Computational Access and Use of Texts and Data behind Paywalls: Challenges and Resources 

The rise of applied data science, digital humanities, machine learning, and artificial intelligence has resulted in an increased need for computational access and reuse of research data and publications, many of which are only available behind paywalls and governed by restrictive terms of use. What can you do with proprietary sources, how do you gain access, and how can you make your own research output from such sources shareable are questions that many are asking. Join three experts from the MIT Libraries in this session to learn about the copyright and contractual implications of paywalled data sources and how you can use them and share your results.

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