Understanding the application of handwritten text recognition technology in heritage contexts: a systematic review of Transkribus in published research.

Handwritten Text Recognition (HTR) technology is now a mature machine learning tool, becoming integrated in the digitisation processes of libraries and archives, speeding up the transcription of primary sources and facilitating full text searching and analysis of historic texts at scale. However, research into how HTR is changing our information environment is scant. This paper presents a systematic literature review regarding how researchers are using one particular HTR platform, Transkribus, to indicate the domains where HTR is applied, the approach taken, and how the technology is understood. 381 papers from 2015 to 2020 were gathered from Google Scholar, Scopus, and Web of Science, then grouped and coded into categories using quantitative and qualitative approaches. Published research that mentions Transkribus is international and rapidly growing. Transkribus features primarily in archival and library science publications, while a long tail of broad and eclectic disciplines, including history, computer science, citizen science, law and education, demonstrate the wider applicability of the tool. The most common paper categories were humanities applications (67%), technological (25%), users (5%) and tutorials (3%). This paper presents the first overarching review of HTR as featured in published research, while also elucidating how HTR is affecting the information environment.

Replacing Sanger with Next Generation Sequencing to improve coverage and quality of reference DNA barcodes for plants.

We estimate the global BOLD Systems database holds core DNA barcodes (rbcL + matK) for about 15% of land plant species and that comprehensive species coverage is still many decades away. Interim performance of the resource is compromised by variable sequence overlap and modest information content within each barcode. Our model predicts that the proportion of species-unique barcodes reduces as the database grows and that 'false' species-unique barcodes remain >5% until the database is almost complete. We conclude the current rbcL + matK barcode is unfit for purpose. Genome skimming and supplementary barcodes could improve diagnostic power but would slow new barcode acquisition. We therefore present two novel Next Generation Sequencing protocols (with freeware) capable of accurate, massively parallel de novo assembly of high quality DNA barcodes of >1400 bp. We explore how these capabilities could enhance species diagnosis in the coming decades.