Skip to main content
It looks like you're using Internet Explorer 11 or older. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. If you continue with this browser, you may see unexpected results.

Data Science: Data Management Plans

Resources for scientific systems, methods, and processes for data scientists.

Data Principles

The FAIR Data Principles outline a minimal set of guiding principles and practices that data producers, and data consumers (both machine and human) should employ to make it easier ot share, use, and cite the vast quantities of information being generated by researchers across the disciplines.


FAIR Principles are

  • Findable
  • Accessible
  • Interoperable, and
  • Reusable

Open Data Licensing

Data Management Plan

"A data management plan (DMP) is a document that outlines how you will work with data during and after your research project. It describes the existing data you will use in your study, the new data you will produce and collect, where you will store  data, and if and how you will share data with others." (Rochester)

Your DMP should address the following: 

Backups

Where will you backup your data (locally, in the cloud, etc.)? How often will you backup your files? Will backups happen manually or automatically?

Existing Data

What existing data will need to find? How will you access it? How will you manage it? 

Data to be Created

What data will your project create? How much data will you produce? What file format(s) will you use for your data? 

Metadata

What metadata will you keep? What format or standard will you follow? 

File Organization

How will you name your data files? How will you organise your data into folders? How will you manage transfers and synchronization of data between different machines? How will you manage collaborative writing with your colleagues? How will you keep track of the different versions of your data files and documents? 

Access Control

Who will have access to your data? If the data is sensitive, how will you protect it from unauthorized access?

Storage

Where will your data be stored? Who will pay for the storage? Who will manage it? For how long?

Sharing

What data will you share with others? What license will you apply? When will the data become available?

Responsibilities

Who will be responsible for each of the items in this plan? What happens if a team member leaves? 

 Table adapted from the ANDS Guide to Data Management Plans.