Spatial Data Collections And Services

With the onslaught of emergent technology in academia, libraries are privy to many innovative techniques to recognize and classify geospatial data?above and beyond the traditional map librarianship. As librarians become more involved in the development and provision of GIS services and resources, they encounter both problems and solutions. Integrating Geographic Information Systems into Library Services: A Guide for Academic Libraries integrates traditional map librarianship and contemporary issues in digital librarianship within a framework of a global embedded information infrastructure, addressing technical, legal, and institutional factors such as collection development, reference and research services, and cataloging/metadata, as well as issues in accessibility and standards.

Metadata play a fundamental role in both DLs and SDIs. Commonly defined as "structured data about data" or "data which describe attributes of a resource" or, more simply, "information about data", it is an essential requirement for locating and evaluating available data. Therefore, this book focuses on the study of different metadata aspects, which contribute to a more efficient use of DLs and SDIs. The three main issues addressed are: the management of nested collections of resources, the interoperability between metadata schemas, and the integration of information retrieval techniques to the discovery services of geographic data catalogs (contributing in this way to avoid metadata content heterogeneity).

The Availability of Spatial and Environmental Data in the European Union

This book places spatial data within the broader domain of information technology (IT) while providing a comprehensive and coherent explanation of the guiding principles, methods, implementation and operational management of spatial databases within the workplace. The text explains the key concepts, issues and processes of spatial data implementation and provides a holistic management perspective.

This book documents the latest research relating to the legal aspects of satellite remote sensing, which is still largely unregulated, and identifies shortcomings in the current legal regime before proposing improvements needed for its full utilisation.

With the turn of the century our ability to collect and store geospatial information has increased considerably. This has resulted in ever-increasing amounts of heterogeneous geospatial data, an issue that poses new challenges and opportunities. As these rich sources of data are made available, users rely, now more than ever, on the geospatial data infrastructure. The availability and accessibility of such data, as well as the ability to effectively manage, model, index and query the data is becoming a cornerstone in numerous applications. Moreover, the ability to formalize and represent data is becoming key to integration and interoperability. With the introduction of distributed geospatial data infrastructure and the implementation of web-based services, the impact of such issues is becoming even more evident. Inspired by these challenges, this book on Next Generation Geospatial Information offers a collection of original contributions from leading experts in spatial information modeling, image processing and analysis, database management, ontologies and data mining. It provides a unique insight into the current state-of-the-art and future challenges in geospatial information through four thematic chapters, each of which represents a primary research theme, namely distributed spatial infrastructure, image-based geospatial information management, indexing and querying geospatial databases, and ontology and semantics for geospatial data.

These Transactions publish research in computer-based methods of computational collective intelligence (CCI) and their applications in a wide range of fields such as the Semantic Web, social networks and multi-agent systems. TCCI strives to cover new methodological, theoretical and practical aspects of CCI understood as the form of intelligence that emerges from the collaboration and competition of many individuals (artificial and/or natural). The application of multiple computational intelligence technologies such as fuzzy systems, evolutionary computation, neural systems, consensus theory, etc., aims to support human and other collective intelligence and to create new forms of CCI in natural and/or artificial systems. This third issue contains a collection of 10 articles selected from high-quality submissions addressing advances in the foundations and applications of computational collective intelligence.