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The role open-source geospatial software plays in data handling within the spatial information technology industry is the overarching theme of the book. It also examines new tools and applications for those already using OS approaches to software development.
"This set of books represents a detailed compendium of authoritative, research-based entries that define the contemporary state of knowledge on technology"--Provided by publisher.
Computing and communications are becoming essential tools of science. Together, they make possible new kinds and degrees of collaboration. This book addresses technical, scientific, and social aspects of fostering scientific collaboration using information technology. It explores issues in molecular biology, oceanography, and space physics, and derives recommendations for a partnership between scientists and technologists to develop better collaboration technology to support science.
A comprehensive guide to everything scientists need to know about data management, this book is essential for researchers who need to learn how to organize, document and take care of their own data. Researchers in all disciplines are faced with the challenge of managing the growing amounts of digital data that are the foundation of their research. Kristin Briney offers practical advice and clearly explains policies and principles, in an accessible and in-depth text that will allow researchers to understand and achieve the goal of better research data management. Data Management for Researchers includes sections on: * The data problem – an introduction to the growing importance and challenges of using digital data in research. Covers both the inherent problems with managing digital information, as well as how the research landscape is changing to give more value to research datasets and code. * The data lifecycle – a framework for data’s place within the research process and how data’s role is changing. Greater emphasis on data sharing and data reuse will not only change the way we conduct research but also how we manage research data. * Planning for data management – covers the many aspects of data management and how to put them together in a data management plan. This section also includes sample data management plans. * Documenting your data – an often overlooked part of the data management process, but one that is critical to good management; data without documentation are frequently unusable. * Organizing your data – explains how to keep your data in order using organizational systems and file naming conventions. This section also covers using a database to organize and analyze content. * Improving data analysis – covers managing information through the analysis process. This section starts by comparing the management of raw and analyzed data and then describes ways to make analysis easier, such as spreadsheet best practices. It also examines practices for research code, including version control systems. * Managing secure and private data – many researchers are dealing with data that require extra security. This section outlines what data falls into this category and some of the policies that apply, before addressing the best practices for keeping data secure. * Short-term storage – deals with the practical matters of storage and backup and covers the many options available. This section also goes through the best practices to insure that data are not lost. * Preserving and archiving your data – digital data can have a long life if properly cared for. This section covers managing data in the long term including choosing good file formats and media, as well as determining who will manage the data after the end of the project. * Sharing/publishing your data – addresses how to make data sharing across research groups easier, as well as how and why to publicly share data. This section covers intellectual property and licenses for datasets, before ending with the altmetrics that measure the impact of publicly shared data. * Reusing data – as more data are shared, it becomes possible to use outside data in your research. This chapter discusses strategies for finding datasets and lays out how to cite data once you have found it. This book is designed for active scientific researchers but it is useful for anyone who wants to get more from their data: academics, educators, professionals or anyone who teaches data management, sharing and preservation. "An excellent practical treatise on the art and practice of data management, this book is essential to any researcher, regardless of subject or discipline." —Robert Buntrock, Chemical Information Bulletin
Data use in the library has specific characteristics and common problems. Data Clean-up and Management addresses these, and provides methods to clean up frequently-occurring data problems using readily-available applications. The authors highlight the importance and methods of data analysis and presentation, and offer guidelines and recommendations for a data quality policy. The book gives step-by-step how-to directions for common dirty data issues. - Focused towards libraries and practicing librarians - Deals with practical, real-life issues and addresses common problems that all libraries face - Offers cradle-to-grave treatment for preparing and using data, including download, clean-up, management, analysis and presentation
USA. Report on the need for a national level system of handling documentation and library material in the fields of science and technology - includes statement of the problem, study of general management requirements and systems requirements, review of legislation and of advanced information systems involving automation and the use of computer equipment, etc., conclusions and recommendations. Selected references, bibliography and glossary.
J.-E. Dubois and N. Gershon This book was inspired by the Symposium on "Communications and Computer Aided Systems" held at the 14th International CODATA Conference in September 1994 in Chambery, France. It was conceived and influenced by the discussions at the symposium and most of the contributions were written following the Conference. This is the first comprehensive book, published in one volume, of issues concerning the challenges and the vital impact of the information revolution (including the Internet and the World Wide Web) on science and technology. Topics concerning the impact of the information revolution on science and technology include: • Dramatic improvement in sharing of data and information among scientists and engineers around the world • Collaborations (on-line and off-line) of scientists and engineers separated by distance . • Availability of visual tools and methods to view, understand, search, and share information contained in data • Improvements in data and information browsing, search and access and • New ways of publishing scientific and technological data and information. These changes have dramatically modified the way research and development in science and technology are being carried out. However, to facilitate this information flow nationally and internationally, the science and technology communities need to develop and put in place new standards and policies and resolve some legal issues.