Guide to Publishing and Sharing Sensitive Data

The Australian National Data Service (ANDS) has just released a Guide to Publishing and Sharing Sensitive Data which includes a decision tree to help researchers decide whether they can publish such data. The guide is written for the Australian context; however it provides generic information on the issues associated with handling sensitive data.

PGR workshops – Research Data Management

Date Information

Date Time
Wed, 19th November 2014 9:30am – 12:30pm

Who Should Attend?

This session is aimed at early career researchers, although mid-career researchers would also benefit from the principles discussed.

Course Overview

Whilst the management of research data has always been important to the individual researcher, effective research data management is increasingly important within the whole research lifecycle for all disciplines. This session based around the structure of a data management plan, explores what research data management is, why it is important and introduces participants to the key concepts involved to enable them to incorporate best practice within their projects.

Intended Learning Outcomes

Participants will have the opportunity to:

  1. Explore research data management (RDM) within the research lifecycle
  2. Recognise the key terms and concepts involved in RDM
  3. Identify the benefits and drivers for good data management
  4. Reflect on best practice for managing digital data effectively
  5. Discuss common elements of an effective data management plan
  6. Identify the support offered by IT Services and other Professional Services within the University
  7. Discuss the benefits and challenges of sharing data
  8. Meet and network with PGRs from across campus

This session maps to Research Development Framework – Domain C: Research governance and organisation. Sub-domain 1- Professional conduct; Sub-domain 2 – Research management


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New release of Research Data MANTRA (Management Training) free online course

The Research Data MANTRA course is an open, online training course that provides instruction in good practice in research data management. There are eight interactive learning units on key topics such as data management planning, organising and formatting data, using shared data and licensing your own data, as well as four data handling tutorials with open datasets for use in R, SPSS, NVivo and ArcGIS.

This fourth release of MANTRA has been revised and systematically updated with new content, videos, reading lists, and interactive quizzes. Three of the data handling tutorials have been rewritten and tested for newer software versions too.

New content in the online learning modules with the September, 2014 release:

  • New video footage from previous interviewees and introducing Richard Rodger, Professor of Economic and Social History and Stephen Lawrie, Professor of Psychiatry & Neuro-Imaging
  • Big Data now in Research Data Explained
  • Data citation and ‘reproducible research’ added to Documentation and Metadata
  • Safe password practice and more on encryption in Storage and Security
  • Refined information about the DPA and IPR in Data Protection, Rights and Access   Linked Open Data and CC 4.0 and CC0 now covered in Sharing, Preservation & Licensing

MANTRA was originally created with funding from Jisc and is maintained by EDINA and Data Library, a division of Information Services, University of Edinburgh. It is an integral part of the University’s Research Data Management Programme and is designed to be modular and self-paced for maximum convenience; it is a non-assessed training course targeted at postgraduate research students and early career researchers. Data management skills enable researchers to better organise, document, store and share data, making research more reproducible and preserving it for future use. Researchers in 144 countries used MANTRA last year, which is available without registration from the website. Postgraduate training organisations in the UK, Canada, and Australia have used the Creative Commons licensed material in the Jorum repository to create their own training.