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Brief Guide to Data Management Planning

How to write a DMP for your project.

Introduction

This document provides guidelines for the best practices around data management and the data lifecycle.  Please note that, most times, a data management plan is project specific; many granting agencies, for example, have specific requirements for data management that need to be addressed on a project-by-project basis. 

It is recommended to include the department library liaison, department Academic Computing Systems liaison, Head of Digital Scholarship and Technology Services, and the Digital Preservation Librarian early on in the grant writing process. Each of them will have a unique area of expertise to advise on the access, preservation, and sustainability of your data. Their guidance will ensure an achievable data management plan for grant success. 

What is a DMP? 

A DMP describes data that will be acquired or produced during your project; how the data will be managed, described, stored, accessed, and preserved during and after the completion of the project.
 

Vassar College is now a member of dmptool.org!

Using your Vassar email you can login via SSO to your own dashboard to create DMP’s! The DMPTool is a free, open-source, online application that helps researchers create data management plans. The tool provides a click-through wizard for creating a DMP that complies with funder requirements. It also has direct links to funder websites, help text for answering questions, and data management best practices resources.

A typical DMP consists of the following components:

  • Project Overview
    • Project title and a brief description
    • Project timeline
    • Contact information
    • Estimated budget for data management activities
    • Identify any data sharing agreements
  • Data Collection
    • Basic information on each data set (type, source, description)
    • Purpose of the data in the context of the project
    • Restrictions on the data
    • Amount of data to be generated by the project or over time
    • Ethical and legal considerations related to your data gathering
  • Metadata
    • Tools used to create and edit metadata
    • Tools needed for the data to be read and interpreted in the future
    • Standards to be followed
    • Contact responsible for the metadata
  • Process
    • Workflow detailing how the data will be produced
    • Technologies, capabilities, or models that will be used for data processing
    • Location of internal storage resources, that provide backup capability, that will be used to store data during process and analysis
    • Who will manage or is responsible for the integrity of the storage resource 
  • Preservation
    • What will be preserved
    • Open data formats to be used
    • Estimated storage volume of the final approved data releases
    • Where the data will be stored for long term preservation
    • Who will be responsible for data preservation
    • Timeline / schedule for data transfers to be received for preservation
  • Access
    • Information on anticipated publishing mediums whether in print or online
    • Format and audience for each access point
    • How each of these access points will be maintained
    • Use restrictions
  • Quality Assurance
    • Project team roles and operational procedures that will ensure quality outputs.

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