Introduction to Research Data Management (RDM) - Data Management plans (DMP)

Duration: 65 min, for online or face-to-face format.

This seminar aims to provide a quick introduction on Research Data Management (RDM), while detailing how scientists can begin to implement RDM practices in their work by writing Data Management Plans (DMP). DMPs should align with relevant policies applicable to the project. These can be, institutional, research funders and publishers - data policies.

To start, relevant aspects on RDM are presented to explain how to produce self-describing and reusable data sets. It then explains what a DMP is, why to write it and how to write it.

The last and longer part of the seminar develops in an interactive section to give participants the opportunity to think about relevant aspects for handling data by identifying correct statements to formulate a DMP.

The slides provide relevant links for further consultation, including the practical guide to the international Alignment of RDM published by Science Europe (2021). This document guides researchers and reviewers through six core requirements of DMPs.

Learning Goals:
1. How to produce self-describing and reusable data sets
2. How to start with RDM-practices by writing a data management plan. 3. What is a DMP, why to write it and how to write it.

Prerequisites: none

本研讨会旨在对研究数据管理（RDM）进行快速介绍，并详细阐述科学家如何通过撰写数据管理计划（DMP）来开始在他们的工作中实施RDM实践。DMP应与项目相关的政策相一致，这些政策可以是机构、研究资助者和出版商的数据政策。首先，介绍RDM的相关方面，以解释如何产生自描述和可重复使用的数据集。随后，阐述DMP的含义、为何需要撰写以及如何撰写。研讨会的最后部分，通过互动环节，为参与者提供思考数据管理相关方面的机会，通过识别正确的陈述来制定DMP。幻灯片提供了相关链接，以便进一步咨询，包括由Science Europe于2021年发布的RDM国际对齐的实用指南。该文件引导研究人员和审稿人了解DMP的六个核心要求。学习目标：1. 如何产生自描述和可重复使用的数据集；2. 如何通过撰写数据管理计划开始实施RDM实践；3. 什么是DMP，为何需要撰写以及如何撰写。先决条件：无。