Demonstrating Success: Web Analytics and Continuous Improvement

As free and low-cost Web analytics tools become more sophisticated, libraries’ approach to user analysis can become more nuanced and precise. Tracking appropriate metrics with a well-formulated analytics program can inform design decisions, demonstrate the degree to which those decisions have succeeded, and thereby inform the next iteration in the design process. The Health Sciences Libraries of the University of Minnesota have been using Google Analytics as their primary analytics solution since 2005, and as Google has continued to add functionality and flexibility to the platform, the Health Sciences Libraries has capitalized on the opportunities made available. In this article the author outlines the Health Sciences Libraries strategy for using Google Analytics and describes several of the more novel methods they have developed, providing a roadmap for others seeking to strengthen their understanding of the behavior of users on their library's Web sites.     

Knowledge diffusion path analysis of data quality literature: A main path analysis

This study presents a unique approach in investigating the knowledge diffusion structure for the field of data quality through an analysis of the main paths. We study a dataset of 1880 papers to explore the knowledge diffusion path, using citation data to build the citation network. The main paths are then investigated and visualized via social network analysis. This paper takes three different main path analyses, namely local, global, and key-route, to depict the knowledge diffusion path and additionally implements the g-index and h-index to evaluate the most important journals and researchers in the data quality domain.     

Measuring journal performance for multidisciplinary research: An efficiency perspective

One of the flaws of the journal impact factor (IF) is that it cannot be used to compare journals from different fields or multidisciplinary journals because the IF differs significantly across research fields. This study proposes a new measure of journal performance that captures field-different citation characteristics. We view journal performance from the perspective of the efficiency of a journal's citation generation process. Together with the conventional variables used in calculating the IF, the number of articles as an input and the number of total citations as an output, we additionally consider the two field-different factors, citation density and citation dynamics, as inputs. We also separately capture the contribution of external citations and self-citations and incorporate their relative importance in measuring journal performance. To accommodate multiple inputs and outputs whose relationships are unknown, this study employs data envelopment analysis (DEA), a multi-factor productivity model for measuring the relative efficiency of decision-making units without any assumption of a production function. The resulting efficiency score, called DEA-IF, can then be used for the comparative evaluation of multidisciplinary journals’ performance. A case study example of industrial engineering journals is provided to illustrate how to measure DEA-IF and its usefulness.     

大数据时代档案数据质量控制:现状、机制与优化路径

档案数据是大数据时代经济社会发展的重要信息资源,进行档案数据质量控制研究有助于促进档案治理能力现代化的提升。通过调查分析可知,档案数据存有政策法规缺失、数量巨大结构复杂、数据实践处于起步阶段等现状。基于现状特征构建了档案数据质量控制机制:数据监督管控机制、技术保障机制、质量评估机制,并提出增强档案数据质量控制顶层设计,筑造档案数据质量技术保护屏障,构建档案数据质量评估方法体系等优化路径。     

Tabs and Tabulations: Results of a Transaction Log Analysis of a Tabbed-Search Interface

The following study analyzes user search behavior using a tabbed-search interface. For this study, a transaction log was used to collect information about user searches and included tab used; search terms; date, time, and location of search (on campus or off campus); as well as a unique ID to identify the user session and another ID to identify each transaction. This article explains the process for examining 4,300 search queries conducted on the library homepage during an academic semester and presents findings from the analysis. The article also details enhancements that were made to the tabbed-search interface as a result of the transaction log analysis. Additionally, the article discusses the merits of using a transaction log as a method of ongoing assessment of a library Web site's search interface.     

Google Scholar,Web of Science,and Scopus: A systematic comparison of citations in 252 subject categories

Despite citation counts from Google Scholar (GS), Web of Science (WoS), and Scopus being widely consulted by researchers and sometimes used in research evaluations, there is no recent or systematic evidence about the differences between them. In response, this paper investigates 2,448,055 citations to 2299 English-language highly-cited documents from 252 GS subject categories published in 2006, comparing GS, the WoS Core Collection, and Scopus. GS consistently found the largest percentage of citations across all areas (93%–96%), far ahead of Scopus (35%–77%) and WoS (27%–73%). GS found nearly all the WoS (95%) and Scopus (92%) citations. Most citations found only by GS were from non-journal sources (48%–65%), including theses, books, conference papers, and unpublished materials. Many were non-English (19%–38%), and they tended to be much less cited than citing sources that were also in Scopus or WoS. Despite the many unique GS citing sources, Spearman correlations between citation counts in GS and WoS or Scopus are high (0.78-0.99). They are lower in the Humanities, and lower between GS and WoS than between GS and Scopus. The results suggest that in all areas GS citation data is essentially a superset of WoS and Scopus, with substantial extra coverage.     

Of Fans,Friends, and Followers: Methods for Assessing Social Media Outreach in Special Collections Repositories

Increasing adoption and implementation of social media applications suggests a cultural shift in the way special collections departments communicate with external constituents. Research shows many social networking tools are used successfully to connect with special collections patrons, but limited documentation exists to describe whether special collections departments receive demonstrable returns for the time, effort, and energy expended to sustain social media activity. This article provides the results of an empirical study that examined social media usage in special collections departments at 125 Association of Research Libraries member institutions. By analyzing publicly available data from profiles on a variety of social media platforms, the authors explore how special collections units employ social networking tools and whether it is possible to determine success in terms of benefits received by the department, such as increased dialogue between departments and supporters. By using return on investment, this study found that special collections departments achieve moderate success when using social media to advertise collections, events, and activities, but they have little success when using social media to engage with external constituents. To address less successful aspects of social media projects, departments can engage in routine assessment activities, such as return on investment, to make the most of new technologies.