Data Management for Researchers
Data Management for Researchers
Research data is increasingly being recognised as a valuable asset and a valid research output. Journals are starting to require that data be made available to support the research conclusions. The sharing of data is being required as a condition of research funding.
High quality data must be well managed. Most research institutions have comprehensive data management policies and procedures to support their researchers.
Good data management practices are a requirement for researchers (and institutions) under the Australian Code for Responsible Conduct of Research.
Guides
ANDS publishes a number of guides covering many aspects of data management. The following selection is particularly relevant to individual researchers working without institutional infrastructure.
| Data management planning (Awareness level) | A basic level guide to what needs to be included in a data management plan. | |
| Metadata (Awareness level) | This is an introduction to metadata (data about data). | |
| ANDS and Data Storage (Awareness level) | An introduction to data storage requirements under the Code for Responsible Conduct of Research along with different types and places for data storage. | |
| The Data Curation Continuum | Explains how effective sharing and re-use of research datasets is built upon end-to-end data management processes. | |
| Data Citation | Guide to the issues around data citation, and activities underway to change the culture around data citation in order to support improved data management and sharing. | |
| File Formats | Choosing a suitable file format for data preservation and sharing. This is more important and more subtle than it might seem. |
