John N. Wilson

Improving XML Processing Using Adapted Data Structures

From its origins in document processing, XML has developed into a medium for communicating all kinds of data between applications. More recently, interest has focused on the concept of native XML databases. This paradigm requires that database queries can be resolved by direct searching of XML data structures. Relational databases can be compressed without the loss of direct addressability. A similar approach can be applied to XML data structures. Compression in the relational paradigm is associated with improved performance. We review this approach and show results from the implementation of a prototype compressed DOM. Our research indicates that it is possible to optimise queries over compact XML structures by choosing appropriate physical representations.

Decision support for sentencing in a common law jurisdiction

The inherent variability of each new conviction and the volume of potentially useful data complicate the provision of relevant information to judges carrying out sentencing activities. This paper describes a prototype sentencing information system which allows a judge to retrieve previous examples of sentencing behaviour by interactive instantiation of detailed templates. The case-based advisory system uses a direct manipulation interface to facilitate user interaction, The direct manipulation interface was well received and judges found that they were rapidly able to construct meaningful queries and retrieve appropriate data despite having limited prior experience of computer use. We identify the importance of dynamic query systems in relation to further development of applications of this type.

Uses of peer assessment in database teaching and learning

This discussion paper introduces three very different methods and contexts for the use of peer assessment in introductory database classes, each of which is supported by different learning software tools. In the first case study, at Glasgow Caledonian University, Contributing Student Pedagogy is used, where students contribute to the learning of others through the collaborative creation of a bank of self-assessment questions. This is supported by the Peerwise software tool. Secondly, at the University of Strathclyde, students undertake formative assessment of others in providing feedback on an initial element of a larger coursework assessment. A number of virtual learning environments (VLEs) are capable of supporting this method through customisable discussion fora. Finally, at the University of Abertay Dundee, peer and self assessment are used in a group project to adjust the group grade for individual students. This is effected through the use of the WebPA software tool.

Information Systems Development for Concurrent Engineering

An integrated CEIS underpinned by heterogeneous database management technology is an ambitious effort to integrate the information processing work of an entire organization. In an organization which is large, decentralized and dynamic, problems of linking widely differing data‐oriented functional area information systems become apparent. A key feature becomes the means of facilitating the creation, manipulation and dissemination of the social and technical knowledge necessary for the CE participants to work together within the operating policies, procedures and standards of the organization. The real benefits of a CEIS supported by heterogeneous database technology will be derived from its constructive combination with the host organization and whether people understand and effectively exploit the information they are receiving in the form of new ideas to be expressed in terms of innovative product development.

Database Compression Using an Offline Dictionary Method

Off-line dictionary compression is becoming more attractive for applications where compressed data are searched directly in compressed form. While there has been large body of related work describing specific database compression algorithms, the Hibase [10] architecture is unique in processing queries in compressed data. However, this technique does not compress the representation of strings in the domain dictionaries. Primary keys, data with high cardinality and semi-structured data contribute very little or no compression. To achieve high performance irrespective of type of data, the string representation must be in compressed form. At the same time, the direct addressability of compressed data is maintained. Serial compression techniques cannot be used. In this paper, we present a prefix dictionary-based off-line method that can be incorporated with systems like Hibase where compressed data can be accessed directly without prior decompression. The complexity is O(n) in time and space.

Biochemical network matching and composition

Graph composition has applications in a variety of practical applications. In drug development, for instance, in order to understand possible drug interactions, one has to merge known networks and examine topological variants arising from such composition. Similarly, the design of sensor nets may use existing network infrastructures, and the superpositon of one network on another can help with network design and optimisation. The problem of network composition has not received much attention in algorithm and database research. Here, we work with biological networks encoded in Systems Biology Markup Language (SBML), based on XML syntax. We focus on XML merging and examine the algorithmic and performance challenges we encountered in our work and the possible solutions to the graph merge problem. We show that our XML graph merge solution performs well in practice and improves on the existing toolsets. This leads us into future work directions and the plan of research which will aim to implement graph merging primitives in a database engine.

A resource efficient hybrid data structure for twig queries

Designing data structures for use in mobile devices requires attention on optimising data volumes with associated benefits for data transmission, storage space and battery use. For semistructured data, tree summarisation techniques can be used to reduce the volume of structured elements while dictionary compression can efficiently deal with value-based predicates. This paper introduces an integration of the two approaches using numbering schemes to connect the separate elements, the key strength of this hybrid technique is that both structural and value predicates can be resolved in one graph, while further allowing for compression of the resulting data structure. Performance measures that show advantages of using this hybrid structure are presented, together with an analysis of query resolution using a number of different index granularities. As the current trend is towards the requirement for working with larger semi-structured data sets this work allows for the utilisation of these data sets whilst reducing both the bandwidth and storage space necessary.

The role of computer systems in organizational decision making

Decision making is regarded as a key feature of managerial activity. As a result, a considerable amount of research activity has been undertaken that aims to enhance understanding and to improve on the decision‐making process within organizational settings. This research has been paralleled by a technological response in the development of information and communication technology that is heralded by many for its significant potential for improving decision making in terms of both efficiency and effectiveness. This paper examines the complex nature of decision making within organizations and examines the extent to which computer systems may provide effective managerial support in the face of increasing organizational complexity.

Compressed Materialised Views of Semi-Structured Data

Query performance issues over semi-structured data have led to the emergence of materialised XML views as a means of restricting the data structure processed by a query. However preserving the conventional representation of such views remains a significant limiting factor especially in the context of mobile devices where processing power, memory usage and bandwidth are significant factors. To explore the concept of a compressed materialised view, we extend our earlier work on structural XML compression to produce a combination of structural summarization and data compression techniques. These techniques provide a basis for efficiently dealing with both structural queries and valuebased predicates. We evaluate the effectiveness of such a scheme, presenting results and performance measures that show advantages of using such structures.

Extracting Partition Statistics from Semistructured Data

The effective grouping, or partitioning, of semistructured data is of fundamental importance when providing support for queries. Partitions allow items within the data set that share common structural properties to be identified efficiently. This allows queries that make use of these properties, such as branching path expressions, to be accelerated. Here, we evaluate the effectiveness of several partitioning techniques by establishing the number of partitions that each scheme can identify over a given data set. In particular, we explore the use of parameterised indexes, based upon the notion of forward and backward bisimilarity, as a means of partitioning semistructured data; demonstrating that even restricted instances of such indexes can be used to identify the majority of relevant partitions in the data