The advantages and cost effectiveness of database improvement methods

Relational databases have proved inadequate for supporting new classes of applications, and as a consequence, a number of new approaches have been taken (Blaha 1998), (Harrington 2000). The most salient alternatives are denormalisation and conversion to an object-oriented database (Douglas 1997). Denormalisation can provide better performance but has deficiencies with respect to data modelling. Object-oriented databases can provide increased performance efficiency but without the deficiencies in data modelling (Blaha 2000). Although there have been various benchmark tests reported, none of these tests have compared normalised, object oriented and de-normalised databases. This research shows that a non-normalised database for data containing type code complexity would be normalised in the process of conversion to an objectoriented database. This helps to correct badly organised data and so gives the performance benefits of de-normalisation while improving data modelling. The costs of conversion from relational databases to object oriented databases were also examined. Costs were based on published benchmark tests, a benchmark carried out during this study and case studies. The benchmark tests were based on an engineering database benchmark. Engineering problems such as computer-aided design and manufacturing have much to gain from conversion to object-oriented databases. Costs were calculated for coding and development, and also for operation. It was found that conversion to an object-oriented database was not usually cost effective as many of the performance benefits could be achieved by the far cheaper process of de-normalisation, or by using the performance improving facilities provided by many relational database systems such as indexing or partitioning or by simply upgrading the system hardware. It is concluded therefore that while object oriented databases are a better alternative for databases built from scratch, the conversion of a legacy relational database to an object oriented database is not necessarily cost effective

Digital Image Access & Retrieval

The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio

Changing Trains at Wigan: Digital Preservation and the Future of Scholarship

This paper examines the impact of the emerging digital landscape on long term access to material created in digital form and its use for research; it examines challenges, risks and expectations.

Active database behaviour: the REFLEX approach

Modern day and new generation applications have more demanding requirements than traditional database management systems (DBMS) are able to support. Two of these requirements, timely responses to the change of database state and application domain knowledge stored within the database, are embodied within active database technology. Currently, there are a number of research prototype active database systems throughout the world. In order for an organisation to use any such prototype system, it may have to forsake existing products and resources and embark on substantial reinvestment in the new database products and associated resources and retraining costs. This approach would clearly be unfavourable as it is expensive both in terms of time and money. A more suitable approach would be to allow active behaviour to be added onto their existing systems. This scenario is addressed within this research. It investigates how best active behaviour can be augmented to existing DBMSs, so as to preserve the investments in an organisation's resources, by examining the following issues, (i.) what form the knowledge model should take, (ii.) should rules and events be modelled as first class objects, (iii.) how will the triggering events be specified, (iv.) how the user will interact with the system. Various design decisions were taken, which were investigated by implementation of a series of working prototypes, on the ONTOS DBMS platform. The resultant REFLEX model was successfully ported and adapted onto a second POET platform. The porting process uncovered some interesting issues regarding preconceived ideas about the portability of open systems

Next generation software environments : principles, problems, and research directions

The past decade has seen a burgeoning of research and development in software environments. Conferences have been devoted to the topic of practical environments, journal papers produced, and commercial systems sold. Given all the activity, one might expect a great deal of consensus on issues, approaches, and techniques. This is not the case, however. Indeed, the term "environment" is still used in a variety of conflicting ways. Nevertheless substantial progress has been made and we are at least nearing consensus on many critical issues.The purpose of this paper is to characterize environments, describe several important principles that have emerged in the last decade or so, note current open problems, and describe some approaches to these problems, with particular emphasis on the activities of one large-scale research program, the Arcadia project. Consideration is also given to two related topics: empirical evaluation and technology transition. That is, how can environments and their constituents be evaluated, and how can new developments be moved effectively into the production sector

Object Relational Mapping for Enterprise Application Architecture

This project investigates the patterns/techniques used and issues that are encountered in developing object-oriented (OO) to relational data mappings for enterprise application architectures. The research will identify the different techniques of object relational data mapping as documented by Martin Fowler in Patterns of Enterprise Application Architecture (text for MSCS 630). A prototype implementation will be developed using the techniques found in this research. The goal of the project is to analyze and understand Martin Fowler\u27s patterns and other object relational mapping patterns used in industry and to recommend a set of best practices

A Survey on Mapping Semi-Structured Data and Graph Data to Relational Data

The data produced by various services should be stored and managed in an appropriate format for gaining valuable knowledge conveniently. This leads to the emergence of various data models, including relational, semi-structured, and graph models, and so on. Considering the fact that the mature relational databases established on relational data models are still predominant in today's market, it has fueled interest in storing and processing semi-structured data and graph data in relational databases so that mature and powerful relational databases' capabilities can all be applied to these various data. In this survey, we review existing methods on mapping semi-structured data and graph data into relational tables, analyze their major features, and give a detailed classification of those methods. We also summarize the merits and demerits of each method, introduce open research challenges, and present future research directions. With this comprehensive investigation of existing methods and open problems, we hope this survey can motivate new mapping approaches through drawing lessons from eachmodel's mapping strategies, aswell as a newresearch topic - mapping multi-model data into relational tables.Peer reviewe

PREDON Scientific Data Preservation 2014

LPSC14037Scientific data collected with modern sensors or dedicated detectors exceed very often the perimeter of the initial scientific design. These data are obtained more and more frequently with large material and human efforts. A large class of scientific experiments are in fact unique because of their large scale, with very small chances to be repeated and to superseded by new experiments in the same domain: for instance high energy physics and astrophysics experiments involve multi-annual developments and a simple duplication of efforts in order to reproduce old data is simply not affordable. Other scientific experiments are in fact unique by nature: earth science, medical sciences etc. since the collected data is "time-stamped" and thereby non-reproducible by new experiments or observations. In addition, scientific data collection increased dramatically in the recent years, participating to the so-called "data deluge" and inviting for common reflection in the context of "big data" investigations. The new knowledge obtained using these data should be preserved long term such that the access and the re-use are made possible and lead to an enhancement of the initial investment. Data observatories, based on open access policies and coupled with multi-disciplinary techniques for indexing and mining may lead to truly new paradigms in science. It is therefore of outmost importance to pursue a coherent and vigorous approach to preserve the scientific data at long term. The preservation remains nevertheless a challenge due to the complexity of the data structure, the fragility of the custom-made software environments as well as the lack of rigorous approaches in workflows and algorithms. To address this challenge, the PREDON project has been initiated in France in 2012 within the MASTODONS program: a Big Data scientific challenge, initiated and supported by the Interdisciplinary Mission of the National Centre for Scientific Research (CNRS). PREDON is a study group formed by researchers from different disciplines and institutes. Several meetings and workshops lead to a rich exchange in ideas, paradigms and methods. The present document includes contributions of the participants to the PREDON Study Group, as well as invited papers, related to the scientific case, methodology and technology. This document should be read as a "facts finding" resource pointing to a concrete and significant scientific interest for long term research data preservation, as well as to cutting edge methods and technologies to achieve this goal. A sustained, coherent and long term action in the area of scientific data preservation would be highly beneficial