Research data across the lifecycle

Best Practice Throughout the Data Life Cycle: 6th Edition (as of Sep. 2022)

"Research data management is a critical aspect of empirical research that enhances its ability to advance scientific inquiry. Managing data involves performing a series of tasks – from identifying and locating potentially useful data sources; to collecting, organizing, reducing, and processing them; to generating informative documentation for them; to storing and preserving them."

"MANTRA is a free, online non-assessed course with guidelines to help you understand and reflect on how to manage the digital data you collect throughout your research. It has been crafted for the use of post-graduate students, early career researchers, and also information professionals. It is freely available on the web for anyone to explore on their own."

"This course will provide learners with an introduction to research data management and sharing. After completing this course, learners will understand the diversity of data and their management needs across the research data lifecycle, be able to identify the components of good data management plans, and be familiar with best practices for working with data including the organization, documentation, and storage and security of data. Learners will also understand the impetus and importance of archiving and sharing data as well as how to assess the trustworthiness of repositories."

"This tutorial covers the importance of research data and provides examples for effective management and sharing strategies for organization, reproducibility, and enabling better credibility and recognition through sharing your data."

"The typical README in social science journals serves the purpose of guiding a reader through the available material and a route to replicating the results in the research paper, including the description of the origins of data and/or description of programs. As such, a good README file should first provide a brief overview of the available material and a brief guide as to how to proceed from beginning to end, before then diving into the specifics. These template files structure such a README in a way that is compliant with the typical data and code workflow in the social sciences."

"A readme file provides information about a data file and is intended to help ensure that the data can be correctly interpreted, by yourself at a later date or by others when sharing or publishing data. Standards-based metadata is generally preferable, but where no appropriate standard exists, for internal use, writing “readme” style metadata is an appropriate strategy."

"README Files are a common way to document the contents and structure of a folder and/or a dataset so that a researcher can locate the information they need."

Includes "Elements of a Data Management and Sharing Plan," "Set Yourself Up for Success" and "Cleaning Data Using OpenRefine" among other topics.

This resource "was created in a collaboration between the U.S. Geological Survey's Community for Data Integration, the Earth Sciences Information Partnership (ESIP), and DataONE."

"This website provides resources and guidance for research data management planning and assistance with elements of data management that will be relevant throughout your career. It provides access to tools and resources, including information on funding agency and institutional requirements, that help you manage your data effectively and prepare it for sharing, and reuse."

"...research data management (RDM) is a discipline concerned with making data—generated in the course of research—to be accessed as easily as possible by peers, contributors, and readers. This article plans to outline what it is, what it can do, and how to make an effective RDM plan."