The Research Lifecycle is a heuristic model for understanding the steps of the process of scientific discovery (research), often represented in a wheel to emphasize the continuous nature of research with one project leading into the next. The research data lifecycle includes everything from planning how data will be collected, to publication, to long term data preservation, to possible reuses of data. Steps of the lifecycle include: Plan, Acquire, Process, Analyze, Preserve, Share Results, and Reuse, but terms may differ based on institution, field of research, or model author.
Planning:A researcher designs a study model and identifies the data they need to collect for the study. Acquire: The researcher finds an authoritative resource with the collected data points they need. Process: They clean and organize the data and prep for analysis. Analyze: The researcher runs various models and tests to study the data. Preserve: They backup their data and prepare it for long term preservation. Share Results: The researcher publishes an article on their findings and shares their data on a subject specific repository. Reuse: Other researchers find the data and use it for their own research, or the original researcher continues to use the data for other studies.
Harvard Medical School’s Data Lifecycle: https://datamanagement.hms.harvard.edu/about/what-research-data-management/biomedical-data-lifecycle
Princeton Research Lifecycle Guide: https://researchdata.princeton.edu/research-lifecycle-guide/research-lifecycle-guide