The significance of Data Management Plans (DMP) as a critical element of the research process for researchers in higher learning institutions (HLIs)

Published: 1 July 2024| Version 1 | DOI: 10.17632/5vvb44n57g.1
Neema Mosha


Quantitative data was gathered from 206 postgraduate students at the Nelson Mandela African Institution of Science and Technology, a public university in the United Republic of Tanzania, with a return rate of 104 (50%). The data collection involved structured questionnaires. Data Management Plans (DMPs) are essential for researchers in higher learning institutions (HLIs). While DMPs offer various benefits such as ensuring compliance with funder and institutional requirements, promoting data sharing and reuse, and addressing ethical considerations, HLIs encounter challenges in developing and utilising DMPs for research projects. DMPs assist researchers in planning the collection, storage, and management of data throughout their projects, specifying data formats, metadata standards, file naming conventions, and documentation practices. Moreover, DMPs foster collaboration among researchers across different disciplines by establishing common data management practices and standards, particularly beneficial in HLIs where interdisciplinary projects necessitate effective data sharing and integration. Proper organization and documentation of data are critical for maintaining data quality, reproducibility, and long-term usability. Researchers have access to DMP template tools online or as Word documents, with many favoring DMPonline templates due to their user-friendly nature and availability at no cost. This enables HLIs and researchers to adopt and customize these tools to align with their specific needs. In essence, DMPs play a vital role in guiding researchers through the entire data lifecycle, from collection to sharing and preservation. By developing and implementing robust DMPs, researchers in HLIs can improve the quality, integrity, and impact of their research outputs while meeting compliance requirements and ethical standards.



University of South Africa, Nelson Mandela African Institute of Science and Technology


Quantitative Genetics