ArticleBiodiversity data journal2025
The digitisation workflow of the herbarium of the State Museum of Natural History of the NAS of Ukraine (LWS).
Article in Biodiversity data journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Automated information extraction from plant specimen labels using OCR and large language models.Biodiversity data journal · 2026Article
- herbUA Collectors: An open-source framework for online publication of the herbarium collector-centric data.Biodiversity data journal · 2026Article
- The data archiving in the small herbaria digitisation workflow.Biodiversity data journal · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The digitisation workflow currently applied at the Herbarium of the State Museum of Natural History of the National Academy of Sciences of Ukraine (LWS) differs from other similar by cascade ('object-to-data-to-image') multilevel organisation. Its application is predicted by the need to preselect specimens by taxon and region, as well as by batched digitisation, which occurs with significant interruptions. Focusing on certain taxonomic groups from specific regions allows us to digitise specimens that could be more valuable for early scientific processing. At the same time, the herbarium benefits from such a digitisation model by revising the existing collection classification and keeping the initial ID system. The presented digitisation workflow can be easily reproduced in any herbarium with a limited budget. The purpose of this paper is to provide detailed description and schemas of the principal digitisation stages applied at the LWS Herbarium and to briefly discuss the steps crucial for a successful result. Provided information should help to maintain the digitisation and choose appropriate equipment and materials. We can conclude that, despite its general complexity, the described workflow demonstrated itself as viable and relevant due to its robust design and focus on data quality. Despite a focus on specialists' involvement, it maintains flexibility that allows combining volunteers and, if needed, outsourced efforts. Moreover, its modularity promotes independence of principal digitisation stages and allows long interruptions between the digitisation batches.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.