This seven-volume set offers a core collection of hand-selected titles in 58 curriculum-specific subject areas. Volumes are organized into broad subject areas such as Humanities, Languages and Literature, History, Social Sciences and Professional Studies, Science and Technology, and Interdisciplinary and Area Studies. The seventh volume provides helpful cross-referencing indexes which explain the relationship between RCL subject taxonomy and LC ranges. New to this edition are the inclusion of interdisciplinary subject areas and the selection of electronic resources and web sites essential for undergraduate library collections. Non-book selections will be easily identified by a graphic indicator included in the item record. All selections will be assigned an audience level marker indicating whether the title is most appropriate for lower-division undergraduate, upper-division undergraduate, faculty, or general readership. Records will also include a notation if they previously appeared in BCL3 (Books for College Libraries, 1988) or have been reviewed by Choice.

Includes subject area sections that describe all pertinent census data products available, i.e. "Business--trade and services", "Geography", "Transportation," etc.

This open access book summarises the latest developments on data management in the EU H2020 ENVRIplus project, which brought together more than 20 environmental and Earth science research infrastructures into a single community. It provides readers with a systematic overview of the common challenges faced by research infrastructures and how a ‘reference model guided’ engineering approach can be used to achieve greater interoperability among such infrastructures in the environmental and earth sciences. The 20 contributions in this book are structured in 5 parts on the design, development, deployment, operation and use of research infrastructures. Part one provides an overview of the state of the art of research infrastructure and relevant e-Infrastructure technologies, part two discusses the reference model guided engineering approach, the third part presents the software and tools developed for common data management challenges, the fourth part demonstrates the software via several use cases, and the last part discusses the sustainability and future directions.