Megan Senseney et al. Transforming Library Services for Computational Research with Text Data. Chicago, IL: Association of College and Research Libraries, 2021.

This white paper has sought to explore the issues and challenges associated with the legal, social and technical aspects of conducting computational research with text data from the perspective of academic librarians.

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Go to the profile of Pablo Markin
almost 3 years ago

Open Access to monographs, collected volumes and articles also prospectively promotes the data mining of their text contents, as it removes the copyright concerns that closed access involves. Conversely, academic libraries need to negotiate data mining access to closed access databases, which can be a protracted, case-by-case process. Thus, as Open Access takes hold via community standards for data sharing, code deposition and open source software, as part of increasing the transparency of scholarly research, closed access frameworks are likely to come under an increasing pressure to develop alternative arrangements for data processing. Yet, as the authors of this publication note, Creative Commons licensing, on which Open Access largely relies, can be complex to handle in the context of private-public partnerships or publisher-side commercial reuse alongside author-side copyright retention. Likewise, even though Open Access encompasses the data-related principles of findability, accessibility, interoperability and reproducibility (FAIR), intellectual property rights are governed by geography-bound copyright legislation, the harmonization of which is likely to require the development of international data processing standards.