3D content, like the Widener 360 tour, is a spatialized experience that is a very familiar aspect of our offline lives. Zoom), and the YouTube rabbit holes, all of which we are now experiencing ad nauseam. These scans also represent an online media type that transcends the traditional wall-of-text, the “Brady Bunch” call experience (e.g.
We’ve seen an encouraging number of site visitors to the tour page in the few months since it has gone live, and I imagine other libraries are seeing similar uptake. Longhand leverages our, “…ability to rapidly report object identiy or category after just a single brief glimpse of visual input” ( DiCarlo & Cox, 2007).Ĭheck out some preliminary test results, below, and the GitHub repo for more. In addition to exposing text-centric researchers to the historically STEM-oriented benefits of Reality (e.g. Longhand exists to explore unwieldy text corpora (including in virtual reality) earlier in the research lifecycle. Longhand is a word cloud generator, but the “words” are 3D models projected in 360 degrees around the user. – are helpful at this exploratory research stage, when a researcher is simply trying to grasp the contents of a text corpus. So, how might one glimpse the contents of a text corpus, to generate preliminary research questions that might inform downstream search and more sophisticated analyses related to topics, sentiments, parts of speech, or named entities? Visualization – charts, graphs, diagrams, word clouds, etc. Keyword search results don’t reveal the nature of a corpus as a whole though, nor do they represent the relationships between tokens whose source material might span media, time, or location.
But while a keyword search is a useful way to collate and confirm hypotheses, it assumes the researcher has some ideas about where to begin some existing research questions. handwritten) source material, allowing the search of vast material collections. Increasingly accurate computational workflows can generate machine-actionable data from “raw” (e.g.
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