Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
6
datasets available to search
ShareScore release 0.9.0
Dataset results
6 results for “Optical Character Recognition”
Low resolution scanned text dataset for optical character recognition
<p>A collection of scanned pages of English text designed for testing low resolution OCR systems. There are 11 different pieces of text, each of which contains 5 pages of text. Each of these 55 pages is typeset in 18 different fonts and then scanned at 300 dpi, producing a total of 990 pages of scanned text. Downsampled 60 dpi and 75 dpi versions are included.</p>
Trained tesseract networks for low-resolution optical character recognition
<p>Tesseract eng.traineddata files for low-resolution optical character recognition (English).</p>
Figure 2 from: Drinkwater R, Cubey R, Haston E (2014) The use of Optical Character Recognition (OCR) in the digitisation of herbarium specimen labels. PhytoKeys 38: 15-30. https://doi.org/10.3897/phytokeys.38.7168
Figure 2 - Box plot of Complete and Partial Protocol results. R1C – Random 1 complete; R1P – Random 1 Partial; CollC – Collector only Complete; CollP – Collector only Partial; CouC – Country only Complete; CouP – Country only Partial; CCC – Collector & Country Complete; CCP – Collector & Country Partial; OCRC – Collector & Country OCR Complete; OCRP – Collector & Country OCR Partial; R2C – Random 2 Complete; R2P – Random 2 Partial.
Figure 1 from: Drinkwater R, Cubey R, Haston E (2014) The use of Optical Character Recognition (OCR) in the digitisation of herbarium specimen labels. PhytoKeys 38: 15-30. https://doi.org/10.3897/phytokeys.38.7168
Figure 1 - Example labels: a Pre-printed label with handwritten details b and c mixed labels with pre-printed and typed information d Mainly handwritten label, with printers mark e Mainly handwritten label with unusual phrasing.
Figure 4 from: Drinkwater R, Cubey R, Haston E (2014) The use of Optical Character Recognition (OCR) in the digitisation of herbarium specimen labels. PhytoKeys 38: 15-30. https://doi.org/10.3897/phytokeys.38.7168
Figure 4 - Digitiser responses to questions 1, 2 and 3 of survey
Figure 3 from: Drinkwater R, Cubey R, Haston E (2014) The use of Optical Character Recognition (OCR) in the digitisation of herbarium specimen labels. PhytoKeys 38: 15-30. https://doi.org/10.3897/phytokeys.38.7168
Figure 3 - Box plot of Partial Protocol results.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.