Search

This paper examines the decision points over the course of ten years of development of an institutional repository. Specifically, the focus is on the impact and influence from the open-source community, the needs of the local institution, the role that team dynamics plays, and the chosen platform. Frequently, the discussion revolves around the technology stack and its limitations and capabilities. Inherently, any technology will have several features and limitations, and these are important in determining a solution that will work for your institution. However, the people running the system and developing the software, and their enthusiasm to continue work within the existing software environment in order to provide features for your campus and the larger open-source community, will play a bigger role than the technical platform. These lenses are analyzed through three points in time: the initial roll out of our institutional repository, our long-term running and maintenance, and eventual new development and why we made the decisions we made at each of those points in time. [ABSTRACT FROM AUTHOR]

University libraries provide access to thousands of online journals and other content, spending millions of dollars annually on these electronic resources. Providing access to these online resources is costly, and it is difficult both to analyze the value of this content to the institution and to discern those journals that comparatively provide more value. In this research, we examine 1,510 journals from a large research university library, representing more than 40% of the university's annual subscription cost for electronic resources at the time of the study. We utilize a web analytics approach for the creation of a linear regression model to predict usage among these journals. We categorize metrics into two classes: global (journal focused) and local (institution dependent). Using 275 journals for our training set, our analysis shows that a combination of global and local metrics creates the strongest model for predicting full-text downloads. Our linear regression model has an accuracy of more than 80% in predicting downloads for the 1,235 journals in our test set. The implications of the findings are that university libraries that use local metrics have better insight into the value of a journal and therefore more efficient cost content management. [ABSTRACT FROM AUTHOR]

Academic libraries are often called upon by their university communities to collect, manage, and curate information about the research activity produced at their campuses. Proper research information management (RIM) can be leveraged for multiple institutional contexts, including networking, reporting activities, building faculty profiles, and supporting the reputation management of the institution. In the last ten to fifteen years the adoption and implementation of RIM infrastructure has become widespread throughout the academic world. Approaches to developing and implementing this infrastructure have varied, from commercial and open-source options to locally developed instances. Each piece of infrastructure has its own functionality, features, and metadata sources. There is no single application or data source to meet all the needs of these varying pieces of research information, many of these systems together create an ecosystem to provide for the diverse set of needs and contexts. This paper examines the systems at Pennsylvania State University that contribute to our RIM ecosystem; how and why we developed another piece of supporting infrastructure for our Open Access policy and the successes and challenges of this work. [ABSTRACT FROM AUTHOR]