---
title: "Research Data"
source: The Turing Way
source_url: https://github.com/the-turing-way/the-turing-way
licence: CC-BY-4.0
domain: data-and-analysis
subdomain: turing-way
date_added: 2026-04-25
---

(rr-rdm-data)=
# Research Data

(rr-rdm-data-definition)=
## What is Data?

Data are objects that you use and produce during your research life cycle, encompassing datasets, software, code, workflow, models, figures, tables, images and videos, interviews, articles. 
Data are your research asset. 
A good way of thinking about what might be classed as data that needs to be managed is to ask yourself the questions: "What is the information that I need to use and write about in my paper or book?", "What information would I need to back up my conclusions?" and "What information is needed by others to understand and possibly replicate the research that I have done?". 
This information is your data.

> Data are: _Facts, measurements, recordings, records, or observations about the world, collected by researchers, that are yet to be processed/interpreted/analysed.
Data may be in any format or medium taking the form of writings, notes, numbers, symbols, text, images, films, video, sound recordings, pictorial reproductions, drawings, designs or other graphical representations, procedural manuals, forms, diagrams, work flow charts, equipment descriptions, data files, data processing algorithms, or statistical records._
[CODATA Research Data Management Terminology ](https://vocabs.ardc.edu.au/viewById/685)

(rr-rdm-data-lifecycle)=
## The Research Data Lifecycle - A Model for Data Management

Research data often follows a 'lifecycle' which follows the research project as it evolves; here is a [video](https://www.youtube.com/watch?v=-wjFMMQD3UA) that describes it. 
This model provides a sound basis on which to plan for research data management, from data creation at the start of a research project, through to publishing and sharing research at the end of the project, and archiving any research data for the long-term and future reuse once the project has ended.

The research data lifecycle involves data creation, data use, data publication and sharing, data archiving, and data reuse or destruction.
However, data have a longer lifespan than the research project that creates them. 
In a [](#rr-rdm-dmp) you can structure how you will manage and share your research data.
