Research Data Management

Sensitive data are data that can be used to identify an individual, species, object, process, or location that introduces a risk of discrimination, harm, or unwanted attention. Under law and the research ethics governance of most institutions, sensitive data cannot typically be shared in this form, with few exceptions.

Key messages from the ANDS Guide to Sensitive Data:

• The advantages of publishing your sensitive data will probably far outweigh any potential disadvantages when simple and appropriate steps are taken
• Publishing your data, or just a description of your data (i.e., the metadata ), means that others can discover it and cite it
• You can publish a description of your data without making the data itself openly accessible
• You can place conditions around access to published data
• Sensitive data that has been confidentialised can be shared

This Guide outlines best practice for the publication and sharing of sensitive research data in the Australian context.

Force11 offer a set of guiding principles to make data FAIR: Findable, Accessible, Interoperable, and Re-usable.

Force 11 is a community of scholars, librarians, archivists, publishers and research funders that has arisen organically to help facilitate the change toward improved knowledge creation and sharing.

Sound, reproducible scholarship rests upon a foundation of robust, accessible data.

For this to be so in practice as well as theory, data must be accorded due importance in the practice of scholarship and in the enduring scholarly record. In other words, data should be considered legitimate, citable products of research. Data citation, like the citation of other evidence and sources, is good research practice and is part of the scholarly ecosystem supporting data reuse.

A fundamental aspiration of the Australian Research Data Commons is that more data is reusable.

One of the essential ingredients of reusable data is clarity of reuse permissions, terms, and conditions.

Prospective users need to know exactly what they can do with the data. Those conditions and permissions need to be explicit. Within the Australian context, this information about the permissions and conditions of reuse can be expressed in different kinds of notices, licences, contracts, etc accompanying the data. Not being clear about permission to reuse data can have the same result as forbidding data reuse, because uncertainty can be enough to discourage the potential user.

AusGOAL is an open access and licensing framework and programme designed to assist organisations to select the least restrictive of an endorsed set of licences that are appropriate to the dataset being published. In November 2013, The Council of Australian University Librarians (CAUL) officially endorsed AusGOAL, meaning there is now a common approach to data licensing across research and government, facilitating use and reuse of data for further innovation and research.

(Australian National Data Service website https://ands.org.au/publishing/licensing.html
Accessed 2015-02-13)

AusGOAL endorses eight licensing options:

• The six Australian Creative Commons (CC) Version 3.0 licences
• The Restrictive Licence Template (RLT)
• The BSD 3-Clause Software Licence

The six Creative Commons licences recommended in AusGOAL are the preferred licences for opening access to publicly funded information. Among those, the Creative Commons Attribution Licence (CC BY) is the most popular and provides the greatest opportunities for re-use of information. Use of the Creative Commons licences promotes a common standard of licensing.

(AusGOAL website https://www.ausgoal.gov.au/the-ausgoal-licence-suite
Accessed 2015-04-27)

If you haven't heard of Creative Commons before, here is a brief video explaining what its all about:

Open Knowledge is a worldwide non-profit network of people passionate about openness, using advocacy, technology and training to unlock information and enable people to work with it to create and share knowledge.

The Open Definition gives full details on the requirements for ‘open’ data and content. Open data are the building blocks of open knowledge. Open knowledge is what open data becomes when it’s useful, usable and used.

The key features of openness are:

• Availability and access: the data must be available as a whole and at no more than a reasonable reproduction cost, preferably by downloading over the internet. The data must also be available in a convenient and modifiable form.
• Reuse and redistribution: the data must be provided under terms that permit reuse and redistribution including the intermixing with other datasets.
• Universal participation: everyone must be able to use, reuse and redistribute - there should be no discrimination against fields of endeavour or against persons or groups. For example, ‘non-commercial’ restrictions that would prevent ‘commercial’ use, or restrictions of use for certain purposes (e.g. only in education), are not allowed.

For a more complete look at open data including a detailed guide on how to open it up and a glossary of key terms, visit the Open Data Handbook online.