Japan Biodiversity Information Initiative (JBIF)'s Efforts to Collect and Publish Biodiversity Information from Japan
Bibliographic record
Abstract
The Japan Biodiversity Information Initiative (JBIF) was originally established in 2007 as the Global Biodiversity Information Facility (GBIF) Japan National Node to aggregate biodiversity data in Japan and conduct publications through GBIF. JBIF was later renamed after Japan became a GBIF observer, but activities including data publication through GBIF have continued to the present. JBIF operates with the support of the National BioResource Project (NBRP) by the Ministry of Education, Culture, Sports, Science and Technology (MEXT), with collaboration from three institutions: the National Institute of Genetics (NIG), the National Institute for Environmental Studies (NIES), and the National Museum of Nature and Science (NMNS). The NBRP is a project that focuses on the collection, preservation, provision, and enhancement of bioresources. JBIF collects both observation and specimen data and publishes them through GBIF. For domestic data use, a search system for data published by JBIF is available on the JBIF website. Moreover, NMNS managed a museum network called the Science Museum Net (S-Net), and bilingual (Japanese and English) specimen data collected by S-Net is also available via the S-Net portal site. We are working to promote the biodiversity informatics field in Japan through a translation of the GBIF resources, including the website, important documents such as the GBIF Science Review, as well as organize workshops and conferences, primarily targeting students, researchers, museum curators, and local government officials, to facilitate the sharing of information and exchange of opinions on biodiversity information. To date, Japan has published 564 datasets and over 12 million occurrences to GBIF, making it the third-largest contributor of data to GBIF in Asia, following India and Taiwan. Moreover, regarding specimen-based occurrence data, Japan is the largest contributor in Asia. In this presentation, we will introduce JBIF's initiatives and future activities.
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.024 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.008 |
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".