UC San Diego Library

In 2009, the original Blueprint for the Digital University set the stage for UC San Diego’s many accomplishments in cyberinfrastructure over the following decade. Many contemporary services and infrastructure used across campus have their origins in this document and subsequent projects. But research evolves, new needs arise, and new requirements are placed on researchers. Thus, campus leadership recognized the need for a new, updated Blueprint, helping point the way to the next generation of support.

To compile this new Blueprint, the Research Computing and Data Services Governance Committee engaged in a multi-year process to obtain expert input into the future of research and research technology, including consulting a faculty advisory group, surveying campus faculty, engaging in in-depth interviews with UC San Diego administrators such as the Executive Vice Chancellor and Vice Chancellor for Research, and conducting faculty focus groups.

This document outlines the priorities and directions our University must take to maximize new discoveries, increase funding, facilitate science, comply with regulatory demands and propel us forward in the decade to come.

The themes described in this document come from trends in research processes and workflow, and are not specific to UC San Diego. This document is being shared publicly with the hope that it will be of assistance to other institutions facing similar generational evolution in both the conduct of research and in their research support infrastructure.

During Winter 2020 - Summer 2021, the UC San Diego Library participated in the Ithaka S+R multi-institutional research study “Supporting Big Data Research”. The purpose of this study was to learn more about how researchers on the UC San Diego campus work with big data in their research and provide a set of recommendations to enhance and develop resources and services that will directly support and benefit this research. While definitions of “big data” may vary by discipline, we use the term here to refer to datasets large enough to be challenging to analyze within a traditional spreadsheet, or on a single computer. 

In-depth interviews with twelve UC San Diego big data researchers of various academic ranks and departmental affiliations were conducted, with questions focusing on various aspects of collecting and analyzing big data, infrastructure needs, research communication and data sharing, and training and support needs. Based on these interviews, we identify three primary themes for big data researchers on the UC San Diego campus: Curation, Open Science, and Training. For each of these areas, we offer a set of recommendations for the campus to better support existing big data research at UC San Diego, as well as develop capacity to support future big data initiatives.

The University of California, San Diego is accredited by the Western Association of Schools and Colleges (WASC) Senior College and University Commission (WSCUC), and was undergoing review to reaffirm accreditation during the library’s rubric project. Since the university’s previous review in 2010, WSCUC has introduced information literacy as a core competency to be included in “an integrated course of study of sufficient breadth and depth to prepare…[students] for work, citizenship, and life-long learning” (WSCUC, 2013). Additionally, “for each core competency, the institution may set a specific level of performance expected at graduation and gather evidence of the achievement of that level of performance (which can be based on sampling) using the assessment methods of its choice” (WSCUC, 2013). Information literacy instruction and assessment has long been at the core of academic library services, so it made sense for the library to partner with campus to help set the standard of performance expected of undergraduate students for information literacy.

Within the same 2010-2020 timeframe, the Association of College and Research Libraries (ACRL) replaced their long-standing Information Literacy Competency Standards for Higher Education (2000) with the Framework for Information Literacy for Higher Education (2016). However, the WSCUC’s 2013 handbook mentions the use of Association of Colleges & Universities (AAC&U) VALUE rubrics, and the Information Literacy VALUE Rubric (n.d.) is based on the now-outdated ACRL Standards. Therefore, UC San Diego librarians needed to find a way to align the new accreditation core competencies with their new professional standards. To do so, a library task force combined the two documents by mapping the ACRL Framework onto the existing structure of the AAC&U rubric. However, there were several aspects of the ACRL Framework that did not directly relate to the AAC&U rubric, so the task force made two significant additions: 1) when the knowledge practices or dispositions described in the ACRL Framework were more basic or foundational than the “Benchmark” (i.e., scoring a 1) category on the rubric, the task force included the additional column of “Foundation” (i.e., scoring a 0) to indicate that without this fundamental knowledge, a learner would have difficulty reaching the “Benchmark,” and 2) when the knowledge practices or dispositions described in the ACRL Framework did not fit into the pre-existing rubric rows (i.e., labelled with the ACRL Standards), the task force found that adding the row “Understand How Information is Organized” would encapsulate the remaining, uncategorized knowledge practices and dispositions of the ACRL Framework.

The UC San Diego Library’s ultimate goal for this combined rubric is to provide the foundation for creating an in-house online database that instruction librarians can use to create appropriate information literacy learning outcomes for their workshops or courses, paving the way for designing deep learning and creating appropriate formative and summative assessments.

This paper presents the results of a preliminary study designed to examine the feasibility of conducting research into the learning outcomes associated with research consultation between reference librarians and university students. The researcher studied the teaching taking place at an academic library reference desk and assessed the student’s ability to apply what was taught to a new information need. The results indicate that participant awareness of library resources increased and their skill in searching online databases improved. Although participants demonstrated greater skill in identifying and obtaining useful information, they were unable to demonstrate an increased ability to assess the quality of the information acquired. The paper demonstrated that it is both possible and useful to assess the learning taking place at academic library reference desks.

Consolidation of journal publishers and declining library budgets has resulted in conflicts between academic libraries over price and access. Several conflict theories, including conflict spiral, power dependence, and game theory can be used to explain how this relationship developed and possible approaches to improving a libraries position.

This report provides the rationale and design for a campus‐wide research cyberinfrastructure (RCI) that will meet federal mandates for research data preservation, improve UCSD’s academic competitiveness, and achieve economies‐of‐scale savings through centralization of core infrastructure elements, while at the same time recognizing the diverse and distributed nature of UCSD’s research enterprise.

Informed by a campus survey conducted in 2008, as well as a number of case studies analyzed by the Research Cyberinfrastructure Design Team (RCIDT), our design focuses primarily (but not exclusively) on digital data. Driven by proliferating high throughput instruments, wireless sensor nets, and supercomputer simulations, the amount of digital data at the heart of the modern research enterprise is growing exponentially at UCSD and around the world. Our proposed data‐centric RCI will not only allow us to cope with the data deluge, it will position UCSD to prosper from it, and become an international leader and innovator in this area.

This report describes efforts  to advance and stabilize the intrastructure for a shared cataloging utility for art images by developing a set of production-quality tools that operate on a large, standardized set of legacy metadata.

This report describes the work done to build a prototype for a union catalog of art images as a proof-of-concept that it is technically possible to create such a union database.