This 100+ page report looks closely at the data curation and management practices of 17 colleges and universities including the University of Surrey, Columbia University, the Massachusetts Institute of Technology, the University of Toronto, the University of Brasilia, Colorado State University and many others. The report covers how libraries deal with data management plans for grant proposals, tutorials and training in data management for scholars, library spending for data curation, relations with other players in data curation such as offices of research and academic faculties, metadata development for datasets, and other issues in data curation and data management

We surveyed college and university and other research libraries in the United Kingdom and United States to find out more about their approach to data curation. Ten libraries were surveyed in each country. Two non-academic libraries with profiles similar to academic libraries were also included.The study presents a broad range of data on budgets, staffing, assessment, technology use, interdepartmental cooperation, metadata development, data security, discovery tools, marketing, archiving, data preservation and other aspects of data curation management. Some of the participating institutions include: Tulane, Syracuse University, the University of New Mexico, Imperial College London, the University of Edinburgh, the University of Bath, Pacific Northwest National Laboratory, the University of London, the Center for Research Libraries and Arizona State University. Just a few of the 108 page report's many findings are that:· The majority of libraries (70%) surveyed assisted faculty with advice on how to develop data management plans for grants or personal use.· For 30% of the UK libraries surveyed, data curation was a line item in the library budget.· The mean average percentage of overall data management staff time spent on the development of metadata and other cataloguing issues was 31 per cent.· We asked about the number of grant proposals that had been reviewed or contributed to by data curation office or service in the past year. The mean average was 15.38. However, the numbers were much higher in the United States than in the UK. US libraries reported a mean average of 21.4 compared to 5.33.

This survey looks closely at the data curation practices of a sample of research-oriented universities largely from the USA, the UK, Australia and Scandinavia but also including India, South Africa and other countries. The study looks at how major universities are assisting faculty in developing data curation and management plans for large scale data projects, largely in the sciences and social sciences, often as pre-conditions for major grants. The report looks at which departments of universities are shouldering the data curation burden, the personnel involved in the efforts, the costs involved, types of software used, difficulties in procuring scientific experiment logs and other hard to obtain information, types of training offered to faculty, and other issues in large scale data management

Technological advances and the rise of collaborative, interdisciplinary approaches have changed the practice of research. The 21st century researcher not only faces the challenge of managing increasingly complex datasets, but also new data sharing requirements from funders and journals. Success in today’s research enterprise requires an understanding of how to work effectively with data, yet most researchers have never had any formal training in data management. Libraries have begun developing services and programs to help researchers meet the demands of the data-driven research enterprise, giving librarians exciting new opportunities to use their expertise and skills. The Medical Library Association Guide to Data Management for Librarians highlights the many ways that librarians are addressing researchers’ changing needs at a variety of institutions, including academic, hospital, and government libraries. Each chapter ends with “pearls of wisdom,” a bulleted list of 5-10 takeaway messages from the chapter that will help readers quickly put the ideas from the chapter into practice. From theoretical foundations to practical applications, this book provides a background for librarians who are new to data management as well as new ideas and approaches for experienced data librarians.

This landmark collection will help readers understand the open access movement, open data, open educational resources, open knowledge, and the opportunities for an open and transformed world they promise.