Data Management Plan Database
A Data Management Plan (DMP) describes how you will manage, store, secure, document, and share research data. DMPs can vary broadly across disciplines, methodologies, and data types. DMPs are a growing requirement for grants, and can also guide data practices for individuals and teams. DMP Assistant is a free webtool that guides you through drafting your DMP and the easiest way to start building a DMP.
Our database gathers examples from across the world including DMPs from the Digital Research Alliance of Canada, National Institutes of Health (NIH), Qualitative DMP Competition, DataOne, Digital Curation Centre, Liber, the Working Group on NIH DMSP Guidance, and UC San Diego Research Data Curation into one searchable, open-access platform.
Download the amalgamated dataset: https://doi.org/10.5683/SP3/SDITUG
Project Team: Rebeca Gaston Jothyraj (RDM Assistant - 2024), Shrey Acharya (RDM Assistant - 2023), Sarthak Behal (RDM Assistant 2022-23), Danica Evering and Isaac Pratt (RDM Specialists), Debbie Lawlor (Developer).
Data Management Plan Database
Search and Browse Data Management Plans
Displaying 1 - 30 of 30
This is an example of a data management plan from the NIH, intended to collect clinical, demographic, and dialysis data from research participants.
This DMP aims to collect text, binary (ASCII, binary), images, audio, etc. data to develop advanced research computing frameworks and infrastructure for application in various fields like quantum chemistry, biochemistry, machine learning, and artificial intelligence.
This is a template DMP for mixed-methods research where data is obtained from surveys and qualitative interviews/focus groups.
This is a template DMP for use in systematic review projects in any field.
Developed by researchers for the University of Ottawa Heart Institute, this guidance and worked example extracts examples from Beck, Leblanc, and Morissette's systematic review protocol on depression screening of children and adolescents. It outlines a data management plan for a systematic review study.
Developed by researchers for the University of Ottawa Heart Institute, this guidance and worked example outlines a data management plan for a pre-clinical laboratory animal study. This DMP outlines a project to explore stroke treatments using biocellulose duroplasty with rat subjects.
Developed by researchers for the University of Ottawa Heart Institute, this guidance and worked example outlines a data management plan for a randomized controlled trial conducted with 100 human participants. Demographic data will be collected from participants, and then other data is collected by an electroencephalogram, electroculogram, electromyogram, as well as video and sound.
Developed by researchers for the University of Ottawa Heart Institute, this guidance and worked example outlines a hypothetical genomic study into acute lymphoblastic leukaemia using blood drawn from patients, healthy volunteers, and mouse models.
This is a DMP example for a fictional research study that will use a mixed-methods approach to collect participant data from interviews, surveys, and focus groups. This example uses the new Alliance Simplified Template (Funding Application Stage) which focuses on 5 questions that are helpful for a DMP that meets new Tri-Agency requirements.
This DMP aims to collect questionnaires, personal data, computer-based tasks & output, ECG’s, EDA’s, videos, audio recordings, data analysis files, linkage data, interviews, and transcripts. This data will be used for the Promoting Healthy Families project, which will assess whether Triple P and COSP can help promote healthy family relationships.
This is a student data management record created by the vascular dynamics lab. Although it was created for students working within this lab and is structured for kinesiology related research, it has broad applicability as an exit protocol for labs working across Natural and Health Sciences.
This DMP aims to collect clinical data for 1000 women for an observational study to assess the effectiveness of a cardiovascular screening program and identify any potential biomarkers that are predicative for cardiovascular disease.