Preface - Digital Libraries : research and development - First International DELOS Conference
Bibliographic record
Abstract
Digital Libraries represent the meeting point of a large number of technical areas within the field of informatics, i.e., information retrieval, document management, information systems, the web, image processing, artificial intelligence, human-computer interaction, mass-storage systems, and others. Moreover, Digital Libraries draw upon other disciplines beyond informatics, such as library sciences, museum sciences, archives, sociology, psychology, etc. However, they constitute a relatively young scientific field, whose life spans roughly the last fifteen years. During these years the DELOS Network of Excellence on Digital Libraries (http://www.delos.info) has represented a constant presence aiming to contribute to the consolidation of the field. The activities of DELOS started many years ago, with the "DELOS Working Group" at the end of the nineties, and the DELOS Thematic Network, under the Fifth Framework Program, from 2001 to 2003. Since the beginning, the main objective of DELOS has been to advance the state of the art in the field of Digital Libraries by coordinating the efforts of the major European research teams conducting activities in the major fields of interest. Every year DELOS organises the All-Tasks meeting, the annual appointment of the DELOS community where the scientific results achieved during the previous year are presented. Instead of the usual status reports from the various DELOS Tasks, in 2006 it was decided to issue a Call for Papers, soliciting papers reporting the scientific achievements of the DELOS members during 2006, and to organize a Conference. The first DELOS Conference was held on February 13-14, 2007, at the Grand Hotel Continental in Tirrenia, Pisa, Italy. The Conference represented a good coverage of the 27 research tasks in DELOS, with 38 papers being presented. In addition, two invited papers: "Semantic Digital Libraries" (John Mylopoulos, University of Toronto) and "Digital Libraries: From proposals to pro jects to systems to theory to curricula" (Edward Fox, Virginia Tech) completed the program. The Conference was open to the larger Digital Library Community and not just to the DELOS partners. About 120 people attended , half of which were not from DELOS partners. We believe that this is an indication of the increased interest in Digital Libraries, and the recognition that the DELOS research activities have played and are playing an important role in the European Digital Library scene. This volume includes extended and revised versions of the papers presented at the DELOS Conference. We believe that it should be of interest to the broad audience potentially interested in the Digital Library research area. It has been structured into 10 sections, corresponding to the different sessions in which the Conference was structured, which in turn correspond to the ma jor areas of research where DELOS has focussed its attention recently.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.172 | 0.087 |
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".