Research Data Lifecycle Overview

To formulate the initial research idea or hypothesis, and define the scope of the research project and the data component/requirements of that project.

To establish a structured strategic framework for management of the research project, outlining aims, objectives, methodologies, and resources required for data collection, management and analysis.

To identify and acquire financial resources to support the research project, including data collection, management, analysis, sharing, publishing and preservation.

To use predefined procedures, methodologies and instruments to acquire and store data that is reliable, fit for purpose and of sufficient quality to test the research hypothesis.

To make new and existing data analysis-ready. This may involve standardised pre-processing, cleaning, reformatting, structuring, filtering, and performing quality control checks on data.

To derive insights, knowledge, and understanding from processed data.

To record data using technological media appropriate for processing and analysis whilst maintaining data integrity and security.

To release research data in published form for use by others with appropriate metadata for citation (including a unique persistent identifier) based on FAIR principles.

To ensure the safety, integrity, and accessibility of data for as long as necessary so that data is as FAIR as possible.

To make data available and accessible to humans and/or machines.

To control and manage data access by designated users and reusers.

To create new data from the original, for example by migration into a different format or by creating a subset.