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 - 13 of 13

Alaska Regional Office (AKRO); NOA Fisheries
This DMP aims to collect telemetry data, digital numeric data, imagery, photographs, video, audio, database, location data, biological samples, and tabular data. This data will be used for assessing the pinnipeds inhabiting the California Current in relation to the sea lions and seals.
Alaska Regional Office (AKRO); NOA Fisheries
This DMP was created for Alaska Steller sea lion capture data. The project collects digital numeric data, imagery, photographs, video, audio, database, and tabular data.
Engineer Research and Development Center (U.S.); Defense Technical Information Centre
This DMP is a template for the US Army Engineer Research and Development Center (ERDC).
USDA; National Agricultural Library
This DMP is an example provided by the National Agriculture Library.
USDA; National Agricultural Library
This DMP is an annotated example provided by the National Agriculture Library.
University of Florida
This DMP was created for a project aimed to quantify ecosystem service development in human-made oyster reefs. The data collected is expected to consist of both observational and sampled data, along with water quality information such as salinity and temperature.
Pennsylvania State University
This DMP aims to collect DNA and RNA sequencing data translated into genomes and transcriptomes, count data, phenotypic measurements, and site-specific methylation status data. This data will be used in the aim to guide epigenetic breeding in related cereal crops to enhance biotic and abiotic stress-tolerance.
California State University, Channel Islands
This DMP aims to collect observational data including oak tree height, Lat, log, width, and acorn count. This data will be collected by surveying Harmon Canyons Oak trees in order to understand Canopy cover and the biodiversity that lies under the cover.
University of Georgia
This DMP aims to collect both quantitative and qualitative data. This will mainly consist of experimental and analysis data, which will be used in the efforts of investigating the genetic diversity of pantoea ananatis.
Alaska Regional Office (AKRO); NOA Fisheries
This DMP was created for Platform Removal Observer Program databases. The project collects digital numeric data, imagery, photographs, video, audio, database, and tabular data.
Arizona State University
This DMP aims to collect seedlings establishment population data, seedlings density, statistical analyses, and text information. This data will be used in the efforts of studying seedling establishment and woody-plant encroachment in southwest rangelands.
Montana State University
This DMP was curated for the STARS project, which aims to develop and deploy a framework for soil testing, analysis, and risk-management. The data collected will include education data, administrative data, research data, evaluation data, satellite and geospatial data, unmanned aerial systems images, and regression models.
University of California, Riverside
This DMP aims to collect both non-digital and digital data. The specific forms of data are hand-written observations, images, videos, nucleotide and protein sequences, genome sequences, genome annotations, metabolic models, metabolomics and transcriptomics data, as well as genetic and phenotypic data. This data will be used in the aim to create citrus trees that are resistant or tolerant to Huanglongbing (HLB) disease, and/or to create effective treatments.