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 - 18 of 18

National Institutes of Health (NIH); National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)

This is an example of a data management plan from the NIH, intended to collect genomic data and subsequent phenotype data from cancerous mice models.

National Institutes of Health (NIH); National Institute of Mental Health (NIMH)
This is a sample data management plan from the NIH, intended for submission to the NIMH, presenting a proposal to collect and analyze demographic, clinical and MRI data from human subjects.
National Institutes of Health (NIH); National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)

This is an example of a data management plan from the NIH, intended to collect clinical, demographic, and dialysis data from research participants.

University of Calgary; Digital Research Alliance of Canada

This is a template DMP for use in systematic review projects in any field.

University of Ottawa Heart Institute; Metaresearch and Open Science

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.

University of Ottawa Heart Institute; Metaresearch and Open Science

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.

University of Ottawa Heart Institute; Metaresearch and Open Science

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.

Johns Hopkins University; Working Group on NIH DMSP Guidance
This DMP aims to collect and create a public dataset of over 4000 MRI and CT scans of patients with various brain illnesses including but not limited to acute stroke and manual lesions.
University of Ottawa Heart Institute; Metaresearch and Open Science

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.

ISGLOBAL
This DMP was created for the Harmonic project which aims to collect cancer patient data, cardiac patient data, as well as biomarker analysis data. The overall goal of the project is to build two cohorts of pediatric populations treated with medical ionizing radiation. The two cohorts are cardiac patients and cancer patients.
University of Helsinki (UH)
This DMP was created for the HERCULES project, which aims to perform single-cell analysis to characterize and target high-grade serous ovarian cancer.
University of Edinburgh
This DMP aims to collect medical record data, questionnaire data, images, genotypic data, and quantitative molecular genetic data. This data will be used in the effort of enhancing molecular pathology cancer epidemiology studies.
UMC Utrecht
This DMP aims to collect blood samples and EPD samples, in order to investigate the clinical performance of a liquid biopsy test.
Utrecht University
This DMP aims to collect clinical health data from electronic records from approximately 400-500 patients. The relationship between the size of the preoperative radiological tumor and the size of the lumpectomy after surgery will be examined using this data.
UNIPI
This DMP was created for the PRIMAGE project which works in the area of medical imaging, artificial intelligence, and childhood cancer research. The project will collect data such as clinical data, biomarker information, and images.
McMaster University; Offord Center for Child Studies

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.

McMaster University

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. 

University of Manitoba; Digital Research Alliance of Canada

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.