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Research Data Toolkit

This guide is intended to help researchers, data creators or others who manage digital data as part of a research project, plan, organize, describe, share and preserve their research data for the long term.

What Are Data?

Before you begin the data management process, it is important to develop a good understanding of data. Data are the variety of information collected, used, manipulated, and analyzed throughout the research process and are necessary to validate research findings.

Data can take many forms including photographs, specimens, spreadsheets, images, software programs, survey responses, codebooks, digital objects or database content. 

Examples of research data may include, but not limited to:

  • Text documents and spreadsheet
  • Lab notebooks, field notebooks, diaries
  • Questionnaires, transcripts, codebooks
  • Audiotapes, videotapes
  • Photographs
  • Films and other moving images
  • Protein or genetic sequences
  • Survey responses
  • Slides, artifacts, specimens, samples
  • Digital objects
  • Database contents (video, audio, text, images)
  • Models, algorithms, scripts
  • Contents of an application (input, output, logfiles for analysis software, simulation software, schemas)
  • Methodologies and workflows
  • Standard operating procedures and protocols

Understanding the Research Data Lifecycle

The research data lifecycle covers the stages through which research data is collected, recorded, processed, published, shared and preserved.

Using the research data lifecycle as a guide in data management is helpful because it initiates thoughtful planning and ensures that all phases of the research data lifecycle are covered including creation, processing, analysis, preservation, sharing, and reuse. 

The video below, which was produced by the UK Data Service, provides examples of various research data management tasks and activities that can be performed at each stage of the research lifecycle. 

Tips for Writing A Data Management Plan

The research data management plan (DMP) is considered a formal "living document" because as you progress through the research process it should be kept up-to-date or modified often. This document should also be kept accessible to the entire research team both during and after a research project so that it can be used as a handy reference guide. This is also important because DMP's usually outlive the research project itself.

Requirements for the information to be included in your plan can vary by funding agency and institution. The required length and structure of your plan will also vary. The best way to start is to look for what your funder expects you to cover. You can find this information on the funder's website or by using the DMPonline tool

The DMPonline is a free interactive online tool designed to help researchers create data management plans. This site provides step-by-step guidance as well as funder's template and sample data management plans.

The research division at A & T (DORED) provides a simple data management plan template as well as other resources on its website, if your funder does not provide guidance on data plans, this might be a good starting point.

Public DMPs are sample plans created using the DMPTool and shared publicly by their owners. They are not vetted for quality, completeness, or adherence to funder guidelines.

Questions to Consider Before Writing Your Data Management Plan

  • What type of data will my project produce or collect? (description, data size & formats)
  • How will I organize and describe my data files? (file naming, versioning, metadata)
  • How will I backup or store my data? (hardware or software needed, sufficient storage, data recovery)
  • How will I manage access and security? (access control, data vulnerability, confidentiality level)
  • How will I communicate data with collaborators? (email, cloud-based communication)
  • What are my plans for data sharing? (institutional repository, open access journals, domain repository, website)
  • Will I have data that are sensitive or need to be restricted? (anonymizing data, endangered species geo-data, embargoes)
  • What are the copyright and intellectual property rights of the data? (who owns the data, authors addendum completed)

The webinar below outlines recommendations on creating a data management plan from ICPSR's Director of Data Acquisition Amy Pienta.