ASSURE: Case for Support

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22 Οκτ 2013 (πριν από 3 χρόνια και 9 μήνες)

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Case for Support


"There is strong evidence that high levels of rural business aspiration are not being translated into
their full potential for growth, whilst high levels of entrepreneurship are not bringing with them
commensurate leve
ls of wealth creation”, that “[t]
here is also strong evidence that rural businesses
struggle to […] work effectively in partnership to address the obstacles they face” and that “[r]ural
areas need support to pioneer forms of brokerage and create virtual cl
usters or networks to access
such services and share good practice.”

(Burgess, 2008).

Social networks offer means for people to express their interests, views, etc. within a certain area,
link to and interact with others with similar interests, and, to som
e extent, discover others with
similar interests/views. These technol
ogies, through systems such as l
.com and r
are now becoming prevalent in the modern “wired” business world, with services intended, for
example, to help establish new busin
ess partnerships. These systems, effectively, provide a single
“shop front” for individual entrepreneurs or companies, presenting externally available information to
any other subscriber of the system. Potential partners are identified through keyword sear
ches or
browsing established business links. Such systems are restricted in the level of information available

typically high
level skills or service keywords

and hence offer only an initial point of contact that
may be followed up through traditional
means (face
face or virtual meetings, email, etc.). They
can, however, support the development of new business partnerships, but are most effective if the
number of subscribers is high.

At the same time, extensive research has been conducted in systems
for the (semi
gement of business processes (Jennings et al., 2000)
, the formation of coalitions to meet
identified market needs
(Norman et al., 2004;
De Roure
et al., 2005; Wang and Pan, 2007; Heath
and Motta, 2008)

and exploring important i
ssues such as security

and trust in such systems (Kagal
et al., 2004; Burnett et al., 2010)
. These systems rely upon the availability of detailed service
descriptions, often the existence of multiple, transferable, service providers, and (ideally) operate
trusted virtual marketplaces that treat all service providers equitably. Effort is required on the part of
service providers and consumers in ensuring that their offers and requirements, respectively, are
comprehensively and accurately described, and tr
ust must be placed in the system that privileged
service/costing information is kept secure. If these barriers to involvement can be overcome, these
systems offer significant benefits in opening new markets to businesses.

Many of the assumptions that under
pin the success of social networks and virtual marketplaces are
not necessarily valid in rural economies. In rural communities there is greater awareness of other
businesses in the area, but not necessarily the details of the range of services that may be
on offer.
Businesses tend to be smaller, but often more diverse in the range of services they offer. There are
fewer instances of the same service offering, and hence the benefits of open virtual marketplaces
are not so clear. In fact, the characteristics
of the business environment within rural communities are
such that interaction is more focused on collaboration than direct competition. The question here is:
how the benefits of social networking, semantic web and intelligent agent technologies be combine
to better support the formation of new and resilient business partnerships in rural communities?

Rural enterprise is not exclusively inward focussed, however. A critical issue in sustaining and
developing rural economies is for rurally located businesses

and entrepreneurs to compete in a
global marketplace. The use of social networking technologies can aid in reducing the impact of
barriers to collaboration due to location. The limitations of these technologies outlined above
remain, however: they provide

only simple (keyword search/browse) matchmaking services. The
question here is, therefore, how the benefits of social networking technologies be enhanced using
semantic web and agent technologies to better support and sustain rurally located business
ete in the wider marketplace?

Technological Focus

Social networks are designed to capture and support relationships between individuals, but
relationships are varied and have different social norms associated with them. The relationships
between individual
s may also vary over time and according to the context of the interaction between


them. Intelligent agents are highly suited to supporting interactions between individuals with such
complex interrelationships and dependencies. In this way, agents do not op
erate automatically
within, say, a marketplace, but work to support (teams of) human decision
makers; for example, in
supporting dialogue i
n a joint planning activity (Sycara et al., 2009)
. Such agent
based support has,
to date, been oriented to small grou
ps or pairs of individuals with shared goals, and so there is an
open research question concerning how these techniques can be scaled up to larger and looser
social networks, as well as how to perform dynamic semantic matchmaking based on real
data and knowledge from social network and business related data sources. There are,
however, technologies emerging that are oriented to such systems, including models developed by
the Semantically
Interlinked Online Communities (Breslin et al., 2007)

ect and the
Interchange Format (Rahwan et al., 2007)

The vision of this research project from the perspective of computing science is to explore how
agents can support individuals and groups in identifying business connections, provide accessibl
explanations of suggested partners given identified or specified needs, ensuring that individual
privacy policies are respected, and supporting dialogue within teams. This research vision is, we
believe, highly relevant for the development and support of

rural business networks and for the
support of rurally located businesses competing in a wider market.


illustrate some of the ideas presented above, consider the following scenario (suggested during
a meeting with partners in Cybermoor):


A small, rural
ly located design company receives a significant order for marketing materials
to be developed, printed and delivered. They have an existing contract with an ISP for
standard business applications such as email, website hosting, etc., and have worked with
reliable, high
quality printing firm in the past. The problem is that to deliver on this order they
need to identify a company that can provide reprographics services and need to transfer
large files with their partners that require greater bandwidth tha
n normally provided in their
contract with the ISP.


Through the
system, the
designer needs to identify potential reprographics
companies that can deliver a service within the timescale required. The system can support
this through matchmaking agains
t the service requirements specified by the designer.
Alternatively, the printing company may recommend an appropriate service provider that
they trust. Once identified the designer
contacts and engages in dialogue with
both the
printers and potential repr
ographics companies. Aided by an agent supporting the

goal of
a workflow for delivering on the order
the designer establishes an agreement
among them.


Individually or as a group they then approach the ISP (or ISPs) to put in place a short
higher bandwidth service the enable them to transfer files during the enactment of the


agreed workflow (or plan) is then managed in a decentralised manner by the agents
supporting each member of the team, and the order is delivered to spe

Each stage of this process

identifying potential business partners, establishing agreements
between them, adapting the team where necessary, and the construction of a joint plan of action
would, we envisage, be supported by intelligent agent
s that can identify options, present them in a
coherent way to decision
makers, support various types of dialogue between them (e.g. negotiation
and deliberation, or joint planning, dialogues), and keep track of decisions made and justifications
for those

Social Science


The current debates about social capital emphasise the role social networks in building community
cohesion. These social networks develop through and are enhanced by participation in associations
and civic life and a corolla
ry of this participation is the development of bonds of trust, which are a
prerequisite for collective social action
(Putnam, 2000, Halpern, 2005)
. Some studies have
emphasised the role of social

capital in improving business opportunities and here most stu
have focused upon business

links at a local level
(Uzzi, 1997)
. Regional policies have tried to build
on these findings through creating opportunities for interaction through business clusters and
business parks. However, rural busines
ses are usually small, frequently isolated by distance and


therefore less able to take advantage of this kind of business networking

(Rusten and Skerratt,
. Business associations such as the Chamber of Commerce try to bring together these
businesses to promote linking and to assist with representation of the business community more
generally. Other kinds of bus
iness clusters might emerge from other initiatives

the initiative “Plan
for Success” from Scottish Enterprise is one such example. Recent research suggests that it is
through sharing knowledge rather than acting in competitive isolation that
business ca
n be more

and indeed that information technology might be promoting this kind of sharing
communication culture
(Rifkin, 2009)

Research has suggested that infor
mation and communication technologies (ICT) can enable the
development of growth
oriented rural SMEs (Deakins et al. 2004). Technology, such a social
networking and workflow management systems, can help to reduce the impact of remoteness and
increase the g
lobal reach of businesses. However, as Smallbone and North (1999, cited in Huggins
and Izushi 2002) note, remote rural businesses are less likely than their urban counterparts to be
exposed to technology because they have fewer opportunities to interact wi
th other local
organizations that may be using such technologies, and also have a lower propensity to work with
larger organizations from which transfer of ICT understanding might take place and through which
ICT expertise may be developed. Where rural bus
inesses do trade beyond their local markets they
tend to be more sophisticated users of ICT (Grimes 2005). Furthermore, it is not clear whether I
has an enhancing or inhibiting role on the formation of social capital
(Huysman and Wulf, 2004)
The existence of strong social networks for example is a factor in the success of establishing
electronic networks
(Fukuyama, 1995)
. On the other hand, other evidence suggests that I
T can
help to create or enhance social capital
(Huysman and Wulf, 2004)
. The expandi
ng role of electronic
networking through media such as Linked
In, Facebook and other social networking sites would
suggest that electronic networking makes increasing use of “weak ties” to build communities of
interest or to find information (for example i
n searching for jobs)
(Granovetter, 1974)

and also by
helping businesses communicate with each other

even if they do share the same site
. This would sugge
st therefore that it can at least facilitate network ties and communication.
However, it seems clear that in rural areas, with dispersed populations and thin nets of enterprises,
electronic communications would lend themselves to better networking.

y rural small businesses tend to concentrate their efforts in supplying local markets rather than
reaching out into wider markets, though it has been noted that ICT can help to reduce the impact of
remoteness and increase the global reach of rural business
es (Deakins et al. 2004). Writers have
pointed to the need for areas that traditionally have low uptake of ICT to have appropriate methods
for stimulating the adoption of computer
based systems (Huggins and Izushu 2002). This suggests
that there is a perce
ived problem of incompatibility between solutions offered and the needs
perceived by rural enterprises. It is, therefore, important to understand the extent to which proposed
solutions meet the real needs of rural businesses. An desirable starting point in

developing tools for
use by rural enterprises is therefore to understand how, if at all, rural enterprises use ICT
networking to interact with other businesses or agencies serving rural communities, and how rural
enterprises envisage collaboration s
upport tools could aid them in growing and developing their

The research questions would focus upon: (i) identifying any (if they exist) ways in which rural
enterprises (or other enterprises) use networking sites and tools in developing busine
ss relations,
and to understand how such tools could be used; (ii) to what extent IT links can strengthen existing
social capital (frequency of communication, creating shared communities of interest, developing
trust etc.); (iii) to what extent this streng
thening of social capital might lead to enhanced business
opportunities/activities/growth/efficiency; (iv) what opportunities and barriers there are to inclusion in
IT networks of this kind; (v) establish what kind of networking tool works best for this gr
oup through
creation of the tool; (vi) the impact of the collaboration tool on relationships factors, such as trust
and ways of working, as the tool is deployed, and whether this may lead to suggestions of new
collaboration models.

Outline Project Plan

The aim of this project is t
o understand the impact of existing social networking technologies in
developing and sustaining rural enterprise, and to evaluate how Semantic Web and Agent
technologies can be exploited to enhance and add value to rural busines
s networks.



In meeting this aim, we will focus the research on the following work packages, work package 3
building upon work within 1 and 2, work package 4 building upon 3 each building upon each other:


Assess how existing social networking technologies a
re used by rural businesses both within
communities and to support wider collaboration. For what purpose are they used in what
business sectors, what are the perceived benefits and in what ways can these benefits be

In some user communities, no

such systems may be used at present, and during
this stage of the project we will work with user communities to provide off
shelf social
networking systems (e.g. and investigate their use to provide a baseline for
future developments. [m
onths 0


Development of an early prototype ASSURE systems that incorporates elements of semantic
matchmaking and agent technologies that extends an existing off
shelf social networking

[months 0


Explore, through mechanisms such as focus
groups, surveys and structured interviews (to
be decided), the possible ways in which semantic matchmaking and intelligent agent
technologies could enhance existing, and facilitate the formation of new business
collaborations. This exercise will be run joi
ntly by social and computing science researchers,
and utilise the prototype ASSURE system. Issues of trust and information security will be
explored with stakeholders in this context.

[months 12


Refinement of ASSURE system in response to outcomes of ea
rly evaluation exercise. This
refinement may operate as a process of co
creation between end users and computer
scientists facilitated by the social sciences Research Fellow (to be appointed).

[months 15
23 (core); continuing months 24
35 (refinement & tec
hnical evaluation)]


Deploy and evaluate a stable version of the ASSURE system with an existing rural business
community (identified in objective 1) with the aim of assessing the impact of next generation
social networking systems on rural enterprise.

hs 24

A key component of this research agenda is to examine and assess the impact of the use of ICT to
support rural enterprise. This will involve a p
reliminary investigation with the group develo
through Scottish Enterprise’s
“Plan for Success”
. The network (consisting of about 20
30 businesses) is regionally based and has been reinforced by infrequent communication

face contact at
dinners, seminars

etc. The group are keen to expand their activities but have
variable knowl
edge of IT.

In order to measure impact it would be necessary to first gather “base line”
material and then to look at how interaction was transformed during the

course of the project
. This
would therefore proceed in a series of

stages as the project develo

Stage 1:

Attend a

meeting of the network and introduce the project. Elicit consent to


the project.

Stage 2:

Administering a questionnaire to all network participants to find out the extent of their
involvement in the network, how it hel
ped or hindered their business, to what extent they used IT
either personally or professionally.

Stage 3
: Introduce a fairly simple social networking technology geared towards business needs and
provide training to use it.

Evaluate how it has been used

rough in
depth interviews.

Stage 4
: Introduce more sophisticated applications having taken into account the needs of the
network and the evaluation at Stage

3. Co
production of materials.

Evaluate this stage through in
depth interviews

Stage 5:

re and f
inal evaluation.

Presentation of the findings at a meeting of the group.

Stage 6:

Presenting the networking tool to a wider audience through SE and Scottish Chambers of


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Professor Katia Sycara

Katia Sycara is a

Professor in the School of Computer Science at Carnegie Mellon Univer
sity. She
is also the Director of the Laboratory for Agents Technology & Semantic Web Technologies. She
holds the Sixth Century Chair in Computing at the University of Aberdeen.

She has a B.S in Applied Mathematics from Brown University, M.S. in Electrical

Engineering from
the University of Wisconsin & PhD in Computer Science from Georgia Institute of Technology. She
has an Honorary Doctorate in Mechanical and Communications Engineering from the University of
the Aegean (2004).

Prof. Sycara is a Fellow of

the Association for Advancement of Artificial Intelligence (AAAI), Fellow
of the Institute of Electrical & Electronic Engineers (IEEE), & the recipient of the 2002 ACM/SIGART
Agents Research Award. She is also the recipient of the Outstanding Alumnus Awar
d from the
University of Wisconsin (2005). She is a member of the Scientific Advisory Board of France
Telecom, & a member of the Scientific Advisory Board of the Greek National Center of Scientific
Research “Demokritos” Information Technology Division.

has received the Association of
Computing Machinery Recognition of Service Award (1998). She was an invited plenary speaker at
the National Conference on Artificial Intelligence (AAAI) in 1997 and an invited plenary speaker at
the First International Conf
erence on Multi
Agent systems (ICMAS) in 1995.

Prof. Sycara

has given numerous invited talks, & has authored or co
authored more than 350
technical papers dealing with Multiagent Systems, Human Agent/Robot Interaction, Game Theory,
Agents Supporting Human
Teams, Web Services, the Semantic Web, Negotiation, Machine
Learning & the application of these techniques to crisis action planning, scheduling, manufacturing
& financial planning & e
commerce. She has led multimillion dollar research effort funded by
PA, NASA, AFOSR, ONR, AFRL, NSF & industry. Research results have been transitioned to
AFRL/MN, Sandia, Wright Patterson AFB, CERDEC and other DoD organizations.

Sycara is
one of the contributors to the developmen
t of OWL
S, the Darpa

age for Semantic
Web services, as well as matchmaking & brokering software for agent discovery, service integration
& semantic interoperation.

Prof. Sycara has served as the Program Chair of the Second International Semantic Web
Conference (ISWC 2003), as

General Chair of the Second International Conference on Autonomous
Agents (Agents 98), as the Chair of the Steering Committee of the Agents Conference (1999
as the Scholarship chair of AAAI (1993
1999) & as a member of the AAAI Executive Council (1
99). From 2001
2003 she served as Invited Expert of the W3C (the World Wide Web Consortium)
Working Group on Web Services Architecture


a member of the OASIS Technical committee
2005) on the development of UDDI (Universal Description & Discov
ery for Interoperability)

which is an industry standard.

Prof. Sycara’s robotic team STEEL (jointly between CMU and the University of Pittsburgh) has won
several awards in international robotics com
petitions. In particular, STEEL

placed third in

Worldwide Robocup Championship Competition in the Urban Search and Rescue Virtual robots
League, Bejing, China 2008. STEEL was World Champion International Robocup Search and
Rescue Simulation League Competition, Atlanta, GA. May 2007. STEEL also won
First in Class
Award for Autonomy and Fi
rst in Class award for Mobility

in Robocup Urban Search and Rescue US
Open, Atlanta, GA, 2005.

She is a founding member & member of the Board of Directors of the International Foundation of
Multiagent Systems (IFMAS
). She is a founding member of the Semantic Web Science Association,


serves as the US co
chair of the US
Europe Semantic Web Services Initiative. She is on
Scientific Advisory Board of the European Science Foundation Initiative on “Science and
hnology of Agreement”, 2008.

She co
founded (with Nick Jennings) the journal “Autonomous Agents & Multiagent Systems”

she served as Editor in Chief from the journal’s inception in 1999 till 2009

she is an Editor
of the Springer Series on Ag
ents; on the Editorial Board of the Kluwer book series on “Multiagent
Systems, Artificial Societies & Simulated Organizations”; the Area Editor for AI & Management
Science of the journal “Group Decision & Negotiation”. She also serves on the editorial boar
d of the
journal “Agent Oriented Software Engineering”, “Web Intelligence & Agent Technologies”, “Journal
of Infonomics”, “Fundamenda Informaticae”,


“Concurrent Engineering: Research &
Applications”. She has served on the editorial board of the “ETA
I journal on the Semantic Web”


2001), on the Editorial Board of “IEEE Intelligent Systems & their Applications” (1992
& “AI in Engineering” (1990

Dr Alison Smart

Alison Smart is Senior Lecturer in Management at the University of Aberde
en, and is currently Head
of the Management Studies Group. Before moving to the University of Aberdeen in 2009 Dr Smart
was Lecturer in Operations Management at Manchester Business School and a Research Fellow at
the University of Edinburgh. She has a BSc
and a D.Phil in Chemistry from the University of York,
and an MBA from the University of Edinburgh. She spent a number of years working as a research
and development chemist for ICI and Zeneca before joining the University of Edinburgh.

Dr Smart’s researc
h interests centre around process innovation, particularly innovations that sit at
the interfaces of organizations. Her recent publications have concentrated on the adoption of RFID
to improve the tracking and tracing of goods in supply chains. She is curr
ently involved in a study to
assess a pilot initiative to outsource glaucoma care in NHS Grampian. She has worked with Gary
Graham at the University of Manchester to examine the impact of the Internet on regional
newspapers (the initial paper won a best pa
per award at the British Academy of Management
Conference in Harrogate in 2008).

With colleagues at the University of Edinburgh she was an investigator for the
The Network Enterprise: the Shaping of Institutions and Stand
ards in e

and a co
investigator for the EPSRC sponsored
Manufacturing Futures Network

colleagues from several UK universities

With colleagues from the University of Manchester s
he was
a c
grant holder
for a
Teaching Company Scheme
grant wi
Northern Technologies Ltd

and was
involved in the supervision of a project with Marl International Ltd in Ulverston, Cumbria.

Recent Publications:

Bunduchi R. and Smart A.U. (forthcoming) ‘
Process innovation costs in supply networks: A

rnational Journal of Management Reviews

Graham G., and Smart A. U. (2010) ‘
The British Newspaper Industry Supply Chain and the Internet’
Supply Chain Management: an International Journal

15 (3) 196


Smart A. U., Bunduchi R. and
Gerst M. (2010) ‘The co
sts of

adoption of RFID technologies in
supply networks’
International Journal of Operations and Production Management

30 (4) 423


Bunduchi R, Smart A, Graham I and Williams R. (2008), 'Homogeneity and Heterogeneity in IT
Private Standard Settings

The Institutional Account'
Technology Analysis and Strategic

11 (3) 389


Dr Jeff Z Pan

Jeff Pan

is a Lecturer in Computing Science at the
University of Aberdeen
. He received his Ph.D. in
computer science from The University of Manchester i
n 2004

joined the faculty in the
Department of Computing Science at University of Aberdeen in 2005. His research focuses primarily
on knowledge representation and reasoning, in particular scalable ontology reasoning and querying,
and their applications

Dr Pan is an
Advisory Committee Re
presentative in the
World Wide Web Consortium (W3C)
, an
international organisation for setting up Web standards such as HTML, RDF and OWL. He is a
Primary Member Repres
entative of
Object Management Group (OMG)
a leading

proponent of
IT integration standards
. He chairs the OWL task force on uncertainty reasoning. He also
chaired the
W3C Multimedia Semantics Incubator Group

and the Software Engineering Task Force
in the
Semantic Web Best Practice and Deployment (S
WBPD) Working Group
. He is a Member
Representative of
Semantic Technology Institute International


Dr Pan is a key contributor to the W3C OWL2 standard. He

work of the TrOWL Tractable
2 reasoning infrastructure. He is widely r

for his work on scal
able and efficient
ontology reasoning; he gave tutorials on this topic in e.g. AAAI2010, ESWC2010 and the Reasoning
Web Summer School 2010.



Dr Pan published over 90 referred papers. He and his colleagues won the Best Paper Award in

2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI

and the Best Student
Paper Award in
the 5th International Semantic Web Conference (ISWC2006)
. He
has served as the
Program Chair of

the First International Conference on Web Reasonin
g and Rule System (RR2007,
which is the first Semantic Web conference on Reasoning), of the Ontology and Reasoning Track in
the Extended Semantic Web Conference (ESWC2010) and of
Doctoral Consortium

of the 9th
International Semantic Web Conference (ISWC201

He is
a founding member of
International Conference on Web Reasoning and Rule System
. He
founded the Fuzzy RuleML Technical Group.
He is an Associate Editor of the Journal of
Advances in Artificial Intelligence and on the Editorial Board of bot
h the International Journal on
Semantic Web and Information Systems (IJSWIS) and the Journal of Emerging Technologies in
Web Intelligence (JETWI). He serve/served as a guest editor of special issues of a number of
international journals, such as the Journa
l of Web Semantics, the Journal of Logic and Computation,
the Journal on Data Semantics and IEEE Transactions on Systems, Man and Cybernetics Part C
(Applications and Reviews).

Dr. Pan has contributed to several high
profile projects, such as the EPSRC
ded Interdisciplinary
Research Collaboration on Advanced Knowledge Technologies (AKT) and the European
Commission FET project Wonder Web, which effectively contributed to the creation of the W3C
OWL Web Ontology Language. He has also led The Aberdeen Unive
rsity's contribution to several
funded and national projects, such as the European Commission Network of Excellent
Knowledge Web project and the MOST project
, as well as the EPSRC CASE LITRO project

Recent Publications:

Yuan Ren, Jeff Z. Pan and Yuting

Zhao. Soundness Preserving Approximation for TBox Reasoning.
Proc. of the 25th AAAI Conference Conference (AAAI2010)
. 2010.

Aidan Hogan, Jeff Z. Pan and Axel Polleres. SAOR: Template Rule Optimisations for Distributed
Reasoning over 1 Billion Linked D
ata Triples. In
Proc. of the 9th International Semantic Web
Conference (ISWC2010)
, 2010.

Jianfeng Du, Guilin Qi, Jeff Z. Pan and Yi
Dong Shen. A Decomposition
based Approach to
Optimizing Conjunctive Query Answering in OWL DL . In
Proc. of the 8th Internat
ional Semantic
Web Conference (ISWC 2009)
. 2009.

Jeff Z. Pan, Stuart Taylor and Edward Thomas. Reducing Ambiguity in Tagging Systems with
Folksonomy Search Expansion. In
Proc. of the 6th European Semantic Web Conference
. 2009.

Jeff Z. Pan, Gior
gos Stamou, Giorgos Stoilos, Stuart Taylor and Edward Thomas. Scalable
Querying Services over Fuzzy Ontologies. In
Proc. of the 17th International World Wide Web
Conference (WWW2008)
. 575
584. 2008.

Guilin Qi, Peter Haase, Zhisheng Huang, Qiu Ji, Jeff Z.
Pan, Johanna Völker. A Kernel Revision
Operator for Terminologies . In
Proc. of the 7th International Semantic Web Conference
. 2008.

Shenghui Wang and Jeff Z. Pan. Ontology
based Integration and Retrieval over Multiple Quantities

What if "Ovat
e leaves and often blue to purple flowers". In
Proc. of the 2007 IEEE/WIC/ACM
International Conference on Web Intelligence (WI
. 388
394. 2007.

Jeff Z. Pan and Edward Thomas. Approximating OWL
DL Ontologies. In
Proc. of the 22nd AAAI
Conference on Ar
tificial Intelligence (AAAI
. 1434
1439. 2007.

Yuting Zhao, Kewen Wang, Rodney Topor, Jeff Z. Pan and Fausto Giunchiglia. Semantic
Cooperation and Knowledge Reuse by Using Autonomous Ontology. In
Proc. of the 6th
International Semantic Web Conference (I
. 666
679. 2007.

Wolf Siberski, Jeff Z. Pan and Uwe Thaden. Querying the Semantic Web with Preferences. In
of the 5th International Semantic Web Conference (ISWC2006)
, 612

624. 2006. (
Best Student
Paper Award



Joey Lam, Jeff Z. Pan, Derek S
leeman and Wamberto Vasconcelos. A Fine
Grained Approach to
Resolving Unsatisfiable Ontologies. In
Proc. of the 2006 IEEE/WIC/ACM International
Conference on Web Intelligence (WI
, 428

434. 2006. (
Best Paper Award

Giorgos Flouris, Zhisheng Huang, J
eff Z. Pan, Dimitris Plexousakis and Holger Wache.
Inconsistencies, Negations and Changes in Ontologies. In
Proc. of the 21st National Conference
on Artificial Intelligence (AAAI
, 1295
1300. 2006.