Data mining is the use of computational techniques to find patterns or relationships within large sets of organised or "structured" data.
Text analysis is similar to data mining, but uses large collections of text or "unstructured data" to identify patterns or connections.
For more detail, see the definitions set out by the Australian Law Reform Commission:
There are a number of factors to be aware of when conducting data mining and text analysis.
See this ARDC guide below for an overview, and check the resources available below for questions of Copyright, Licencing and Permissions.
There is no Australian copyright exemption for text and data analysis, as explained in this Australian Law Reform Commission discussion paper. Even publicly accessible arrangements of datasets are still protected by copyright and may require permission for use in a text analysis or data mining project.
Data and database publishers vary widely in the degree to which they permit text and data mining of their collections. First consult the licence in the LibrarySearch record for the database, as illustrated in the image below:
If the Show License option does not appear, or if the information does not mention data mining, contact the Library Research support team.
The Australian Research Data Commons has two easy-to-follow flowcharts that illustrate the licencing process.
For some data, you may need to acquire special permission from the rightsholder before performing analysis on datasets.
Be aware that if you are granted permission to use data for your research, this may not extend to use for publication. It is easier to seek permission for all uses of the data upfront.
For tips on permission seeking for researchers, please see the Copyright guide section for researchers.
Even when access is permitted, in performing text and data mining, it is important that researchers respect the rights of the owners of the content, and abide by their terms of the access. Researchers also need to respect the privacy of the subjects of research, and be aware that data mining may reveal confidential details. Information on the responsibilities of researchers can be found on this page on Academic Integrity.
Access to ProQuest TDM Studio
Log in using an existing Proquest profile account if you have one.
Log in using an existing My Research account or TDM Studio Visualization account if you've registered before.
Otherwise, here is how to create a password for your account