This is the list of some of the projects using Protégé. If you want to add yours, we suggest that you use the following template ProjectThatUseProtegeTemplate (the explanations on how to use this template are included).    (3N1)

The 4M Project envisages a system that supports a maintenance man in his service activities. The system uses OWL ontologies to represent multilinguistic information about the domain. Protégé is used to create these ontologies.    (5J6)

Transformation of geospatial information given in texts into map representations.    (5CC)

AKT is a multimillion pound project between 5 top UK universities (Southampton U., Open U., Sheffield U., Aberdeen U., and Edinburgh U.). The project investigates a wide range of issues related to the life cycle of knowledge managements.    (5I1)

Uses Protégé to prototype a repository for the product design of investment advice in wealth management. It is a research project at the University of Fribourg, Switzerland    (4W0)

This work investigates the use of ontologies in the data analysis step of the KDD process. Our objective is to support the data preparation phase adding a semantic level to the data in order to select the most important features to the target problem. More specifically, this project applies an on-line analytical process to explore ontologies and makes a semantic mapping between the multi-dimensional ontology representation and the tabular format used in the OLAP tools. This tabular format can be translated to specific formats used by different data mining workbenches or can be exported as an XML file or imported back to refine the ontology model.    (5G2)

A common background underlying database and ontology research is well known. Although ontologists and data modellers have been working together to bridge both areas, for example, in topics like conceptual modelling, database integration and metadata representation, less has been discussed about online analysis and multi-dimension mapping among ontologies and databases. Our approach explores this gap and applies Online Analytical Processing (OLAP) to the ontology analysis in order to refine the ontology model and improve the data and domain understanding. The Ontology On-line Analytical Preprocessing (OOLAP) enables detailed and human driven analysis of the domain.    (5G3)

Creating episode guides, cross references, translated titles, collectables, people, and events database. The Japanese series UruseiYatsura will be the test series. It is our hope that our ontology will be useful to anyone who wants to catalog any fictional series.    (4M8)

One portion of the World Engineering Anthropometry Resource (WEAR) project is to develop an ontology of anthropometric landmarks. This effort is currently in progress and Protege is invaluable to this work.    (5L6)

Exploring the use of Protege for documenting and developing work on modelling archaeological Information using the CIDOC Conceptual Reference Model (CRM)    (5CY)

Using Ontologies in the humanities to combine historical repositories for researcher investigation. This is focused upon London social history and using ontologies as a common medium to interlink information in existing repositories.    (5HO)

This project aims to design a distributed architecture of brokers deployed on the internet in order to federate bioinformatics resources (databases for example) and to propose those services as a unique interface to several profiles of users (researchers, doctors, ...).    (5HH)

We have used Protege to develop an ontology for internet business models. We work with companies in Africa primarily to help them become more competitive in the international markets utilizing the internet. We came up with the idea to develop an ontology of the different internet business models. The application will guide a business in choosing the appropiate business model.    (5HJ)

An Ontolog project in formalizing representation of the UN/CEFACT ebXML Core Component Types. The goal of this project is to provide that the ontological basis to help influence the adoption of ontologies and ontological engineering methodologies in eBusiness standards.    (5F7)

A data structure/Ontology for experimental results of cell biology, specifically the expression and perturbation.    (4HC)

The CNOSSO Project is partially funded by MIUR – Ministero dell’Istruzione, dell’Università e della Ricerca – Italy. Among the project's objectives is the re-usability of the knowledge concerning Cultural Heritage. To this end, whithin the project, we combine the different points of view through which dissimilar users observe the same cultural assets, attempting to safeguard their "knowledge customization" needs. This aim is pursued through the construction of a CIDOC CRM-based CORE ontology on which several and independent Domain ontologies are based (i.e. Domain ontology import the Core Ontology). Ontologies are produced by means of Protege.    (5L8)

We aim to realize computer services that are delivered to people in an implicit, indirect, and unobtrusive way. This will free people to interact with people and reposition machines to be in the background and - like electronic butlers - attempting to anticipate and serve people's needs.    (5H8)

Primarily interested in OWL development using Protege through Protege-OWL and several of its common plugins (such as OWLViz etc).    (4X8)

The COBrA-CT project will develop a client/server-based model for ontology curation using the OGSA-DAI Grid middleware.    (5HU)

The system will allow remote users to create and submit annotated changes to ontologies and also to participate in the review process. The system will also support the curator by providing the appropriate management tools and visualisations. A key element of our solution is to re-engineer the COBrA ontology editor and mapping tool as a Protege plug-in. This tool will communicate with an ontology management server. COBrA was originally developed by the XSPAN project (http://www.xspan.org).    (5HV)

COBrA-CT will specifically address bio-ontologies: the Open Biological Ontologies (OBO) and the Gene Ontology (GO).    (5HW)

A joint SMI / CIM3 project to develop and host an open Collaborative Ontology Development Service and Ontology Repository for the ontology community at large.    (5FB)

Distributed, loosely-controlled, and evolving ontologies pose an interesting challenge to groupware technology. Available tools do not promote collaboration, discussion, and exchange of ideas, all of which are critical components of any ontology development process in a geographically distributed community. Although it is possible for several users to edit the same file, discussion amongst domain experts is not promoted by the interaction nor the interactivity between information and informants. Groupware technology should support, in a more sophisticated way, those processes in which different domain experts have to interact via electronic means. It is necessary to provide cognitive support for the ontology development process in loosely centralized environments. Conceptual maps should play a more central role in the ontology development process, not only during knowledge elicitation but also promoting interaction and access to the information. We are developing an extension of Protege that aims to provide an environment for ontology development within distributed, loosely-controlled, and evolving environments.    (5L2)

The project will develop the world’s first theoretical framework and original computational models of biologically plausible artificial neural networks that simulate neural activity of certain brain areas in relation to internal networks of genes. We call these models “computational neurogenetic models”. They may lead to the discovery of yet unknown dynamic relationships between genes and states of the brain. Models will integrate relevant gene and brain data and knowledge to model certain dynamic aspects of brain functioning, especially in genetically-related diseases such as epilepsy and schizophrenia, under different conditions, for instance with the presence of drugs, and to allow qualified prognosis. Models will be validated on real data. So far such a scientific endeavour has not been attempted. The results and knowledge will be made publicly available through an online Gene-Brain-Disease Ontology database and scientific publications. An extension of computational neurogenetic framework for modelling other complex biological processes will also be investigated. The research will help the software industry to develop more sophisticated intelligent information systems for applications in medicine and healthcare. The computational neurogenetic framework will make a significant contribution to the areas of computer and information sciences, neuroinformatics, and bioinformatics, and will have a high international impact.    (5EB)

Coalition Secure Management and Operations System will provide a capability for multiple disparate Command and Control applications to share vital battlefield information within a coalition enviornment. With a smarter exchange of information to the right systems at the right time we hope to reduce confusion on the battlefield thus reducing "Friendly Fire" incidents. In order to accomplish this we would like to make use of the Protege product in order to model ontologies that would allow a more productive use of the information exchange.    (5KD)

The Finnish Chapter of http://www.dama.org develops an ontology in data management domain. We have passed the basic studying phase of OWL and Protege and the year 2006 should see the first version, defined in Finnish language. Later, we will try to modify it into a multilingual version, adding Swedish and English.    (5L4)

Design-a-Trial is a complex decision support system that helps medical researchers plan a randomised controlled trial (RCT) and authors a trial protocol. The system incorporates an ontology of RCTs developed using Protege and is based on prior work by the Stanford Protege team.    (5L0)

As part of a 10 year modernization of a large government agency (unidentified), The MITRE Corproation is developing a 10 year roadmap for information technology projects. It was necessary to catalogue and characterize over 200 projects currently underway or planned, how they interrelate, and how they were sequenced. The Protege system was used to catalogue and categorize all the agency's projects and relate them in a long term sequencing plan. The resulting ontology is being used as a program management tool by the Agency to gain an understanding of their current "as-is" architecture and plans and create a roadmap to the "to-be".    (5JB)

The European project for Standardized Transparant Representations in order to Extend Legal Accessibility (Estrella, IST-027665) aims to develop and validate an open, standards-based platform allowing public administrations to develop and deploy comprehensive legal knowledge management solutions, without becoming dependent on proprietary products of particular vendors. Estrella will support, in an integrated way, both legal document management and legal knowledge-based systems, to provide a complete solution for improving the quality and efficiency of the determinative processes of public administration requiring the application of complex legislation and other legal sources. Estrella will facilitate a market of interoperable components for legal knowledge-based systems, allowing public administrations and other users to freely choose among competing development environments, inference engines, and other tools.    (5CB)

The aim of this project is to extract the regularities in the folksonomies created by user tagging on sites like del.icio.us. Social tagging is a new phenomenon which has recently been surrounded by a lot of noise. Many claim that they are superior to ontologies and that Semantic Web applications based on formal ontologies have been super ceded. My aim is to show that folksonomies and ontologies are not that different.    (5LA)

I am currently building a method for translating between folksonomy and ontology. This will be implemented in Protege. The link above points to my blog in which I discuss my ideas, and potential contributions to the Protege implementation are very welcome. Protege projects will be made available on that site.    (5LB)

An ontology and knowledgebase describing gene functions enabeling biologists to annotate (multiple) genes on Affymetrix Microarrays per simple drag and drop. Annotation-classes and genes (instances) can be linked for fast and intuitive context-exploration and extensive querying using relations and is_a subsumptions. Generated gene annotations can be explored as interactive semantic networks with advanced visualisation tools.    (5DI)

The Generalized Upper Model (GUM) is a general task and domain independent `linguistically motivated ontology' intended for organizing information for expression in natural language. It is a descendent of the Penman Upper Model, originally developed by Bill Mann, Christian Matthiessen and others at the USC/ISI in Los Angeles. We are currently providing a full re-axiomatization of the Generalized Upper Model in OWL-DL using Protégé as the main development environment. The current ontology contains around 220 classes and 80 properties. Domain knowledge organized in terms of the GUM is known to be expressible in natural language and so forms a useful interface language for relating between applications and natural language technology. The GUM is a development of the Bremen Ontology Research Group.    (5LP)

Developing a next generation crop information platform which is very domain model and ontology driven. Protege is being incorporated as part of the strategy for ontology management on the project. We are also trying to couple Protege with other ontology systems, like the GMOD CV module. We are also working to directly integrate OWL/RDF with our Java-based platform, portions of which are using the Eclipse Rich Client Platform.    (5IP)

Dr. Richard Bruskiewich, Senior Scientist, Bioinformatics, International Rice Research Institute, (Principal Investigator: GCP domain modeling)    (5IU)

The multiplicity of Network Management models (SNMP, CMIP, DMI, CORBA, WBEM...) has posed in the last decade the set up of mechanisms to allow the interoperability among all involved management domains. One of the basic pillars of such interoperability is the mapping between the information models that each domain specifies. Usually, these mappings have been carried out with syntactical translations that do not bear in mind the semantic aspects of the defined information. These translations could reach the semantic level by using ontologies. These ontologies, widely used in Artificial Intelligence, exactly focus on the meaning of those concepts composing an information model. The goal of this project is the improvement of current network management interoperability techniques through the study and application of formal ontologies. They would eventually allow the specification of management information in an optimal way, obtaining the integration of all concepts that currently belongs to different management domains in the same model. One of the additional advantages of this approach is the ability of using the capacity of the ontologies to specify behavior for including it as part of the managed resources definitions, so that intelligent network managers can interpret these rules to perform management tasks.    (5KA)

In this way, the management information handling can be simplified, avoiding managers' current problems, which have to deal with independent information models for each domain, and without the possibility of setting up direct relationships between them.    (5KB)

The idea is to develop an ontology for the whole of the Ghana Tourism Industry.    (5HL)

Multidisciplinary model-based water management projects have to follow a complex process and may encounter many problems, related to miscommunication, malpractice, misuse of the model, insufficient problem knowledge and overselling of model capabilities. This leads to model projects, which are not transparent and difficult to audit. The knowledge based system (KBS) discussed here provides guidelines on what to do, derived from an ontological knowledge base (KB) with state-of-the-art knowledge on 'best modelling practice' for teams, which members have different disciplinary backgrounds and play different roles in a project. Furthermore, the KBS monitors what team members actually do and helps in generating project reports for various audiences and purposes. Multimedia training material helps novice users to find their way in the KBS. The KBS is organized in a client-server architecture, enabling cooperation in distributed teams. The developers of this KBS learned that arriving at consensus on a process KB for model-based water management has an intrinsic value in itself. Professional users tested the KBS in two series of ten test cases, touching different types of problems and coping with a variety of environmental conditions across Europe. They like the KBS and their numerous comments have significantly improved the KBS. But they also expect that it will be hard to persuade the professional modelling community to use it.    (5J7)

The HarmonISA project uses Protege to model ontologies of land-use catalogues that are then used to provide semantic integration of land-use data.    (5H5)

Hermes is an human machine interface that allows users inexperienced in the image processing field to formulate their problem in their own terms. I use two ontologies for this project : one for the user with visual concepts to describe his images, the effects of the acquisition system, and his objectives of image transformation, the other ontology is made from an image processing viewpoint and permits the Hermes system to translate the user formulation in an image processing formulation for his application.    (5H1)

It is a research project as I work on this for my PhD. It is far to be efficient but the main goal of this work is to make explicit image processing knowledge used during application development. My home page is only in french at the moment. Translation into english will come soon.    (5H2)

A Java-based platform for modelling and managing complex configuration data for various applications and systems.    (4CX)

The DiCo is French lexical database of semantic derivations (synonymy, antonymy, conversivity, standard names of actants/instruments/..., etc.) and collocations. In this project, we use semantic labels to tag each lexical unit described in the database. A semantic label can be seen as being the core (genus) of the definition of the lexical unit it is associated to, and is used as a classifying "semantic identifier" for that unit.    (5KU)

We make use of Protege as a tool for building, structuring, and accessing our hierarchy of semantic labels. Our methodology is data-driven and this hierarchy is developed together with the lexical database itself.    (5KV)

HyBrow (Hypothesis Browser) system is a proof-of-concept, prototype tool for designing hypotheses and evaluating them for consistency with existing knowledge. HyBrow consists of a mathematical framework with the ability to represent diverse biological information sources, an ontology for describing biological processes at different levels of detail, a database to query information in the ontology, and programs to design, evaluate and revise hypotheses. HyBrow allows the integration of different types of biological information, such as gene expression data, gene and protein sequence homologies, as well as data on protein interactions and modifications for the purpose of evaluating alternative hypotheses about biological processes.    (5KM)

Development of a technical reference model for identity management for use with The Open Group Architecture Framework (TOGAF).    (5EM)

The Resource Aggregation Model for Learning Education and Training is a new activity within the IEEE Learning Technology Standards Committee (LTSC). This activity is defining a nomenclature and a conceptual model for digital aggregates of resources for learning, education, and training applications.    (5GD)

The project has the objective of increasing petroleum production from subsea systems by making accessible high quality real time information for decision support in operational centres onshore. An optimal set of real time data from reservoirs, wells and subsea production facilities will be identified, partially improved and integrated to provide an open and standardised information platform.    (5G9)

Integrated Knowledge Environment for development of PreAct knowledge bases.    (504)

INBIOMED is a Thematic Network of Cooperative Investigation about Biomedical Informatics funded by FIS (Health Investigation Found) of Institute Carlos III (Spain). In the technological context is the name of a storage, integration and clinical, genetics, epidemiology and images data analysis platform.    (5LF)

First an overview of insurance-related standards within the European countries participating to the eEG7 will be made. This overview can be completed with remaining European countries later on.    (5GH)

The focus will be initially on data standards, such as libraries and data models, and who is using them. Later on the overview should be extended with more technical standards such as internet protocols, XML etc.    (5GI)

Uses Protégé-OWL with a GUI created by the CO-ODE group to develop a terminology for Anesthesia. It is a project originated by the Anesthetic Patient Safety Foundation (APSF) and the terms are submitted by IOTA for inclusion in SNOMED CT.    (50M)

This project is focused on development and support of a knowledge-based framework for integration and control to support research into individualized radiation therapy. This project builds on the EON project using protocol-based guidelines for process sequencing, data gathering, and decision support. Various existing systems to be integrated include medical image acquisition and analysis, treatment planning, and treatment delivery.    (5KO)

Contact: Daniel L. McShan (dlmcshan@umich.edu)    (5KP)

Affiliation: University of Michigan / Department of Radiation Oncology    (5KQ)

No actual project Web page yet, but we have used Protege for projects discussed in LOAIT and AAAI workshops. We are looking at how legal codes can effectively be represented via ontologies.    (5JK)

Contacts: Tracy Mullen, John Bagby    (5JL)

LISp-Miner is an academic project for support research and teaching of knowledge discovery in databases. It is suitable namely for students, pilot, and mid-size KDD projects.    (5GX)

A sub-project deals with exploitation of ontologies in the course of the KDD process.    (5GV)

Note: Some of the ontologies were developed in Protege.    (5GW)

MathServe is a framework that integrates automated reasoning tools as Semantic Web Services described in OWL-S. MathServe can perform automated service matchmaking and service composition. We are using the Protege tool to model the domain ontology for MathServe.    (5GZ)

The Metadata Extraction and Tagging Service (METS) combines COTS categorization and extraction software with custom ontology-based software, to produce various XML and OWL representations of the semantic content of documents. The extracted content is stored in various XML and RDF data stores for subsequent search and analysis. The emphasis of the METS program is on the generation of large volumes of semantic information, which we hope will drive the development of more sophisticated search and analysis tools using that information.    (5JD)

The METS Program along with several other associated Governmnet Programs used Protege to share, view, and understand the METS developed ontology.    (5JE)

The Center develops and interactively integrates analysitcal and modeling technologies to acquire or create context-appropriate molecular biology information from emerging experimental data, international genomic databases, and the published literature (Supported by The National Institute of Health, Roadmap Initiative for Bioinformatics and Computational Biology).    (4X9)

NeuronBank is a new effort to create a knowledge base of identified neurons and synaptic connections in invertebrate nervous systems. Currently, there is no standard way to represent neurons and the information about neuronal identities and neural circuits is distributed across the scientific literature. NeuronBank will serve as a central catalog of neurons and be a federated system of databases that will allow users to publish information about neurons and their connections. Protege is useful because it allows the descriptions of neurons to evolve as we learn more about neurons and be modified to capture the important features of different animal species. NeuronBank is funded by a grant from that National Institute of Mental Health (NIMH) and by internal funding from the Brains & Behavior Program at Georgia State University.    (5J9)

We are developing new methods for building ontology maps and are applying them to build ontology maps of genes and proteins that are related to specific brain related disorders like epilepsy and schizophrenia. Here in this ongoing research we basically focus on the crucial neuronal parameters like AMPA, GABA, NMDA, SCN, KCN and CLC that are in some way controlling the phenomenon of epileptic seizures through their direct or indirect interactions with several genes/proteins.    (5FP)

Ontologies can provide conceptual framework and factual knowledge that is necessary to understand more on the relationship between genes involved during brain disorders and is the best way to provide a semantic repository of systematically ordered concerned molecules.    (5FQ)

Ontological representation can be used to bridge the different notions in various databases by explicitly specifying the meaning of and relations between fundamental concepts.    (5FR)

We are graphically representing these relationships in a way that enables visualization and creation of new relationships, and each instance in our ontology map is traceable through a query language that allows us, for example, to answer questions such as "which genes are related with epilepsy"?    (5FS)

This project is focusing on nutrigenomics related to aging and diabetes, with the aims of utilizing genomic data for personalized dietary advice, and managing and organizing metadata related to nutrigenomics ontologies related to diabetes and aging. Microarray data from experiments of diabetic vs. healthy and old vs. young patients is linked with nutritional data and artificial intelligence methods used to pinpoint genes of interest and diet components of relevance for healthy and disease-preventing advice.    (5FW)

GENERIC DESCRIPTION: CMBI (now become Dept. of Medical Informatics) in Peking University Health Science Center, P.R.C., has been making an effort to build formal mediating ontologies for cardiovascular domain databases. As a case study for this effort, we launched the OntoCardio project in around 2003, which is an improvement initiative to a legacy database called "Cardio". The knowledge representation methodology is extend-worthy to other analogous biomedical information systems.    (5GK)

KEY FEATURES: OWL-DL based core ontology releases; Inter-terminology mediation design (ontology framework design level); Protege Tab based java agent for instantiating DB entries into OWL-DL individuals (currently gene-centric); etc.    (5GL)

RESEARCHER/GRANT: This was a theoretical exploration on domain application knowledge engineering in around 2003. Mr. QIN Pu led the research effort and cooperated with the leader/maintainer Mr. ZHANG Qipeng et al, "Cardio DB" -- the case study database project which was supported by the China National Projects #973 Series Grant on Cardiovasculat Sciences. Currently the Cardio DB is running at http://cardio.bjmu.edu.cn.    (5GM)

CONTACT: QIN Pu (qinpu at pku.org.cn), now in National Institute of Hospital Administration, Ministry of Health, P. R. China.    (5GN)

The project aims at developing a collection of richly axiomatised 'parallel' ontologies in OWL. All ontologies model the same domain, that of conference organisation, based on different conferences and conference support tools. On the top of the collection, a HTML-based application is being built, which offers various reasoning services.    (5GS)

Note: most ontologies were built using Protege.    (5GT)

One of the greatest challenges we now face in Grid Computing regards the ability to explicitly share and deploy knowledge to be used for the development of innovative Grid infrastructure, and for Grid applications – the Semantic Grid. To address this challenge the OntoGrid project will produce the technological infrastructure for the rapid prototyping and development of knowledge-intensive distributed open services for the Semantic Grid.    (52Q)

In an Ontology-centric approach to multi-agent design, rules, heuristics, and statistical attributes that define agent behaviour are included in an ontology-layer. By placing Semantic Web technologies at the heart of a multi-agent system it is possible to create a system in which agent behaviours and internal representation are abstracted from coding. Each agent in the system uses this layer, in addition to instances, to form a knowledge base defining its behaviour. The ontology-layer is a mixture of domain specific and generic ontologies, which structures the behaviour of a multi-agent system. Such a level of abstraction makes editing the behaviour of agents more convenient, requiring only the altering of domain specific ontologies without any major changes to the coding of the system. This ontology-centric approach encourages re-use, allowing the system to move from one problem domain into another by creating an ontology layer defining the new environment and system behaviour. These features make the future possibilities of such methods exciting. Protege has been invaluable in the implementation of such systems.    (5I3)

Used Protege to produce the "OrgCode Translator" application in response to the client’s request to demonstrate a solution to Social Security Administration's long standing problems regarding integrating information from various "stove-pipe" applications that use different organization codes to index the information. The demonstrated solution is based on a federated information architecture that implements an abstract organizational code repository. The interface to the repository is modularly re-usable by both humans and automated systems and can be delivered as a web service. The changing associations between different organization codes that reside in the repository is self-maintaining and derives this quality from the solution's design architecture and not from complex and maintenance-prone business logic.    (5J0)

Contact: dennis.g.lamarre@ssa.gov    (5J1)

At the Aoyama Gakuin University we use Protege and Protege-OWL for developing ontological models for development and evaluation of management systems. Protege's ability to generate easy to use forms for dialog system enables us to use the developed ontologies not only as OWL models, but also to use the Protge project file as it is for applications. Currently we are working on ontologies for ISO 9000, ISO 9001 and ISO/IEZC 27001. With the help of the OWL-S plug-in we are developing a system, which helps to develop processes in compliance with requirements for a process approach.    (5KX)

Contact: gehrmann@yhc.att.ne.jp    (5KY)

BACKGROUND: Notifiable disease surveillance in the United States is predominantly a passive process that is often limited by poor timeliness and low sensitivity. Interoperable tools are needed that interact more seamlessly with existing clinical and laboratory data to improve notifiable disease surveillance.    (5JG)

DESCRIPTION: The Public Health Surveillance Knowledgebase (PHSkb™) is a computer database designed to provide quick, easy access to domain knowledge regarding notifiable diseases and conditions in the United States. The database was developed using Protégé ontology and knowledgebase editing software. Data regarding the notifiable disease domain were collected via a comprehensive review of state health department websites and integrated with other information used to support the National Notifiable Diseases Surveillance System (NNDSS). Domain concepts were harmonized, wherever possible, to existing vocabulary standards. The knowledgebase can be used: 1) as the basis for a controlled vocabulary of reportable conditions needed for data aggregation in public health surveillance systems; 2) to provide queriable domain knowledge for public health surveillance partners; 3) to facilitate more automated case detection and surveillance decision support as a reusable component in an architecture for intelligent clinical, laboratory, and public health surveillance information systems.    (5JH)

CONCLUSIONS: The PHSkb provides an extensible, interoperable system architecture component to support notifiable disease surveillance. Further development and testing of this resource is needed.    (5JI)

A semantic model and architecture for capturing the user perspective on Data Quality in e-science. The model lets e-scientists define, share, and reuse conceptual definitions for data quality functions, which are then bound to services. The service-based Qurator framework provides an execution environment for quality services, and supports their embedding within host data processing environments. Current applications are mostly on qualitative proteomics data.    (5FO)

The goal of the project is to develop a flexible architecture for knowledge-based analysis of the WWW. The Rainbow system employs the web service and semantic web technology to analyse and present to a user or computer agent the content and structure of legacy websites. The analysis of a website is multiway, with results being integrated. The conspicuous feature of analysis services is their systematic categorisation according to four dimensions: abstract type of task (classification, retrieval, extraction), type of ‘current’ object (e.g. document, hyperlink, image), type of analysed data (e.g. free text, HTML tags, link topology, image data), and problem domain (e.g. bicycle sales). This four-dimensional approach is captured by the so-called ‘task-object-datatype-domain’ (TODD) knowledge-level framework and by an associated collection of ontologies.    (5GP)

Note: the ontologies were developed using Protege.    (5GQ)

Situation Aware Protocols in Edge Network Technologies; the SPARTA, Inc. & Sandpiper Software team uses Protege to assist in converting OWL ontologies for use with Jess, including ontology components that describe networks, network technologies and applications.    (5FM)

The activities of this workpackage performed by the Industrial Ontologies Group for SCOMA project, focused on adding explicit semantics to the target mathematical resources, which were integrated to the SCOMA knowledge portal. The alpha version of the engine was implemented and showed the feasibility of the real portal implementation including sophisticated search features. Semantics were added in a form of metadata represented according to the standards of W3C’s Semantic Activity using Protege. SCOMA (Center for Scientific Computing and Optimization in Multidisciplinary Applications - http://www.jyu.fi/scoma/) will be a gateway between multi-disciplinary technologies and the future knowledge society in intertwining mathematical information technologies, with human behavioral and societal research groups at the university, and through partnerships with small and large industries.    (5LD)

Scyllarus is a network security alert correlator and analyzer developed by Honeywell Laboratories that uses Protégé to maintain an ontology of the protected environment, vulnerabilities and capabilities of sensors that provides the context for alert correlation. The ontology is initially populated by a number of automated tools and is then reviewed and edited using the Protégé GUI. While the Protégé GUI is used to edit the ontology, much of the work with Scyllarus has been to use the Protégé server in the backend to allow clients to access the ontology without needing to load all of the frames in their respective memory spaces.    (5FN)

The software is a collection of open-source programs designed to work together: (1) a semantic-based search engine named Kit (with recommendation capability), (2) a set of ontologies for representing knowledge relationships, (3) a navigator tool for navigating between points in the ontologies, and (4) a tagging procedure so anyone can create and publicly register a standard tag for their content and then find it with the search engine.    (5KH)

The software is available immediately on the site: http://semantical.org. It is based entirely on Semantic Web standards approved by the W3C.    (5KI)

Semantic Integration Technology Applied in Grid-based, Model-driven Architectures    (5JQ)

Used Protege to develop an ontology of the Software Engineering Body of Knowledge (SWEBOK). This ontology is based on the document of the same name that is produced and maintained by IEEE.    (5J3)

Contact: dennis.g.lamarre@ssa.gov    (5J4)

Utilized Protege to develop an ontology of SAN technology. Mapped specific vendor hardware offerings as instances of the ontology classes. This enabled a clear separation of each vendor’s SAN technology from their extensive marketing hype. One outcome was a clear "apples-to-apples" comparison of vendor technology.    (5IX)

Contact: dennis.g.lamarre@ssa.gov    (5IY)

The TaskTracer project at Oregon State University has been developing fully-functional prototypes of new task-oriented personal computer environments that track a user's interactions with all applications, automatically organize the user's information naturally according to tasks, and intelligently leverage the collected data to make desktop applications more task-aware. TaskTracer not only improves personal productivity by reducing overhead interaction and cognitive costs, but also will support collaboration in workgroups by allowing the sharing of task profiles - records of how a user completed a task, incorporating both the resources used, and high level records of actions on those resources.    (5KK)

We are using Protege with our students to generate a "biodatabase ontology" covering all concepts represented by the databases we access through the SRS portal at the European Bioinformatics Institute (EBI). This "project" has been started as an exercise for the students and is expanding now into a small research project carried on by students and some of the scientists at Fraunhofer Institute for Algorithms and Scientific Computing (SCAI). We hope to be able to publish our results this year. The final "biodatabase ontology" could serve as an abstraction layer covering concepts of all major biodatabases and thus supporting efforts to use this abstraction layer for semantic mediation.    (5HQ)

Protege is an essential tool for us and I am promoting the use of Protege wherever and whenever possible. Thanks to the scientists at Stanford and the entire Protege project for their contribution.    (5HR)

Martin Hofmann, Head of the Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing and Acting Professor for Applied Bioinformatics, Bonn-Aachen International Center for Information Technology (B-IT)    (5HS)

The Typological Database System (TDS) provides an online interface to multiple independently developed typological databases. It allows unified querying by means of an integrated global ontology developed in Protégé.    (5I5)

The TDS project is being carried out by a research group of the Netherlands Graduate School of Linguistics (LOT), with members representing the University of Amsterdam, Leiden University, Radboud University Nijmegen, and Utrecht University.    (5I6)

The Universal Data Element Framework (UDEF) provides simplification of information management through consistent classification and assignment of a structured indexing identifier to metadata. A Protégé project with the UDEF embedded in it was developed to enable UDEF identifiers to be assigned to Protégé classes and slots.    (5EN)

Prototype for multi disciplinary assessments of urban development plans (urban masterplans and neighborhood designs).    (4UE)

Course covers current research issues in M&S, including model semantics, interoperability, composability, coercion, multiresolution modeling, validation, and emergence. Semantic description underlies all of these issues. We investigate current best practices to semantic description. That includes OWL/RDF and the best editor to support its use: Protege.    (5K7)

Paul Reynolds, Professor, Computer Science, University of Virginia    (5K8)

I am presenting a paper at the ISDC 2006 in Los Angeles in May. Protege is a key component of the tool set for the paper.    (5KF)

Uses Protege-OWL for the representation of a virtual world, and for creating a causal structure of a story.    (5HC)

Complete environment for Interactive Voice Response applications definition and management. Protege is used to store all the parameters for those multilingual applications. A complete set of JSTL tags has been developed specifically for Voice Application Content Management (this is not a generic set of JSTL tags for Protege). Commercial product.    (5KS)

Vox Populi is a system for automatic generation of Biased Video Sequences. In few words, Vox Populi uses rhetorical annotations to generate video sequences. Our annotation schema encodes the verbal information contained in the audio channel, identifying the claims the interviewees make and the argumentation structures they use to make those claims.    (5HY)

Based on this schema, we construct a semantic graph which is traversed by rhetoric-based strategies selecting video segments.    (5HZ)

Uses OWL to represent design patterns used in object oriented software engineering.    (4CH)