
[hidden] Contact and Biography Research and Projects Publications Homepage Search People		[hidden] School of Electronics and Computer Science University of Southampton Southampton SO17 1BJ United Kingdom Position: Guest in Learning Societies Lab Fax: Work (Fax): 08714338824 Email: ft at ecs dot ac dot uk URI: http://id.ecs.soton.ac.uk/person/4425 [browse] Interests: data mining, engineering design search optimisation, geospatial data managment, knowledge management, learning technologies, ocean science, semantic web, sensor, xml The group secretary for the Learning Societies Lab is Lauren J Dampier. Biography Dr Feng (Barry) TAO graduated from School of Computer Science, the Queen's University Belfast, U.K. (1999-2002) with a PhD degree in the subject of Data Mining and Knowledge Discovery. He then joined the University of Southampton as a researcher in ECS working for GEODISE project, one of the e-Science pilot projects in Southampton Regional e-Science center. His main contribution in the project was Geodise Knowledge Management and its intergration within the Engineering Problem Solving Environment. In 2004, he moved to LSL in ECS, working in Semantic Web based Technology Enhanced Learning. He is now a consultant in ECS but working full-time as a Data and Knowledge Engineer for National Oceanography Centre, Southampton in the area of Geospatial data managment and semantic web application for multiuse of oceanographic data. Duties Geodise provides a set of intelligent design search tools which are vital components of all engineering design systems to yield better designs using Engineering Design Search and Optimization (EDSO). The tools are built on top of the Grid infrastructure hence physically distributed in terms of their supporting components and resources, such as the computation nodes, data repository and knowledge base. The tools at the client side present as a suite of light weight Matlab toolboxes (a set of grid enabled Matlab functions) that call out services (Grid service and web service) at the server side, where complex and distributed operation of Grid computing, database management and knowledge base operations happen. Beside, there are also java based GUI front end that consumes services for workflow building. My role focuses on the specification of the knowledge infrastructure, engineering a knowledge base and its integration with the system. The goal is to share experience, provide knowledge support and make the tools more intelligent and user friendly. For example, EDSO related key process, functions and optimization methods, etc have been semantically enriched using the Ontology and put into a semantic repository where they are reused through semantic web based information retrial and even deeper processes such as Declarative Logic (DL) based reasoning and semantic matching for service discovery and advice on their configuration. To make this happen, technologies of semantic web, Grid computing and web services, etc. have been used. Many types of knowledge infrastructures have been experimented with, two major endeavors are the traditional rule based knowledge base and more popular semantic web based knowledge repository. We address the second approach in this text. The semantic infrastructure: This is built on top of the instance store and Ontoview, the instance store is the place where all semantics are stored in DAML+OIL. We have experienced the following phases in the whole life cycle of semantic web based knowledge management. Step 1 - Knowledge Acquisition (KA) Ontologies are built through KA with the domain expertise aiming to extract key domain concepts and their relationships. These are the controlled vocabulary, attributes, relations and axioms of a knowledge base to be built. KA tools such as PC-PACK, Prot駩 and OilEd have been used to build ontology and the outputs are saved in RDF, OWL and DAML+OIL. Step 2 ? Knowledge population While knowledge structures such as function and optimization method templates can be derived from the ontology (ontology driven knowledge structure), their population can be regarded as the generation of semantic instances, also known as annotation. Tools and APIs for this purpose have been built to facilitate these operations. Step 3 ? Knowledge modeling and specification This is about the definition of what useful knowledge is and how it should be presented in a particular Problem Solving Environment. In Geodise, we identified the following: 1. advice on function assembly and workflow composition 2. construction of a knowledge structure 3. semantic based query of a particular concept (obtaining semantics) 4. advice on function configuration Step 4 ? Knowledge Reuse This is all about generating the customized knowledge (as defined in step 3) on the fly according to users? directions. This often involves server side processing of the semantics, which is made available but transparent to the end-users through web services, therefore platform independent as well. The end-users can choose their own favorite platform at the client side: in Geodise, this includes a KnowledgeToolbox in Matlab, Standalone workflow application and a GUI based function query interface in Java. Advisor based on semantic matching over the semantic repository is developed to suggest semantically compatible functions for function assembly and workflow composition. Additionally, function configuration advice is also available to show how a function should be configured (according to the manual) and how it was previously configured by other people with similar aims (according to historical data). For example, the optionsMatlab is an important optimization tool in Geodise, it can be configured to carry out different optimization tasks, each of which requires appropriate construction of a input structure. The input structure contains mandatory and optional control parameters which depend on the optimization methods chosen. Since the advisor has direct access to the knowledge base, it can take this structure passed from the client side and has its correspondent advice routines trigged by specific fields in the structure. Qualifications Bsc in Computer Science, PhD in Computer Science Consultancy New paradiam of Geodise Knowledge Management for 3Clix Three main activies of the Semantic Web based knowledge management in Geodise Knowledge are ontology modelling, semantic annotation and its reuse and intergration in PSE. Ontology forms the conceptual structure of the knowledge base and the semantic annotation populates the knowledge base by semantic instances. Knowledge reuse is then done through semantically analysing these instances to generate knowledgeable decisions and integrate intelligent interaction within the PSE. In e-Science practice, it is quite often that the activities of generating and reusing the instances are conducted by different parties (human and computers), in different locations, time and environments. For example, in Geodise, Various Grid services and domain software components are being used, such as Java Cog in Globus toolkit and OPTIONS design exploration package for EDSO, etc. They are wrapped as Matlab functions which form the key resource in Grid enabled engineering problem solving. Semantic instances of these resources can be generated by knowledge engineers using knowledge acquisition tools such as Protégé and Function Annotator. Semantics acquired in either way can be represented in Web Ontology Language (OWL), which is a standard in W3C aiming to help machine understanding of data. Third-party programs can be used to process the instances in the knowledge base for different knowledge reuse purposes. This allows that the knowledge to be used potentially outside the awareness of its providers. In Geodise, the purpose of knowledge support is to help engineers exploit reusable resources. We use Jena semantic toolkit to process the semantic information of these existing resources and make advice on activities of domain script editing and workflow assembly that require appropriate manipulation on these resources. Advantages and Limitations Geodise Knowledge is a ontology driven Semantic Web model where knowledge are represented in a knowledge repository as ontologies and semantic annotations, in the form of W3C RDF triples. At the moment, ontology engineering and its population through semantic annotation acitivities are all carried out by knowledge engineers outside the Matlab PSE, through manually processing the KA results with knowledge engineering tools such as OilEd, Protege and Function Annotator. EDSO Domain experts/users can only reuse these semantic annotations, in a stand-along SW driven matlab function query application, within the Matlab PSE through the Knowledge Toolbox or through the intergration of a knowledge advisor in EDSO workflow editor. The limitation of this paradiam is that Knowledge engineers need to regularly receive feedbacks from the domain experts and users in order to drive the improvement of the knowledge model and its population. This makes it difficult for collaberative knowledge evolution where domain experts/users are enpowered with ability to more directly participant activities in knowledge modeling and populations to make available resource for knowledge reuse. Possible solutions - Collaberative Agile Knowledge Engineering (AKE) Web2.0 technologies that support the Semantic Web, such as Semantic MediaWiki and OntoWiki, can be used to enable this collaberative knowledge evolution. Knowledge Engineers can provide a start-kit of ontology and a few instances, along with KA documents (from PC-PACK) of the domain, all of which are wiki based (editable and version controled). Domain experts and users follow this as a blueprint to collaberatively add more resources into the knowledge base, either on the web, or witin the Matlab PSE via a command-based toolbox. This enables domain experts, end users (including software agents such as a sensor proxy) and knowledge engineers to collaberatively contribute to the construction of a knowledge base. Similar approaches are Agile development method in Software engineering and Wiki in collaberative Web Content authoring. The AKE emphasis distributed contribution of knowledge as semantics encoded statements change logging and versioning - the wiki philosophy (make it easy to correction mistake rather than hard to make the mistake) intuitive rendering/representation of knowledge Persistent and scalable data storage Within the 3Clix context, improvement based on Geodise Knowledge can be made by switching to this Web2.0 paradiam and adding command-based toolbox in Geodise knowledge toolbox. Data interopobility is another important factor - all knowledge data should be stored as OWL and RDF triples in a scalable and persistant storage with facilities like import/export so that data won't be locked into any one semantic web appliction. Conferences Attended J Fredericks, S Haines, JS Cervantes, Feng (Barry) Tao, etc. Integrating QA/QC into Open Geospatial Consortium Sensor Web Enablement, position paper in OceanObs’09. Tao, Feng, Campbell, Jon, Pagnani, Maureen and Griffiths, Gwyn (2009) Collaborative ocean resource interoperability - multi-use of ocean data on the semantic web. In, The 6th Annual European Semantic Web Conference (ESWC2009). Heidelberg, Germany, Springer. (Lecture Notes in Computer Science). (In Press) Guan, T., Fowler, D., Crowder, R., Tao, F., Shadbolt, N. and Wills, G. (2009) A Semantic Matching Approach for Distributed RDF Data Query on a Knowledge Bus. In: The Third Chinese Semantic Web Symposium, 29-31, Aug, Nanjing, China. Guan, T., Fowler, D., Crowder, R., Shadbolt, N., Tao, F. and Wills, G. (2009) A Semantic System for Rapid Information Search and Access. In: European Semantic Web Conference 2009, 28 May - 4 June 2009, Heraklion, Greece. Tao, Feng and Campbell, Jon (2008) Enriching Ferryboxes on the Semantic Web for a Collaborative Ocean. At, Ferrybox Technology Conference 2008, National Oceanography Centre, Southampton UK, 29-30 Sep 2008. Southampton, UK, National Oceanography Centre Southampton. Tao, Feng (Barry), Campbell, Jon and Griffiths, Gwyn (2008) Multiuse of Oceanographic Data on the Semantic Web. At, NERC Technology Forum 2008, Oban, Scotland, 12-14 May 2008. . Tao, Feng (Barry), Khoja, Shakeel, Gravell, Andy and Davis, Hugh (2008) Academic Administration and Management Scenarios on the Semantic Web. At, 8th IEEE International Conference on Advanced Learning Technologies, Santander, Spain, 01-05 July 2008. . Chen, L. and Tao, F. (2007) An Intelligent Recommender System for Web Resource Discovery and Selection. (Edited by Edited by Da Ruan, Frank Hardeman eds.), The Springer, accepted and in press Tao, F., Millard, D., Zalfan, M., Chen, L. and Davis, H. (2007) Knowledge based Learning Experience Management on the Semantic Web. In Proceedings of IADIS International Conference of e-Learning (in press), Lisburn, Portugal. Chen, L., Shadbolt, N., Goble, C. and Tao, F. (2006) Managing Semantic Metadata for Web Grid Services. International Journal of Web Services Research 3(4) pp. 73-94. Millard, D., Tao, F., Doody, K., Woukeu, A. and Davis, H. (2006) The Knowledge Life Cycle for e-learning. International Journal of Continuing Engineering Education and Lifelong Learning: Special Issue on Application of Semantic Web Technologies in E-learning 16(1/2) pp. 110-121. Tao, F., Millard, D., Zalfan, M., Chen, l. and Davis, h. (2006) Semantic Web Assisted Learning Experience Management – Architecture and Strategy for Collaborative Learning Experience Sharing. Technical Report, LTG, ECS. Chen, L., Shadbolt, N., Goble, C., Tao, F., Puleston, C. and Cox, S. (2005) Semantics-assisted Problem Solving on the Semantic Grid. Journal of Computational Intelligence, special issue 21(2). Tao, F., Millard, D., Zalfan, M., Chen, L. and Davis, H. (2007) Knowledge based Learning Experience Management on the Semantic Web . In Proceedings of IADIS International Conference of e-Learning (in press), Lisburn, Portugal. Chen, L., Tao, F. and Shadbolt, N. (2006) A Semantic Web Service Based Approach for Augmented Provenance. In Proceedings of IEEE/WIC/ACM Web Intelligent -2006 (in press), Hong Kong. Woukeu, A., Millard, D., Tao, F. and Davis, H. (2005) Challenges for Semantic Grid based Mobile Learning. In Proceedings of IEEE SITIS 2005, Yaoundé. Millard, D., Woukeu, A., Tao, F. B. and Davis, H. (2005) Experiences with Writing Grid Clients for Mobile devices. In Proceedings of 1st International ELeGI Conference on Advanced Technology for Enhanced Learning BCS Electronic Workshops in Computing (eWiC), Vico Equense, (Napoli), Italy. Tao, F. B., Millard, D., Davis, H. and Woukeu, A. (2005) Managing the Semantic Aspects of Learning using the Knowledge Life Cycle. In Proceedings of The 5th IEEE International Conference on Advanced Learning Technologies (ICALT 2005), pp. 575-579, Kaohsiung, Taiwan. Tao, F., Millard, D., Woukeu,, A. and Davis, H. (2005) Semantic Grid based e-Learning using the Knowledge Life Cycle (Speech). In Proceedings of International Workshop on Applications of Semantic Web Technologies for E-Learning (SW-EL), in conjuction with ICALT2005 and AIED'05 The Proceedings of IEEE ICALT 2005, pp. 954-955, Kaohsiung and Amstdem. TAO, F., Neumann, F. and Ritrovato, P. (2005) The ELeGI Project (Speech). In Proceedings of Exhibition in eLearning Conference "Towards a Learning Society", Brussels. Millard, D., Woukeu, A., Tao, F. B. and Davis, H. (2005) The Potential of Grid for Mobile e-Learning (Poster). In Proceedings of The 4th World Conference on Mobile Learning (MLEARN 2005), Cape Town, South Africa. Tao, F., Davis, H., Millard, D. and Woukeu, A. (2005) The Semantic Aspects of e-Learning: Using the Knowledge Life Cycle to Manage Semantics for Grid and Service Oriented Systems (Speech). In Proceedings of 1st International ELeGI Conference on Advanced Technology for Enhanced Learning, Hotel Oriente, Vico Equense - Napoli (Italy). Tao, F., Puleston, C., Goble, C., Shadbolt, N., Chen, L., Pound, G. and Cox, S. (2004) Applying the Semantic Web to Manage Knowledge on the Grid. In Proceedings of UK e-Science AHM Conference, Nottingham, UK. Chen, L., Cox, S., Tao, F., Shadbolt, N., Goble, C. and Puleston, C. (2004) Empower Resource Providers to Build the Semantic Grid. In Proceedings of 2004 IEEE/WIC/ACM International Conference on Web Intelligence (WI'04), Beijing, China. Chen, L., Shadbolt, N., Tao, F., Goble, C., Puleston, C. and Cox, S. (2004) Managing Semantic Metadata for the Semantic Grid (Speech). In Proceedings of Knowledge Grid and Grid Intelligence (KGGI) workshop, Beijing, China. Tao, F., Shadbolt, N., Chen, L., Xu, F. and Cox, S. (2004) Semantic Web based Content Enrichment and Knowledge Reuse in e-Science. In Proceedings of 3rd International Conference on Ontologies, DataBases, and Applications of Semantics for Large Scale Information Systems (ODBASE), Larnaca, Cyprus. Xu, F., Eres, H., Tao, F. and Cox, S. (2004) Workflow Support for Advanced Grid-Enabled Computing. In Proceedings of UK e-Science AHM Conference, Nottingham, UK. Chen, L., Shadbolt, N., Tao, F., Puleston, C., Goble, C. and Cox, S. (2003) Exploiting Semantics for e-Science on the Semantic Grid. In Proceedings of Web Intelligence (WI2003) workshop on Knowledge Grid and Grid Intelligence, pp. 122-132, Halifax, Canada. Tao, F., Chen, L., Cox, S., Shadbolt, N., Puleston, C. and Goble, C. (2003) Semantic Support for Grid-Enabled Design Search in Engineering. In Proceedings of the First GGF Semantic Grid Workshop, the Ninth Global Grid Forum (GGF9), Chicago IL, USA. Chen, L., Shadbolt, N., Goble, C., Tao, F., Cox, S., Puleston, C. and Smart, P. (2003) Towards a Knowledge-based Approach to Semantic Service Composition. In Proceedings of 2nd International Semantic Web Conference (ISWC2003) 2870, pp. 319-334, Florida, USA. Tao, F., Cox, S., Chen, L., Shadbolt, N., Xu, F., Puleston, C., Goble, C. and Song, W. (2003) Towards the Semantic Grid: Enriching Content for Management and Reuse. In Proceedings of Delivering e-Science, UK e-Science All-hand Conference 2003, Nottingham, UK. Tao, F., Chen, L., Shadbolt, N., Pound, G. and Cox, S. (2003) Towards the Semantic Grid: Putting Knowledge to Work in Design Optimisation. selected for extented version in J.UCS 9(6) pp. 551-562. (2003) Towards the Semantic Grid: Putting Knowledge to Work in Design Optimisation. In Proceedings of The 3rd International Conference on Knowledge Management (I-KNOW '03), Graz, Austria. Tao, F., Chen, L., Shadbolt, N., Pound, G. and Cox, S., Eds. Tao, F., Chen, L., Shadbolt, N. R., Pound, G. and Cox, S. J. (2003) Towards the Semantic Grid: Putting Knowledge to Work in Design Optimisation. In Proceedings of The 3rd International Conference on Knowledge Management (I-KNOW '03), Graz, Austria. Tao, F., Murtagh, F. and Farid, M. (2003) Weighted Association Rule Mining using Weighted Support and Significance Framework. In Proceedings of The Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (ACM SIGKDD 2003), pp. 661-666, Washington DC, USA. Chen, L., Cox, S. J., Goble, C., Keane, A., Roberts, A., Shadbolt, N. R., Smart, P. and Tao, F. (2002) Engineering Knowledge for Engineering Grid Applications. In Proceedings of Euroweb 2002 Conference, The Web and the GRID: from e-science to e-business, pp. 12-25, Oxford, UK. Cox, S. J., Chen, L., Campobasso, S., Duta, M. H., Eres, M. H., Giles, M. B., Goble, C., Jiao, Z., Keane, A. J., Pound, G. E., Roberts, A., Shadbolt, N. R., Tao, F., Wason, J. L. and Xu, F. (2002) Grid Enabled Optimisation and Design Search (Geodise). In Proceedings of UK e-Science All Hands Meeting 1(1), pp. 54-55, Sheffield, UK. Cox, S. J., Boardman, R. P., Chen, L., Duta, M., Eres, M. H., Fairman, M. J., Jiao, Z., Giles, M., Goble, C., Pound, G. E., Keane, A. J., Shadbolt, N. R., Tao, F. and Wason, J. (2002) Grid Services in Action: Grid Enabled Optimisation and Design Search. In Proceedings of The 11th IEEE International Symposium on High Performance Distributed Computing HPDC-11 2002 1(1), pp. 413-413, Edinburgh, Scotland, UK. Taskaya, T., Contreras, P., Tao, F. and Murtagh, F. (2001) Data Visualization for large dataset. In Proceedings of HCI 2001 International conference in human and computer interface, New Orleans, La., USA. Tao, F., Contreras, P., Pauer, B., Taskaya, T. and Murtagh, F. (2001) User interest correlation in log data. In Proceedings of HCI 2001 International conference in human computer interface, New Orleans, La., USA. Tao, F. and Murtagh, F. (2000) Information self-organization for knowledge discovery. In Proceedings of MIW'2000 International Workshop on Management of Information on the Web - Methodologies and Applications, DEXA 2000, Greenwich, London. Tao, F. and Murtagh, F. (2000) Towards knowledge discovery from WWW log data. In Proceedings of IEEE International Conference on Information Technology: Coding and Computing, pp. 302-307, Las Vegas, USA. Data Protection Act Any member of ECS with their name preceded by a sign has not given their permission for their information to appear on the public website. More Information

[hidden]

School of Electronics and Computer Science
University of Southampton
Southampton
SO17 1BJ
United Kingdom

Position: Guest in Learning Societies Lab
Fax: 08714338824
Email: ft at ecs dot ac dot uk
URI: http://id.ecs.soton.ac.uk/person/4425 [browse]

Interests: data mining, engineering design search optimisation, geospatial data managment, knowledge management, learning technologies, ocean science, semantic web, sensor, xml

The group secretary for the Learning Societies Lab is Lauren J Dampier.

Biography

Dr Feng (Barry) TAO graduated from School of Computer Science, the Queen's University Belfast, U.K. (1999-2002) with a PhD degree in the subject of Data Mining and Knowledge Discovery.

He then joined the University of Southampton as a researcher in ECS working for GEODISE project, one of the e-Science pilot projects in Southampton Regional e-Science center. His main contribution in the project was Geodise Knowledge Management and its intergration within the Engineering Problem Solving Environment. In 2004, he moved to LSL in ECS, working in Semantic Web based Technology Enhanced Learning.

He is now a consultant in ECS but working full-time as a Data and Knowledge Engineer for National Oceanography Centre, Southampton in the area of Geospatial data managment and semantic web application for multiuse of oceanographic data.

Duties

Geodise provides a set of intelligent design search tools which are vital components of all engineering design systems to yield better designs using Engineering Design Search and Optimization (EDSO). The tools are built on top of the Grid infrastructure hence physically distributed in terms of their supporting components and resources, such as the computation nodes, data repository and knowledge base. The tools at the client side present as a suite of light weight Matlab toolboxes (a set of grid enabled Matlab functions) that call out services (Grid service and web service) at the server side, where complex and distributed operation of Grid computing, database management and knowledge base operations happen. Beside, there are also java based GUI front end that consumes services for workflow building.

My role focuses on the specification of the knowledge infrastructure, engineering a knowledge base and its integration with the system. The goal is to share experience, provide knowledge support and make the tools more intelligent and user friendly. For example, EDSO related key process, functions and optimization methods, etc have been semantically enriched using the Ontology and put into a semantic repository where they are reused through semantic web based information retrial and even deeper processes such as Declarative Logic (DL) based reasoning and semantic matching for service discovery and advice on their configuration. To make this happen, technologies of semantic web, Grid computing and web services, etc. have been used.

Many types of knowledge infrastructures have been experimented with, two major endeavors are the traditional rule based knowledge base and more popular semantic web based knowledge repository. We address the second approach in this text.

The semantic infrastructure: This is built on top of the instance store and Ontoview, the instance store is the place where all semantics are stored in DAML+OIL.

We have experienced the following phases in the whole life cycle of semantic web based knowledge management.

Step 1 - Knowledge Acquisition (KA)

Ontologies are built through KA with the domain expertise aiming to extract key domain concepts and their relationships. These are the controlled vocabulary, attributes, relations and axioms of a knowledge base to be built. KA tools such as PC-PACK, Prot駩 and OilEd have been used to build ontology and the outputs are saved in RDF, OWL and DAML+OIL.

Step 2 ? Knowledge population

While knowledge structures such as function and optimization method templates can be derived from the ontology (ontology driven knowledge structure), their population can be regarded as the generation of semantic instances, also known as annotation. Tools and APIs for this purpose have been built to facilitate these operations.

Step 3 ? Knowledge modeling and specification

This is about the definition of what useful knowledge is and how it should be presented in a particular Problem Solving Environment. In Geodise, we identified the following:
1. advice on function assembly and workflow composition
2. construction of a knowledge structure
3. semantic based query of a particular concept (obtaining semantics)
4. advice on function configuration

Step 4 ? Knowledge Reuse

This is all about generating the customized knowledge (as defined in step 3) on the fly according to users? directions. This often involves server side processing of the semantics, which is made available but transparent to the end-users through web services, therefore platform independent as well. The end-users can choose their own favorite platform at the client side: in Geodise, this includes a KnowledgeToolbox in Matlab, Standalone workflow application and a GUI based function query interface in Java.

Advisor based on semantic matching over the semantic repository is developed to suggest semantically compatible functions for function assembly and workflow composition.

Additionally, function configuration advice is also available to show how a function should be configured (according to the manual) and how it was previously configured by other people with similar aims (according to historical data). For example, the optionsMatlab is an important optimization tool in Geodise, it can be configured to carry out different optimization tasks, each of which requires appropriate construction of a input structure. The input structure contains mandatory and optional control parameters which depend on the optimization methods chosen. Since the advisor has direct access to the knowledge base, it can take this structure passed from the client side and has its correspondent advice routines trigged by specific fields in the structure.

Qualifications

Bsc in Computer Science,
PhD in Computer Science

Consultancy

New paradiam of Geodise Knowledge Management for 3Clix

Three main activies of the Semantic Web based knowledge management in Geodise Knowledge are ontology modelling, semantic annotation and its reuse and intergration in PSE. Ontology forms the conceptual structure of the knowledge base and the semantic annotation populates the knowledge base by semantic instances. Knowledge reuse is then done through semantically analysing these instances to generate knowledgeable decisions and integrate intelligent interaction within the PSE. In e-Science practice, it is quite often that the activities of generating and reusing the instances are conducted by different parties (human and computers), in different locations, time and environments. For example, in Geodise, Various Grid services and domain software components are being used, such as Java Cog in Globus toolkit and OPTIONS design exploration package for EDSO, etc. They are wrapped as Matlab functions which form the key resource in Grid enabled engineering problem solving. Semantic instances of these resources can be generated by knowledge engineers using knowledge acquisition tools such as Protégé and Function Annotator. Semantics acquired in either way can be represented in Web Ontology Language (OWL), which is a standard in W3C aiming to help machine understanding of data. Third-party programs can be used to process the instances in the knowledge base for different knowledge reuse purposes. This allows that the knowledge to be used potentially outside the awareness of its providers. In Geodise, the purpose of knowledge support is to help engineers exploit reusable resources. We use Jena semantic toolkit to process the semantic information of these existing resources and make advice on activities of domain script editing and workflow assembly that require appropriate manipulation on these resources.

Advantages and Limitations

Geodise Knowledge is a ontology driven Semantic Web model where knowledge are represented in a knowledge repository as ontologies and semantic annotations, in the form of W3C RDF triples. At the moment, ontology engineering and its population through semantic annotation acitivities are all carried out by knowledge engineers outside the Matlab PSE, through manually processing the KA results with knowledge engineering tools such as OilEd, Protege and Function Annotator. EDSO Domain experts/users can only reuse these semantic annotations, in a stand-along SW driven matlab function query application, within the Matlab PSE through the Knowledge Toolbox or through the intergration of a knowledge advisor in EDSO workflow editor. The limitation of this paradiam is that Knowledge engineers need to regularly receive feedbacks from the domain experts and users in order to drive the improvement of the knowledge model and its population. This makes it difficult for collaberative knowledge evolution where domain experts/users are enpowered with ability to more directly participant activities in knowledge modeling and populations to make available resource for knowledge reuse.

Possible solutions - Collaberative Agile Knowledge Engineering (AKE)

Web2.0 technologies that support the Semantic Web, such as Semantic MediaWiki and OntoWiki, can be used to enable this collaberative knowledge evolution. Knowledge Engineers can provide a start-kit of ontology and a few instances, along with KA documents (from PC-PACK) of the domain, all of which are wiki based (editable and version controled). Domain experts and users follow this as a blueprint to collaberatively add more resources into the knowledge base, either on the web, or witin the Matlab PSE via a command-based toolbox.

This enables domain experts, end users (including software agents such as a sensor proxy) and knowledge engineers to collaberatively contribute to the construction of a knowledge base. Similar approaches are Agile development method in Software engineering and Wiki in collaberative Web Content authoring.

The AKE emphasis

distributed contribution of knowledge as semantics encoded statements

change logging and versioning - the wiki philosophy (make it easy to correction mistake rather than hard to make the mistake)

intuitive rendering/representation of knowledge

Persistent and scalable data storage

Within the 3Clix context, improvement based on Geodise Knowledge can be made by switching to this Web2.0 paradiam and adding command-based toolbox in Geodise knowledge toolbox. Data interopobility is another important factor - all knowledge data should be stored as OWL and RDF triples in a scalable and persistant storage with facilities like import/export so that data won't be locked into any one semantic web appliction.

Conferences Attended

J Fredericks, S Haines, JS Cervantes, Feng (Barry) Tao, etc. Integrating QA/QC into Open Geospatial Consortium Sensor Web Enablement, position paper in OceanObs’09.

Tao, Feng, Campbell, Jon, Pagnani, Maureen and Griffiths, Gwyn (2009) Collaborative ocean resource interoperability - multi-use of ocean data on the semantic web. In, The 6th Annual European Semantic Web Conference (ESWC2009). Heidelberg, Germany, Springer. (Lecture Notes in Computer Science). (In Press)

Guan, T., Fowler, D., Crowder, R., Tao, F., Shadbolt, N. and Wills, G. (2009) A Semantic Matching Approach for Distributed RDF Data Query on a Knowledge Bus. In: The Third Chinese Semantic Web Symposium, 29-31, Aug, Nanjing, China.

Guan, T., Fowler, D., Crowder, R., Shadbolt, N., Tao, F. and Wills, G. (2009) A Semantic System for Rapid Information Search and Access. In: European Semantic Web Conference 2009, 28 May - 4 June 2009, Heraklion, Greece.

Tao, Feng and Campbell, Jon (2008) Enriching Ferryboxes on the Semantic Web for a Collaborative Ocean. At, Ferrybox Technology Conference 2008, National Oceanography Centre, Southampton UK, 29-30 Sep 2008. Southampton, UK, National Oceanography Centre Southampton.

Tao, Feng (Barry), Campbell, Jon and Griffiths, Gwyn (2008) Multiuse of Oceanographic Data on the Semantic Web. At, NERC Technology Forum 2008, Oban, Scotland, 12-14 May 2008. .

Tao, Feng (Barry), Khoja, Shakeel, Gravell, Andy and Davis, Hugh (2008) Academic Administration and Management Scenarios on the Semantic Web. At, 8th IEEE International Conference on Advanced Learning Technologies, Santander, Spain, 01-05 July 2008. .

Chen, L. and Tao, F. (2007) An Intelligent Recommender System for Web Resource Discovery and Selection. (Edited by Edited by Da Ruan, Frank Hardeman eds.), The Springer, accepted and in press

Tao, F., Millard, D., Zalfan, M., Chen, L. and Davis, H. (2007) Knowledge based Learning Experience Management on the Semantic Web. In Proceedings of IADIS International Conference of e-Learning (in press), Lisburn, Portugal.

Chen, L., Shadbolt, N., Goble, C. and Tao, F. (2006) Managing Semantic Metadata for Web Grid Services. International Journal of Web Services Research 3(4) pp. 73-94.

Millard, D., Tao, F., Doody, K., Woukeu, A. and Davis, H. (2006) The Knowledge Life Cycle for e-learning. International Journal of Continuing Engineering Education and Lifelong Learning: Special Issue on Application of Semantic Web Technologies in E-learning 16(1/2) pp. 110-121.

Tao, F., Millard, D., Zalfan, M., Chen, l. and Davis, h. (2006) Semantic Web Assisted Learning Experience Management – Architecture and Strategy for Collaborative Learning Experience Sharing. Technical Report, LTG, ECS.

Chen, L., Shadbolt, N., Goble, C., Tao, F., Puleston, C. and Cox, S. (2005) Semantics-assisted Problem Solving on the Semantic Grid. Journal of Computational Intelligence, special issue 21(2).

Tao, F., Millard, D., Zalfan, M., Chen, L. and Davis, H. (2007) Knowledge based Learning Experience Management on the Semantic Web . In Proceedings of IADIS International Conference of e-Learning (in press), Lisburn, Portugal.

Chen, L., Tao, F. and Shadbolt, N. (2006) A Semantic Web Service Based Approach for Augmented Provenance. In Proceedings of IEEE/WIC/ACM Web Intelligent -2006 (in press), Hong Kong.

Woukeu, A., Millard, D., Tao, F. and Davis, H. (2005) Challenges for Semantic Grid based Mobile Learning. In Proceedings of IEEE SITIS 2005, Yaoundé.

Millard, D., Woukeu, A., Tao, F. B. and Davis, H. (2005) Experiences with Writing Grid Clients for Mobile devices. In Proceedings of 1st International ELeGI Conference on Advanced Technology for Enhanced Learning BCS Electronic Workshops in Computing (eWiC), Vico Equense, (Napoli), Italy.

Tao, F. B., Millard, D., Davis, H. and Woukeu, A. (2005) Managing the Semantic Aspects of Learning using the Knowledge Life Cycle. In Proceedings of The 5th IEEE International Conference on Advanced Learning Technologies (ICALT 2005), pp. 575-579, Kaohsiung, Taiwan.

Tao, F., Millard, D., Woukeu,, A. and Davis, H. (2005) Semantic Grid based e-Learning using the Knowledge Life Cycle (Speech). In Proceedings of International Workshop on Applications of Semantic Web Technologies for E-Learning (SW-EL), in conjuction with ICALT2005 and AIED'05 The Proceedings of IEEE ICALT 2005, pp. 954-955, Kaohsiung and Amstdem.

TAO, F., Neumann, F. and Ritrovato, P. (2005) The ELeGI Project (Speech). In Proceedings of Exhibition in eLearning Conference "Towards a Learning Society", Brussels.

Millard, D., Woukeu, A., Tao, F. B. and Davis, H. (2005) The Potential of Grid for Mobile e-Learning (Poster). In Proceedings of The 4th World Conference on Mobile Learning (MLEARN 2005), Cape Town, South Africa.

Tao, F., Davis, H., Millard, D. and Woukeu, A. (2005) The Semantic Aspects of e-Learning: Using the Knowledge Life Cycle to Manage Semantics for Grid and Service Oriented Systems (Speech). In Proceedings of 1st International ELeGI Conference on Advanced Technology for Enhanced Learning, Hotel Oriente, Vico Equense - Napoli (Italy).

Tao, F., Puleston, C., Goble, C., Shadbolt, N., Chen, L., Pound, G. and Cox, S. (2004) Applying the Semantic Web to Manage Knowledge on the Grid. In Proceedings of UK e-Science AHM Conference, Nottingham, UK.

Chen, L., Cox, S., Tao, F., Shadbolt, N., Goble, C. and Puleston, C. (2004) Empower Resource Providers to Build the Semantic Grid. In Proceedings of 2004 IEEE/WIC/ACM International Conference on Web Intelligence (WI'04), Beijing, China.

Chen, L., Shadbolt, N., Tao, F., Goble, C., Puleston, C. and Cox, S. (2004) Managing Semantic Metadata for the Semantic Grid (Speech). In Proceedings of Knowledge Grid and Grid Intelligence (KGGI) workshop, Beijing, China.

Tao, F., Shadbolt, N., Chen, L., Xu, F. and Cox, S. (2004) Semantic Web based Content Enrichment and Knowledge Reuse in e-Science. In Proceedings of 3rd International Conference on Ontologies, DataBases, and Applications of Semantics for Large Scale Information Systems (ODBASE), Larnaca, Cyprus.

Xu, F., Eres, H., Tao, F. and Cox, S. (2004) Workflow Support for Advanced Grid-Enabled Computing. In Proceedings of UK e-Science AHM Conference, Nottingham, UK.

Chen, L., Shadbolt, N., Tao, F., Puleston, C., Goble, C. and Cox, S. (2003) Exploiting Semantics for e-Science on the Semantic Grid. In Proceedings of Web Intelligence (WI2003) workshop on Knowledge Grid and Grid Intelligence, pp. 122-132, Halifax, Canada.

Tao, F., Chen, L., Cox, S., Shadbolt, N., Puleston, C. and Goble, C. (2003) Semantic Support for Grid-Enabled Design Search in Engineering. In Proceedings of the First GGF Semantic Grid Workshop, the Ninth Global Grid Forum (GGF9), Chicago IL, USA.

Chen, L., Shadbolt, N., Goble, C., Tao, F., Cox, S., Puleston, C. and Smart, P. (2003) Towards a Knowledge-based Approach to Semantic Service Composition. In Proceedings of 2nd International Semantic Web Conference (ISWC2003) 2870, pp. 319-334, Florida, USA.

Tao, F., Cox, S., Chen, L., Shadbolt, N., Xu, F., Puleston, C., Goble, C. and Song, W. (2003) Towards the Semantic Grid: Enriching Content for Management and Reuse. In Proceedings of Delivering e-Science, UK e-Science All-hand Conference 2003, Nottingham, UK.

Tao, F., Chen, L., Shadbolt, N., Pound, G. and Cox, S. (2003) Towards the Semantic Grid: Putting Knowledge to Work in Design Optimisation. selected for extented version in J.UCS 9(6) pp. 551-562.

(2003) Towards the Semantic Grid: Putting Knowledge to Work in Design Optimisation. In Proceedings of The 3rd International Conference on Knowledge Management (I-KNOW '03), Graz, Austria. Tao, F., Chen, L., Shadbolt, N., Pound, G. and Cox, S., Eds.

Tao, F., Chen, L., Shadbolt, N. R., Pound, G. and Cox, S. J. (2003) Towards the Semantic Grid: Putting Knowledge to Work in Design Optimisation. In Proceedings of The 3rd International Conference on Knowledge Management (I-KNOW '03), Graz, Austria.

Tao, F., Murtagh, F. and Farid, M. (2003) Weighted Association Rule Mining using Weighted Support and Significance Framework. In Proceedings of The Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (ACM SIGKDD 2003), pp. 661-666, Washington DC, USA.

Chen, L., Cox, S. J., Goble, C., Keane, A., Roberts, A., Shadbolt, N. R., Smart, P. and Tao, F. (2002) Engineering Knowledge for Engineering Grid Applications. In Proceedings of Euroweb 2002 Conference, The Web and the GRID: from e-science to e-business, pp. 12-25, Oxford, UK.

Cox, S. J., Chen, L., Campobasso, S., Duta, M. H., Eres, M. H., Giles, M. B., Goble, C., Jiao, Z., Keane, A. J., Pound, G. E., Roberts, A., Shadbolt, N. R., Tao, F., Wason, J. L. and Xu, F. (2002) Grid Enabled Optimisation and Design Search (Geodise). In Proceedings of UK e-Science All Hands Meeting 1(1), pp. 54-55, Sheffield, UK.

Cox, S. J., Boardman, R. P., Chen, L., Duta, M., Eres, M. H., Fairman, M. J., Jiao, Z., Giles, M., Goble, C., Pound, G. E., Keane, A. J., Shadbolt, N. R., Tao, F. and Wason, J. (2002) Grid Services in Action: Grid Enabled Optimisation and Design Search. In Proceedings of The 11th IEEE International Symposium on High Performance Distributed Computing HPDC-11 2002 1(1), pp. 413-413, Edinburgh, Scotland, UK.

Taskaya, T., Contreras, P., Tao, F. and Murtagh, F. (2001) Data Visualization for large dataset. In Proceedings of HCI 2001 International conference in human and computer interface, New Orleans, La., USA.

Tao, F., Contreras, P., Pauer, B., Taskaya, T. and Murtagh, F. (2001) User interest correlation in log data. In Proceedings of HCI 2001 International conference in human computer interface, New Orleans, La., USA.

Tao, F. and Murtagh, F. (2000) Information self-organization for knowledge discovery. In Proceedings of MIW'2000 International Workshop on Management of Information on the Web - Methodologies and Applications, DEXA 2000, Greenwich, London.

Tao, F. and Murtagh, F. (2000) Towards knowledge discovery from WWW log data. In Proceedings of IEEE International Conference on Information Technology: Coding and Computing, pp. 302-307, Las Vegas, USA.

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