This guide will provide general information on research data management with an emphasis on health and human sciences, working with sensitive data, and related federal funding policy. Topics from the research data lifecycle will be explored, including:
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With continuous advancements in technology, the precision and breadth of data creation, collection, and acquisition have significantly improved, alongside an enhanced capacity for storage. Consequently, the importance of managing, integrating, and reusing data has increased. As an increasing number of publishers and funding agencies mandate data sharing and preservation, establishing robust data management practices at an early stage will facilitate the organization of your data, ensure compliance with funder requirements, and prepare your data for dissemination to others.
Data management addresses the lifecycle of your research output including its creation, organization, accessibility, archiving and distribution. Proper data management helps maintain scientific rigor and research integrity. When discussing research data management, “data” will include any scientific data from a project that will be preserved and shared. While all data collected will not fit this category, you should decide which scientific data to preserve and share based on ethical, legal, and technical factors.
Below is a description of the core stages of the inner section of the lifecycle. The diagram's outer layer represents the processes and concepts that are integral to each stage. However, many of the stages overlap.
Research Data Lifecycle by LMA Research Data Management Working Group is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
