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Wednesday, October 16 • 10:30am - 11:00am
Text and data mining big scholarly data

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Staff and students affiliated with a university can access and download all the research papers to which the institution subscribes, provided that they are logged in to that institution’s network. While readers can quite easily access research literature to which their university subscribes, it is not possible for text and data miners to do the same using machine access effectively and at scale. The current amendments and exceptions in UK copyright law have created new opportunities for those who conduct research or study in the UK, who are now able to text and data mine (TDM) content as long as they have lawful access to the resource and as long as it is for the purposes of non-commercial research. In this talk, eduTDM is proposed as a solution for how to deliver this content to text and data miners as easily as possible, based on the subscriptions to which they have access.

The proposed eduTDM architecture is inspired by eduroam, the widely popular solution for internet access across universities, which provides users a common platform for accessing the internet from a network of universities. We would like to propose the eduTDM framework as a one-point access platform for text and data miners to access content from multiple different publishers. In the eduTDM model, users can issue a single API call to obtain all documents matching their needs. This talk will describe the technical components of this work, the proposed design and how it compares with existing services, explaining how the model can support researchers in mining content from multiple publishers. We will also seek feedback from the publishers attending this conference on the technical and organisational challenges of this effort.

avatar for Nancy Pontika

Nancy Pontika

Open Science Advisor , CORE, KMi, The Open University

Wednesday October 16, 2019 10:30am - 11:00am BST
Presidents Room