@INPROCEEDINGS{Edwards2011,
  author = {Peter Edwards and Edoardo Pignotti and David Corsar},
  title = {Provenance on the Web, Leaving the Walled Garden Behind \dots},
  booktitle = {Third International Conference on Web Science, ACM WebSci '11},
  year = {2011},
  misc ={In press},
  abstract = {Provenance has been identified as essential for the development of a more trustworthy machine-processable web. We
discuss issues associated with provenance on the Web by
comparing two different systems, a closed e-science platform
and a more open public transport information system.}
}
				

@ARTICLE{Corsar2010,
  author = {Corsar, David and Chorley, Alison and Vasconcelos, Wamberto},
  title = {{Organisation-based (re)planning for web service composition}},
  year = {2010},
  pages = {649--652},
  acmid = {1967587},
  address = {New York, NY, USA},
  booktitle = {Proceedings of the 12th International Conference on Information Integration
	and Web-based Applications \& Services},
  doi = {http://doi.acm.org/10.1145/1967486.1967587},
  isbn = {978-1-4503-0421-4},
  keywords = {agents, planning, service oriented architecture, web service composition},
  location = {Paris, France},
  numpages = {4},
  publisher = {ACM},
  series = {iiWAS '10},
  url = {http://doi.acm.org/10.1145/1967486.1967587}
}

@PHDTHESIS{Corsar2009a,
  author = {David Corsar},
  title = {{Developing Knowledge-Based Systems through Ontology Mapping and
	Ontology Guided Knowledge Acquisition}},
  school = {Department of Computing Science, University of Aberdeen},
  year = {2009},
  url = {http://www.csd.abdn.ac.uk/~dcorsar/papers/DCorsarThesis.pdf},
  abstract = {This thesis focuses on reusing domain ontologies and generic problem
	solvers (PSs) in the development of new Knowledge Based Systems (KBSs).
	A two-stage methodology for achieving this has been developed: in
	the first stage, knowledge is mapped from a domain ontology to the
	requirements of a generic PS (expressed in a PS ontology); in the
	second stage, this mapped knowledge and the domain specific reasoning
	requirements of the generic PS are used to ``drive'' the acquisition
	of additional (domain specific) procedural knowledge required by
	the PS. This acquired knowledge can then be used to generate an executable
	KBS.
	
	
	Developing this methodology involved a detailed review of the earlier
	reuse literature, in order to understand the strengths and weaknesses
	of earlier approaches. Generic PSs for propose-and-revise design
	and diagnosis were also developed based on two existing KBSs which
	performed these tasks in the elevator domain. To gain insights into
	the KBS development process, the generic PSs were used to manually
	build two new executable KBSs. A tool, MAKTab, was then developed
	to support the methodology by semi-automatically performing the actions
	undertaken during the manual building of the two KBSs. MAKTab has
	been used to successfully recreate the two elevator systems, and
	fully develop diagnosis and design KBSs in the computer hardware
	domain. 
	
	
	The findings described in the thesis support the belief that a domain
	ontology developed for one type of PS will, in general, be unable
	to fully meet the procedural requirements of another type of PS;
	this knowledge must therefore be acquired. This work also shows that
	a single, general knowledge acquisition technique can be applied
	with different types of generic PSs, to acquire the necessary procedural
	knowledge. These findings are significant as they show shortcomings
	of previous approaches have been identified and addressed in the
	proposed methodology, which along with MAKTab, moves the Knowledge
	Engineering community closer to fulfilling the dream of KBS creation
	by configuring reusable components.}
}

@INPROCEEDINGS{Corsar2009b,
  author = {David Corsar and Laura Moss and Derek Sleeman and Malcolm Sim},
  title = {{Supporting the Development of Medical Ontologies}},
  booktitle = {Frontiers in Artificial Intelligence and Applications: Formal Ontologies
	Meet Industry},
  year = {2009},
  pages = {114-125},
  month = {September},
  publisher = {IOS Press},
  abstract = {Ontologies have recently become widely used in the biomedical community,
	which has included several efforts to build standard reference ontologies
	for various aspects of medicine. These projects have produced general,
	wide-ranging descriptions of the medical domain, resulting in large,
	complex ontologies which can be difficult to reuse as part of a single
	application. We describe four ontologies which have been used to
	support the creation of a domain model for the purpose of performing
	intelligent reasoning about a particular aspect of the medical domain.
	We also describe how concepts in these ontologies can be aligned
	with standard reference ontologies to promote interoperability, and
	provide an application in which these ontologies are used.}
}

@ARTICLE{Sleeman2009a,
  author = {Derek H. Sleeman and Ken Barker and David Corsar},
  title = {{Report on the Fourth International Conference on Knowledge Capture
	(K-CAP 2007)}},
  journal = {AI Magazine},
  year = {2009},
  volume = {30},
  pages = {126-127},
  number = {1},
  abstract = {The Fourth International Conference on Knowledge Capture was held
	October 28-31, 2007 in Whistler, British Columbia. K-CAP 2007 included
	two invited talks, technical papers, posters, and demonstrations.
	Topics included knowledge engineering and modeling methodologies,
	knowledge engineering and the semantic web, mixed-initiative planning
	and decision-support tools, acquisition of problem-solving knowledge,
	knowledge-based markup techniques, knowledge extraction systems,
	knowledge acquisition tools, and advice taking systems.},
  url = {http://www.aaai.org/ojs/index.php/aimagazine/article/view/2211}
}

@INPROCEEDINGS{Corsar2008b,
  author = {D. Corsar and D. Sleeman},
  title = {{Developing Knowledge-Based Systems using the Semantic Web}},
  booktitle = {{Visions of Computer Science, BCS International Academic Conference
	(London, UK)}},
  year = {2008},
  editor = {E. Gelenbe and S. Abramsky and V. Sassone},
  pages = {29--40},
  month = {September},
  abstract = {The benefits of reuse have long been recognized in the knowledge engineering
	community where the dream of creating knowledge-based systems on-the-fly
	from libraries of reusable components is still to be fully realised.
	In this paper we present a two stage methodology for creating knowledge-based
	systems: first reusing domain knowledge by mapping it, where appropriate,
	to the requirements of a generic problem solver; and secondly using
	this mapped knowledge and the requirements of the problem solver
	to ``drive'' the acquisition of the additional knowledge it needs.
	For example, suppose we have available a knowledge-based systems
	which is composed of a propose-and-revise problem solver linked with
	an appropriate knowledge base/ontology from the elevator domain.
	Then to create a diagnostic knowledge-based systems in the same domain,
	we require to map relevant information from the elevator knowledge
	base/ontology, such as component information, to a diagnostic problem
	solver, and then to extend it with diagnostic information such as
	malfunctions, symptoms and repairs for each component. We have developed
	MAKTab, a Prot\'eg\'e plug-in which supports both these steps and
	results in a composite knowledge-based systems which is executable.
	In the final section of this paper we discuss the issues involved
	in extending MAKTab so that it would be able to operate in the context
	of the (Semantic) Web. Here we use the idea of centralised mapping
	repositories and mapping composition. This work contributes to the
	vision of the Web, which contains components (both problem solvers
	and instantiated ontologies (knowledge bases)) that tools (like MAKTab)
	can use to create knowledge-based systems which subsequently can
	enhance the richness of the Web by providing yet further knowledge-based
	Web-services.},
  keywords = {Knowledge-Based Systems, Ontology Mapping, Knowledge Acquisition}
}

@INPROCEEDINGS{Corsar2008a,
  author = {David Corsar and Derek Sleeman.},
  title = {{KBS Development on the (Semantic) Web}},
  booktitle = {{Symbiotic Relationships between Semantic Web and Knowledge Engineering,
	Papers from the AAAI Spring Symposium, Technical Report SS-08-07}},
  year = {2008},
  pages = {35--44},
  month = {March},
  publisher = {AAAI Press, Menlo Park, California},
  abstract = {The benefits of reuse have long been recognized in the knowledge engineering
	community where the dream of creating knowledge based systems (KBSs)
	on-the-fly from libraries of reusable components is still to be fully
	realised. In this paper we present a two stage methodology for creating
	KBSs: first reusing domain knowledge by mapping it, where appropriate,
	to the requirements of a generic problem solver; and secondly using
	this mapped knowledge and the requirements of the problem solver
	to ``drive'' the acquisition of the additional knowledge it needs.
	For example, suppose we have available a KBS which is composed of
	a propose-and-revise problem solver linked with an appropriate knowledge
	base/ontology from the elevator domain. Then to create a diagnostic
	KBS in the same domain, we require to map relevant information from
	the elevator knowledge base/ontology, such as component information,
	to a diagnostic problem solver, and then to extend it with diagnostic
	information such as malfunctions, symptoms and repairs for each component.
	We have developed MAKTab, a Prot\'eg\'e plug-in which supports both
	these steps and results in a composite KBS which is executable. In
	the final section of this paper we speculate/discuss the issues involved
	in extending MAKTab so that it would be able to operate in the context
	of the (Semantic) Web. Here we introduce the idea of centralised
	mapping repositories.},
  institution = {AAAI Press, Menlo Park, California. 2008}
}

@INPROCEEDINGS{Corsar2007b,
  author = {David Corsar and Derek Sleeman and Anne McKenzie},
  title = {{Extending Jess to Handle Uncertainty}},
  booktitle = {{Research and Development in Intelligent Systems XXIV Proceedings
	of AI-2007, the Twenty-seventh SGAI International Conference on Innovative
	Techniques and Applications of Artificial Intelligence (Cambridge,
	UK)}},
  year = {2007},
  editor = {M. Bramer and F. Coenen and M. Petridis},
  pages = {81--93},
  month = {December},
  publisher = {Springer, London},
  abstract = {Computer scientists are often faced with the challenge of having to
	model the world and its associated uncertainties. One area in particular
	where modelling uncertainty is important are Expert Systems (also
	referred to as Knowledge Based Systems and Intelligent Systems),
	where procedural / classification knowledge is often captured as
	facts and rules. One of the earliest Expert Systems to incorporate
	uncertainty was MYCIN. The developers realized that uncertainty had
	to be associated with both the properties of the objects they were
	modelling and with the knowledge (the rules themselves). A popular
	engine for building Knowledge Based Systems currently is Jess, which
	has been extended to handle uncertain knowledge by using fuzzy logic.
	However, systems written using this extension are generally composed
	of two interrelated components – namely a Java program and a Jess
	knowledge base. Further, this technique has several other disadvantages
	which are also discussed. We have developed a system, Uncertainty
	Jess, which provides Jess with the same powerful, yet easy to use,
	uncertainty handling as MYCIN. Uncertainty Jess allows the user to
	assign certainty factors / scores to both the properties of their
	data and to the rules, which it then makes use of to determine the
	certainty of rule conclusions for single and multiple identical conclusions.},
  citeseerurl = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.110.5704}
}

@INPROCEEDINGS{Corsar2007a,
  author = {D. Corsar and D. Sleeman},
  title = {{KBS Development Through Ontology Mapping and Ontology Driven Acquisition}},
  booktitle = {Proceedings of the 4th international Conference on Knowledge Capture
	(Whistler, BC, Canada)},
  year = {2007},
  editor = {D. Sleeman and K. Brown},
  series = {23--30},
  month = {October},
  publisher = {ACM, New York, New York},
  abstract = {The benefits of reuse have long been recognized in the knowledge engineering
	community where the dream of creating knowledge based systems (KBSs)
	on-the-fly from libraries of reusable components is still to be fully
	realised. In this paper we present a two stage methodology for creating
	KBSs: first reusing domain knowledge by mapping it, where appropriate,
	to the requirements of a generic problem solver; and secondly using
	this mapped knowledge and the requirements of the problem solver
	to ``drive'' the acquisition of the additional knowledge it needs.
	For example, suppose we have available a KBS which is composed of
	a propose-and-revise problem solver linked with an appropriate knowledge
	base/ontology from the elevator domain. Then to create a diagnostic
	KBS in the same domain, we require to map relevant information from
	the elevator knowledge base/ontology, such as component information,
	to a diagnostic problem solver, and then to extend it with diagnostic
	information such as malfunctions, symptoms and repairs for each component.
	We have developed MAKTab, a Prot\'eg\'e plug-in which supports both
	these steps and results in a composite KBS which is executable.},
  citeseerurl = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.141.1154},
  doi = {http://doi.acm.org/10.1145/1298406.1298412},
  keywords = {Reuse, KBS, Problem Solvers, Ontology, Mapping, Knowledge Acquisition},
  url = {http://www.csd.abdn.ac.uk/~dcorsar/papers/DCorsarDSleemanKCAP2007.php}
}

@ARTICLE{Corsar2006a,
  author = {David Corsar and Derek Sleeman},
  title = {{Reusing JessTab Rules in Prot\'eg\'e}},
  journal = {Knowledge-Based Systems},
  year = {2006},
  volume = {19},
  pages = {291--297},
  number = {5},
  month = {September},
  note = {AI 2005 SI},
  abstract = {Prot\'eg\'e provides a complete ontology and knowledge base management
	tool. Along with JESS, JessTab provides one method of rule based
	reasoning over a Prot\'eg\'e ontology and knowledge base. However
	once JessTab rules have been created for a knowledge base, they are
	explicitly tied to it as they name particular classes and slots,
	which greatly hinders their reuse with further knowledge bases. We
	have developed a two phase process and a supporting tool to support
	the reuse of JessTab rule sets. The first phase involves changing
	the class and slot references in the rule set into an abstract reference;
	the second phase involves automatically mapping between the abstract
	rules and further knowledge bases. Once mappings have been defined
	and applied for all the classes and slots in the abstract rules,
	the new rule set can then be run against the new knowledge base.
	We have satisfactorily tested our tool with several ontologies and
	associated rule sets; moreover, some of these tests have identified
	possible future improvements to the tool.},
  doi = {DOI: 10.1016/j.knosys.2005.11.010},
  keywords = {Prot\'eg\'e, JESS, JessTab, rule set reuse, ontology mapping},
  owner = {David Corsar},
  timestamp = {2008.10.04},
  url = {http://www.sciencedirect.com/science/article/B6V0P-4J6NGJM-1/2/9b09c0645b00a89ab005719623364237}
}

@INPROCEEDINGS{Corsar2005c,
  author = {D. Corsar and D. Sleeman},
  title = {{Reusing JessTab Rules in Prot\'eg\'e}},
  booktitle = {{Research and Development in Intelligent Systems XXII Proceedings
	of AI-2005 the Twenty-fifth SGAI International Conference on Innovative
	Techniques and Applications of Artificial Intelligence (Cambridge,
	UK)}},
  year = {2005},
  editor = {{M. Bramer and F. Coenen and T. Allen}},
  pages = {{7-20}},
  month = {December},
  publisher = {Springer, Berlin},
  url = {http://www.csd.abdn.ac.uk/~dcorsar/papers/DCorsarDSleemanAI2005.pdf},
  abstract = {Prot\'eg\'e provides a complete ontology and knowledge base management
	tool. Along with JESS, JessTab provides one method of rule based
	reasoning over a Prot\'eg\'e ontology and knowledge base. However
	once JessTab rules have been created for a knowledge base, they are
	explicitly tied to it as they name particular classes and slots,
	which greatly hinders their reuse with further knowledge bases. We
	have developed a two phase process and a supporting tool to support
	the reuse of JessTab rule sets. The first phase involves changing
	the class and slot references in the rule set into an abstract reference;
	the second phase involves automatically mapping between the abstract
	rules and further knowledge bases. Once mappings have been defined
	and applied for all the classes and slots in the abstract rules,
	the new rule set can then be run against the new knowledge base.
	We have satisfactorily tested our tool with several ontologies and
	associated rule sets; moreover, some of these tests have identified
	possible future improvements to the tool.}
}

@INPROCEEDINGS{Corsar2005b,
  author = {David Corsar and Derek Sleeman},
  title = {{Reusing JessTab Rules in Prot\'eg\'e}},
  booktitle = {{Proceedings of the 1st AKT Doctoral Symposium (Milton Keynes, UK)}},
  year = {2005},
  month = {June},
  url = {http://www.csd.abdn.ac.uk/~dcorsar/papers/DCorsarDSleemanAKT2005.pdf}
}

@INPROCEEDINGS{Corsar2005a,
  author = {David Corsar and Derek Sleeman.},
  title = {{Reuse of JessTab Rule Sets within the Prot\'eg\'e Environment}},
  booktitle = {{Proceedings of the 8th International Prot\'eg\'e Conference (Madrid,
	Spain)}},
  year = {2005},
  month = {July},
  url = {http://www.csd.abdn.ac.uk/~dcorsar/software/PJMappingTab/docs/ProtegeDemo.pdf}
}