Modeling views in the layered view model for XML using UML

In data engineering, view formalisms are used to provide flexibility to users and user applications by allowing them to extract and elaborate data from the stored data sources. Conversely, since the introduction of Extensible Markup Language (XML), it is fast emerging as the dominant standard for storing, describing, and interchanging data among various web and heterogeneous data sources. In combination with XML Schema, XML provides rich facilities for defining and constraining user-defined data semantics and properties, a feature that is unique to XML. In this context, it is interesting to investigate traditional database features, such as view models and view design techniques for XML. However, traditional view formalisms are strongly coupled to the data language and its syntax, thus it proves to be a difficult task to support views in the case of semi-structured data models. Therefore, in this paper we propose a Layered View Model (LVM) for XML with conceptual and schemata extensions. Here our work is three-fold; first we propose an approach to separate the implementation and conceptual aspects of the views that provides a clear separation of concerns, thus, allowing analysis and design of views to be separated from their implementation. Secondly, we define representations to express and construct these views at the conceptual level. Thirdly, we define a view transformation methodology for XML views in the LVM, which carries out automated transformation to a view schema and a view query expression in an appropriate query language. Also, to validate and apply the LVM concepts, methods and transformations developed, we propose a view-driven application development framework with the flexibility to develop web and database applications for XML, at varying levels of abstraction

Querying Large Physics Data Sets Over an Information Grid

Optimising use of the Web (WWW) for LHC data analysis is a complex problem and illustrates the challenges arising from the integration of and computation across massive amounts of information distributed worldwide. Finding the right piece of information can, at times, be extremely time-consuming, if not impossible. So-called Grids have been proposed to facilitate LHC computing and many groups have embarked on studies of data replication, data migration and networking philosophies. Other aspects such as the role of 'middleware' for Grids are emerging as requiring research. This paper positions the need for appropriate middleware that enables users to resolve physics queries across massive data sets. It identifies the role of meta-data for query resolution and the importance of Information Grids for high-energy physics analysis rather than just Computational or Data Grids. This paper identifies software that is being implemented at CERN to enable the querying of very large collaborating HEP data-sets, initially being employed for the construction of CMS detectors.Comment: 4 pages, 3 figure

Towards a Framework for Developing Mobile Agents for Managing Distributed Information Resources

Distributed information management tools allow users to author, disseminate, discover and manage information within large-scale networked environments, such as the Internet. Agent technology provides the flexibility and scalability necessary to develop such distributed information management applications. We present a layered organisation that is shared by the specific applications that we build. Within this organisation we describe an architecture where mobile agents can move across distributed environments, integrate with local resources and other mobile agents, and communicate their results back to the user

Semantic web technologies for video surveillance metadata

Video surveillance systems are growing in size and complexity. Such systems typically consist of integrated modules of different vendors to cope with the increasing demands on network and storage capacity, intelligent video analytics, picture quality, and enhanced visual interfaces. Within a surveillance system, relevant information (like technical details on the video sequences, or analysis results of the monitored environment) is described using metadata standards. However, different modules typically use different standards, resulting in metadata interoperability problems. In this paper, we introduce the application of Semantic Web Technologies to overcome such problems. We present a semantic, layered metadata model and integrate it within a video surveillance system. Besides dealing with the metadata interoperability problem, the advantages of using Semantic Web Technologies and the inherent rule support are shown. A practical use case scenario is presented to illustrate the benefits of our novel approach

A Process Framework for Semantics-aware Tourism Information Systems

The growing sophistication of user requirements in tourism due to the advent of new technologies such as the Semantic Web and mobile computing has imposed new possibilities for improved intelligence in Tourism Information Systems (TIS). Traditional software engineering and web engineering approaches cannot suffice, hence the need to find new product development approaches that would sufficiently enable the next generation of TIS. The next generation of TIS are expected among other things to: enable semantics-based information processing, exhibit natural language capabilities, facilitate inter-organization exchange of information in a seamless way, and evolve proactively in tandem with dynamic user requirements. In this paper, a product development approach called Product Line for Ontology-based Semantics-Aware Tourism Information Systems (PLOSATIS) which is a novel hybridization of software product line engineering, and Semantic Web engineering concepts is proposed. PLOSATIS is presented as potentially effective, predictable and amenable to software process improvement initiatives

A schema-based P2P network to enable publish-subscribe for multimedia content in open hypermedia systems

Open Hypermedia Systems (OHS) aim to provide efficient dissemination, adaptation and integration of hyperlinked multimedia resources. Content available in Peer-to-Peer (P2P) networks could add significant value to OHS provided that challenges for efficient discovery and prompt delivery of rich and up-to-date content are successfully addressed. This paper proposes an architecture that enables the operation of OHS over a P2P overlay network of OHS servers based on semantic annotation of (a) peer OHS servers and of (b) multimedia resources that can be obtained through the link services of the OHS. The architecture provides efficient resource discovery. Semantic query-based subscriptions over this P2P network can enable access to up-to-date content, while caching at certain peers enables prompt delivery of multimedia content. Advanced query resolution techniques are employed to match different parts of subscription queries (subqueries). These subscriptions can be shared among different interested peers, thus increasing the efficiency of multimedia content dissemination

An infrastructure for building semantic web portals

In this paper, we present our KMi semantic web portal infrastructure, which supports two important tasks of semantic web portals, namely metadata extraction and data querying. Central to our infrastructure are three components: i) an automated metadata extraction tool, ASDI, which supports the extraction of high quality metadata from heterogeneous sources, ii) an ontology-driven question answering tool, AquaLog, which makes use of the domain specific ontology and the semantic metadata extracted by ASDI to answers questions in natural language format, and iii) a semantic search engine, which enhances traditional text-based searching by making use of the underlying ontologies and the extracted metadata. A semantic web portal application has been built, which illustrates the usage of this infrastructure

A layered framework for pattern-based ontology evolution

The challenge of ontology-driven modelling of information components is well known in both academia and industry. In this paper, we present a novel approach to deal with customisation and abstraction of ontology-based model evolution. As a result of an empirical study, we identify a layered change operator framework based on the granularity, domain-specificity and abstraction of changes. The implementation of the operator framework is supported through layered change logs. Layered change logs capture the objective of ontology changes at a higher level of granularity and support a comprehensive understanding of ontology evolution. The layered change logs are formalised using a graph-based approach. We identify the recurrent ontology change patterns from an ontology change log for their reuse. The identified patterns facilitate optimizing and improving the definition of domain-specific change patterns

HARD: Hybrid Adaptive Resource Discovery for Jungle Computing

In recent years, Jungle Computing has emerged as a distributed computing paradigm based on simultaneous combination of various hierarchical and distributed computing environments which are composed by large number of heterogeneous resources. In such a computing environment, the resources and the underlying computation and communication infrastructures are highly-hierarchical and heterogeneous. This creates a lot of difficulty and complexity for finding the proper resources in a precise way in order to run a particular job on the system efficiently. This paper proposes Hybrid Adaptive Resource Discovery (HARD), a novel efficient and highly scalable resource-discovery approach which is built upon a virtual hierarchical overlay based on self-organization and self-adaptation of processing resources in the system, where the computing resources are organized into distributed hierarchies according to a proposed hierarchical multi-layered resource description model. The proposed approach supports distributed query processing within and across hierarchical layers by deploying various distributed resource discovery services and functionalities in the system which are implemented using different adapted algorithms and mechanisms in each level of hierarchy. The proposed approach addresses the requirements for resource discovery in Jungle Computing environments such as high-hierarchy, high-heterogeneity, high-scalability and dynamicity. Simulation results show significant scalability and efficiency of the proposed approach over highly heterogeneous, hierarchical and dynamic computing environments