Formats over Time: Exploring UK Web History: Paper - iPRES 2012 - Digital Curation Institute, iSchool, Toronto
Bibliographic record
Abstract
Is software obsolescence a significant risk?To explore this issue, we analysed a corpus of over 2.5 billion resources corresponding to the UK Web domain, as crawled between 1996 and 2010.Using the DROID and Apache Tika identification tools, we examined each resource and captured the results as extended MIME types, embedding version, software and hardware identifiers alongside the format information.The combined results form a detailed temporal format profile of the corpus, which we have made available as open data.We present the results of our initial analysis of this dataset.We look at image, HTML and PDF resources in some detail, showing how the usage of different formats, versions and software implementations has changed over time.Furthermore, we show that software obsolescence is rare on the web and uncover evidence indicating that network effects act to stabilise formats against obsolescence.
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How this classification was reachedexpand
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.845 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.024 | 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; both teacher heads agree on what is shown here.
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".