What’s newat OCLC Research

Two current projects represent OCLC’s ongoing collective collection efforts:

• Stewarding the Collective Collection: Exploratory Data Analysis—A collaborative project between OCLC and The Partnership for Shared Book Collections has examined the nature of retention commitments currently registered in WorldCat. The findings from this research have been published in the report Stewarding the Collective Collection: An Analysis of Print Retention Data in the US and Canada.
• Stewarding the Collective Collection: Data and Tools for Shared Print Workflows—A project investigating the data and tools used and needed to support stewardship of and access to monographic shared collections.

OCLC Research partnered with two Dutch library consortia to investigate how libraries can improve the discoverability of scholarly, peer-reviewed open access (OA) publications for their communities. The research team asked staff at seven Dutch academic libraries what they were doing to support OA discovery and surveyed their user communities about their experiences with scholarly, peer-reviewed publications and OA.

The resulting research report, Improving Open Access Discovery for Academic Library Users, identifies strategies for making OA publications more discoverable for library users. The findings can serve as a catalyst for academic libraries worldwide to engage in meaningful conversations about enhancing OA discoverability given local contexts and user needs.

Academic libraries increasingly collaborate with other campus units to provide an expanding array of services in support of the university research enterprise. These cross-campus partnerships represent a range of emerging operational models that facilitate library engagement with other campus units to support institutional research priorities. They also suggest a need for clear articulations of the library value proposition as academic libraries project their skills, expertise, services, and roles beyond the library into the broader campus environment through new research support responsibilities and partners. We call this idea the “library beyond the library.”

Libraries have a rich history of working together to meet mutual needs. Current advances in digital and network technologies have amplified the benefits and lowered the costs of cross-institutional collaboration, making it an inviting choice for academic libraries seeking to acquire new services, expertise, and infrastructure. As interest in library collaboration grows, it becomes more important for academic libraries to be purposeful and strategic in their use of this sourcing option.

These two thematically linked reports explore library collaboration from both theoretical and practical perspectives, and   will be of special interest to senior academic library leadership, library consortia/group leadership, and academic library staff responsible for managing collaborative relationships.

The Operationalizing the Art Research Collective Collection project investigated challenges faced by art research collections by exploring opportunities for collaboration between art, academic, and independent research libraries. The project was designed to identify new possibilities for collaboration and partnership models that support sustainable, ongoing availability of rich collections of art libraries to researchers, wherever they may be.

The project outcomes are shared in two reports:

• Sustaining Art Research Collections: Using Data to Explore Collaboration—Models how quantitative analysis of library collection and activity data can be leveraged by library leaders to inform decisions about collaboration opportunities supporting art research collections.
• Sustaining Art Research Collections: Case Studies in Collaboration—Shares recommendations for building successful collaborations and identifies typical challenges library partnerships navigate based on case study research of current library collaborations. 

• Transitioning to the Next Generation of Metadata: Traces how metadata is evolving and considers the impact this transition may have on library services.
• Transforming Metadata into Linked Data: Shares project findings where OCLC and five partner institutions investigated methods for—and the feasibility of—transforming metadata into linked data to improve the discoverability and management of digitized cultural materials using CONTENTdm.
• Reimagine Descriptive Workflows: Contextualizes the challenges facing the library and information field in inclusive and reparative metadata work and offers a framework of guidance that can help frame institutions’ local priorities and areas for change.

Working in consultation with Shift Collective, OCLC hosted a conversation among community stakeholders who discussed how to address the systemic issues of bias and inequity within our current collection description infrastructure. The input from the convening, shaped by substantive input from advisory group leaders was published in the report Reimagine Descriptive Workflows: A Community-informed Agenda for Reparative and Inclusive Descriptive Practice that provides two action pathways:

• A guiding framework for making necessary, fundamental shifts both in organizational culture and individual mindset to enact transformative and sustainable change in the descriptive process.
• Recommendations for operational changes that organizations can make to reimagine descriptive practices in their local and global contexts.

OCLC published five reports on its research findings:

• Summary of Research—Synthesizes findings from across all research activities on the NAFAN project
• Pop-up Survey—Summarizes results from a national survey of online archive users on their search behavior, information needs, and demographic characteristics
• User Interviews—Details findings from interviews with archival aggregation end users on their information needs and information-seeking behavior
• Focus Group Interviews—Shares outcomes from discussions with archivists about their needs for describing collections and contributing description to an archival aggregation
• EAD Analysis—Analyzes EAD data as raw material for building a finding aid aggregation by looking for common data structures present and identifying gaps that could impede user discovery