Day/Time: May 15, 2024, 10:15 a.m. to 11:15 a.m.

Title: Author Name Removed at Request of Original Publisher”: an OER Adventure


  • Nancy Sims, any pronouns, Director, Copyright & Scholarly Communication, University of Minnesota Libraries
  • Shane Nackerud (he/him) Director, Affordable Learning and Open Education (ALOE), University of Minnesota Libraries

Description: The University of Minnesota Libraries updated and republished numerous open textbooks starting about a decade ago. The publisher of those books changed their business model, and stopped offering their own copies with open licenses. Although the original open license remained valid, specific elements of the older Creative Commons license they used did enable them to require removal of all attribution on the books. As the books aged, we considered updating them, but decided against it based on this complex history of interaction. In this brief session, we will share more details of this history, our decision-making about these books, and we will discuss open licensing and OER sustainability in general.

Title: Rights Reversion to OER: Four Stories from the Field

Presenter: Anita Walz, Assistant Director of Open Education and Scholarly Communication Librarian, Virginia Tech

Description: Rights-reversion is a powerful tool for broadening access to books which are still-in-demand but paywalled or out-of-print. Converting these works to Open Educational Resources (OER) broadens their availability and meets reader and instructional needs while utilizing workflows and services most library publishers already have in place. This presentation presents stories of four different rights-reverted works, project rationale, processes, lessons learned, and current outcomes. Due to existing “good customer” relationships with commercial publishers, Library Publishers may have more leverage than we realize to release valuable content more openly. Titles to be discussed are all textbooks used for instruction and include: Veterinary Epidemiology, Construction Contracting 2nd edition, Radio Systems Engineering, and Composite Construction: Design for Buildings.

Title: Not Your Grandfather’s Statistics Textbook: W&M’s Library Faculty Scholar Program Supports Publishing Open Access Monographs, A Case Study

Presenter: Rosie Liljenquist, William & Mary

Description: William & Mary Libraries created the Faculty Scholar position in 2016 to support tenured faculty working full-time to advance a digital project while furthering library and institutional initiatives. The Faculty Scholar works closely with library staff on new or existing research and making it openly accessible. W&M Libraries believes access to information is a human right. We advocate to remove barriers to information and create pathways to discovery. Dr. Lawrence Leemis was selected as the 2019 Faculty Scholar. His textbook Statistical Modeling: Regression, Survival Analysis, and Time-Series Analysis was openly published in Summer 2023 with the purpose of enabling a single-semester (post-calculus) class to survey these three important topics.

Dr. Leemis is no stranger to publishing – he has seven textbooks under his belt – however, this is his first experience publishing with open access principles in mind. Creating open access content takes a significant amount of time and requires additional support in areas of copyright law, preservation, and access. Through the Library Faculty Scholar Program, Dr. Leemis was able to dedicate his time and receive the expertise necessary to create and complete an open access textbook.

Dr. Leemis wanted to create this upper-division statistics textbook to support students pursuing majors and careers that require advanced statistical and mathematical courses. For many years, the price of textbooks has exceeded national inflation, making the purchase of course materials a burden for many college students and their parents. STEM textbooks tend to have higher purchase costs than their humanities counterparts.Furthermore, since there are three important topics surveyed in the work (regression, survival analysis, and time-series analysis), it lends itself to adapting the work for the specific content choosing one or two sections. Publishing OA allows the work to be widely distributed and contributes significantly to the field.