ArticleDatabase : the journal of biological databases and curation2018
Toward a service-based workflow for automated information extraction from herbarium specimens.
Article in Database : the journal of biological databases and curation, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Mining buried plant trait data from the Global Biodiversity Information Facility (GBIF): Comparison and integration with multiple plant trait databases.Applications in plant sciences · 2026Article
- Manage your image database with computer vision-Lessons learned at Encyclopedia of Life.Bioscience · 2026Article
- Long-term preservation strategy for legume root nodule phenotypes coupled with a comprehensive evaluation method.BMC plant biology · 2026Article
- Automated information extraction from plant specimen labels using OCR and large language models.Biodiversity data journal · 2026Article
- Hespi: a pipeline for automatically detecting information from herbarium specimen sheets.Bioscience · 2025Article
- The digitisation workflow of the herbarium of the State Museum of Natural History of the NAS of Ukraine (LWS).Biodiversity data journal · 2025Article
- Identification of herbarium specimen sheet components from high-resolution images using deep learning.Ecology and evolution · 2023Article
- Comprehensive leaf size traits dataset for seven plant species from digitised herbarium specimen images covering more than two centuries.Biodiversity data journal · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Over the past years, herbarium collections worldwide have started to digitize millions of specimens on an industrial scale. Although the imaging costs are steadily falling, capturing the accompanying label information is still predominantly done manually and develops into the principal cost factor. In order to streamline the process of capturing herbarium specimen metadata, we specified a formal extensible workflow integrating a wide range of automated specimen image analysis services. We implemented the workflow on the basis of OpenRefine together with a plugin for handling service calls and responses. The evolving system presently covers the generation of optical character recognition (OCR) from specimen images, the identification of regions of interest in images and the extraction of meaningful information items from OCR. These implementations were developed as part of the Deutsche Forschungsgemeinschaft-funded a standardised and optimised process for data acquisition from digital images of herbarium specimens (StanDAP-Herb) Project.
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.