University of British Columbia
This DMP aims to collect interviews, videos, transcripts, and word documents. This data will be used for the purpose of interviewing nursing librarians from CARL to understand what they learned from COVID-19 and their thoughts about academic support post-pandemic.
McMaster University
This data management plan template is designed to facilitate group collaboration among a diverse range of stakeholders, including artists, researchers, research participants, social service workers, community organizers, and community workers. It is intentionally crafted in plain language to facilitate accessibility and understanding for all parties involved. Additionally, it frames the process as conversation as opposed to a more traditional form, fostering relational approaches to interdisciplinary collaboration.
CRACKER Consortium
This DMP was created in accordance with the project CRACKER, which aims to “crack the language barrier”. The DMP outlines the collection of various forms of data including, text, audio, video, machine-readable dictionaries, terminological resources, and computational grammars.
Digital Research Alliance of Canada; University of Waterloo
This DMP example show uses a case study of relativistic astrophysics and gravitational physics data to show how management strategies can support computational reproducibility in High-Performance Computing. Data are the inputs and outputs of the numerical simulation model.
University of Cape Town (SA); Working Group on NIH DMSP Guidance
This DMP will collect and make publicly available tobacco related data in certain African countries to increase research in this field such that a continent-wide approach to tobacco control can be developed.
Cégep de Sherbrooke; Digital Research Alliance of Canada
This DMP aims to collect digital, tabular, and graphic data on plastic production parameters, environmental conditions, and inspectional measures among other factors to optimize the industrial extrusion process.
RTI International
This DMP aims to collect geographic data, survey data, statistics, microdata, and code.
University of Plymouth
This DMP aims to collect survey data to be used for understanding the employee perception of the economic outlook in Myanmar.
EuDEco Consortium; University of Vienna (PHAIDRA)
This DMP aims to collect case study data, model data, survey data, and observational data for the EuDEco project. This project will indulge in establishing a self-sustaining data market in the context of developing the data economy.
FIRES Consortium; University of Vienna (PHAIDRA)
This DMP aims to collect interview data, and numerical data, in order to assist the FIRES project. This project will look into smart, inclusive and sustainable growth in Europe, specifically pertaining to entrepreneurial activity.
Florida PALM Consortium
This DMP was created for the Florida PALM project, which aims to implement a statewide accounting system.
Temple University; Working Group on NIH DMSP Guidance
This DMP aims to collect audio recordings, surveys, and observations to revitalize and endangered language.
Montreal Neurological Institute
This DMP aims to collect reaction time, choice, and eye-tracking data which will be used for a mock behavioral and eye-tracking project.
National Science Foundation (NSF)
This DMP was created by the NSF as a template for Education and Human Resources.
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.
R2PI Consortium; University of Vienna (PHAIDRA)
This DMP aims to collect research and case study data for the R2Pi project, which has the intent of developing sustainable business models to create a circular economy.
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.
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.