All Learning Resources
Environmental Data Management Best Practices Part 1: Tabular Data
This webinar is the first in a two-part webinar focused on Environmental Data Management Best Practices. The topic of this webinar is tabular data, and is one of a series of educational workshops focused on best practices for and tips to best manage environmental research data presented by experts from the NASA's Distributed Active Archive Center for Biogeochemical Dynamics.
Do-It-Yourself Research Data Management Training Kit for Librarians
Online training materials on topics designed for small groups of librarians who wish to gain conficence and understanding of research data management. The DIY Training Kit is designed to contain everything needed to complete a similar training course on your own (in small groups) and is based on open educational materials. The materials have been enhanced with Data Curation Profiles and reflective questions based on the experience of academic librarians who have taken the course.
The training kit includes:
- Promotional slides for the RDM Training Kit
- Training schedule
- Research Data MANTRA online course by EDINA and Data Library, University of Edinburgh
- Reflective writing questions
- Selected group exercises (with answers) from UK Data Archive, University of Essex - Managing and sharing data: Training resources. September, 2011 (PDF). Complete RDM Resources Training Pack available:
- Podcasts for short talks by the original Edinburgh speakers if running course without ‘live’ speakers (Windows or Quicktime versions).
- Presentation files (pptx) if learners decide to take turns presenting each topic.
- Evaluation forms
- Independent study assignment: Interview with a researcher, based on Data Curation Profile, from D2C2, Purdue University Libraries and Boston University Libraries.
LEARN Toolkit of Best Practice for Research Data Management
The LEARN Project's Toolkit of Best Practice for Research Data Management expands on the issues outlines in the LERU Roadmap for Research Data (2013). It is freely downloadable, and is a deliverable for the European Commission. It includes:
- 23 Best-Practice Case Studies from institutions around the world, drawn from issues in the original LERU Roadmap;
- 8 Main Sections, on topics such as Policy and Leadership, Open Data, Advocacy and Costs;
- One Model RDM Policy, produced by the University of Vienna and accompanied by guidance and an overview of 20 RDMpolicies across Europe;
- An Executive Briefing in six languages, aimed at senior institutional decision makers.
The Executive Briefing of the LEARN Toolkit is available in English, Spanish, German, Portuguese, French and Italian translations.
MANTRA Research Data Management Training
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.
Through a series of interactive online units you will learn about terminology, key concepts, and best practice in research data management.
There are eight online units in this course and one set of offline (downloadable) data handling tutorials that will help you:
Understand the nature of research data in a variety of disciplinary settings
Create a data management plan and apply it from the start to the finish of your research project
Name, organise, and version your data files effectively
Gain familiarity with different kinds of data formats and know how and when to transform your data
Document your data well for yourself and others, learn about metadata standards and cite data properly
Know how to store and transport your data safely and securely (backup and encryption)
Understand legal and ethical requirements for managing data about human subjects; manage intellectual property rights
Understand the benefits of sharing, preserving and licensing data for re-use
Improve your data handling skills in one of four software environments: R, SPSS, NVivo, or ArcGIS