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The rapid development of Extensible Markup Language (XML) from a mere data exchange format to a universal syntax for encoding domain specific information increases the need of new query languages specifically visualized to address the characteristics of XML. Such languages should be able not only to extract information from XML documents, but also to apply powerful restructuring operators, based on a well‐defined semantics. Moreover, XML queries should be natural to write and understand, as also end‐users are expected to access the large XML information bases supporting their businesses. The purpose of this paper is to propose a new graphical query language for XML (GQLX) for querying and restructuring XML data.

The methodology emphasizes on GQLX's development, which is based on G‐XML data model syntax to express a wide variety of XML queries, ranging from simple selection to expressive data transformations involving grouping, aggregation and sorting. GQLX has an operational semantics based on the annotated XML, which serves to express queries and data trees in the form of XML. The paper also presents an algorithm to achieve the matching between data and query trees after translating them into annotated XML.

Developed and demonstrated were: a G‐XML syntax; annotated XML for the semantic operations and a matching algorithm.

The future research work on this language lies in expanding it to include recursion and nested queries.

The algorithms/approaches proposed can be implemented to enhance the performance of the XML query language.

The proposed work integrates various novel techniques for XML query syntax/semantic into a single language with a suitable matching algorithm.

eXtensible Markup Language (XML) data are data which are not necessarily constrained by a schema, XML is fast emerging as a standard for data representation and exchange on the world wide web, the ability to intelligently query XML data becomes increasingly important. Some XML graphical query languages for XML data have been proposed but they are either too complex or too limited in the power of expression and in their use. The purpose of this paper is to propose a recursive graphical query language for querying and restructuring XML data (RGQLX). The expressive power of RGQLX is comparable to Fixpoint. RGQLX language is a multi‐sorted graphical language integrating grouping, aggregate functions, nested queries and recursion.

The methodology emphasizes on RGQLX's development which is base of G‐XML data model syntax to express a wide variety of XML queries, ranging from simple selection, to expressive data transformations involving grouping, aggregation and sorting. RGQLX allows users to express recursive visual queries in an elegant manner. RGQLX has an operational semantics based on the annotated XML, which serves to express queries and data trees in form of XML. The paper presents an algorithm to achieve the matching between data and query trees after translating a query tree into annotated XML.

Developed and demonstrated were: a G‐XML model; recursive queries; annotated XML for the semantic operations and a matching algorithm.

The future research work on RGQLX language will be expanding it to include recursive aggregations.

The algorithms/approaches proposed can be easily integrated in any commercial product to enhance the performance of XML query languages.

The proposed work integrates various novel techniques for XML query syntax/semantic into a single language with a suitable matching algorithm. The power of this proposal is in the class of Fixpoint queries.

Linked data (LD) has promoted publishing information, and links published information. There are increasing number of LD datasets containing numerical data such as statistics. For this reason, analyzing numerical facts on LD has attracted attentions from diverse domains. This paper aims to support analytical processing for LD data.

This paper proposes a framework called H-SPOOL which provides series of SPARQL (SPARQL Protocol and RDF Query Language) queries extracting objects and attributes from LD data sets, converts them into star/snowflake schemas and materializes relevant triples as fact and dimension tables for online analytical processing (OLAP).

The applicability of H-SPOOL is evaluated using exiting LD data sets on the Web, and H-SPOOL successfully processes the LD data sets to ETL (Extract, Transform, and Load) for OLAP. Besides, experiments show that H-SPOOL reduces the number of downloaded triples comparing with existing approach.

H-SPOOL is the first work for extracting OLAP-related information from SPARQL endpoints, and H-SPOOL drastically reduces the amount of downloaded triples.

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 viewdriven application development framework with the flexibility to develop web and database applications for XML, at varying levels of abstraction.

To review the variety of software solutions available for putting CDS/ISIS databases on the internet. To help anyone considering which route to take.

Briefly describes the characteristics, history, origin and availability of each package. Identifies the type of skills required to implement the package and the kind of application it is suited to. Covers CDS/ISIS Unix version, JavaISIS, IsisWWW, WWWISIS Versions 3 and 5, Genisis, IAH, WWW‐ISIS, and OpenIsis.

There is no obvious single “best” solution. Several are free but may require more investment in acquiring the skills to install and configure them. The choice will depend on the user's experience with CDS/ISIS formatting language, HTML, programming languages, operating systems, open source software, and so on.

There is detailed documentation available for most of these packages, but little previous guidance to help potential users to distinguish and choose between them.

One of the main motivations associated with the adoption of electronic commerce (e‐commerce) is the integration and automation of business processes. Yet, for many years the integration of systems has been a barrier to business process automation. However, a new generation of software called application integration (AI) efficiently addresses integration problems and leads to more flexible and maintainable solutions. AI incorporates functionality from disparate applications through a diversity of integration technologies. Regardless, confusion surrounding terminology in the integration area has led to a debate regarding the capabilities of AI, as each term proposes a different range of AI technologies. Therefore, there appears a clear need to clarify this confusion. In doing so, a novel taxonomy is proposed, which is based on the critical analysis and evaluation of existing case studies extrapolated from the AI literature. The proposed taxonomy separates AI into intra‐organisational AI, hybrid AI and inter‐organisational AI. The novelty of the taxonomy centres on the synthesis of a comprehensive set of systems that efficiently describe the range of AI technology in terms of application. In doing so, the taxonomy presented will allow developers and integrators to navigate better through the portfolio of integration technologies and therefore better understand the integration area. The proposed taxonomy might also be used as a tool for decision making.

It seems that manufacturers are increasingly accepting that the focus in today’s market is innovation; products that clearly differentiate themselves from others while also being affordable, reliable, and early to market. Moreover, there is a realisation that past initiatives aimed solely at product performance, cost, quality, or time to market are no longer sufficient to gain competitive advantage. Only through total management of the product lifecycle, and truly collaborative work processes involving widely distributed teams of people throughout an extended enterprise, can products be developed to meet customer needs innovately without driving up costs, sacrificing quality or delaying product delivery.

During the 1990s, companies focused on the adoption of enterprise resource planning (ERP) systems to solve integration problems. However, ERP systems automate core business activities without solving underlying business structures and processes. As a result a number of disparate applications often coexist with ERP systems. To better understand ERP and application integration (AI) problems, this paper proposes to identify, analyse and present the problems of ERP systems, as well as examining new approaches for AI. In doing so, a multi‐choice questionnaire has been designed, and was distributed to ERP specialists over the Internet. Responses show that ERP systems amplified the need for integration, as existing systems have to be incorporated with ERP applications. AI securely incorporates functionality from disparate applications, and has shown to lead to the development of new strategic business solutions for enterprises. The results of the research confirm AI as a new means of system integration that adds value by placing business logic in the applications network, thus creating a more dynamic information systems infrastructure.

New Zealand is a small country, physically isolated but increasingly “connected” in a world of fast growing “enabling” technology and telecommunications. The traditional resource sharing model (for document supply and cataloguing) is being challenged and new approaches to enhance access to information are being researched, piloted or are part of a digital programme. This article identifies some of the current challenges and resource sharing activities in New Zealand, particularly from the perspective of the role of the National Library.