6. Multimedia collection
A7. Information filtering
A10. Online advertising
A11. Serendipity
A12. Flexible vocabulary
A2. Agents
A3. KM
A4. Integration
A8. Machine dialogue
A11. Serendipity
A4. Integration
A5. Composition
A7. Information filtering
A9. Virtual community
A3. KM
A4. Integration
A5. Composition
A3. KM
A4. Integration
A5. Composition
In short, the SW technology could be applied in
the following aspects:
1. Searching for more exact and relevant data
using flexible words, e.g. products and services.
2. B2B automation and ubiquitous computing via
intelligent agents.
3. Online marketing through ontology-based
metadata description, thereby resulting in being
easily searched and processed.
4. Using flexible vocabulary for annotating and
registering Web contents and services as well as
communications.
5. Virtual community formed through ontologybased computing.
6. KM enabling dispersed and unlinked
documents (customer information and product data)
to be organized.
7. More complex workflow management calling
for sophisticated mediation services such as
ontology mappings and mergers.
4 RESEARCH ISSUES
It is not easy to apply SW in Internet commerce,
mainly due to the obvious contradiction between the
opennessviii of SW and the serious requirements for
Internet commerce. Besides some common issuesix,
the following issues can be critical.
To demonstrate the benefits of SW for Internet
commerce, one of the direct ways is to develop some
applications using SW and to show its tangible
benefits and technical maturity if possible. We can
conduct the following experiments: growing the
applications from the simplest business process to
more complex ones. For instance, (1) it is interesting
to build an agent to automatically and dynamically
create a new catalogue of the suppliers or to modify
the existing one. Thus the dynamic catalogue
providers may reduce the workload of buyers and
enhance the performance of buying. (2) An agent is
needed to automatically report the special sales from
many suppliers. (3) A filtering agent filters those
unwanted information and malicious codes.
One fundamental issue for Internet commerce is
lack of basic ontology for the domainx. This
ontology should lay a solid foundation for future
development and may cover the existing standards
(Zhao 2001; Zhao and Sandahl 2000), e.g. EDI
(Electronic Data Interchange), OBI (Open Buying
on the Internet), ebXML, UDDL, RosettaNet and
xCBL (XML Common Business Library), involving
the
classifications
of
business
processes,
components, products & services, geographies as
well as linguistics and currency. For example, UDDI
selects the North American Industry Classification
System (NAICS), the Universal Standard Products
and Services Code System (UNSPSC), and the ISO
Geographic taxonomy (ISO 3166) (Curbera et al
2002). These taxonomies are available in the nonontology forms and certainly can be reused to build
the ontology in terms of the existing ontology
languages such as DAML+OIL and OWL (Zhao
2003). Without basic ontology it is fairly difficult to
start; or if started, it has created new integration
issue. So it urgently demands building/organizing
the ontology. How to do that is an open issue. 1.
Two ways could be taken, either combining these
taxonomies and/or the existing ontologies into one
or translating each one and then keeping them
consistent through some mediation services. 2. For
the first way, what are the criteria to evaluate if the
single ontology is complete and efficient enough to
support the related applications? What are the
theories behind ontology conflict detection,
resolution and merger? 3. For the second, what are
the mediation services and who will maintain them
and how the services from multiple vendors are
integrated? 4. Both may need to show how to link
the well-known vocabulary such as WordNet, and its
usability.
Semantic routing could be interesting. Semantic
routing, differentiated from normal routing without
considering the meaning of the message, is to route
the requesting service to the right responding
services at the application level by processing its
metadata and contents. Two cases exit. One is for
the processes of dynamic service composition on the
Web, which demand analyzing the semantics of the
requesting service, decomposing it to multiple
services to meet the objectives, routing each
responding service to the right one among many
options, and composing the whole service. The other
is to route the requesting service outside an
enterprise to the right applications/services inside
the enterprise in terms of availability, geography,
pricing, and/or response time. Semantic routing
could be applied to enhance the intelligence and
dynamics of supply chain planning in e-business.
Another issue is the migration. Taking advantage
of SW technology is subject to the existing
technology and related investments. Some
conditions and infrastructures are significant and
unchangeable in some period of time, for example,
no standardized ontology language, the extent of
business partners’ adoption, interoperability, etc. To
leverage SW technology in Internet commerce, it
cannot ignore the past investments in the exiting
techniques. The obvious benefits of running both
technologies in parallel can enhance the quick
adoption.
Special inference engine for Internet commerce
should be studied. Are there any special
requirements of ontology inference rules for this
special domain? If so, are they sufficient to be
expressed in current inference tools? And how can
we improve them?
5 CONCLUSIONS
To achieve the dream applications for Internet
commerce depicted in Berners-Lee et al (2001),
there is a long way ahead. SW enriches current Web
with semantics in terms of some standards and could
improve Internet commerce from several aspects. It
is potentially beneficial to enhance the exactness and
amount of Internet search, independent intelligent
agents, knowledge management, integration between
applications (internally and externally), composition
of complex systems, multimedia collections,
information filtering, machine dialogue across
domains, virtual community creation, online
advertising, serendipity, as well as vocabulary
standardization and flexibility. Our case study shows
how the potential advantages could be useful in the
identified processes of e-procurement. Several
research issues are proposed for collecting real
benefits of SW for Internet commerce.
ACKNOWLEDGEMENTS
We would like to thank Andreas Borg for his
suggestions and two anonymous for their comments.
This work has been financed by SSF (Swedish
Strategic Foundations) through ECSEL (Excellence
School in Computer Science and Systems
Engineering in Linköping), Linköping University,
Sweden.
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i
http://www.w3.org/2001/sw/
Resource Description Framework and RDF Schema,
http://www.w3.org/RDF/.
iii
http://www.w3.org/2001/sw/WebOnt/
iv DARPA Agent Markup Language + Ontology Inference
Layer, http://www.daml.org/.
ii
v
We attempt to categorize these twelve potential
advantages as business and technical advantages. But we
find it hard because their relationships are interweaving
and the categorization may cause unnecessary
misunderstandings.
vi Universal Description, Discovery and Integration, see
http://www.uddi.org/.
vii Schatz (2002) provided a distributed way to navigate
concepts through semantic indexing locally and an
analysis environment to navigate the indexed contents.
Ontology is used to glue concepts, categories and
collections for further development. But it didn’t
mention feasibility for handling business processes.
viii One of motivations of RDF design is applied in
applications that require open rather than constrained
information formats (e.g. scheduling activities,
describing organizational processes, annotation of Web
resources, etc) (Klyne et al 2002). Euzenat (2002b) also
emphasized the openness of SW.
ix For example, more skilful professionals in XML, RDF,
ontology, artificial intelligence, etc; tightly cooperation
with industry standards; ROI demonstration; service
pricing; stable and neutral specifications; privacy &
trust.
x Many exist in http://www.daml.org/ontologies/, but they
look in the rough state and lack validation and
verification but they do offer a quick start. McGuinness
(1999) built the huge ontology for e-commerce but we
cannot find its source so far. Fensel et al (2001b)
presented the prototype ontology of product catalog in
terms of UNSPSC. Lack of basic ontology results in
building individual ontology from scratch and/or using
various ways: DTD, XML Schema (Ströbet 2002),
RDF/RDFS (Fillies et al 2002), DAML+OIL (Cost et al
2002), DAML-S (Paolucci et al 2002), or multiple ways
like Payne et al (2002) using ways of RDF, DAML,
DAML-S, etc.