Scholarly Work - Library
Permanent URI for this collectionhttps://scholarworks.montana.edu/handle/1/320
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Item Digital Library User Research Data [dataset](Montana State University ScholarWorks, 2017-03) Young, Scott W. H.Hex UX is an integrated method for generating, analyzing, and reporting user experience research data.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 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.Item Library-Vendor Relations: Data from a Survey of Libraries and of Vendors [dataset](Montana State University ScholarWorks, 2016-02) Ostergaard, Kirsten; Rossmann, DoralynItem Cited/Downloaded Dataset and Repository Characteristics [dataset](Montana State University ScholarWorks, 2016-02) Mannheimer, Sara; Borda, Susan; Sterman, Leila B.This rubric documents the characteristics of high-use datasets and their repositories, with “high-use” defined as either highly cited in Thomson Reuters' Data Citation Index or highly downloaded in an institutional repository. The authors reviewed publicly-available information on repository websites and inputted our observations into the rubric. The rubric addresses six major characteristics of high-use datasets and their repositories: basic information; funding agency and journal information; linking and sharing; factors to encourage reuse; repository characteristics; and data description.Item Library Web Performance Data [dataset](2016-01) Young, Scott W. H.This dataset is associated with the following article: Young, SWH (2016) Speed Matters: Performance Enhancements for Library Websites. Weave UX 1(4). http://doi.org/10.3998/weave.12535642.0001.401Item A/B Testing Web Analytics Data [dataset](2014-07) Young, Scott W. H.This dataset is associated with the following article: Young, Scott WH (2014) Improving Library User Experience with A/B Testing: Principles and Process. Weave: Journal of Library User Experience. University of Michigan Library. doi:10.3998/weave.12535642.0001.101