No Comments on Review Update: Qinsight 311
Tobin Magle, PhD
Health Sciences Library
University of Colorado Anschutz Medical Campus
Much has changed since my review of the biomedical search engine Quetzal was published in the July 2016 issue of Doody’s Collection Development Monthly (http://dcdm.doody.com/2016/07/a-review-of-quetzal/). Now known as Qinsights, this database maintains its core audience of biomedical researchers by combining its intuitive AI-powered search interface and filters with new visualizations that help researchers identify emerging trends in the literature as well as expanded content.
Qinsight includes all that was in Quetzal, plus full-text articles from Oxford University Press journals, and it searches Dow Jones Factiva News, but the latter content requires a separate subscription.
Qinsight adds a suite of interactive visualizations to help researchers sift through their search results. The first two visualizations act primarily as filters to narrow the search results. The Category Map lays out key themes found in the search results in a hierarchical grid. Clicking on a theme either leads the user to more specific themes or applies the selected theme as a search filter. Similarly, the Concept Cloud uses AI technology to create a word cloud of clickable color-coded terms. Only relevant terms related to the user’s search appear in the cloud. The final two visualizations purport to go beyond simple exploration of the literature into predictive analytics. Concept Trends creates a visualization composed of concept bubbles where the larger the bubble size, the more prevalent the concept is in the search. This visualization also addresses when these concepts were mentioned in the search results and assigns these concepts as growing or waning trends. This feature allows researchers to identify emerging concepts in their area to pursue. Finally, Concept Connections visualizes how relevant concepts in the search relate to each other by indicating how often the two terms are connected meaningfully within a document using its AI algorithms. Images and the underlying data for these visualizations are available for download.
The business model for Qinsight has remained largely the same as Quetzal, with the notable absence of a free version. The advanced version of Quetzal is equivalent to Qinsight, while the more pared down professional version is called Qexplorer, which is only available to academic and nonprofit institutions. (Compare features between these versions at https://quertle.com/products/). The pricing for an individual account remains the same as it was at the time of my previous review.
Libraries that serve a large proportion of biomedical researchers should consider licensing Qinsights because of its ability to decipher natural language search queries that often contain gene names and abbreviations that can confound interfaces like PubMed. The new visualizations add value by visually representing rich metadata about the concepts identified in the search, such as the frequency in the literature over time and how they are connected to each other, providing potentially predictive value to the literature search.
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