Welcome to Data Curation for Researchers.

This guide was developed by a project team at the School of Information and Library Science, University of North Carolina at Chapel Hill, and funded by the Institute of Museum and Library Services. It is intended to assist library and information science and other social science researchers in planning for the long-term management and secondary use of the primary data they collect through research.  It is a product of the third stage of the Workforce Issues in Library and Information Science (WILIS) Project. Additional information about WILIS may be found at http://wilis.unc.edu/.

As a collaborating team of researchers, survey design and data collection experts, and data archivists involved in the Workforce Issues in Library and Information Science (WILIS) project, we have experienced first-hand the challenges of project design and planning, data collection, data sharing and data analysis. 

This guide was written to provide an interactive view of the issues to consider at all stages of a project. Upfront planning is likely to increase the quality of the resources available for researchers, methodologists and students using secondary data. Such use has long term benefits for the public by increasing access to research data and maximizing the utility of funded research projects over the long term.

There is a great need for high quality social science data that can be used again by researchers and other stakeholders who may or may not have been involved with the original data collection. The data can be repurposed to test methodologies, replicate results, and further interdisciplinary or multidisciplinary research efforts. Data archives facilitate secondary use by providing a stable storage location and making datasets easier to find, understand, and use by novice and expert researchers alike. Additionally, archives help to extend the life and economic value of data collected.

Archiving datasets without contextual documents limits their usefulness to the secondary analyst. Documentation that is as complete as possible will allow secondary users to properly interpret and manipulate the data. Such documentation includes the original research design and methodology, data management memos, codebooks, methodology briefs and other background and contextual information. This guide will help investigators document those decision points that impact data archiving at each stage of their research and create contextual clues for future users.

Another reason to archive datasets and contextual documents is that funding agencies, such as the National Science Foundation (NSF) and National Institutes of Health (NIH), are increasingly requiring data management and sharing plans. The Institute of Museum and Library Services (IMLS) is also interested in continued access to the products of the projects it funds. Journals and other venues for scholarly communication are also asking for additional materials such as questionnaires, survey recruitment materials/letters and even datasets that can be appended to articles and accessed online as supplementary materials. Funders, publishers and data experts publish guides to help researchers comply with data management plan requirements. For example, existing guides such as those issued by the United Kingdom Data Archive (UKDA) (Van den Eynden, V., Corti, L., Woollard, M., Bishop, L., & Horton, L., 2011) and the Inter-university Consortium for Political and Social Research (ICPSR) (ICPSR, 2012) provide the researcher with best practice guidelines through all research stages and the data life cycle. The fact that updated editions of the UKDA (3rd) and ICPSR (5th) guides were published during the writing of our guide demonstrates the fast evolution of data management principles and practices.

This guide supplements existing guides at the time of writing since it targets problem-solving, planning and decision making related to the process of archiving data from web-based survey research, particularly for library and information science (LIS) and other social science researchers. Data curation activities are vastly simplified if prepared for during the initial research planning stages. Our goal is to help researchers navigate their own contexts, by walking them step by step through each stage of research, focusing on pivotal considerations, and providing case studies and examples of how to apply the recommendations for successful data archiving. The guide is intended for all researchers whether they are conducting small or large scale projects. The guide will help researchers, data managers and archivists to follow best practice guidelines for designing and implementing a data management plan that takes into account each stage of the research, from project planning to data collection, analysis, long term archiving, and secondary use. While the guide will help those who are at any stage of their research, it will be a particularly helpful reference source for those who are beginning their project planning. Ultimately, better planning for data archiving may result in more secondary analyses, and a streamlined experience for both the researcher who wants to continue to use the data and the secondary analyst.