Legal reform to enhance global text and data mining research

Fiil-Flynn, Sean M; Butler, Brandon; Carroll, Michael W.; Cohen-Sasson, Or; Craig, Carys J.; Guibault, Lucie; Jaszi, Peter; Jütte, Bernd Justin; Katz, Ariel; Quintais, João Pedro; Margoni, Thomas; Souza, Allan Rocha de; Sag, Matthew; Samberg, Rachael; Schirru, Luca; Senftleben, Martin; Tur-Sinai, Ofer; Contreras, Jorge L.

doi:10.1126/science.add6124

Cited by 19 publications

(12 citation statements)

References 4 publications

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“…While underlying algorithms and applications are used globally, important differences exist across jurisdictions with respect to copyright exceptions for research and data mining (Fiil-Flynn et al, 2022). These differences, however, may create quasi-experimental settings that let researchers study how more or less restrictive copyright systems causally affect innovation in AI and data-driven and AI-enabled innovation.…”

Section: Algorithmic Licensing and Blockchain Technologymentioning

confidence: 99%

The economics of copyright in the digital age

Peukert,

Windisch

2024

Journal of Economic Surveys

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Intellectual property rights are fundamental to how economies organize innovation and steer the diffusion of knowledge. Copyright law, in particular, has developed constantly to keep up with emerging technologies and the interests of creators, consumers, and intermediaries of the different creative industries. We provide a synthesis of the literature on the law and economics of copyright in the digital age, with a particular focus on the available empirical evidence. First, we discuss the legal foundations of the copyright system and developments of length and scope throughout the era of digitization. Second, we review the literature on technological change with its opportunities and challenges for the stakeholders involved. We give special attention to empirical evidence on online copyright enforcement, changes in the supply of works due to digital technology, and the importance of creative re‐use and new licensing and business models. We then set out avenues for further research identifying critical gaps in the literature regarding the scope of empirical copyright research, the effects of technology that enables algorithmic licensing, and copyright issues related to software, data and artificial intelligence.

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Section: Algorithmic Licensing and Blockchain Technologymentioning

confidence: 99%

The economics of copyright in the digital age

Peukert,

Windisch

2024

Journal of Economic Surveys

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“…However, not all meta-data can openly be shared because abstracts might fall under the strict copyright of the publisher, which limits the application of global text and data mining research [40]. Until publishers adhere to the plea for releasing such restrictions, we propose storing a list of persistent digital object identifiers, like the DOIs.…”

Section: Input Datamentioning

confidence: 99%

Reproducibility and Data storage Checklist for Active Learning-Aided Systematic Reviews

Lombaers¹,

Bruin²,

Schoot³

2023

Preprint

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In the screening phase of a systematic review, screening prioritization via active learning effectively reduces the workload. However, the PRISMA guidelines are not sufficient for reporting the screening phase in a reproducible manner. Text screening with active learning is an iterative process, but the labeling decisions and the training of the active learning model can happen independently of each other in time. So it is not trivial to store the data from both events so that you can still know which iteration of the model was used for each labeling decision. Moreover, many iterations of the active learning model will be trained throughout the screening process, producing an enormous amount of data (think of many gigabytes or even terabytes of data), and machine learning models are continually becoming larger. Together this can add up to an undesirable amount of data when naively storing all the data produced at every iteration of the active learning pipeline. This article clarifies the steps in an active learning-aided screening process and what data is produced at every step. We show how this data can be stored efficiently in terms of size. Most notably, the data produced by the model is where we need to strike a balance between reproducibility and storage size. Finally, we created the RDAL-Checklist (Reproducibility and Data storage for Active Learning-aided systematic reviews – checklist) that helps users and creators of active learning software make their screening process reproducible.

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“…Copyright laws in many other countries include exceptions for research or scientific uses; as a group of global scholars wrote in December 2022, these exceptions may be interpreted to apply to text and data mining research, or TDM. 8 According to the scholars, "TDM is a crucial first step to many machine learning, digital humanities, and social science applications, addressing some of the world's greatest scientific and societal challenges, from predicting and tracking COV-ID-19 to battling hate speech and disinformation." The Authors Guild v. HathiTrust case mentioned above upheld TDM research as an exercise of fair use rights under US copyright law.…”

Section: Researchmentioning

confidence: 99%

Protecting library rights: Considerations for Congress

Klosek

2023

CRLN

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T he US Congress granted libraries special rights through limitations and exceptions in the US Copyright Act, but there is nothing to stop private contracts from contravening these rights and conflicting with the public policy objectives that Congress intended. This article suggests approaches that the US Congress may take to protect library rights, including revisiting a 2002 legislative proposal by Representative Zoe Lofgren.

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Legal reform to enhance global text and data mining research

Abstract: Outdated copyright laws around the world hinder research

Cited by 19 publications

References 4 publications

The economics of copyright in the digital age

The economics of copyright in the digital age

Reproducibility and Data storage Checklist for Active Learning-Aided Systematic Reviews

Protecting library rights: Considerations for Congress

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