Download Research Data Management: Practical Strategies for by Joyce Ray PDF

By Joyce Ray

It has turn into more and more approved that very important electronic info has to be retained and shared so as to look after and advertise wisdom, increase study in and throughout all disciplines of scholarly exercise, and maximize the go back on funding of public cash. to satisfy this problem, faculties and universities are including information companies to latest infrastructures by way of drawing at the services of knowledge execs who're already excited about the purchase, administration and protection of knowledge of their day-by-day jobs. information companies contain making plans and imposing solid info administration practices, thereby expanding researchers' skill to compete for provide investment and making sure that information collections with carrying on with worth are preserved for reuse. This quantity presents a framework to lead details pros in educational libraries, presses, and knowledge facilities during the technique of coping with learn info from the making plans phases throughout the lifetime of a furnish venture and past. It illustrates ideas of excellent perform with use-case examples and illuminates promising information carrier types via case experiences of cutting edge, profitable initiatives and collaborations.

individuals contain: James L. Mullins, Purdue college; MacKenzie Smith, college of California at Davis; Sherry Lake, collage of Virginia; John Kunze, collage of California; Bernard Reilly, middle for learn Libraries; Jacob Carlson, Purdue college; Melissa Levine, college of Michigan; Jenn Riley, collage of North Carolina at Chapel Hill; Jan Brase, German nationwide Library of technological know-how and know-how; Seamus Ross, college of Toronto; Sarah Shreeves, collage of Illinois at Urbana-Champaign; Jared Lyle, collage of Michigan; Michele Kimpton, DuraSpace; Brian Schottlaender, college of California San Diego; Suzie Allard, collage of Tennessee; Angus Whyte, electronic Curation Centre; Scott Brandt, Purdue collage; Brian Westra, college of Oregon; Geneva Henry, Rice college; Gail Steinhart, Cornell collage; and Cliff Lynch, Coalition for Networked Information.

Charleston Insights in Library, info, and Archival Sciences is a brand new sequence produced as a collaboration among the organizers of the Charleston Library convention and Purdue college Press. Volumes within the sequence specialize in very important issues in library and knowledge technological know-how, featuring the problems in a comparatively jargon-free manner that's obtainable to every kind of knowledge professionals.

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However, as datasets become larger, it often is no longer possible to publish the data as part of the publication. The datasets referenced in publications frequently are composite data objects with multiple constituent parts, as researchers typically generate many versions of datasets in the course of their research. The purpose of data citation, then, is to provide enough information to locate the referenced dataset as a single, unambiguous object; to serve as evidence for claims made about the data; to verify that the cited dataset is equivalent to the one used to make the claims; and to correctly attribute the dataset.

This framework helped to identify the tools and resources needed at each stage of the life cycle. The evaluation team then developed plans for evaluating existing tools to assess potential improvements and for identifying needs for new tools and services that could be addressed in the work plan. Allard concludes with recommendations for the organizational design and management of the evaluation process. In “What to Measure: Toward Metrics for Research Data Management,” Angus Whyte, Laura Molloy, Neil Beagrie, and John Houghton discuss evaluation metrics from a high conceptual level, asking program and evaluation planners to think carefully about what they are trying to achieve and what metrics they can realistically use to measure results.

The authors point out that data have been linked traditionally to the publications that are based on them through tables, graphs, and images embedded in the publications. However, as datasets become larger, it often is no longer possible to publish the data as part of the publication. The datasets referenced in publications frequently are composite data objects with multiple constituent parts, as researchers typically generate many versions of datasets in the course of their research. The purpose of data citation, then, is to provide enough information to locate the referenced dataset as a single, unambiguous object; to serve as evidence for claims made about the data; to verify that the cited dataset is equivalent to the one used to make the claims; and to correctly attribute the dataset.

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