Successful Semantic Web-based applications not only need large amounts of underlying well-organised and well-interrelated ontologies to support their infrastructures, but also need to provide the end-users with the consistent and continuous services as usual while the underlying ontologies changing. Research on ontology versioning and evolution addresses the issues of how ontologies cope with the internal and external changing environment so as to keep ontologies consistent. The existing works on ontology versioning and evolution focus on the changes inside ontology itself, i.e., the relationships and interoperability of the various versions, and largely neglected the issue of how changes during ontology versioning and evolution could affect the existing applications/services. The potential research work presented in this report aims at addressing how we could apply ontology versioning and evolution technologies in the existing applications so as to enable applications to provide consistent and continuous services as usual by adapting to the newly updating underlying ontologies. In this report, a middle layer between the underlying ontologies and dependent applications is proposed to build, which is used to monitor and detect any changes performed on the important parts of an ontology specific for the applications, and divert queries accordingly. The framework and requirements of the middle layer are discussed, in addition to a review of progress to date and anticipated future work.

Keeping track of ontology changes is becoming a critical issue for ontology-based applications. Updating an ontology that is in use may result in inconsistencies between the ontology and the knowledge base, dependent ontologies and applications/services. Current research concentrates on the creation of ontologies and how to manage ontology changes in terms of mapping ontology versions and keeping consistent with the instances. Very little work investigated controlling the impact on dependent applications/services; which is the aim of the system presented in this paper. The approach we propose is to make use of ontology change logs to analyse incoming RDQL queries and amend them as necessary. Revised queries can then be used to query the ontology and knowledge base as requested by the applications and services. We describe the design of our prototype system, and discuss related problems and future directions.

Updating an ontology that is in use may result in inconsistencies between the ontology and the knowledge base, dependent ontologies and applications/services. Current research concentrates on the creation of ontologies and how to manage ontology changes in terms of mapping ontology versions and keeping consistent with the instances. Very little work investigated controlling the impact on dependent applications/services; which is the aim of the system presented in this paper. The approach we propose is to make use of ontology change logs to analyse incoming RDQL queries and amend them as necessary. Revised queries can then be used to query the ontology and knowledge base as requested by the applications and services. We describe our prototype system and discuss related problems and future directions.

Keeping track of ontology changes is becoming a critical issue for ontology-based applications because updating an ontology that is in use may result in inconsistencies between the ontology and the knowledge base, dependent ontologies and dependent applications/services. Current research concentrates on the creation of ontologies and how to manage ontology changes in terms of the attempts to ease the communications between ontology versions and keep consistent with the instances, and there is little work available on controlling the impact to dependent appli- cations/services which is the aims of the system presented in this paper. The approach we propose in this paper is to manually capture and log ontology changes, use this log to analyse incoming RDQL queries and amend them as necessary. Revised queries can then be used to query the knowledge base of the applications/services. We present the infrastruc- ture of our approach based on the problems and scenarios identi?ed within ontology-based systems. We discuss the issues met during our de- sign and implementation, and consider some problems whose solutions will be bene?cial to the development of our approach.

Knowledge management is all about delivering data to the right person at the right time and in the right format. Yet there are massive amounts of very valuable data stored in inaccessible databases, and written in machine unreadable formats. The applications below attempt to unlock the potential of some of this data, and serve it back to the consumer. Funded by the Office of Public Sector Information (OPSI) to demonstrate how Semantic Web technology can be used by government to unlock the potential of public sector information.

Enabling traceable ontology changes is becoming a critical issue for ontology-based applications. Updating an ontology that is in use may result in inconsistencies between the ontology and the knowledge base, dependent ontologies and applications/services. Current research concentrates on the creation of ontologies and how to manage ontology changes in terms of mapping ontology versions and keeping consistent with the instances. Very little work investigated on-the-fly keeping track of ontology changes while update (active ontology versioning) and using these information to control the impact on dependent applications/services, which is the aim of our research presented in this thesis. The approach we propose is to make use of ontology change logs as a check-point to analyse changed entities related to the requested services via end-user?s incoming queries (RDQL/SPARQL) and amend them as necessary to maintain the validation and continuousness of the dependent application. Firstly, We build up Log Ontology I as the concept structure to organize and construct the change information, develop our prototype system to demonstrate how the change information retrieved from Log Ontology I could be used to control the impacts brought by the ontology changes on the dependent applications and services. And then, by analysing the limitations and difficulties of our prototype system in maintaining the services related to the more complex ontology changes, we identify that the problem which fails the system facing the more complex ontology changes is the inabilities of Log Ontology I to represent complex change information in a semantic fashion. Therefore, we retract to put more focuses on Log Ontology I to enable the implementation of the mechanism to on-the-fly keep track of ontology change information, forming Log Ontology II, in order to reserve the semantics of ontology change from the beginning of ontology update process. Finally we discuss the future direction in terms of how the improved Log Ontology II enables the better service validation and continuousness maintenance of changing-ontology-based applications.