Linking Archives, Linked Open Data, and the Development of the World-Wide Directory of Repositories Holding Archives of Literature and Art
Bibliographic record
Abstract
Literary and artistic archives are frequently dispersed across heritage institutions, posing a challenge to researchers and archivists whose work is all the more complex given the challenges of identifying the location of archival collections. Knowing where an archives is located is fundamental to research, and for archivists it is useful to know what repositories have related collections in order to redirect potential acquisitions or to develop cross-institutional collaborations. The International Council on Archives (ICA) Section on Archives of Literature and Art (SLA) developed the World-Wide Directory of Repositories holding Archives of Literature and Art as a means for connecting archivists and linking researchers with collections. In this article, we provide a history of the directory, detail the process of incorporating Wikidata maps into the directory, and consider questions around the directory’s purpose, development, maintenance, and future directions.
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 | 0.031 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.018 | 0.027 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.016 | 0.038 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".