Text & Data Mining LibGuide

We are keen to help the research process where we may be able to make a contribution towards facilitating text & data mining in the University.  To that end we offer a new LibGuide on text & data mining in the growing number of guides in the Cambridge Libraries’ family of LibGuides.

The aim of this guide is to make a start towards exposing the breadth of content (mostly library-subscribed) that may be of potential exploitation by Cambridge researchers wanting to use the techniques of text and data mining in their research.  The guide summarizes the main points in the Hargreaves exception and builds on and links out to professional bodies and information sources to provide librarians and University members with a beginner’s guide to first steps in TDM and considerations it is important to make.

The guide provides a means of contacting us to clear any issues that may arise with site access when TDM is performed on publisher content, as appropriate to researchers’ rights and needs.  As everyone acknowledges, these are still early days in experience with the exception and so we hope and expect the guide to develop with your feedback and grow to become more useful over time. Just now the emphasis of the guide is more on the side of supply of library provided content for mining, and how we can help with that.  In the University the Research Data Management website and the Office of Scholarly Communication have the expertise to support researchers more broadly in their wider remits and maintain resources to support every stage of a research project.

As we’re releasing this guide with Wimbledon in full swing, we thought a visualization from Tableau – the tool to inspire colleagues with the findings and insights from analysis on big data – of the genius that is Roger Federer might be pertinent …


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