Past and future uses of text mining in ecology and evolution

MJ Farrell, L Brierley, A Willoughby… - Proceedings of the …, 2022 - royalsocietypublishing.org
Ecology and evolutionary biology, like other scientific fields, are experiencing an
exponential growth of academic manuscripts. As domain knowledge accumulates, scientists …

Applications of computer vision and machine learning techniques for digitized herbarium specimens: A systematic literature review

BR Hussein, OA Malik, WH Ong, JWF Slik - Ecological Informatics, 2022 - Elsevier
Herbaria contain the treasure of millions of specimens that have been preserved for several
years for scientific studies. To increase the rate of scientific discoveries, digitization of these …

A novel automated label data extraction and data base generation system from herbarium specimen images using OCR and NER

A Takano, TCH Cole, H Konagai - Scientific Reports, 2024 - nature.com
Digital extraction of label data from natural history specimens along with more efficient
procedures of data entry and processing is essential for improving documentation and …

Drowning in data, thirsty for information and starved for understanding: A biodiversity information hub for cooperative environmental monitoring in South Africa

S MacFadyen, N Allsopp, R Altwegg, S Archibald… - Biological …, 2022 - Elsevier
The world is firmly cemented in a notitian age (Latin: notitia, meaning data)–drowning in
data, yet thirsty for information and the synthesis of knowledge into understanding. As …

Humans in the loop: Community science and machine learning synergies for overcoming herbarium digitization bottlenecks

R Guralnick, R LaFrance, M Denslow… - Applications in Plant …, 2024 - Wiley Online Library
Premise Among the slowest steps in the digitization of natural history collections is
converting imaged labels into digital text. We present here a working solution to overcome …

The specimen data refinery: a canonical workflow framework and FAIR digital object approach to speeding up digital mobilisation of natural history collections

A Hardisty, P Brack, C Goble, L Livermore, B Scott… - Data …, 2022 - direct.mit.edu
A key limiting factor in organising and using information from physical specimens curated in
natural science collections is making that information computable, with institutional …

Landscape analysis for the specimen data refinery

S Walton, L Livermore, O Bánki… - Research Ideas …, 2020 - research.manchester.ac.uk
This report reviews the current state-of-the-art applied approaches on automated tools,
services and workflows for extracting information from images of natural history specimens …

PENet: A phenotype encoding network for automatic extraction and representation of morphological discriminative features

Z Zhao, Y Lu, Y Tong, X Chen… - Methods in Ecology and …, 2023 - Wiley Online Library
Digitalized natural history collections serve as vital ecological and evolutionary research
resources. Specimen retrieval based on morphological features allows for the rapid …

A cost analysis of transcription systems

S Walton, L Livermore, M Dillen… - Research Ideas …, 2020 - researchportal.helsinki.fi
We compare different approaches to transcribing natural history data and summarise the
advantages and disadvantages of each approach using six case studies from four different …

Hespi: A pipeline for automatically detecting information from hebarium specimen sheets

R Turnbull, E Fitzgerald, K Thompson… - arxiv preprint arxiv …, 2024 - arxiv.org
Specimen associated biodiversity data are sought after for biological, environmental,
climate, and conservation sciences. A rate shift is required for the extraction of data from …