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

Data Management Plans Overview

Search and Browse Data Management Plans

Displaying 1 - 9 of 9

Afro-Descendant Movements and Territories of Life in Urban Spaces: Examples from Brazil

Original Source

University of Massachusetts Amherst; Working Group on NIH DMSP Guidance

This DMP investigates Afro-descendant movement in Latin America and subsequent self-determined collectives using participant observation, semi-structured interviews, and participatory workshops.

An Annotated Digital Edition of Franz Boas’s Pioneering Ethnography

Original Source

Bard Graduate Center; Open Anthropology Research Repository

This DMP aims to collect digitized materials, fonts, search algorithms, and software. The digitized materials will consist of historical and recent photographs, newspaper clippings, sound recordings, video clips, interviews, published essays, narratives, and songs.

Doctoral Dissertation Research: AnAgent-Based Model of Population Changes in a Vulnerable Coastal Environment

Original Source

Louisiana State University; Open Anthropology Research Repository

This DMP aims to collect coastal hazard data, GIS shape files and data, social-economic data, and demographic data. This data will be used for investigating population changes in a vulnerable coastal environment.

Human genomic data

Original Source

National Institutes of Health (NIH); National Human Genome Research Institute Home (NHGRI)

This is a sample data management plan from the NIH, intended for submission to the NHGRI, that provides an outline for a project involving human genomic and clinical data.

Language Endangerment and Revitalization at the Dialectal Level: A current analysis of Salasaca Kichwa (ISO 639-3 = qxl)

Original Source

Temple University; Working Group on NIH DMSP Guidance

This DMP aims to collect audio recordings, surveys, and observations to revitalize and endangered language.

Phonological aspects of word learning: Advantages of bilingualism and impacts of developmental language disorder

Original Source

Portland State University; Working Group on NIH DMSP Guidance

This DMP aims to collect linguistic and developmental data to determine how phonological learning and bilingualism impacts development.

Survey and Interview Example

Original Source

National Institutes of Health (NIH); National Human Genome Research Institute (NHGRI)

This is an example of a data management plan from the NIH, intended to collect anthropologic and public policy data from surveys and interviews.

Text analysis of Taldash (GAL) in Support of Nuu-wee-ya' Language Revitalization: Indigenous-based linguistic analysis and methodological reflections

Original Source

University of Oregon; Qualitative Data Management Plan (DMP) Competition

This DMP aims to digitize data and create a database of semantics, lexicon, and morphemes to preserve the Nuu-wee-ya' language.

Using natural language processing to determine predictors of healthy diet and physical activity behavior change in ovarian cancer survivors

Original Source

University of Arizona; Working Group on NIH DMSP Guidance

This DMP will use longitudinal speech data of cancer survivors from another study to develop a Machine Learning model that can increase participant compliance with health lifestyle habits.