University of the West of England Home Page - Peter Hale Home Page - SEEDS Site Map - SEEDS Page - Text Only Site MapUniversity of the West of England Home Page - Peter Hale Home Page - SEEDS Site Map - SEEDS Page - Text Only Site Map
Software Engineering Research Group - 
Centre for Complex Cooperative Systems
Automated Generation of Modelling Programs Using Jena and Protege - article.
Drag and Drop Programming - Example and Information - http://www.cems.uwe.ac.uk/amrc/seeds/Ajax/ajax.htm#DragandDropProgramming.
Examples and Explanations - Visualisation and Interaction.
Interoperability - http://www.cems.uwe.ac.uk/amrc/seeds/softwareengineering.htm#Interoperability.
Modelling - Examples and Explanations - Modelling, Decision Support and Knowledge Management.
Models for Visualisation and/or calculation - Semantic Web Modelling Examples Page - Semantic Web Examples.
OntoREM: Ontology-driven Requirements Engineering Methodology - This research aims to investigate and develop an Ontology driven Requirements Engineering Methodology (OntoREM) that addresses the needs of complex, trans-national and multidisciplinary fields with particular reference but not limited to the aerospace industry.
Research in Modelling Simulation and Collaboration Over the Web - Article.
SEEDS Modelling - SEEDS - Modelling
SEEDS Modelling Page - SEEDS - Modelling Page
Semantic Web Applications - http://userdrivenmodelling.blogspot.com/2008/05/semantic-web-applications.html - This article is about the need for provision of Semantic Web applications to increase the amount of Semantic Web information that could be searched. This could result in a virtuous circle of Semantic Web applications creating Semantic Web information, and so justifying the creation of more Semantic Web applications to access it. The article advocates the use of Semantic Web applications for modelling and end-user programming, and integration into business applications.
Semantic Web Development - article - Peter Hale.
Semantic Web Modelling - Semantic Web Modelling.
Semantic Web, Ontologies and Science/Engineering - http://www.cems.uwe.ac.uk/amrc/seeds/PeterHale/RDF/RDF.htm#SemanticWebScience.
Semantic Web Page - Semantic Web Page.
Software Engineering Page - http://www.cems.uwe.ac.uk/amrc/seeds/softwareengineering.htm.
Software Engineering Research Group - http://www.cems.uwe.ac.uk/cccs/researchgroup.php?menu=off&group=serg - SERG's mission is to bridge the gap between software engineering research and its application to different disciplines.
Survey Results - http://www.cems.uwe.ac.uk/amrc/seeds/EndUserProgramming.htm#SurveyResults - http://www.toluna.com/polls/37921/Do_You_Think_End-User_Programming_can_be_made_possible?.
SVG (Scalable Vector Graphics) - SVG Wing Box - Interactive Diagrams
Systems Engineering and Simulation Page - http://www.cems.uwe.ac.uk/amrc/seeds/systemsengineering.htm.
Translation for De-abstraction - article - Peter Hale.
User Driven Modelling Semantic Wiki - http://www.visualknowledge.com/wikikey/A143074S3496911 - Community.
UWE Student Project - http://www.cems.uwe.ac.uk/amrc/seeds/Web%20Semantic/Index.html - Investigating and implement the idea of 'ModConsWest' (Modelling and Constructionism with Web based E-Learning Semantic Tools)" - Lee Ediagbonya and Awaab Eltahir.
Visualisation and Interaction Page - http://www.cems.uwe.ac.uk/amrc/seeds/Visualisation.
A project was created by Leaver (2008) to enable End-User functionality for web based ontology construction and search. This was also used within my research to create an online wing ontology and search this.
Leaver, N., (2008) Using RDF as an Enabling Technology. MSc. Dissertation, University of the West of England, Bristol.
Semantic Web Applications - http://userdrivenmodelling.blogspot.com/2008/05/semantic-web-applications.html - This article is about the need for provision of Semantic Web applications to increase the amount of Semantic Web information that could be searched. This could result in a virtuous circle of Semantic Web applications creating Semantic Web information, and so justifying the creation of more Semantic Web applications to access it. The article advocates the use of Semantic Web applications for modelling and end-user programming, and integration into business applications. - 5th May 2008
Semantic Web Collaboration - http://ezinearticles.com/?Semantic-Web-Collaboration&id=1160019 - This article discusses how Semantic Web/Web 2.0 collaboration can enable ontology editing. This helps reach agreement on the meaning of terms, and encourages end-user modelling/programming by enabling simplified development of online applications. This could be an efficient way of managing large ontologies with multiple users. - 9th May 2008.
A web interface has been developed for Protégé WebProtege http://protege.cim3.net/cgi-bin/wiki.pl?WebProtege. An example of the use of this is shown here - where I used WebProtege to create an ontology and a search is made for information on the cure cycle for composites manufacturing.
The SEEDS team intends to partner with industry, other academics, and interested people in order to build a semantic web modelling system for end user programming. In order to achieve this we want to examine applications that aim to assist in this, and then write extensively about how we used them and how they helped towards our goal. We particularly want to target modelling that is too complex for use of spreadsheets, and sharing of information via an ontology.
The aim of our research is to enable decision support during product development, whilst minimising dependence on specialist software and detailed programming effort. The basis of this is an Ontology that can be visualised and edited in tree form. We are using the open standard Ontology tool Protégé from Stanford University. This Ontology can be translated into a Decision Support tool called DecisionPro (now renamed Vanguard System), which runs the model. Software we have created using DecisionPro (now Vanguard System) allows calculations of the cost of a design to be made, and provides a colour-coded representation of the product tree. It is then possible to output this tree in the form of web pages, interactive diagrams and code in programming languages. It is possible to search the information both in Protégé and on the web as it is represented using searchable semantic web languages.
The background research has been on semantic web techniques that can be applied to this problem. The intention behind this research is to provide a tool that can be used by people who don't have access to CAD tools or other specialist software. It is to aid communication of product information throughout an organisation.
The Figure shows the methodology behind the semantic web modelling. The diagram explains the semantic web modelling process, at all stages from ontology to results visualisation. We have already prototyped all these stages, but have not yet developed a fully working modelling system to be used outside the university.
We have been using a Decision Support and Modelling tool provided by Vanguard Corporation [1], for calculation and modelling.
1. Connections are established between the ontology system and any databases, spreadsheets, or other systems that hold relevant information for that modelling problem.
2. The ontology is created using RDF/OWL [2], and an interface built to allow domain experts to edit the ontology.
3. Libraries are created in a partnership between ourselves and domain experts.
4. Taxonomies are populated by model builders who want to use them for their modelling problem. These are based on the libraries created in step 3.
5. Taxonomies are colour coded for ease of understanding, this part of the diagram was built with Vanguard system (explained below). We have created a link between the ontology tool and this decision support and calculation tool. Vanguard system reads information from the ontology tool.
6. There are 2 sorts of constraints that can be used in order to make it easier for users to build and adapt models. These are constraints on the way the ontology, and models are built, and user interface constraints to reduce the scope for error.
7. The colour coding makes calculation clearer because all taxonomies can be used in any calculation, this results in a multicoloured result tree that represents the entire calculation history. User choices affect how items are related for the calculation; choices could be made manually or via a search. Colour can also be used to represent cost, time, or uncertainty.
8. Each node can also represent uncertainty, and we have prototyped including uncertainty expressions in the calculations.
9. The result tree can be represented on the web and in other programs, this allows for further searching, processing and evaluation of results. Visualisation techniques and the use of searchable languages such as XML, and SVG can assist in this.
10. and 11. Experts such as designers can interact with the ontology, the model, and results, it's intended that there will be a two way feedback mechanism where the expert can make changes at any stage, and this filters into changed results. This can then support a cycle of results and rework.
Software that is been investigated for representing ontologies and translating to program code and visualisation is Stanford University's Protégé [3], Jena [4], and Kaon [5]. Applications that are built with ontology tools such as the above and include a development environment for calculation and decision support are Metatomix m3t4 [6], TopBraid Composer [7], and General Electric's ACUITy enterprise modelling tool [8]. These tools include Java Eclipse extensions for high level programming. We have also investigated transformations that can translate the ontology into representations in other languages and tools. We have prototyped this translation for decision support tools Vanguard System [1] and Cost Estimator [9], and languages including XML (eXtensible Mark-up Language), and Java. XML has mainly been used as a neutral format for representing information, but its rich structure makes it suitable for use as a programming language e.g. AspectXML [10]. Further research can be undertaken into representing the information in Meta languages such as metaL [11] and Simkin [12]. The result documents could be searched using XQuery within Exist [13] and SPARQL (Simple Protocol and RDF Query Language) [14] and edited using XForm editors such as Orbeon XForms [15].
An elaborator needs to follow a structured taxonomy to establish how related concepts represented visually can be represented in equivalent code and vice versa. The visualisation can be either as a tree (that can be colour coded to represent different types of information) or as an interactive SVG (Scalable Vector Graphics) diagram of a component to be modelled. This example shows a tree based representation of an aircraft spar http://www.cems.uwe.ac.uk/~phale/Flash/FlashHCI.htm, this uses software by Rhodes et al. explained in [16]. This example http://www.cems.uwe.ac.uk/~phale/InteractiveSVGExamples.htm shows how a tree based representation is converted into an interactive diagrammatic representation, and explains how this transformation is performed. This elaboration process converts an abstract representation of a problem to a concrete model created with the aid of two way communication between the user and the modelling tool.
End-User Programming using the Semantic Web.
[1] Vanguard System http://www.vanguardsw.com/products/vanguard-studio/.
[2] Bechhofer S., Carrol J. (2004) Parsing owl dl: trees or triples? - http://citeseer.ist.psu.edu/713845.html - Proceedings of the 13th international conference on World Wide Web, NY, USA pp 266 - 275.
[3] Protégé http://protege.stanford.edu/ - welcome to protégé.
[4] Jena http://jena.sourceforge.net/ - Jena - A Semantic Web Framework for Java.
[5] Kaon http://kaon.semanticweb.org/ - Welcome to KAON.
[6] Metatomix m3t4 http://www.metatomix.com/news/060307.html - Metatomix Provides Free Semantic Toolkit for Eclipse Developers Worldwide.
[7] TopBraid Composer http://www.topbraidcomposer.com/ - The Complete Semantic Modeling Toolset.
[8] Aragones, A., Bruno, J., Crapo, A., Garbiras M. (2006) An Ontology-Based Architecture for Adaptive Work-Centered User Interface Technology, Jena User Conference 2006, Bristol, UK - Paper - PDF Paper - Presentation - Powerpoint Presentation.
[9] Koonce, D., Judd, R., Keyser, T., Bailey, M. A. (2000) Cost Estimation Tool Integrated into FIPER, American Institute of Aeronautics and Astronautics http://www.engineous.com/resources.htm.
[10] AspectXML Project - http://www.aspectxml.org/.
[11] MetaL http://www.meta-language.net/ - MetaL: An XML based Meta-Programming language.
[12] Simkin. (2006). http://www.simkin.co.uk/ - A high-level lightweight embeddable scripting language which works with Java or C++ and XML.
[13] Exist http://exist.sourceforge.net/xquery.html - Open Source Native XML Database.
[14] SPARQL http://dret.net/glossary/sparql - Simple Protocol and RDF Query Language.
[15] Orbeon Xforms http://www.orbeon.com/ - Form-based web applications, done the right way.
[16] Rhodes, G., Macdonald, J., Jokol, K., Prudence, P., Aylward, P., Shepherd, R., Yard, T., 2002. A Flash Family Tree, in: Flash MX Application and Interface Design Flash MX Application and Interface Design ISBN:1590591585.
A Flash movie that presents this concept using a simple example - User Driven Modelling Demonstration.
Flash Taxonomy viewer that can be used to view eXtensible Markup Language (XML) taxonomies. Flash XML Taxonomy Viewer Example - Flash HCI Example. This is based on an example from a book Flash MX Application and Interface Design (Rhodes, G. et al)
Interactive SVG Examples - Interactive SVG Examples - Wing Components.
Java applet example shows the tree translated to Java - Java Applet Example.
Vanguard Global Knowledge Portal - Spar Example - XML Generator - Spar - Translated from Protégé Ontology - outputs results to other languages - e.g. XML, Java, SVG.
XML example links to an XSL stylesheet. This doesn't render in Mozilla Firefox. XML Example.
An ontology is a classification structure. A Taxonomy can be just a convenient structure to assist programmers or part of an overall 'thesaurus' which describes and agrees the meaning of things. This 'thesaurus' structure is the ontology and may contain one or more taxonomies. Engineers may have different names for the same thing, e.g. wing skin stiffeners may be referred to as stringers, but rib stiffeners are never called stringers. There is a relationship of stringer to stiffener, which needs to be defined, and this definition depends on the context. A classification scheme or ontology is necessary in order to make communication precise. Such an ontology can also be used to help non-specialists to understand a terminology of a particular domain. This should also be aided by publishing the ontology and allowing tagging of content by users, the advantages of this in creating a shared understanding of what things mean is explained in (JISC, 2007). Cayzer (2004) argues for provision of mechanisms to allow web page creators to tag their pages easily and as a natural part of the page creation. The ontology can also enable communication between the computer systems and users (Garcia-Castro and Gomez-Perez, 2006). Hunter (2002) explains how taxonomies can be the basis of the definitions for an ontology, and that commercial software is available. Hunter gives examples of the Ministry of Defense technology taxonomy, and the Boeing online ontology. The taxonomy "Type-Of" and "Part-Of" relationships can indicate how to construct the taxonomy. Ciocoiu et al (2000) explain that taxonomies or ontologies of manufacturing concepts and terms can assist with avoiding misunderstandings and can aid communication. Veryard (2001) and McGuinness (2000) provide useful guides on how ontologies can assist in linking distributed data. This linking and connectivity is also explained by Uschold (2000) and Uschold and Gruninger (2004).
Knowledge based systems need to allow a variety of people in different disciplines to share knowledge across functional, departmental, and disciplinary boundaries. Consideration is needed of the further problem that certain knowledge should be shared with others outside the organisation such as suppliers, and customers.
There is a strong need for uniting of the approaches of top down ontology definition by a small group of experts with that of the bottom up approach of allowing all users to define the ontology. Software applications are needed that allow users with little software knowledge to edit and update ontologies themselves. The extent to which an organisation allows this depends on its structure but if this is completely prevented or not enabled in the first place, there will be user dissatisfaction resulting from their lack of involvement. It is also likely that progress in defining and editing the ontology would be delayed.
The varied user base of knowledge systems results in a further problem, which is that of fragmentation of the language itself. As the users are in different trades and professions they will not necessarily understand the same words, or assign to them the same meaning. Again this makes it necessary to structure the information in a knowledge-based system carefully, to ensure it can be well visualised, and agreements can be reached.
Relationships between terms such as type-of, and part-of become more important than the term itself, as the relationship defines the meaning of the term by relating it to the other terms. These relationships can then be represented in diagrammatic form and navigated, in order to allow the meaning of terms to be agreed and explained. A classification structure such as this is termed the ontology.
The objective is to build a catalogue and make use of it for decision support and costing systems, while demonstrating that the same approach could be used for other types of system(s). It is essential that this catalogue can query information from organisations' existing database systems. Most large organisations have key operational knowledge and information dispersed across different types of information systems, often in Relational Databases. This has the advantage of allowing the use of the standardised language Structured Query Language (SQL) to access this information.
Cayzer, S. 2004. Semantic Blogging and Decentralized knowledge Management. Communications of the ACM. Vol. 47, No. 12, Dec 2004, pp. 47-52. ACM Press.
Ciocoiu, M., Gruninger, M., Nau, D. S., 2000 - Ontologies for Integrating Engineering Applications - Journal of Computing and Information Science in Engineering 1(1) pp 12-22.
Garcia-Castro R, Gomez-Perez A, Interoperability of Protégé using RDF(S) as interchange language, 2006, 9th Intl. Protégé Conference, July 23-26, 2006 - Stanford, California. - http://protege.stanford.edu/conference/2006/submissions/abstracts/3.4_Garcia-Castro_Gomez-Perez_Protege2006.pdf.
Hunter, A., 2002. Engineering Ontologies http://www.cs.ucl.ac.uk/staff/a.hunter/tradepress/eng.html.
JISC - Anderson, P., 2007. What is Web 2.0? Ideas, technologies and implications for education - http://www.jisc.ac.uk/media/documents/techwatch/tsw0701b.pdf - JISC (Joint Information Systems Committee) Technology and Standards Watch, Feb. 2007 - Within 15 years the Web has grown from a group work tool for scientists at CERN into a global information space with more than a billion users. Currently, it is both returning to its roots as a read/write tool and also entering a new, more social and participatory phase. These trends have led to a feeling that the Web is entering a 'second phase' - a new, 'improved' Web version 2.0. But how justified is this perception?
Veryard R., 2001. Data Mappings http://www.users.globalnet.co.uk/~rxv/infomgt/datamapping.pdf.
McGuinness, D. L., 2000. Conceptual Modeling for Distributed Ontology Environments. Proceedings of the Eighth International Conference on Conceptual Structures Logical, Linguistic, and Computational Issues (ICCS 2000), Darmstadt, Germany. August 14-18, 2000.
Uschold, M., 2000. Creating, integrating and maintaining local and global ontologies. In: Proceedings of ECAI-2000: The European Conference on Artificial Intelligence Amsterdam.
Uschold M, Gruninger M, 2004, Ontologies and Semantics for Seamless Connectivity, - http://www.sigmod.org/sigmod/record/issues/0412/12.uschold-9.pdf - Boeing, Univerity of Maryland - Association for Computer Machinery - Special Interest Group on Management of Data - SIGMOD Record December 2004 Vol 33 Number 4.
In this work the focus is on combining the development of dynamic software created in response to user actions, with object oriented, rule based and semantic web techniques. This helps solve problems of mismatch of data between object oriented and relational database systems identified by Ambler (2003). The information is highly structured. Visualisation of this structure in order to represent the relationship between things clarifies the semantics. The meaning can be seen not just by the name of each item but also by the relationship of other items to it. It is envisaged that this taxonomy will provide a design costing capability, but the taxonomy and the techniques used to put it together could be re-used for other purposes. Eventually this taxonomy could become part of an overall ontology. At first this would be a light-weight ontology and this could be evaluated for usefulness before deciding on whether it would need to be more structured. Hunter (2002) evaluates engineering ontologies and gives examples. Issues involved in visualisation of light weight ontologies are examined by Fluit et al (2003). An important reason for creation of an open standards central ontology is that it can be accessed by many different applications. The open standard OWL (Web Ontology Language) is explained by Bechhofer and Carroll (2004). Research of others in this field has been investigated Corcho and Gómez-Pérez (2000), Corcho et al. (2003), and Noy (2004).
The ontology is made up of taxonomies for each domain such as parts, processed, materials. Wherever possible, agreement on the terminology, and method of use, for each taxonomy should be sought, or a published standard used e.g. Process Specification Language (PSL) of the National Institute of Standards and Technology (NIST). A representation of PSL as XML can be found at PSL-XML (Lubell, 2006). PSL-XML can be used with OWL, both OWL and PSL-XML can be based on RDF-XML (Resource Description Framework) implemented with XML (eXtensible Markup Language). This makes our translation process simpler and can enable interaction with other systems. This kind of solution is referred to in 'Ontologies and Semantics for Seamless Connectivity' Uschold and Gruninger (2004).
Process Specification Language (PSL) Page - http://www.cems.uwe.ac.uk/amrc/seeds/PeterHale/ProcessSpecificationLanguage.htm.
RDF/XML can be used to encode an ontology. (Fensel et al. 1998) describe Ontobroker and the use of XML and RDF within this ontology tool. The use of ontologies is being driven by e-commerce and e-procurement where trading is online (UN/CEFACT and ebXML 2007). RDF/XML can provide an explicit and generic way of representing associations between items, or differentiating between an Inheritance and a Contains relationship. XML schemas and DTDs (Document Type Definitions) can be helpful in defining these relationships, but there is then scope for differences in the way they are defined. RDF has provided a layer of standardised semantics which overlays the basic XML. The RDF text can be embedded within XML. RDF extends the XML model and syntax to be specific for describing resources. For example Engine Ring Manufacture sequence can be represented as a sequence of groups of sequential operations. Being XML based an RDF/XML Web page can be linked to an XSL stylesheet to produce a visual representation of the structure as in this example.
Ambler, S. W., 2003. The Object-Relational Impedance Mismatch http://www.agiledata.org/essays/impedanceMismatch.html.
Hunter, A., 2002. Engineering Ontologies http://www.cs.ucl.ac.uk/staff/a.hunter/tradepress/eng.html.
Fluit, C., Marta, S., Harmelen, F. V., 2003. Supporting User Tasks through Visualisation of Light-weight Ontologies http://www.cs.vu.nl/~frankh/abstracts/OntoHandbook03Viz.html.
Bechhofer, S., Carrol, J., 2004. Parsing owl dl: trees or triples?. - http://citeseer.ist.psu.edu/713845.html - Proceedings of the 13th international conference on World Wide Web, NY, USA, pp 266-275.
Corcho, O., Gómez-Pérez, A., 2000. A Roadmap to Ontology Specification Languages. Proceedings of the 12th International Conference on Knowledge Engineering and Knowledge Management, Chicago, USA.
Corcho, O., Fernández-López, M., Gómez-Pérez, A., 2003. Methodologies, Tools and Languages For Building Ontologies. Where is their Meeting Point?. Data and Knowledge Engineering, 46, pp 41-64.
Noy, N.F., 2004. Semantic Integration: A Survey Of Ontology-Based Approaches. SIGMOD Record, Special Issue on Semantic Integration, 33(4).
Lubell, J., 2006. Representation of Process Descriptions http://ats.nist.gov/psl/xml/process-descriptions.html.
Uschold, M., Gruninger, M., 2004. Ontologies and Semantics for Seamless Connectivity, Association for Computer Machinery - Special Interest Group on Management of Data - SIGMOD Record December, 33(4).
Fensel, D. & Angele, J. & Decker, S. & Erdmann, M. & Shnurr, H. & Studer, R. & Witt, A. 1998. On2broker: Lessons Learned from Applying AI to the Web. http://www.aifb.uni-karlsruhe.de/WBS/Publ/2000/llfaattw_dfeetal_2000.pdf, accessed on 9th January 2007.
ebXML 2002, ebXML Enabling a Global Electronic Market. http://www.ebxml.org, OASIS & UN/CEFAC, accessed on 9th January 2007.
Shim et al (2002) explain the importance of the web for all types of decision support activity "At the beginning of the 21st century, the Web is the center of activity in developing DSS." Shim et al explain how decision support systems can be provided at low cost and for geographically dispersed companies, customers and suppliers. They cite Power (2006b) when stating "Web-based DSS have reduced technological barriers and made it easier and less costly to make decision-relevant information and model-driven DSS available to managers and staff users in geographically distributed locations." This was the reasoning behind the DATUM (Design Analysis Tool for Unit-cost Modelling) project research (Scanlan et al, 2006). An open standard web driven method of collaboration is required to make it possible for organisations and individuals to become more deeply involved in projects that are well coordinated using web technologies. Shim et al explain how the use of web technologies to standardise user interface design across different models can dramatically improve the ease of use of decision support software. This standardisation can also ease problems of installation and maintenance.
(Morris et al, 2001) examine Interactivity and collaboration on the web. Aziz et al (2005) examine how open standards software can assist in an organisation's collaborative product development. This approach is outlined in (Ciancarini et al, 2001) that explains ways of designing a document-centric coordination application over the Internet. (Ciancarini et al. 2001) explain that web documents can be generated on the fly. This can allow the user interface to respond dynamically to choices. Program code can be attached to the documents themselves, and code can activate certain behaviour based on the XML (eXtensible Markup Language) content of the document. Code can also be created separately and called on as a service when a document needs it. (Nidamarthi et al (2001) explain how web based collaboration can aid the design process. (Huang and Mak, 2001) evaluate issues in the development and implementation of web applications for product design and manufacture. Reed et al (2000) show how web based modelling and simulation can be used in the aircraft design process. Kim et al (2002) explain their approach to modelling and simulation. Zhang et al (2004) review Internet-based product information sharing and visualisation. Li (2005) examines the role of web based services for distributed process planning optimization.
The intention is to further the research of others into the approach of web based collaboration, and use semantic web software and techniques to achieve this. The above research reinforced our view that this is a robust approach. Modelling collaborations based on these techniques would bring together experts in engineering, systems modelling, computing, and Human Computer Interaction.
Shim, J.P., Warkentin, M., Courtney, J. F., Power, D J., 2002, Past, present, and future of decision support technology. Decision Support Systems 33 pp 111-126.
Power, D. J., 2006. Free Decision Support Systems Glossary - http://www.DSSResources.COM/glossary/.
Scanlan, J., Rao, A., Bru, C., Hale, P., Marsh, R., 2006. DATUM Project: Cost Estimating Environment for Support of Aerospace Design Decision Making. Journal of Aircraft, 43(4).
Morris, S., Neilson, I., Charlton, C., Little, J., 2001. Interactivity and collaboration on the WWW - is the 'WWW shell' sufficient?. Interacting with Computers, 13, pp 717-730.
Aziz, H., Gao, J., Maropoulos, P., Cheung, W. M., 2005. Open standard, open source and peer-to-peer tools and methods for collaborative product development. Computers in Industry, 56, pp 260-271.
Ciancarini, P., Rossi, D., Vitali, F. 2001. Designing a document-centric coordination application over the Internet. Interacting with Computers, 13, pp 677-693.
Nidamarthi, S., Allen, R. H., Ram, D. S., 2001. Observations from supplementing the traditional design process via Internet-based collaboration tools. Computer Integrated Manufacturing, 14(1), pp 95-107.
Huang, G. Q., Mak, K. L., 2001. Issues in the development and implementation of web applications for product design and manufacture. Computer Integrated Manufacturing, Vol 14(1), pp 125-135.
Reed, J. A., Follen, G. J., Afjeh, A. A., 2000. Improving the Aircraft Design Process Using Web-Based Modeling and Simulation. ACM Transactions on Modeling and Computer Simulation, 10(1), pp 58-83.
Kim, T., Lee, T., Fishwick, P., 2002. A Two Stage Modeling and Simulation Process for Web-Based Modeling and Simulation. ACM Transactions on Modeling and Computer Simulation, 12(3), 230-248.
Zhang, S., Weimen, S., Hamada, G., 2004. A review of Internet-based product information sharing and visualization. Computers in Industry, 54, pp 1-15.
Li, W. D., 2005. A Web-based service for distributed process planning optimization. Computers in Industry, 56, pp 272-288.
Information is scattered within organisations and often not held in such a structured way as to be easily accessed by employees or software. This problem was examined by Lau et al (2005) using the example of McDonnell Douglas (now part of Boeing), that demonstrated how difficult it is to gather unstructured knowledge. Therefore, it is important that research is undertaken into methods of capturing, structuring, distributing, analysing, and visualising information. Even where documents are represented using XML or other structured languages, it would be useful to structure the contents and semantics using an ontology, Erdmann and Studer (1999) experiment with this. This structuring using an ontology as could improve the accuracy of searches. XML may not be sufficient on its' own for defining ontologies. The XML syntax defines relationships by their position within the text file. Thus XML syntax always implies a sequence whereas in reality the order of items may be unimportant, also there is no explicit way of representing associations between items, or differentiating between an Inheritance and a Contains relationship. XML schemas and DTDs (Document Type Definitions) can be helpful in defining these relationships, but there is then scope for differences in the way they are defined. RDF has provided a layer of standardised semantics which overlays the basic XML. RDF is explained using a web page annotated with RDF http://www.cems.uwe.ac.uk/amrc/seeds/PeterHale/RDF/RDF.htm#RDFXML. The RDF text can be embedded within XML. McGuinness (2003) explains the role of markup languages in defining content to be machine readable, McGuinness cites a diagram from a presentation by Berners-Lee (2000) that contains a diagrammatic representation of the place of each language in a stacked representation alongside the purpose of the language.
Berners-Lee, T., 2000. Semantic Web on XML http://www.w3.org/2000/Talks/1206-xml2k-tbl/slide1-0.html.
Erdmann, M., Studer, R. 1999. Ontologies as Conceptual Models for XML Documents. In: Proceedings of the 12th Workshop on Knowledge Acquisition, Modelling and Management (KAW'99), Banff, Canada, October 1999. - http://xml.coverpages.org/erdmann-semantic-xql-webdb00.pdf.
Lau, H. C. W., Ning, A., Pun, K. F., Chin, K. S., Ip, W. H., 2005. A knowledge-based system to support procurement decision. Journal of Knowledge Management, 9(1), pp 87-100.
McGuinness D. L., 2003. Ontologies Come of Age. In: Dieter Fensel, Jim Hendler, Henry Lieberman, and Wolfgang Wahlster, ed. Spinning the Semantic Web: Bringing the World Wide Web to Its Full Potential. MIT Press, 2003.
The main area of study for this research is the enabling of users such as engineers to model the problems they encounter in manufacturing and design. However the wider aim is to prototype research for enabling a much larger range of software users to model their problems. The intention is to create collaborative tools that allow users to develop software in a way they will be familiar with from their use of spreadsheets. Sternemann and Zelm (1999) explained that even then it had become necessary to research collaborative modelling and visualization tools, because of the business trend towards global markets and decentralised organisation structures. To achieve this, Semantic Web tools would be used that represent the information to be shared in an open standard way. Cheung et al (2007) explain the necessity for collaboration tools to support early stage product development within networked enterprises. The system should consist of applications to be combined in order to represent a layered architecture of:-
Database - ontology engine - ontology visualizer - calculation engine - inputs visualizer - results visualizer
The aim is to ensure ease of development and use of the software system by using applications that operate at one or more levels in a conceptual hierarchy, while still being able to communicate with the layers above and below in the hierarchy, and with other applications. McGuinness (2003) writes about how ease of use via conceptual modelling support and graphical browsing tools is essential if systems are to be usable for mainstream use. To facilitate this, open standard tools are used and communication tested within the overall system. The communication mechanism should be invisible to the end user who cannot be expected to consider such matters. This communication would involve large amounts of related information being translated and passed on in its entirety rather than just individual objects or messages. The intention for this main prototype is to facilitate full communication between software applications and so make it easier for engineers and others to collaborate and co-ordinate their product design and manufacture.
This system would manage software to be used in the following areas - Knowledge Management, Decision support, and Simulation. The system will provide automated translation from a model provided by the user, or by other systems into the software, ontology, and database representation. Any required calculations would then be made and translated to provide a model that can be interpreted by users. Johnson (2004) explains that successful interaction requires mapping between levels of abstractions and that translation between the levels of abstraction required by users and computers is difficult. He explains that this problem often means systems are created that make the user cope with the problems of this mis-translation. The research is intended to solve this problem by giving users more involvement in the translation process by letting them interactively model the problem themselves until they are satisfied with the solution. This allows the user to establish "common ground" with the computer, an expression used by Johnson. Nurminen et al (2003) evaluate a system called NICAD that used calculation rules in this manner. Nurminen et al emphasize that successful expert systems have in common that they put user needs at the centre of a fast and agile development process. The authors explain that users prefer usability over automation, and that users should drive the more difficult tasks where they are needed and leave routine tasks to the system. As well as translating between the user and computer systems it is necessary to provide translations between different computer systems. Ciocoiu et al (2000) make the point that as it becomes necessary to translate between more systems the number of paths for the translation increases exponentially. To improve interoperability it is therefore necessary to provide either a translator or multiple translators, and the translators would be based on taxonomies or ontologies.
The basis of this research is an ontology that can be visualized and edited in tree form. Gruber (1993a) defines and ontology - "An ontology is an explicit specification of a conceptualization. The term is borrowed from philosophy, where an Ontology is a systematic account of existence. For AI systems, what 'exists' is that which can be represented." Gruber goes on to explain design criteria for ontologies. Fensel et al (2001) explain Grubers' ontology definition. They explain that conceptualization refers to an abstract model of a phenomenon in the real world which identifies its relevant concepts. Explicit means the types of concepts and the constraints are explicitly defined. Fensel et al cite another Gruber paper where Gruber (1993b) defines the ontology as a formal explicit specification, and explains that formal means the ontology should be machine understandable. Cheung et al (2005) cite Davies et al (2002) in explaining that ontologies "provide a shared and common understanding of a domain that can be communicated between people and application systems". McGuinness (2003) explains with the aid of a diagram the level of definition in ontologies, from purely human readable to machine readable. A similar diagram with more specific computing technologies is included in Uscholds' presentation (2006) and his paper of 2003 which shows a continuum -
Implicit - Informal (explicit) - Formal (for humans) - Formal (for machines)
Uschold states that "there is nothing inherently good about being further along the semantic continuum. In some cases there will be advantages; in other cases there will not. What is good is what works." In my research I have tended to move from left to right towards more formal representations but only as necessary to ensure the modelling approach works. Horrocks (2002) explains that "An ontology typically consists of a hierarchical description of important concepts in a domain, along with descriptions of the properties of each concept. The degree of formality employed in capturing these descriptions can be quite variable, ranging from natural language to logical formalisms, but increased formality and regularity clearly facilitates machine understanding."
The ontology created in Protégé for this research has formal definitions of is-a relationships, and formal instances. Therefore it is much more machine readable than those at the human readable only end of the ontology scale. In fact it is tested as machine readable by the automated conversion process from the Protégé representation to the decision support modelling system used for calculations. The decision support system can be made to read hierarchical trees from Protégé and it can split or combine these trees or branches as needed for the model being used, and in response to decisions made by the user. Logical constraints are informal and failures are caught by the modelling tool which will flag any illogical expressions. It would be better to represent such logical constraints in the ontology also, as is done in the most rigorous machine readable ontologies, this was not finished due to time constraints and because it was not necessary for validation of the concept.
In this research I attempt to take a problem, break it down into sub parts that can be represented by a number or equation, and then allow the user to see and interact with the whole solution as applicable to this persons' defined problem. Gruber examines how equations and quantities can be represented in an ontology. To achieve this I have investigated and/or created tools to allow visualization and interaction with models. This approach has also been taken by Crapo et al (2002) who explain "Models are artefacts used to understand our world. As such they are embedded in intelligent systems as representations of knowledge. In the context of mining data to create knowledge, the modeler is often faced with discovering and understanding relationships in data that have no apparent analog in the laws of physical science. Sketches and diagrams as aids in problem solving and as a means of communication are as old as recorded history. The question now is: Can visualization help us not only to discover the patterns and relationships in these data but also to use newly discovered knowledge to build computational models." Eng and Salustri (2006) discuss the role of computers in aiding decision making, and explain that human mind is the best tool for making decisions. They explain that visualization systems must help the user use the information access capabilities of computers. So the task is to enable the creation and sharing of these visualizations in all ways that can aid in the understanding of the problems to be modelled.
Cheung et al (2005) explain that ontologies until recently have been predominately applied in the medical informatics field. Linking ontologies with modelling tools will also make ontologies very useful, in engineering and science, and mathematics whenever calculations are required. The open standard Stanford University (2007) ontology management tool Protégé has been used for this purpose, although there are other ontology tools that could have been used. This ontology can be translated into a Decision Support tool called Vanguard Studio. Vanguard (2007) are creating a modelling network where universities can share decision support models over a network.
Uschold (2003) defines the Semantic Web as being machine usable and associated with more meaning. Semantic web technologies and the use of agents and ontologies are explained by Hendler (2001), Horrocks (2002), and Uschold (2003) who explains that "In order to carry out their required tasks, intelligent agents must communicate and understand meaning". Horrocks explain the use of meta-data annotations and how they can make resources accessible to agents. Meta programming is the writing of programs that write or manipulate other programs (or themselves) as their data. The idea behind the use of this technique is that instead of writing programs to do a task a domain expert needs the program for, the meta program developer creates an environment which all domain experts, in this and similar fields, can use to create their own solutions. The developer then only needs to maintain and improve this programming environment, and can concentrate on this task; the domain expert can concentrate on solving the problem at hand without having to ask the developer to create the code on his or her behalf. This can prevent problems of misunderstanding, delay, and expense that often result from communication of difficult concepts between people who are experts in different areas (domain expert and programming expert).
Meta programming is writing of programs by other programs. The purpose of this is to provide a cascading series of layers that translate a relatively easy to use visual representation of a problem to be modelled, into code that can be run by present day compilers and interpreters. This is to make it easier for computer literate non-programmers to specify instructions to a computer, without learning and writing code in computer languages. To achieve this, any layer of software or information must be able to read the code or the information represented in any other. Code and information are only separated out as a matter of design choice to aid human comprehension, they can be represented in the same way using the same kinds of open standard languages. Meta-programming can be used as a tool to produce software for linking ontologies, Semantic Web, modelling, and visualization.
Cheung, W. M., Maropoulos, P. G., Gao, J. X., Aziz, H., 2005. Ontological Approach for Organisational Knowledge Re-use in Product Developing Environments. In: 11th International Conference on Concurrent Enterprising - ICE 2005, University BW Munich, Germany.
Cheung, W. M., Matthews, P. C., Gao, J. X., Maropoulos, P. G., 2007. Advanced product development integration architecture: an out-of-box solution to support distributed production networks. International Journal of Production Research March 2007.
Ciocoiu, M., Gruninger, M., Nau, D. S., 2000. Ontologies for Integrating Engineering Applications. Journal of Computing and Information Science in Engineering, 1(1) pp 12-22.
Crapo, A. W., Waisel, L. B., Wallace, W. A., Willemain, T. R., 2002. Visualization and Modelling for Intelligent Systems. In: C. T. Leondes, ed. Intelligent Systems: Technology and Applications, Volume I Implementation Techniques, 2002 pp 53-85.
Eng, N., Salustri, F. A., 2006. "Rugplot" Visualization for Preliminary Design. In: CDEN 2006 3rd CDEN/RCCI International Design Conference University of Toronto, Ontario, Canada.
Fensel, D. Van Harmelen, F. Horrocks, I. McGuinness, D. Patel-Schneider, P. F., 2001. OIL: An ontology infrastructure for the semantic web. IEEE Intelligent Systems, 16(2), pp 38-45.
Gruber, T. R. 1993. Toward Principles for the Design of Ontologies Used for Knowledge Sharing. In: N. Guarino and R. Poli, ed. Formal Ontology in conceptual Analysis and Knowledge Representation. Kluwer Academic Publishers.
Gruber, T.R. 1993. A Translation Approach to Portable Ontology Specifications, Knowledge Acquisition, vol 5 pp 199-220.
Hendler, J., 2001. Agents and the Semantic Web. IEEE Intelligent Systems Journal.
Horrocks, I., 2002. DAML+OIL: a Reason-able Web Ontology Language - proceedings of the Eighth Conference on Extending Database Technology (EDBT 2002) March 24-28 2002, Prague. http://www.cs.man.ac.uk/~horrocks/Publications/download/2002/edbt02.pdf.
Johnson, P., 2004. Interactions, Collaborations and breakdowns. In: ACM International Conference Proceeding Series; Proceedings of the 3rd annual conference on Task models and diagrams Vol 86 Prague, Czech Republic.
McGuinness D. L., 2003. Ontologies Come of Age. In: Dieter Fensel, Jim Hendler, Henry Lieberman, and Wolfgang Wahlster, ed. Spinning the Semantic Web: Bringing the World Wide Web to Its Full Potential. MIT Press, 2003.
Nurminen, J. K., Karaonen, O., Hatonen, K., 2003. What makes expert systems survive over 10 years-empirical evaluation of several engineering applications. Expert Systems with Applications 24(2) pp 199-211.
Stanford University, 2007. Welcome to protégé http://protege.stanford.edu/.
Sternemann, K. H., Zelm, M., 1999. Context sensitive provision and visualisation of enterprise information with a hypermedia based system, Computers in Industry Vol 40 (2) pp 173-184.
Uschold, M., 2003. Where are the Semantics in the Semantic Web? - http://lsdis.cs.uga.edu/events/Uschold-talk.htm - Michael Uschold, The Boeing Company - AI Center colloquium - published in AI Magazine 2003 - http://lsdis.cs.uga.edu/SemWebCourse_files/WhereAreSemantics-AI-Mag-FinalSubmittedVersion2.pdf - http://portal.acm.org/citation.cfm?id=958674 - Uschold, M., 2003 Where are the semantics in the semantic web? AI Magazine Vol 24 (3) pp 25 - 36.
Vanguard Studio, 2007. Vanguard Studio http://www.vanguardsw.com/products/vanguard-studio/.
So far my taxonomies include the traditional object oriented relationships such as child, parent, sibling, attribute, and instance. There are other types of relationship that would need to be modelled in order to maximise the capabilities of software that would use the taxonomies. Basic key relationships used within the object oriented programming domain between objects are implemented. These key relationships depict families of objects that may share attributes and methods through inheritance. They also describe aggregations of objects that make (usually) some geometric sense. Semantic descriptions with more relationship types than this allow a more expressive depiction of a problem domain, and can aid some forms of search within a model. One of the main advantages of a semantic net description, in terms of automated model generation, is that labelling relationships between objects allows the depiction of a number of aspects of a domain in one model, and with a consistent syntax. Ciocoiu et al (2000) explain how an engineering ontology can be made more rigorous in order to facilitate interoperability. This allows representation of, say, a product structure and its manufacturing processes together. A single node then is the only representation of that node within the model, with all its relationships depicted as arcs emanating/terminating at the node. More expressive semantic descriptions are possible through the use of one of the standard OWL dialects. Protégé has OWL plug-ins available that provide this functionality, together with links to reasoning tools for maintaining and analysing the logical constructs (Storey et al, 2004) and (Elenius, 2005). The University of Victoria Computer-Human Interaction and Software Engineering lab (CHISEL) (University of Victoria, 2006) has developed Jambalaya (Ernst et al, 2003) for visualization of knowledge and relationships. Cheung et al (2005) provide an ontology editor for knowledge sharing in manufacturing.
It is also important not to stay limited on one ontology development environment but instead explore how ontologies can be developed using a range of development tools and translated between each where necessary (Garcia-Castro and Gomez-Perez, 2006) are testing this as explained in chapter 4. For this reason, a large range of ontology management tools have been investigated and meta languages. An interesting development is SWRL a Semantic Web Rule Language Combining OWL and RuleML and its use in modelling (Miller and Baramidze, 2005).
Bloodsworth, P., Greenwood, S., COSMOA: An Ontology-Centric Multi-Agent System For Coordinating Medical Responses To Large-Scale Disasters, 2005. - AI Communications archive Volume 18 Issue 3 - Agents Applied in Health Care - Pages: 229 - 240 - ISSN:0921-7126 - Citation - http://portal.acm.org/citation.cfm?id=1218877.
Cheung, W. M., Maropoulos, P. G., Gao, J. X., Aziz, H., 2005. Ontological Approach for Organisational Knowledge Re-use in Product Developing Environments. In: 11th International Conference on Concurrent Enterprising - ICE 2005, University BW Munich, Germany.
Ciocoiu, M., Gruninger, M., Nau, D. S., 2000. Ontologies for Integrating Engineering Applications. Journal of Computing and Information Science in Engineering, 1(1) pp 12-22.
Elenius, D., 2005. The OWL-S Editor - A Domain-Specific Extension to Protégé. In: 8th Intl. Protégé Conference - July 18-21, 2005 - Madrid, Spain.
Ernst, N. A., Storey, M., Allen, P., Musen, M., 2003. Addressing cognitive issues in knowledge engineering with Jambalaya http://www.neilernst.net/docs/pubs/ernst-kcap03.pdf - - KCAP workshop - Visualization in Knowledge Engineering.
Frankel, D. Hayes, P. Kendall, E. McGuinness, D., The Model Driven Semantic Web - 1st International Workshop on the Model-Driven Semantic Web (MDSW2004) Enabling Knowledge Representation and MDA® Technologies to Work Together (2004).
Garcia-Castro R, Gomez-Perez A, 2006. Interoperability of Protégé using RDF(S) as interchange language. In: 9th Intl. Protégé Conference, July 23-26, 2006 - Stanford, California.
Storey, M., Lintern, R., Ernst, N., Perrin, D., 2004, Visualization and Protégé In: 7th International Protégé Conference - July 2004 - Bethesda, Maryland.
University of Victoria, 2006. Model Driven Visualization (MDV) http://www.thechiselgroup.org/?q=mdv.
I am developing a project to provide free online collaborative modelling tools.
Peter Hale Research - http://www.cems.uwe.ac.uk/~phale/
Examples - http://www.cems.uwe.ac.uk/~phale/InteractiveSVGExamples.htm
Semantic Web Modelling - http://www.cems.uwe.ac.uk/amrc/seeds/Modelling.htm
Visualization - http://www.cems.uwe.ac.uk/amrc/seeds/Visualisation.htm.
E-Health and Grids - http://www.cems.uwe.ac.uk/cccs/researchgroup.php?menu=off&group=ehealthgrids.
MammoGrid - http://www.cems.uwe.ac.uk/cccs/project.php?menu=off&name=mammogrid - With the advent of the information age in radiology clinicians are being presented with analysis opportunities hitherto unforeseen, both in terms of data volumes and in data interpretation. Grids computing promises to resolve many of the difficulties in facilitating medical image analysis to allow clinicians to collaborate without having to co-locate.
Olive, M., Rahmouni, H., Solomonides, T., From HealthGrid to SHARE: A Selective Review of Projects - http://geneva2007.healthgrid.org/proceedings/proceedings/pdf/32.pdf - Mark OLIVE, Hanene RAHMOUNI and Tony SOLOMONIDES - CCCS - CEMS Faculty - UWE, Bristol - Proceedings of Healthgrid 2007 - Geneva, Switzerland. April 2007 - also available - http://www.cems.uwe.ac.uk/cccs/publications.php?menu=off - PDF.
Home page - http://agent-research.co.uk/ - Welcome to my homepage. I am Peter Bloodsworth a Research Fellow in the Centre for Complex Cooperative Systems at the University of the West of England, Bristol. Before that I was a Research Student within the CAP group at Oxford Brookes University. Prior to this I studied for a BSc in Computing and Mathematics at Bristol UWE - its nice to be back again. I also own a consultancy business - Agentsis Consulting (website pending still!!). - My research is mainly within the field of Artificial Intelligence, especially that involving:
Other areas of interest include:
Peter Bloodsworth Talks with Talis about multi-agent systems, Ontologies, and the Health-e-Child project - http://blogs.talis.com/nodalities/2007/11/peter_bloodsworth_talks_with_t.php - In our latest Talking with Talis podcast, I talk with Dr Peter Bloodsworth of the University of the West of England (UWE) in Bristol. We discuss his research background, and the evolution of his interests from multi-agent systems toward the use of Semantic Web Ontologies. We conclude by looking at the ways in which this research is being put into practice with the European Health-e-Child project. - 27th November 2007.
Peter Bloodsworth Talks with Talis about multi-agent systems, Ontologies, and the Health-e-Child project - http://www.mefeedia.com/entry/peter-bloodsworth-talks-with-talis-about-multi-agent-systems-ontologies-and-the-health-e-child-proje/4773248/ - Video from Talking with Talis.
SHARE - http://www.cems.uwe.ac.uk/cccs/project.php?menu=off&name=share -The SHARE project (Supporting and structuring Healthgrid Activities and Research in Europe) aims to define a roadmap for future healthgrid research, highlighting opportunities, obstacles and potential bottlenecks.
Software Engineering Research Group - http://www.cems.uwe.ac.uk/cccs/researchgroup.php?menu=off&group=serg - SERG's mission is to bridge the gap between software engineering research and its application to different disciplines.
OntoREM: Ontology-driven Requirements Engineering Methodology - This research aims to investigate and develop an Ontology driven Requirements Engineering Methodology (OntoREM) that addresses the needs of complex, trans-national and multidisciplinary fields with particular reference but not limited to the aerospace industry.
SoAgile: Adaptive Model-Driven Service-Oriented Architectures for Agile Cyber-Enterprise Processes - The SoAgile project aims to design, develop, demonstrate, and disseminate a service-adaptable virtualisation layer and an encompassing evolutionary service-oriented and model-driven engineering environment.
Himalia - http://www.himalia.net/index.html - Model-driven user interfaces - Himalia is the first and only high-abstraction level User Interface Builder.
The Semantic Discovery System - http://www.insilicodiscovery.com/v2/index.php - We aim to Accelerate Research in Information Discovery focused Organisations. - The Semantic Web will put enormous new power in the hands of everyone trying to get valuable answers from the web - instead of frustrating Google searches, people will get fast, accurate and highly valuable answers - because they will finally be able to ask the exact questions they really want. Our product - SDS - focuses this new Semantic Web power not just on the 'Web' but also on the valuable information locked inside organisational databases - for the first time, ordinary people will be able to get answers that would otherwise have taken impossible amounts of programming. - http://www.meaning2go.com/ - Ian Goldsmid - http://www.linkedin.com/in/iangoldsmid.
Semantic Web Projects and Applications - http://www.cems.uwe.ac.uk/amrc/seeds/PeterHale/RDF/RDF.htm#SemanticWebProjectsApplications.
Modelling Publications - http://www.cems.uwe.ac.uk/amrc/seeds/Modelling.htm#UsefulPublications.
Semantic Web Applications - http://userdrivenmodelling.blogspot.com/2008/05/semantic-web-applications.html - This article is about the need for provision of Semantic Web applications to increase the amount of Semantic Web information that could be searched. This could result in a virtuous circle of Semantic Web applications creating Semantic Web information, and so justifying the creation of more Semantic Web applications to access it. The article advocates the use of Semantic Web applications for modelling and end-user programming, and integration into business applications. - 5th May 2008
Semantic Web Articles - http://www.cems.uwe.ac.uk/amrc/seeds/PeterHale/RDF/RDF.htm#SemanticWebArticles.
Semantic Web Collaboration - http://ezinearticles.com/?Semantic-Web-Collaboration&id=1160019 - This article discusses how Semantic Web/Web 2.0 collaboration can enable ontology editing. This helps reach agreement on the meaning of terms, and encourages end-user modelling/programming by enabling simplified development of online applications. This could be an efficient way of managing large ontologies with multiple users. - 9th May 2008.
Semantic Web Papers - http://www.cems.uwe.ac.uk/amrc/seeds/PeterHale/RDF/RDF.htm#UsefulPublications.
Semantic Web/Web 2.0 Research - http://www.cems.uwe.ac.uk/amrc/seeds/PeterHale/RDF/RDF.htm#SemanticWebandWeb2Research - Examples from Research.
XForms - http://www.cems.uwe.ac.uk/amrc/seeds/Ajax/ajax.htm#XForms
A Semantic Infosphere - http://www.cs.man.ac.uk/~horrocks/Slides/ISWC-Presentation-SemanticFiltering.pdf - Steve Uczekaj, CaseyFung, Fred Dickey, Michael Wilke, Sonia Smith, Peter Clark, MikeUschold, Ian Horrocks, Sean Bechofer.
A Space Surveillance Ontology: Captured in an XML Schema - http://www.fas.org/spp/military/program/track/space_pulvermacher.pdf - October 2000, Mary K. Pulvermacher - Daniel L. Brandsma - John R. Wilson.
A Theory of Compatible Versions - http://www.xml.com/lpt/a/1684 - XML.com - David Orchard - December 20, 2006.
Addressing The Limitations Of Open Standards - Kelly, B., Guy, M., Dunning, A., 2007. - http://www.ukoln.ac.uk/web-focus/papers/mw-2007/paper-standards/ - Museums and the Web 2007 - San Francisco 11-13th April 2007.
AeroDAML: Applying Information Extraction to Generate DAML Annotations from Web Pages. - Kogut, P. & Holmes, W. 2002. - http://semannot2001.aifb.uni-karlsruhe.de/positionpapers/AeroDAML3.pdf, accessed on 9th January 2007
Aeronautical Information (AICM/AIXM) - http://www.eurocontrol.int/aim/public/standard_page/interop_aicm.html - AICM is a conceptual/logical model that uses entities, attributes and relationships in order to describe aeronautical features such as airports, runways, navaids, obstacles, routes, terminal procedures, airspace structures, services and related aeronautical data.
An XML implementation process model for enterprise applications Tao, Y., Hong, T., Sun S., 2004. Computers in Industry 55 (2004) 181-196.
BBC Radio 4 - Material World - http://www.bbc.co.uk/radio4/science/thematerialworld_20071129.shtml - 2nd item - Intelligent agents - A new breed of intelligent agents could soon be saving our cities and negotiating crucial deals on the Stock Exchange.
Clockwork - http://clockwork.open.ac.uk/ - Open - University - Knowledge Media Institute - Creating Learning Organisations with Contextualised Knowledge-Rich work Artifacts.
DAML+OIL: a Reason-able Web Ontology Language - Horrocks, I., 2002. - proceedings of the Eighth Conference on Extending Database Technology (EDBT 2002) March 24-28 2002, Prague. http://www.cs.man.ac.uk/~horrocks/Publications/download/2002/edbt02.pdf.
Discrete-Event Modeling Ontology (DeMO): - http://www.cs.uga.edu/~jam/jsim/DeMO/ - DeMO is an ontology for discrete-event modeling (DEM) (system dynamics for discrete-event systems (DES)). The models in the ontology focus on how state evolves over time.
Distributed Constructionism - http://llk.media.mit.edu/papers/Distrib-Construc.html - Proceedings of the International Conference on the Learning Sciences Association for the Advancement of Computing in Education, Northwestern University (accepted: March 1996; published: July 1996) - This paper introduces the concept of distributed constructionism, building on previous research on constructionism and on distributed cognition. It focuses particularly on the use of computer networks to support students working together on design and construction activities, and it argues that these types of activities are particularly effective in supporting the development of knowledge-building communities. The paper describes three main categories of distributed constructionist activities: discussing constructions, sharing constructions, and collaborating on constructions. In each category, it describes ongoing research projects at the MIT Media Lab and discusses how these projects support new ways of thinking and learning.
End-User Development Techniques for Enterprise Resource Planning Software Systems - http://drops.dagstuhl.de/opus/volltexte/2007/1097/pdf/07081.SpahnMichael.Paper.1097.pdf - Michael Spahn, Stefan Scheidl, Todor Stoitsev - SAP AG, SAP Research CEC Darmstadt, End-User Software Engineering M. H. Burnett, G. Engels, B. A. Myers, G. Rothermel (Eds.) - http://drops.dagstuhl.de/portals/index.php?semnr=07081.
Engineering Conceptual Data Models from Domain Ontologies: A Critical Evaluation - El-Ghalayini, H., Odeh, M., McClatchey, R. (2005) Engineering Conceptual Data Models from Domain Ontologies: A Critical Evaluation - IASTED International Conference on Databases and Applications, part of the 23rd Multi-Conference on Applied Informatics, Innsbruck, Austria pp 222-227.
Engineering ontologies - http://www.cs.ucl.ac.uk/staff/a.hunter/tradepress/eng.html - Anthony Hunter.
E-Steel - http://www.e-steel.com/home.shtml - Managing Supply Risk & Material Price Volatility of your Extended Supplier Network.
Gartner Group Report - Gartner Says Business Application Vendors Face Challenge to Move to ' The Process of Me' - http://www.gartner.com/press_releases/asset_152638_11.html - Person to Process Interaction is the Next Innovation Step in Business Software Press Release 2006.
Horrocks, I., Patel-Schneider, P. F., van Harmelen, F., 2003. From SHIQ and RDF to OWL: The making of a web ontology language. Journal of Web Semantics, Vol 1(1), pp 7-26.
Ian Horrocks - http://www.cs.man.ac.uk/~horrocks/ - professor in the School of Computer Science at the University of Manchester.
IDEF - Integrated Definition Methods - IDEF Family of Methods - http://www.idef.com/ - A structured approach to enterprise modelling and analysis - IDEF.com was developed and is maintained by Knowledge Based Systems, Inc. (KBSI), the developers of the next generation IDEF methods: the IDEF3 Process Flow and Object State Description Capture Method, the IDEF4 Object-Oriented Design Method, and the IDEF5 Ontology Description Capture Method.
Integrated Visualization for Semantic Web - Ing-Xiang, C., Chun-Lin, F., Pang-Hsiang. L, Li-Chia, K., Cheng-Zen, Y., - http://iswc2004.semanticweb.org/posters/PID-SDILZKDC-1090228300.pdf - 2005. 19th International Conference on Advanced Information Networking and Applications. Vol.2. 28-30 March 2005. pp. 701-706.
INTEROP Newsletter N#9 - Winter 2006 - http://interop-noe.org/newsletter/newsletter-9/ - The INTEROP Knowledge Map.
INTEROP - public deliverables of INTEROP-NoE and ATHENA-IP are already available on the INTEROP-VLab website http://www.interop-vlab.eu - the platform of INTEROP-VLab has been chosen by the European Commission (DG INFSO, unit D4 'Networked Enterprise and RFID) to be the official repository of public deliverables from all projects in the domain of Enterprise Interoperability conducted under the 6th and 7th framework programmes.
Jess the Rule Engine for the JavaTM Platform - http://www.jessrules.com/ - Jess is a rule engine and scripting environment written entirely in Sun's Java language by Ernest Friedman-Hill at Sandia National Laboratories in Livermore, CA.
Knowledge Web - The KnowledgeWeb Project - http://kmi.open.ac.uk/projects/kweb/ - Knowledge Web is a Network of Excellence that aims to support the transition of Ontology technology from Academia to Industry. The current consortium is integrated by 18 participants including leading partners in Semantic Web, Multimedia, Human Language Technology, Workflow and Agents. The NoE will concentrate its efforts around the outreach of this technology to industry. Naturally, this includes education and research efforts to ensure the durability of impact and support of industry.
Knowledge Web FP6-507482 - http://knowledgeweb.semanticweb.org/semanticportal/sewView/frames.jsp - Knowledge Web (KW) is a 4 year Network of Excellence project funded by the European Commission 6th Framework Programme. Knowledge Web began on January 1st, 2004. Supporting the transition process of Ontology technology from Academia to Industry is the main and major goal of Knowledge Web.
Magpie - http://kmi.open.ac.uk/projects/magpie/main.html - Magpie uses our ontology infrastructure to semantically markup web documents on-the-fly. The existing technologies in this problem domain tend to be rather heavyweight, and often modify the appearance of the actual webpage.
Management of a Technical Knowledge in a Company Intranet - http://ieeexplore.ieee.org/iel5/6601/17627/00814278.pdf?arnumber=814278.
McGuinness D. L., 2003. Ontologies Come of Age. In: Dieter Fensel, Jim Hendler, Henry Lieberman, and Wolfgang Wahlster, ed. Spinning the Semantic Web: Bringing the World Wide Web to Its Full Potential. MIT Press, 2003.
Michael F. Uschold - http://ontolog.cim3.net/cgi-bin/wiki.pl?MichaelUschold - Dr. Michael Uschold is a research scientist at Boeing Phantom Works, the advanced research and development organization of The Boeing Company.
MOKA Overview - http://www.kbe.coventry.ac.uk/moka/moka.htm - A Framework for Structuring and Representing Engineering Knowledge.
MONET Home Page - http://monet.nag.co.uk/cocoon/monet/index.html - The MONET project is a two-year investigation into mathematical web services funded by the European Commission, as part of the Information Society Technologies (IST) Programme of the Fifth Framework. The project started on 1st April 2002.
NeOn - http://www.neon-project.org/web-content/ - NeOn is a 14.7 million Euros project involving 14 European partners and co-funded by the European Commission's Sixth Framework Programme under grant number IST-2005-027595. NeOn started in March 2006 and has a duration of 4 years. Our aim is to advance the state of the art in using ontologies for large-scale semantic applications in the distributed organizations.
On2broker: Lessons Learned From Applying AI to the Web, Fensel, D., Angele, J., Decker, S., Erdmann, M., Schnurr, H., Studer, R., Witt, A., 2000. International Journal of Cooperative Information Systems.
On the insufficiency of ontologies: problems in knowledge sharing and alternative solutions - Correa da Silva F.S.; Vasconcelos W.W., Robertson D.S., Brilhante V., de Melo A.C.V., Finger M., Agusti J., - Knowledge-Based Systems, Volume 15, Number 3, March 2002, pp. 147-167(21).
Ontological Approach for Organisational Knowledge Re-use in Product Developing Environments - Wai M Cheung, Paul G Maropoulos, James X Gao, Hayder Aziz - 11th International Conference on Concurrent Enterprising - ICE 2005 - University BW Munich, Germany.
Ontological Modeling, 2003, Kalinichenko L, Missikoff M, Schiappelli F, Skvortsov N, Proceedings of the 5th Russian Conference on Digital Libraries RCDL2003, St. - Petersburg, Russia, 2003 - http://synthesis.ipi.ac.ru/synthesis/publications/ontomodeling/.
Ontologies: An Emerging Discipline - Michael Uschold - Boeing - Phantom Works - Invited lecture at University of Washington, Feb 21, 2006.
Ontologies and Semantics for Seamless Connectivity, 2004 - http://www.sigmod.org/sigmod/record/issues/0412/12.uschold-9.pdf - Uschold M, Gruninger M Boeing, Univerity of Maryland - Association for Computer Machinery - Special Interest Group on Management of Data - SIGMOD Record December 2004 Vol 33 Number 4.
Ontologies Come of Age, 2003. . McGuinness D. L., In: Dieter Fensel, Jim Hendler, Henry Lieberman, and Wolfgang Wahlster, ed. Spinning the Semantic Web: Bringing the World Wide Web to Its Full Potential. MIT Press, 2003.
Ontologies for Integrating Engineering Applications - Mihai Ciocoiu, Michael Gruninger, Dana S. Nau, 2000. - Journal of Computing and Information Science in Engineering 1(1) pp 12-22.
Ontologies For Modeling and Simulation, 2004 Fishwick Paul A, Miller John A, Proceedings of the 2004 Winter Simulation Conference.
Ontologies Ontologies Everywhere - but Who Knows What to Think? 2006 - http://protege.stanford.edu/conference/2006/submissions/slides/1.2_Uschold.pdf - Uschold M, Boeing - 9th Intl. Protégé Conference July 23-26, 2006 - Stanford, California - July 24 Morning Session.
Ontology-based Customizable 3D Modeling for Simulation, 2005, Park Minho, Fishwick Paul A. http://etd.fcla.edu/UF/UFE0010095/park_m.pdf - PhD Dissertation.
Ontology Development 101: A Guide to Creating Your First Ontology - http://protege.stanford.edu/publications/ontology_development/ontology101-noy-mcguinness.html - In recent years the development of ontologies-explicit formal specifications of the terms in the domain and relations among them (Gruber 1993)-has been moving from the realm of Artificial-Intelligence laboratories to the desktops of domain experts.
Ontology Query Languages for the Semantic Web: A Performance Evaluation. Zhang, Z. 2005. - Thesis - (Under the Direction of John.A.Miller).
OntoWiki - http://3ba.se - Explanation - OntoWiki - A Tool for Social, Semantic Collaboration - Auer, S., Riechert, T., Dietzold, S., 2006. - 5th International Semantic Web Conference, Athens, GA, USA, November 5-9, 2006.
OpenMath - http://www.openmath.org/ - OpenMath is a new, extensible standard for representing the semantics of mathematical objects. If you haven't heard about it before you might want to consult the overview.
OWL/SWRL representation methodology for EXPRESS-driven product information model Part I. Implementation methodology, Zhao, W. and Liu, J.K. 2008. Computers in Industry - Article in Press, Corrected Proof - Abstract - This paper presents an ontology-based approach to enable semantic interoperability and reasoning over the product information model. The web ontology language (OWL) and the semantic web rule language (SWRL) in the Semantic Web are employed to construct the product information model. The traditional modeling language called EXPRESS is discussed. The representation methodology for EXPRESS-driven product information model is then proposed. The key of the representation methodology is mapping from EXPRESS to OWL/SWRL. Some illustrated examples are presented. - Keywords - Product information model; OWL; SWRL; EXPRESS; Ontology representation.
Open standard, open source and peer-to-peer tools and methods for collaborative product development. - Aziz, H., Gao, J., Maropoulos, P., Cheung, W. M., 2005. Computers in Industry, 56, pp 260-271.
Potential Modeling and Simulation Applications of the Web Ontology Language - OWL, 2004 Lacy Lee, William Gerber, Proceedings of the 2004 Winter Simulation Conference.
Proceedings of the 2005 Winter Simulation Conference - http://www.informs-cs.org/wsc05papers/297.pdf - Simulation and the Semantic Web - M. E. Kuhl, N. M. Steiger, F. B. Armstrong, and J. A. Joines, eds.
Reap the long-term rewards of knowledge management - http://www.vnunet.com/computing/analysis/2075853/reap-long-term-rewards-knowledge-management - Michael Gubbins, Computing 27 Nov 2003.
Rolls-Royce - Securing the Future at Rolls-Royce - http://www.e-steel.com/resources/pdfs/Rolls-Royce_A_Closer_Look.pdf - Managing Materials Risk for the Extended Supply Chain.
RuleML - http://www.ruleml.org/ - Rules in (and for) the Web have become a mainstream topic since inference rules were marked up for E-Commerce and were identified as a Design Issue of the Semantic Web, and since transformation rules were put to practice for document generation from a central XML repository (as used here). Moreover, rules have continued to play an important role in AI shells for knowledge-based systems and in Intelligent Agents, today both needing a Web interchange format, and such XML/RDF-standardized rules are now also usable for the declarative specification of Web Services. The Rule Markup Initiative has taken steps towards defining a shared Rule Markup Language (RuleML), permitting both forward (bottom-up) and backward (top-down) rules in XML for deduction, rewriting, and further inferential-transformational tasks.
Semantic Filtering - Introduction - Presentation - Mike Uschold, Deborah Folger, Scott Smith, Stephen Uczekaj, Casey Fung - Boeing - April 21 2005.
Semantic Filtering - http://www.cs.man.ac.uk/~horrocks/Publications/download/2003/UCDF+03a.pdf - Paper - A Semantic Infosphere - M. Uschold, P. Clark, F. Dickey, C. Fung, S. Smith1, S. Uczekaj, M. Wilke, S. Bechhofer, and I. Horrocks - Boeing, University of Manchester.
Semantic Learning Webs. Stutt, A. and Motta, E. (2004). Journal of Interactive Media in Education, 2004 (10). Special Issue on the Educational Semantic Web. ISSN:1365-893X http://www-jime.open.ac.uk/2004/10.
Semantic Web Metadata for e-Learning - Some Architectural Guidelines Nilsson, M., Palmér, M., Naeve, A., 2002. - WWW2002 Hawaii USA.
Simulation and the Semantic Web - Miller, J A., Baramidze, G., - 2005. - Proceedings of the 2005 Winter Simulation Conference.
Some industrial information scenarios - Can the Semantic Web help? - http://www.w3c.rl.ac.uk/pastevents/moss_files/frame.htm - Michael Moss Rolls - Royce - W3C European Semantic Web Tour 2003 12 June 2003 London.
Spacecraft Markup Language (SML) - http://www.interfacecontrol.com/sml/sml/mainpage.htm.
The Enterprise Ontology - MIKE USCHOLD, MARTIN KING, STUART MORALEE and YANNIS ZORGIOS - This is a comprehensive description of the Enterprise Ontology, a collection of terms and definitions relevant to business enterprises. We state its intended purposes, describe how we went about building it, define all the terms and describe our experiences in converting these into formal definitions.
The International Workshop on Metamodelling - Utilization in Software Engineering and ICSoft - http://www.icsoft.org/MUSE.htm - July 5, 2008 - Porto, Portugal and ICSoft - July 5-8 - Topics of interest include, but are not limited to: Metamodelling and modelling theory - Metamodelling and ontologies - Impact of metamodelling on standards development - Use of metamodelling in agent-oriented software engineering - Use of metamodelling in object-oriented software engineering - Metamodels as underpinnings for modelling languages - The role of metamodels in MDA and model transformations - Metamodelling in relation to tool building - Metamodel support for process measurement and improvement - Business reasons for adopting a metamodel - in conjunction with the Third International Conference on Software and Data Technologies (ICSOFT 2008).
The Sim Blog - http://thesimblog.org/ - The purpose of this blog is to discuss topics related to all areas of discrete event simulation, robotic simulation, and PLC emulation. - Joe Hugan.
UML for Ontology Development. - Kogut, P. & Cranefield, S. & Hart, L. & Dutra, M. & Baclawski, K. & Kokar, M. & Smith, J. 2002. - http://whitepapers.techrepublic.com.com/whitepaper.aspx?docid=92641, The Knowledge Engineering Review Vol 17(1) pp 61-64.
Visual Knowledge - http://www.visualknowledge.com - Semantic WIKI - Visual Knowledge build conventional applications that are driven by ontologies rather than by code. A great deal of our underlying systems and frameworks are also model driven.
Visualization and Protégé - http://protege.stanford.edu/conference/2004/abstracts/Storey.pdf - Margaret-Anne Storey, Robert Lintern, Neil Ernst, David Perrin - University of Victoria, Victoria, BC, Canada - 7th International Protégé Conference - Tuesday 6th - Friday 9th, July 2004 - Bethesda, Maryland.
Visualization and the process of modeling: a cognitive-theoretic view - Conference on Knowledge Discovery in Data - Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining - Andrew W. Crapo, Laurie B. Waisel, William A. Wallace, Thomas R. Willemain.
Where are the Semantics in the Semantic Web? - http://lsdis.cs.uga.edu/events/Uschold-talk.htm - Michael Uschold, The Boeing Company - AI Center colloquium - published in AI Magazine 2003 - http://lsdis.cs.uga.edu/SemWebCourse_files/WhereAreSemantics-AI-Mag-FinalSubmittedVersion2.pdf - http://portal.acm.org/citation.cfm?id=958674 - Uschold, M., 2003 Where are the semantics in the semantic web? AI Magazine Vol 24 (3) pp 25 - 36.
Modelling - http://www.cems.uwe.ac.uk/amrc/seeds/Modelling.htm#Conferencesrecentandfuture.
Semantic Web - http://www.cems.uwe.ac.uk/amrc/seeds/PeterHale/RDF/RDF.htm#Conferencesrecentandfuture.
Software Engineering Conferences - http://www.cems.uwe.ac.uk/amrc/seeds/softwareengineering.htm#Conferences.
Systems Engineering Conferences - http://www.cems.uwe.ac.uk/amrc/seeds/softwareengineering.htm#Conferences.
SEEDS Page - SEEDS Home Page
Software Engineering Research Group (SERG) - http://www.cems.uwe.ac.uk/cccs/researchgroup.php?menu=off&group=serg - SERG's mission is to bridge the gap between software engineering research and its application to different disciplines.
Peter Home Page - Peter Hale Home Page
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