Presents papers from the September 1994 conference, plus a poster session addressing issues directly related to data management, and keynote addresses on data infrastructure architecture and object databases for scientific computing. Sessions cover subjects such as interfaces and languages, statistical databases, scientific database management, object-oriented techniques, multidimensional data, and content retrieval from image databases. No index. Annotation copyright by Book News, Inc., Portland, OR.
"CHEP (Computing in High Energy Physics) is the largest international meeting of the communities of High Energy Physics, Computing Science and the Computing Industry. The sixth conference in this series was held in Rio de Janeiro, Brazil in September 1995. The focus of the conference was "Computing for the next Millennium". High Energy Physics is at a point where major changes in the way data acquisition and computing problems are addressed will be called for in the high energy physics programs of the year 2000 and beyond. The conference covered a wide spectrum of topics including Data Access, Storage, and Analysis; Data Acquisition and Triggering; Worldwide Collaboration and Networking; Tools, Languages, and Software Development Environments; and special purpose processing systems. The papers presented both recent progress and radical approaches to computing problems as candidates for the basis of future computing in the field of high energy physics."--Provided by publisher
The Fourth International Working Conference on Statistical and Scientific Data Base Management (IV SSDBM) held on June 21-23, 1988 in Rome, Italy, continued the series of conferences initiated in California in December 1981. The purpose of this conference was to bring together database researchers, users and system builders, working in this specific field, to discuss the particular points of interest, to propose new solutions to the problems of the domain and to expand the topics of the previous conferences, both from the theoretical and from the applicational point of view. The papers of four scientific sessions dealt with the following topics: knowledge base and expert system, data model, natural language processing, query language, time performance, user interface, heterogeneous data classification, storage constraints, automatic drawing, ranges and trackers, and arithmetic coding. Two other special sessions presented work on progress papers on geographical data modelling, spatial database queries, user interface in an Object Oriented SDB, interpretation of queries, graphical query language and knowledge browsing front ends. The conference also had three invited papers on topics of particular interest such as "Temporal Data", "Statistical Data Management Requirements" and "Knowledge Based Decision Support Systems", included in this volume. The introductory paper by M. Rafanelli provides both an introduction to the general concepts helpful to people outside the field and a survey of all the papers in these Proceedings. Furthermore, there were three open panels. Papers by the chairmen, contributions of the panelists and a summary of the respective discussions are included in this volume, too.
Ecologists are increasingly tackling difficult issues like global change, loss of biodiversity and sustainability of ecosystem services. These and related topics are enormously challenging, requiring unprecedented multidisciplinary collaboration and rapid synthesis of large amounts of diverse data into information and ultimately knowledge. New sensors, computers, data collection and storage devices and analytical and statistical methods provide a powerful tool kit to support analyses, graphics and visualizations that were unthinkable even a few years ago. New and increased emphasis on accessibility, management, processing and sharing of high-quality, well-maintained and understandable data represents a significant change in how scientists view and treat data. These issues are complex and despite their importance, are typically not addressed in database, ecological and statistical textbooks. This book addresses these issues, providing a much needed resource for those involved in designing and implementing ecological research, as well as students who are entering the environmental sciences. Chapters focus on the design of ecological studies, data management principles, scientific databases, data quality assurance, data documentation, archiving ecological data and information and processing data into information and knowledge. The book stops short of a detailed treatment of data analysis, but does provide pointers to the relevant literature in graphics, statistics and knowledge discovery. The central thesis of the book is that high quality data management systems are critical for addressing future environmental challenges. This requires a new approach to how we conduct ecological research, that views data as a resource and promotes stewardship, recycling and sharing of data. Ecological Data will be particularly useful to those ecologists and information specialists that actively design, manage and analyze environmental databases. However, it will also benefit a wider audience of scientists and students in the ecological and environmental sciences.
Coverage in this text on database and information systems includes: fundamental issues in statistical database management; current problems in scientific databases; new systems; implementation methods; applications of data and process modelling; and requirements and design."
Finding patterns in biomolecular data, particularly in DNA and RNA, is at the center of modern biological research. These data are complex and growing rapidly, so the search for patterns requires increasingly sophisticated computer methods. Pattern Discovery in Biomolecular Data provides a clear, up-to-date summary of the principal techniques. Each chapter is self-contained, and the techniques are drawn from many fields, including graph theory, information theory, statistics, genetic algorithms, computer visualization, and vision. Since pattern searches often benefit from multiple approaches, the book presents methods in their purest form so that readers can best choose the method or combination that fits their needs. The chapters focus on finding patterns in DNA, RNA, and protein sequences, finding patterns in 2D and 3D structures, and choosing system components. This volume will be invaluable for all workers in genomics and genetic analysis, and others whose research requires biocomputing.
