The answer is... probably!
Datasets will be protected by copyright (and defined as "literary works" under the Australian Copyright Act) if they meet certain threshold criteria of human authorship, originality, or creativity. Basically, compiling and presenting raw data (e.g. adding labels, units, performing calculations etc) is often sufficient to attract copyright protection. Note that copyright in research data produced at James Cook University is governed by JCU's Intellectual Property Policy and Procedure.
The Australian Research Data Commons Research Data Management Guide explains the relationship between copyright and research data in the following terms:
If a data logging machine placed in a creek were to generate 'raw data' about (for example) water quality, that data would not attract copyright protection, despite the fact that researchers may have used considerable skill, effort and expertise in siting the machine. Since the 'raw' data itself would have no human authorship and originality, it would not satisfy the legal basis of copyright. However, if a researcher were to examine the data from the data logging machine, notes certain errors and makes corrections to the or reforms the selection and arrangement of the dataset; that (sometimes relatively minor) act of human authorship, originality, and application of skill and judgment may be sufficient for the resulting dataset to attract copyright protection.
Even if your data does not meet the threshold for copyright there is no harm in applying a Creative Commons licence when publishing the data. It lets others know how you would like to be attributed and applies a limitation of liability and warranty clause to the data.
Applying a licence makes the terms and conditions regarding the re-use of your data explicit, and ensures your data is attributed to you correctly.
In Australia, having no licence is regarded in the same way as "all rights reserved" under the Copyright Act. This means other people would have to contact you for permission to do anything with the data. This restricts the future impact of your data by making it difficult (and often impossible) to re-use it or integrate it with other datasets.
Applying a Creative Commons licence to your data is an easy way to ensure correct attribution and enable re-use. The poster at the link below provides a detailed explanation of the benefits, conditions and restrictions associated with the different forms of CC licence:
The six licences are listed on this page. You can also access view the human-readable licence deeds from the links below:
The current generation of Creative Commons licences are International 4.0 licences. Creative Commons recommends you take advantage of the improvements in the 4.0 suite unless there are particular considerations that would require a ported (e.g. Australian) licence. The Australian Creative Commons licence chooser redirects to the international site. Older, ported licences can be selected using the drop-downs in in Data Publication section of Research Data JCU (but this is not usually required).
Rather, you are allowing users to make use of your work in various ways, but only on certain conditions. The core conditions are outlined in the following table; these core conditions can be combined to produce the six CC licences:
No Derivative Works
Applies to every Creative Commons work - except Creative Common Zero (CC 0)
Users are expected to give you appropriate credit, provide a link to the licence and indicate if changes have been made.
|Users may copy, distribute, display or perform your work but only for non-commercial purposes.||Users may not adapt or change your work in any way.||Users may remix, adapt and build on your work, but only if they distribute the derivative works under the same licence terms that govern the original work.|
It is possible to dedicate your work to the Public Domain by using Creative Commons Zero (CC0)
You may prefer to use one of the CC licences listed to ensure any re-use is counted towards your research impact. Proponents of CC 0 would argue that community norms are sufficient to ensure citation. You can explore the arguments here.
This condition has the potential to stifle engagement and innovation. Only some datasets will have commercialization potential but you should check with JCU Connect if you're not sure.
The "preferred" licence at JCU is CC BY-NC but your funder or journal may require you to make your data more open.
Permitting commercial use enables re-use such as sharing content on Wikipedia (which uses CC BY) and commercial organizations preserving content if publishers go bust!
This condition severely restricts re-use including aggregating data and meta-analyses. Open Access journals such as PLoS will not allow you to use this condition. CC BY-NC-ND is often referred to as a "free advertising" licence!
Journals may not permit you to use the ND clause as it limits the ability to do meta-analyses.
This condition can reduce interoperability which is is one of the aims of FAIR data.
A licence can't feature both the Share Alike and No Derivative Works options. The Share Alike condition only applies to derivative works.
(“Creative Commons License Spectrum” by Shaddim (CC BY)).
Creative Commons Zero (CC0) is for dedicating works to the public domain and is used by Dryad and other data repositories.
CC0 works on two levels: as a waiver of a person's rights to the work, and in case that is not effective, as an irrevocable, royalty-free and unconditional licence for anyone to use the work for any purpose. In Australia we always have moral rights (which includes the right to attribution) so the waiver is "ineffective" i.e.CC0 waives all copyright and related rights to the fullest extend allowed by the law of the land.
There are pros and cons for this approach and researchers need to decide what best meets their needs.
As the Digital Curation Centre suggests, this can be an "unattractive option for data whose creators have yet to fully exploit them, either academically or commercially. Nevertheless, it does resolve many of the ambiguities surrounding data use and reuse ... and greatly simplifies integration with other data."
Dryad also argues that CC0 reduces the legal and technical impediments to data re-use. Imagine, for example, the difficulties you would encounter if you were mining multiple sources for data and were legally required to formally attribute all of the data owners. In addition, they believe (as explained in the Panton principles Q11) that community norms for scholarly communication are a more effective way of encouraging positive behaviour, such as data citation, than applying licences and that "Any publication that makes substantive reuse of the data is expected to cite both the data package and the original publication from which it was derived."
The Open Data Commons Public Domain Dedication and Licence (PDDL) is similar to CC0, but is worded specifically in database terms. There is also the Open Data Commons Database Contents Licence (ODC-DbCL), which waives copyright for the contents of the database without affecting the copyright or database right of the database itself.
This very short (1:47) video from Ross Wilkinson at ANDS explains the relationship between data licensing and data integration. Ross gives the example of integrating climate change data from a variety of sources to develop a national park regime in North Queensland. Data integration enables powerful research - but without licences in place it could take a legal team years to work this out!
We acknowledge the Australian Aboriginal and Torres Strait Islander peoples as the first inhabitants of the nation and acknowledge Traditional Owners of the lands where our staff and students, live, learn and work.