Capitalizing on Information Organization and Information Visualization for a New-Generation Catalogue
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Subject searching is difficult with traditional text-based online public access library catalogues (OPACs), and the next-generation discovery layers are keyword searching and result filtering tools that offer little support for subject browsing. Next-generation OPACs ignore the rich network of relations offered by controlled subject vocabulary, which can facilitate subject browsing. A new generation of OPACs could leverage existing information-organization investments and offer online searchers a novel browsing and searching environment. This is a case study of the design and development of a virtual reality subject browsing and information retrieval tool. The functional prototype shows that the Library of Congress subject headings (LCSH) can be shaped into a useful and usable tree structure serving as a visual metaphor that contains a real world collection from the domain of science and engineering. Formative tests show that users can effectively browse the LCSH tree and carve it up based on their keyword search queries. This study uses a complex information-organization structure as a defining characteristic of an OPAC that goes beyond the standard keyword search model, toward the cutting edge of online search tools.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.044 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it