Scholarly Work - Library
Permanent URI for this collectionhttps://scholarworks.montana.edu/handle/1/320
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Item Data-Driven Improvement to Institutional Repository Discoverability and Use(Institute of Museum and Library Services, 2018-09) Arlitsch, Kenning; Kahanda, Indika; OBrien, Patrick; Shanks, Justin D.; Wheeler, JonathanThe Montana State University (MSU) Library, in partnership with the MSU School of Computing, the University of New Mexico Library and DuraSpace, seeks a $49,998 Planning Grant from the Institute of Museum and Library Services through its National Leadership Grant program under its National Digital Platform project category to develop a sustainability plan for the Repositories Analytics & Metrics Portal that will keep its dataset open and available to all researchers. The proposal also includes developing a preliminary institutional repositories (IR) reporting model; a search engine optimization (SEO) audit and remediation plan for IR; and exploring whether machine learning can improve the quality of IR content metadata.The project team expects work conducted in this planning grant to make the case for advanced research projects that will be high-impact and worthy of funding.Item Protecting privacy on the web: A study of HTTPS and Google Analytics(Emerald, 2018-09) OBrien, Patrick; Young, Scott W. H.; Arlitsch, Kenning; Benedict, KarlThe purpose of this paper is to examine the extent to which HTTPS encryption and Google Analytics services have been implemented on academic library websites and to discuss the privacy implications of free services that introduce web tracking of users. The home pages of 279 academic libraries were analyzed for the presence of HTTPS, Google Analytics services and privacy-protection features. Results indicate that HTTPS implementation on library websites is not widespread, and many libraries continue to offer non-secured connections without an automatically enforced redirect to a secure connection. Furthermore, a large majority of library websites included in the study have implemented Google Analytics and/or Google Tag Manager, yet only very few connect securely to Google via HTTPS or have implemented Google Analytics IP anonymization. Librarians are encouraged to increase awareness of this issue and take concerted and coherent action across five interrelated areas: implementing secure web protocols (HTTPS), user education, privacy policies, informed consent and risk/benefit analyses.Item Wikipedia and Wikidata Help Search Engines Understand Your Organization: Using Semantic Web Identity to Improve Recognition and Drive Traffic(ALA Editions, the American Library Association, 2018) Arlitsch, Kenning; Shanks, Justin D.Semantic Web Identity (SWI) is the condition in which search engines formally recognize entities and their relationships. Entities can be people, places, organizations, landmarks, or other “things” but in this chapter, entities will be defined as academic organizations: libraries, but also other academic units such as colleges, departments, centers, and institutes. An entity can be said to have achieved SWI if a formal display known as a Knowledge Graph Card (KC) appears for it in search engine results pages (SERP). The KC offers information about the entity directly in the search engine window, including such elements as address, phone number, hours of operation, description, link to the website, user reviews, etc. More importantly, the KC is an indicator that the search engine has achieved a machine-based comprehension of the existence and nature of the entity. With this understanding, the search engine can be more precise in its referrals and can hand off information about the entity to other semantic technologies. Far from being an end in itself, the display of an accurate and robust KC should simply be considered a positive indicator of SWI. Unfortunately, most academic organizations have not achieved SWI at this time. A search engine displays a KC when it has gathered enough verifiable facts about an entity. Search engines gather some facts organically while indexing website documents. But verifiable facts are more likely to be harvested from proprietary knowledge bases such as Google My Business, and from knowledge bases on the Linked Open Data (LOD) cloud, such as Wikipedia and Wikidata. Academic organizations have the best chance of controlling their SWI by proactively creating and curating records in these knowledge bases. This chapter will: (1) explain the significance of SWI; (2) describe a new library service developed at Montana State University that helps campus organizations implement SWI; and (3) demonstrate how SWI was successfully achieved in three case studies.Item Why So Many Repositories? Examining the Limitations and Possibilities of the Institutional Repositories Landscape(Taylor & Francis, 2018-03) Arlitsch, Kenning; Grant, CarlAcademic libraries fail to take advantage of the network effect because they manage too many digital repositories locally. While this argument applies to all manner of digital repositories, this article examines the fragmented environment of institutional repositories, in which effort and costs are duplicated, numerous software platforms and versions are managed simultaneously, metadata are applied inconsistently, users are served poorly, and libraries are unable to take advantage of collective data about content and users. In the meantime, commercial IR vendors and academic social networks have shown much greater success with cloud-based models. Collectively, the library profession has enough funding to create a national-level IR, but it lacks the willingness to abandon local control.Item RAMP - The Repository Analytics and Metrics Portal: A prototype Web service that accurately counts item downloads from institutional repositories(2016-11) OBrien, Patrick; Arlitsch, Kenning; Mixter, Jeff; Wheeler, Jonathan; Sterman, Leila B.Purpose – The purpose of this paper is to present data that begin to detail the deficiencies of log file analytics reporting methods that are commonly built into institutional repository (IR) platforms. The authors propose a new method for collecting and reporting IR item download metrics. This paper introduces a web service prototype that captures activity that current analytics methods are likely to either miss or over-report. Design/methodology/approach – Data were extracted from DSpace Solr logs of an IR and were cross-referenced with Google Analytics and Google Search Console data to directly compare Citable Content Downloads recorded by each method. Findings – This study provides evidence that log file analytics data appear to grossly over-report due to traffic from robots that are difficult to identify and screen. The study also introduces a proof-of-concept prototype that makes the research method easily accessible to IR managers who seek accurate counts of Citable Content Downloads. Research limitations/implications – The method described in this paper does not account for direct access to Citable Content Downloads that originate outside Google Search properties. Originality/value – This paper proposes that IR managers adopt a new reporting framework that classifies IR page views and download activity into three categories that communicate metrics about user activity related to the research process. It also proposes that IR managers rely on a hybrid of existing Google Services to improve reporting of Citable Content Downloads and offers a prototype web service where IR managers can test results for their repositories.Item Semantic Web Identity of Academic Libraries(Taylor & Francis, 2017-04-21) Arlitsch, KenningSemantic Web Identity (SWI) is proposed as the condition in which search engines recognize the existence and nature of entities. The display of a Knowledge Graph Card in Google search results is an indicator of SWI, as it demonstrates that Google has gathered verifiable facts about the entity. Such recognition is likely to improve the accuracy and relevancy of Google’s referrals to that entity. This article summarizes part of the research conducted for a recent doctoral dissertation, showing that SWI is poor for ARL libraries. The study hypothesizes that the failure to populate records in appropriate Linked Open Data and proprietary Semantic Web knowledge bases contributes to poor SWI.Item Dataset supporting the dissertation “Semantic Web Identity of Academic Organizations: Search engine entity recognition and the sources that influence Knowledge Graph Cards in search results”(Montana State University ScholarWorks, 2016-11) Arlitsch, KenningThis dataset supports the dissertation “Semantic Web Identity in Academic Organizations: Search engine entity recognition and the sources that influence Knowledge Graph Cards in search results,” for a Ph.D. granted by the Institut für Bibliotheks- und Informationswissenschaft (IBI), Humboldt Universität zu Berlin. This dataset contains more than 1400 screen capture files of search results conducted in Google, Google My Business, Google+, Wikipedia, DBpedia, and Wikidata. The subjects of the searches were the 125 member organizations of the Association of Research Libraries (ARL). Searches were also conducted for the eleven colleges of Montana State University and for three libraries that served as case studies. Screenshots were captured in 2015 and 2016 to support the dissertation “Semantic Web Identity for Academic Organizations.” The dataset also includes the spreadsheet file (CSV format) that was used to record results of the searches, as well as the source files with statistical analysis equations used in R.Item Digitizing the Ivan Doig Archive at Montana State University: a rise to the challenge illustrates creative tension(Taylor & Francis, 2017-01) Arlitsch, Kenning; Hawks, Melanie; McKelvey, Hannah; Gollehon, Michelle; Zauha, JanelleThis article contextualizes the leadership concept of creative tension by describing the acquisition, processing and digitization of the Ivan Doig Archive at the Montana State University Library. The project is framed as an illustration of strategies that can generate and sustain momentum toward achieving ambitious goals while building staff confidence. Perspectives from library staff and faculty who worked on the project are included alongside the view of the dean and an external organizational development manager.Item Undercounting File Downloads from Institutional Repositories(Emerald, 2016-10) OBrien, Patrick; Arlitsch, Kenning; Sterman, Leila B.; Mixter, Jeff; Wheeler, Jonathan; Borda, SusanA primary impact metric for institutional repositories (IR) is the number of file downloads, which are commonly measured through third-party web analytics software. Google Analytics, a free service used by most academic libraries, relies on HTML page tagging to log visitor activity on Google’s servers. However, web aggregators such as Google Scholar link directly to high value content (usually PDF files), bypassing the HTML page and failing to register these direct access events. This paper presents evidence of a study of four institutions demonstrating that the majority of IR activity is not counted by page tagging web analytics software, and proposes a practical solution for significantly improving the reporting relevancy and accuracy of IR performance metrics using Google Analytics.Item Data set supporting study on Undercounting File Downloads from Institutional Repositories [dataset](Montana State University ScholarWorks, 2016-07) OBrien, Patrick; Arlitsch, Kenning; Sterman, Leila B.; Mixter, Jeff; Wheeler, Jonathan; Borda, SusanThis dataset supports the study published as “Undercounting File Downloads from IR”. The following items are included: 1. gaEvent.zip = PDF exports of Google Analytics Events reports for each IR. 2. gaItemSummaryPageViews.zip = PDF exports of Google Analytics Item Summary Page Views reports. Also, included is a Text file containing the Regular Expressions used to generate each report’s Advanced Filter. 3. gaSourceSessions.zip = PDF exports of Google Analytics Referral reports to determine the percentage of referral traffic from Google Scholar. Note: does not include Utah due to issues with the structure of Utah’s IR and configuration of their Google Analytics. 4. irDataUnderCount.tsv.zip – TSV file of complete Google Search Console data set containing the 57,087 unique URLs in 413,786 records. 5. irDataUnderCountCiteContentDownloards.tsv.zip = TSV of the Google Search Console records containing the Citable Content Download records that were not counted in google Analytics.
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