It's Alive! Using Linked Open Data to promote discovery within artist-run centre collections
Bibliographic record
Abstract
The Western Front Society's Reverie: Noise City (2005) is a website platform originally built to present live performance art for their annual "Art's Birthday" event. The Reverie website envisions a "virtual city" where online audiences witness these performances and today serves as an archive for the web-streamed events. Despite its innovative nature, the website's content remains largely undiscoverable and hard to access due to the limited terminology exposing the website to search engine queries, the lack of a sitemap in HTML for the website sub-links, and the absence of structured machine-readable data. Using the Reverie website as case study, I argue for the use of Linked Open Data technologies within artist-run organizations hoping to improve discoverability of their multimedia assets. I create a machine-readable document to advance the Reverie website's Search Engine Optimization (SEO) and provide an outline of my methodology to be used by like-minded archivists and artists.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.013 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.019 | 0.025 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".