In this paper, I outline the drawbacks with the two main behavioral approaches to animal behavior problems and argue that each alone is insufficient to underpin a field of clinical animal behavior. Applied ethology offers an interest in an animal’s spontaneous behavior in natural contexts, understood within an ecological and evolutionary context, but lacks an awareness of mechanisms that can be manipulated to modify the behavior of individual animals. Behaviorism in the form of Applied Behavior Analysis offers a toolkit of techniques for modifying the behavior of individual animals, but has seldom been applied to non-human species, and often overlooks phylogenetic aspects of behavior. Notwithstanding the historical animosities between the two fields of animal behavior they are philosophically highly compatible – both being empiricist schools stemming ultimately from Darwin’s insights. Though each individually is incomplete, I argue that an integrated approach that synthesizes the strengths of each holds great promise in helping the many animals who need our assistance to survive and thrive in human-dominated environments.

The relative importance of adaptation and individual ontogenetic experience in dogs' high levels of behavioral compatibility with humans has been a topic of intense scientific attention over the past two decades. Salomons et al. Current Biology, 31, 3137-3144, (2021) recently presented a particularly rich data set of observations on both wolf and dog puppies that has the potential to contribute substantially to this debate. In their study subjecting wolf and dog puppies to batteries of tests, including the ability to follow human pointing gestures, Salomons et al. (2021) reported that dogs, but not wolves, have a specialized innate capacity for cooperation with humans. However, upon reanalyzing this data set, we reach a different conclusion-namely, that when controlling adequately for various environmental factors, wolves and dogs perform similarly in their cooperation with humans.

A two-part presentation from the ASU Library and Knowledge Enterprise Research Data Management Office. Presented at the 2023 Rocky Mountain Advanced Computing Consortium (RMACC).

Session 1: Data management planning is an integral step in the research data life cycle. Large amounts of data and lengthy code accompanying supercomputing runs are no exception. Planning before analysis will benefit research and the researcher by providing a clear strategy for collecting, storing, analyzing, and sharing the data at the end of the research cycle. Supercomputing can require significant storage beyond scratch space, but researchers typically need to be informed of what tools are appropriate and available. Framed within the planning phase of the life cycle, this presentation presents ASU’s Storage Selector as a quick and easy tool to find the most appropriate storage resources provided by the university to help researchers choose a proper storage and management solution for their research data at the right time in their project. We will also explore the DMP Tool, developed by the California Digital Library, which provides a resource-rich platform for writing data management plans, including institutional-specific guidance, feedback request, and public plans that can be used as guides.

Session 2: This presentation overviews the ongoing working relationship between the ASU Library Open Science and Scholarly Communication division, Research Data Management Office, and Research Computing. We will explore these teams’ interdisciplinary relationships and interdependence as the institution increasingly supports open science practices and initiatives. We will include case studies regarding the decision-making process, data-sharing decisions, and opportunities and challenges when transferring research data from a high-performance computing environment to the ASU Research Data Repository. Finally, we will share lessons learned as we intentionally shepherd research data from active project management and storage to final publication and preservation.

In this case study, we reflect on our journey through a major revision of our streaming video reserve guidelines, informed by an environmental scan of comparable library services and current copyright best practices. Once the guidelines were revised, we developed an implementation plan for communicating changes and developing training materials to both instructors and internal library staff. We share our navigation strategies, obstacles faced, lessons learned, and ongoing challenges. Finally, we map out some of our future directions for improving and streamlining our services.

Although they have distinct missions, public libraries and academic libraries serve overlapping populations and can leverage their institutional strengths through collaboration. These diverse partnerships include sharing resources through consortia, joint-use libraries, and shared programming, such as introducing students to public library collections as resources for theses. For the scholarly communication librarian, collaborating with public libraries provides opportunities to educate about the ethical and legal use of information, advocate for the promotion and use of open resources and pedagogies, and interact with communities, particularly in rural areas, that are traditionally underserved by academic libraries. We’ll share two personal examples of the intersection between scholarly communication and public libraries.

The Mixtec pictorial manuscript, now known as the Codex Tonindeye, was stolen from an Italian monastery library in 1859. Several decades later, the Mexican American anthropologist Zelia Nuttall located the document after many years of searching. Determined to reinstate its historical identity, Nuttall closely studied the codex and reproduced it in a lush facsimile; it was named the Codex Nuttall (1902) in her honor. Using Nuttall’s correspondence with her publishers at the Peabody Museum, this article investigates the role of archives and museums in nineteenth-century textual scholarship, explores how Nuttall relocated the codex and labored over creating the facsimile, and addresses the ongoing importance of the document.

In summer 2024, as part of Arizona State University’s collaboration with OpenAI, the ASU Library launched a pilot project using the AI tool ChatGPT. This project aims to enhance the discoverability and curation of digital collections within the library’s repository ecosystem. The use of AI in libraries is gaining attention, with many institutions exploring AI for generating descriptive metadata. ASU Library’s extensive repository platforms, including an institutional repository, data repository, and a digital collections platform, hold approximately over 10,000 objects, with numbers expected to grow. The library lacks a dedicated position for creating metadata, with the responsibility distributed among various units already tasked with other duties. This project aims to determine whether ChatGPT can effectively generate accurate metadata that meets best practices. The library will use an existing archival collection of government documents, which already has human-created metadata, as a benchmark, in comparing the generated metadata for the fields Title, Description, and Keywords. By comparing ChatGPT-generated metadata to the existing metadata, the library will assess the relevance of AI outputs and the level of oversight required. If the AI-generated metadata shows minimal variance from the human-created metadata, the workflow could expand to other collections and reduce the backlog of unpublished archival collections that require descriptive metadata.