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Montana State University Library (MSU Library) is the academic library of Montana State University, Montana's land-grant university, in Bozeman, Montana, United States. It is the flagship library for all of Montana State University System's campuses. In 1978, the library was named the Roland R. Renne Library to honor the sixth president of the university. The library supports the research and information needs of Montana's students, faculty, and the Montana Extension Service.
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Item Radical Collaboration: Making the Computational Turn in Special Collections and Archives(2019-11) Shanks, Justin D.; Mannheimer, Sara; Clark, Jason A.As more archival collections are digitized or born-digital, the work of archivists increasingly overlaps with the work of librarians who are responsible for research data and digital scholarship. This editorial uses Nancy McGovern's idea of radical collaboration as a framework, presenting a case study from Montana State University Library in which we collaborated across the domains of research data management, digital scholarship, archives, and special collections to integrate computational approaches into research, teaching, and service aspects of digital archival collections.Item A National Forum on Web Privacy and Web Analytics: Action Handbook(Montana State University, May 2019) Young, Scott W. H.; Clark, Jason A.; Mannheimer, Sara; Hinchliffe, Lisa JanickeThis is a practice-oriented action handbook that provides background, resources, and good practices to guide libraries in ethically implementing web analytics with a view towards privacy.This guide contains two main parts, followed by a references section. In Part 1, we detail technical strategies for implementing privacy-aware web analytics. In Part 2, we focus on communication strategies for building support for privacy-aware analytics practices.Item A Roadmap for Achieving Privacy in the Age of Analytics: A White Paper from A National Forum on Web Privacy and Web Analytics(Montana State University, May 2019) Young, Scott W. H.; Mannheimer, Sara; Clark, Jason A.; Hinchliffe, Lisa JanickeA National Forum on Web Privacy and Web Analytics is an IMLS-funded, community-fueled effort to shape a better analytics practice that protects our users’ privacy from unwanted third-party tracking and targeting. The main Forum event was held September 2018 in Bozeman, Montana, where 40 librarians, technologists, and privacy researchers collaborated in producing a practical roadmap for enhancing our analytics practice in support of privacy. Forum participants co-created eight Pathways to Action for enhancing web privacy. Forum activities also informed the development of an Action Handbook that contains practical skills and strategies for implementing privacy-oriented, ethical web analytics in libraries. This white paper provides an overview of the project, with a summary of the Pathways to Action and the Action Handbook. We present these resources to the wider community to remix, reuse, and apply towards action.Item The Open SESMO (Search Engine & Social Media Optimization) Project: Linked and Structured Data for Library Subscription Databases to Enable Web-scale Discovery in Search Engines(Taylor & Francis, 2017) Clark, Jason A.; Rossmann, DoralynToday's learners operate in digital environments which can be largely navigated with no human intervention. At the same time, libraries spend millions and millions of dollars to provide access to content which our users may never know is available to them. Through the Open SESMO (Search Engine & Social Media Optimization) database project, Montana State University (MSU) Library applied search engine optimization and structured data with the Schema.org vocabulary, linked data models and practices, and social media optimization techniques to all the library's subscribed databases. Our research shows that Open SESMO creates significant return-on-investment with substantial increased traffic to our paid resources by our users as evidenced through analytics and metrics. In the core research of the article, we take a quantitative look at the pre/post results to assess the Open SESMO method and its impact on organic search referrals and use of the collection analyzing data from three distinct fall semesters. Returns include demonstrated library value through database recommendations, connecting researchers to subject librarians, and increased visitation to our library's paid databases with growth in organic search referrals, impressions, and click-through rates. This project offers a standard and innovative practice for other libraries to employ in surfacing their paid databases to users through the open web by applying structured and linked data methods.Item Citations as Data: Harvesting the Scholarly Record of Your University to Enrich Institutional Knowledge and Support Research(2017-11) Sterman, Leila B.; Clark, Jason A.Many research libraries are looking for new ways to demonstrate value for their parent institutions. Metrics, assessment, and promotion of research continue to grow in importance, but they have not always fallen into the scope of services for the research library. Montana State University (MSU) Library recognized a need and interest to quantify the citation record and scholarly output of our university. With this vision in mind, we began positioning citation collection as the data engine that drives scholarly communication, deposits into our IR, and assessment of research activities. We envisioned a project that might: provide transparency around the acts of scholarship at our university; celebrate the research we produce; and build new relationships between our researchers. The result was our MSU Research Citation application (https://arc.lib.montana.edu/msu-researchcitations/) and our research publication promotion service (www.montana.edu/research/publications/). The application and accompanying services are predicated on the principle that each citation is a discrete data object that can be searched, browsed, exported, and reused. In this formulation, the records of our research publications are the data that can open up possibilities for new library projects and services.Item Montana State University Research Data Census Instrument, Version 2(Montana State University ScholarWorks, 2016-04) Clark, Jason A.; Llovet, Pol; Mannheimer, Sara; Sheehan, JerryMontana State University developed the Research Data Census (RDC) to engage our local research community in an interactive dialogue about their data. The research team was particularly interested in learning more about the following issues at Montana State: the size of research data; data storage needs; data sharing and publication behaviors; and interest in existing services that assist with the curation. Version 1 of the RDC (http://doi.org/10.15788/m2h59m) was distributed in January 2015. Version 2 was distributed in spring 2016.Item Montana State University Research Data Census Instrument, Version 1(2015-01) Arlitsch, Kenning; Clark, Jason A.; Hager, Ben; Heetderks, Thomas; Llovet, Pol; Mannheimer, Sara; Mazurie, Aurélien J.; Sheehan, Jerry; Sterman, Leila B.Montana State University developed the Research Data Census (RDC) to engage our local research community in an interactive dialogue about their data. The research team was particularly interested in learning more about the following issues at Montana State: the size of research data; the role the local and wide area network play in accessing and sharing resources; data sharing behaviors; interest in existing services that assist with the curation, storage, and publication of scientific data discoveries.Item Measuring Up: Assessing Accuracy of Reported Use and Impact of Digital Repositories(2014-02) Arlitsch, Kenning; OBrien, Patrick; Kyrillidou, Martha; Clark, Jason A.; Young, Scott W. H.; Mixter, Jeff; Chao, Zoe; Freels-Stendel, Brian; Stewart, CameronWe propose a research and outreach partnership that will address two issues related to more accurate assessment of digital collections and institutional repositories (IR). 1. Improve the accuracy and privacy of web analytics reporting on digital library use 2. Recommend an assessment framework and web metrics that will help evaluate digital library performance to eventually enable impact studies of IR on author citation rates and university rankings. Libraries routinely collect and report website and digital collection use statistics as part of their assessment and evaluation efforts. The numbers they collect are reported to the libraries’ own institutions, professional organizations, and/or funding agencies. Initial research by the proposed research team suggests the statistics in these reports can be grossly inaccurate, leading to a variance in numbers across the profession that makes it difficult to draw conclusions, build business cases, or engender trust. The inaccuracy runs in both directions, with under reporting numbers as much a problem as over reporting. The team is also concerned with the privacy issues inherent in the use of web analytics software and will recommend best practices to assure that user privacy is protected as much as possible while libraries gather data about use of digital repositories. Institutional Repositories have been in development for well over a decade, and many have accumulated significant mass. The business case for institutional repositories (IR) is built in part on the number of downloads of publications sustained by any individual IR. Yet, preliminary evidence demonstrates that PDF and other non-HTML file downloads in IR are often not counted because search engines like Google Scholar bypass the web analytics code that is supposed to record the download transaction. It has been theorized that Open Access IR can help increase author citation rates, which in turn may affect university rankings. However, no comprehensive studies currently exist to prove or disprove this theory. This may be due to the fact that such a study could take years to produce results due to the publication citation lifecycle and because few libraries have an assessment model in place that will help them to gather data over the long term. We plan to recommend an assessment framework that will help libraries collect data and understand root causes of unexplained errors in their web metrics. The recommendations will provide a foundation for reporting metrics relevant to outcomes based analysis and performance evaluation of digital collections and IR.Item Final Performance Report Narrative: Getting Found(2014-11) Arlitsch, Kenning; OBrien, Patrick; Godby, Jean; Mixter, Jeff; Clark, Jason A.; Young, Scott W. H.; Smith, Devon; Rossmann, Doralyn; Sterman, Leila B.; Tate, Angela; Hansen, Mary AnneThe research we proposed to IMLS in 2011 was prompted by a realization that the digital library at the University of Utah was suffering from low visitation and use. We knew that we had a problem with low visibility on the Web because search engines such as Google were not harvesting and indexing our digitized objects, but we had only a limited understanding of the reasons. We had also done enough quantitative surveys of other digital libraries to know that many libraries were suffering from this problem. IMLS funding helped us understand the reasons why library digital repositories weren’t being harvested and indexed. Thanks to IMLS funding of considerable research and application of better practices we were able to dramatically improve the indexing ratios of Utah’s digital objects in Google, and consequently the numbers of visitors to the digital collections increased. In presentations and publications we shared the practices that led to our accomplishments at Utah. The first year of the grant focused on what the research team has come to call “traditional search engine optimization,” and most of this work was carried out at the University of Utah. The final two years of the grant were conducted at Montana State University after the PI was appointed as dean of the library there. These latter two years moved more toward “Semantic Web optimization,” which includes areas of research in semantic identity, data modeling, analytics and social media optimizationItem Demonstrating library value at network scale: leveraging the Semantic Web with new knowledge work(Routledge, 2014-08) Arlitsch, Kenning; OBrien, Patrick; Clark, Jason A.; Young, Scott W. H.; Rossmann, DoralynLibrarians may enjoy new roles as trusted facilitators who can develop effective and replicable optimization services by delivering measurable value based on metrics that matter to each organization’s leadership. The Montana State University (MSU) Library is engaged in Semantic Web research on several fronts, which we will describe in this article. Our concept of “new knowledge work” encompasses the discoverability, accessibility, and usability of content and services in the Semantic Web. In this article, we survey the following new services that libraries can offer their users and campus partners to aid discovery and understanding of resources at the network scale: 1. Establishing semantic identity for content and entities. 2. Structuring metadata for machine ingest and leveraging external search mechanisms. 3. Centralizing management of faculty activity data for efficient population of Institutional Repository (IR) and other reporting outlets. 4. Developing programmatic social media strategies to connect communities and content. 5. Advancing the role of the library as publisher to include the creation of open extensible book softw