Legal Literacies for Text Data Mining – Cross-Border (“LLTDM-X”): White Paper

Legal Literacies for Text Data Mining - Cross-Border (“LLTDM-X”) is a National Endowment for the Humanities Level 1 Advancement Grant project addressing legal and ethical issues faced by U.S. digital humanities (DH) practitioners whose text data mining (TDM) research and practice intersects with foreign-held or - licensed content, or involves international cooperations.LLTDM-X ​​is a collaboration between the University of California Berkeley Library and Internet Archive, and builds upon the previous NEH-sponsored institute, Building Legal Literacies for Text Data Mining (Building LLTDM). That institute provided guidance and strategies to DH TDM researchers on navigating legal literacies for text data mining (including copyright, contracts, privacy, and ethics) within a U.S. context.A common challenge highlighted during Building LLTDM was the fact that TDM practitioners encounter numerous and complex legal problems in cross-border TDM research. These occur when: (i) the materials practitioners want to mine are housed in a foreign jurisdiction, or are otherwise subject to foreign database licensing or laws; (ii) the human subjects they are studying or who created the underlying content reside in another country; or, (iii) the colleagues with whom they are collaborating reside abroad, yielding uncertainty about which country’s laws, agreements, and policies apply.We designed LLTDM-X to identify and better understand the cross-border issues that DH TDM practitioners face, with the aim of using these issues to inform prospective research and education. We also hoped that LLTDM-X would yield preliminary guidance to benefit researchers in the meantime, as instructional materials are being developed. In early 2023, we hosted a series of three online round tables with U.S.-based cross-border TDM practitioners (“Practitioners”), and law and ethics experts (“Experts”) practicing in six countries. The round table conversations were structured to illustrate the empirical issues