Teaching the Best Research Data Management Practices to PhD Students

Ishwar Kapoor
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Abstract

Good Research Data Management (RDM) practices make it easier for researchers to conduct their research and ensure their data is preserved and stored securely for the long-term. Archiving is one of the last stages of Research Data Lifecycle and deals with depositing and preserving datasets at the end of a project in a suitable storage location (repositories, local server, or hard drive). Students may not find data management topic as interesting as their core course topics. This can result in lack of students’ knowledge of the importance and benefits of good data management practices for their studies. At Warwick, I design and deliver Research Data Management & Planning (RDM&P) case study sessions to PhD students. Students learn different elements of RDM and importance of RDM for long-term preservation. Students work in groups to develop and present Data Management Plan (DMP) and put RDM&P learning into practice. In this presentation, I briefly introduce the above case study, feedbacks received from students across different disciplines and further steps.
向博士生教授最佳研究数据管理实践
良好的研究数据管理(RDM)实践使研究人员更容易进行他们的研究,并确保他们的数据被长期安全地保存和存储。归档是研究数据生命周期的最后阶段之一,处理在项目结束时在合适的存储位置(存储库、本地服务器或硬盘驱动器)存放和保存数据集。学生可能不觉得数据管理主题像他们的核心课程主题那样有趣。这可能导致学生不了解良好数据管理实践对他们学习的重要性和好处。在华威大学,我为博士生设计并提供研究数据管理与规划(RDM&P)案例研究课程。学生将学习RDM的不同元素以及RDM对长期保存的重要性。学生小组合作,制定和提出数据管理计划(DMP),并将RDM&P学习付诸实践。在这次演讲中,我将简要介绍上述案例研究,从不同学科的学生那里收到的反馈以及下一步的步骤。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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