Guidelines for Effective Data Management PlansData Management PlansFederal funding agencies are increasingly recommending or requiring formal data management plans with all grant applications.To help researchers meet those requirements, ICPSR offers these guidelines.Based on our Data Management Plan Web site, this document contains a framework, example data management plans, links to other resources, and a bibliography of related publications.ICPSR also hosts a blog on data management plans, and a recent webinar on the subject can be viewed on our Web site.We hope you find this information helpful as you craft a data management plan. Please contact us at [email protected] with any comments or suggestions.Table of ContentsFramework for Creating a Data Management Plan .............................................................. 2Data Management Plan Resources and Examples ..............................................................11Resources for Development ...........................................................................................11Templates and Tools ......................................................................................................11Guidance on Funder Requirements ..................................................................................11University Data Management Web Sites .......................................................................... 12Good Practice Guidance ................................................................................................ 12Federal Agency Policies on Data Management and Sharing ................................................ 13Other Data Management Plan Examples from Natural Sciences .......................................... 14Appendix A: Elements of a Data Management Plan ........................................................... 16Appendix B: Sample ICPSR Data Management Plan .......................................................... 18Appendix C: Data Management Bibliography ....................................................................21Guidelines for Effective Data Management Plans2This framework takes the form of a list of elements with issues and questions to consider and examples for each element. Also included is information on why each element is important and suggestions for additional reading.Data Description (Recommended)Provide a brief description of the information to be gathered -- the nature, scope, and scale of the data that will be generated or collected.Why this is important A good description of the data to be collected will help reviewers understand the characteristics of the data, their relationship to existing data, and any disclosure risks that may apply. Example 1: This project will produce public-use nationally representative survey data for the United States covering Americans’ social backgrounds, enduring political predispositions, social and political values, perceptions and evaluations of groups and candidates, opinions on questions of public policy, and participation in political life.Example 2: This project will generate data designed to study the prevalence and correlates of DSM III-R psychiatric disorders and patterns and correlates of service utilization for these disorders in a nationally representative sample of over 8000 respondents. The sensitive nature of these data will require that the data be released through a restricted use contract. Access and Sharing (Recommended)Indicate how you intend to archive and share your data and why you have chosen that particular option. Possible mechanisms for archiving and sharing include:• Domain repository like ICPSR (social science) • Self-dissemination through a dedicated Web site that the research team will create and maintain. If this option is chosen, it is recommended that the data producer arrange for eventual archiving of the data after the self-dissemination period terminates and specify the schedule for data sharing in the grant application. • Preservation with delayed dissemination. Under such an agreement the data producer makes an arrangement with a public data repository for archival preservation of the data with dissemination to occur at a later date, usually within a year. • Institutional repositories. Institutional repositories at academic institutions have the goal of preserving and making available some portion of the academic work of their students, faculty, and staff. Note that not all IRs have the capacity to accept and curate data.Why this is important Sharing data helps to advance science and to maximize the research investment. A recent paper reported that when data Framework for Creating a Data Management PlanGuidelines for Effective Data Management Plans3are shared through an archive, research productivity increases and many times the number of publications result as opposed to when data are not shared. Protecting research participants and guarding against disclosure of identities are essential norms in scientific research. Data producers should take efforts to provide effective informed consent statements to respondents, to deidentify data before deposit when necessary, and to communicate to the archive any additional concerns about confidentiality. (See Ethics and Privacy below.) With respect to timeliness of data deposit, archival experience has demonstrated that the durability of the data increases and the cost of processing and preservation decreases when data deposits are timely. It is important that data be deposited while the producers are still familiar with the dataset and able to transfer their knowledge fully to the archive. Example 1: The research data from this project will be deposited with [repository] to ensure that the research community has long-term access to the data.Example 2: The project team will create a dedicated Web site to manage and distribute the data because the audience for the data is small and has a tradition of interacting as a community. The site will be established using a content management system like Drupal or Joomla so that data users can participate in adding site content over time, making the site self-sustaining. The site will be available at a .org location. For preservation, we will supply periodic copies of the data to [repository]. That repository will be the ultimate home for the data.Example 3: The research data from this project will be deposited with [repository] to ensure that the research