Check and Understand Presentation

The Check and Understand steps to curating research data are explained in this presentation

Evaluate Presentation

The Evaluate step to curate research data is explained in this presentation

Chapter 5. Overlooked and overrated data sharing: Why some scientists are confused and/or dismissive

This chapter is an expert from the book Curating Research Data, Volume One: Practical Strategies for Your Digital Repository edited by Lisa R. Johnston published by American College & Research Libraries (ACRL) in January 2017. The book is available from the American Library Association in print and as a open access e-book at www.alastore.ala.org. ISBN-13: 9780838988589Ope

Should We Keep Everything Forever? Determining Long-Term Value of Research Data

The University of Illinois at Urbana-Champaign's library-based Research Data Service (RDS) launched an institutional data repository called the Illinois Data Bank (IDB) in May 2016. The RDS makes a commitment to preserving and facilitating access to published research datasets for a minimum of five years after the date of publication in the Illinois Data Bank. The RDS has developed guidelines and processes for reviewing published datasets after their five-year commitment ends to determine whether to retain, deaccession, or dedicate more stewardship resources to datasets. In this poster, we will describe how the University of Illinois at Urbana-Champaign preservation review planning team drew upon appraisal and reappraisal theory and practices from the archives community to develop preservation review processes and guidelines for datasets published in the Illinois Data Bank.Ope

Public Access to Articles and Data for Funding Agencies

This presentation was prepared in Fall 2015 to cover upcoming public access requirements as they apply to grant funded researchers.Ope

Checklist of DCN CURATE Steps

A checklist and introduction to the Data Curation Network CURATE Steps for curating research data

How Important Are Data Curation Activities to Researchers? Gaps and Opportunities for Academic Libraries

Introduction: Data curation may be an emerging service for academic libraries, but researchers actively “curate” their data in a number of ways—even if terminology may not always align. Building on past user-needs assessments performed via survey and focus groups, the authors sought direct input from researchers on the importance and utilization of specific data curation activities. Methods: Between October 21, 2016, and November 18, 2016, the study team held focus groups with 91 participants at six different academic institutions to determine which data curation activities were most important to researchers, which activities were currently underway for their data, and how satisfied they were with the results. Results: Researchers are actively engaged in a variety of data curation activities, and while they considered most data curation activities to be highly important, a majority of the sample reported dissatisfaction with the current state of data curation at their institution. Discussion: Our findings demonstrate specific gaps and opportunities for academic libraries to focus their data curation services to more effectively meet researcher needs. Conclusion: Research libraries stand to benefit their users by emphasizing, investing in, and/or heavily promoting the highly valued services that may not currently be in use by many researchers

Using a Computational Study of Hydrodynamics in the Wax Lake Delta to Examine Data Sharing Principles

In this paper we describe a complex dataset used to study the circulation and wind-driven flows in the Wax Lake Delta, Louisiana, USA under winter storm conditions. The whole package bundles a large dataset (approximately 74 GB), which includes the numerical model, software and scripts for data analysis and visualization, as well as detailed documentation. The raw data came from multiple external sources, including government agencies, community repositories, and deployed field instruments and surveys. Each raw dataset goes through the processes of data QA/QC, data analysis, visualization, and interpretation. After integrating multiple datasets, new data products are obtained which are then used with the numerical model. The numerical model undergoes model verification, testing, calibration, and optimization. With a complex algorithm of computation, the model generates a structured output dataset, which is, after post-data analysis, presented as informative scientific figures and tables that allow interpretations and conclusions contributing to the science of coastal physical oceanography. Performing this study required a tremendous amount of effort. While the work resulted in traditional dissemination via a thesis, journal articles and conference proceedings, more can be gained. The data can be reused to study reproducibility or as preliminary investigation to explore a new topic. With thorough documentation and well-organized data, both the input and output dataset should be ready for sharing in a domain or institutional repository. Furthermore, the data organization and documentation also serves as a guideline for future research data management and the development of workflow protocols. Here we will describe the dataset created by this study, how sharing the dataset publicly could enable validation of the current study and extension by new studies, and the challenges that arise prior to sharing the dataset

Pre-Metadata Counseling: Putting the DataCite relationType Attribute into Action

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Overly honest data repository development

After a year of development, the library at the University of Illinois at Urbana-Champaign has launched a repository, called the Illinois Data Bank (https://databank.illinois.edu/), to provide Illinois researchers with a free, self-serve publishing platform that centralizes, preserves, and provides persistent and reliable access to Illinois research data. This article presents a holistic view of development by discussing our overarching technical, policy, and interface strategies. By openly presenting our design decisions, the rationales behind those decisions, and associated challenges this paper aims to contribute to the library community’s work to develop repository services that meet growing data preservation and sharing needs.Ope