Unearthing the Recent Past

Clausner, Christian; Hayes, Justin; Antonacopoulos, Apostolos; Pletschacher, Stefan

doi:10.1145/3078081.3078106

Cited by 4 publications

(4 citation statements)

References 7 publications

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“…This is in line with results achieved in ICDAR's historical newspaper layout analysis competition, where best systems achieve accuracy of 83-86% [1][2]. Same range of performance is achieved also in ICDAR 2015 and ICDAR 2017 where documents with complex layout were analyzed [3,7].…”

Section: Selection Of the Article Extraction Toolsupporting

confidence: 86%

“…Article extraction on complex layout digitized newspaper pages is not an easy task. Results of the biannual ICDAR competition on historical newspaper layout analysis show that current algorithms segment and label about 80-85 % of the pages correctly at best [1][2][3]7]. These results, however, are achieved with a smallish evaluation corpus of less than 100 documents [8] and the results are thus only indicative.…”

Section: Selection Of the Article Extraction Toolmentioning

confidence: 89%

“…These results, however, are achieved with a smallish evaluation corpus of less than 100 documents [8] and the results are thus only indicative. Evaluation campaign Maurdor 7 from years 2013 and 2014 is the most comprehensive evaluation task in overall document segmentation and identification. Some results of the Maurdor campaign are shown in [5].…”

Section: Selection Of the Article Extraction Toolmentioning

confidence: 99%

See 2 more Smart Citations

Detecting Articles in a Digitized Finnish Historical Newspaper Collection 1771-1929

Kettunen

Ruokolainen

Liukkonen

et al. 2019

Proceedings of the 3rd International Conference on Digital Access to Textual Cultural Heritage

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Section: Selection Of the Article Extraction Toolsupporting

confidence: 86%

Section: Selection Of the Article Extraction Toolmentioning

confidence: 89%

Section: Selection Of the Article Extraction Toolmentioning

confidence: 99%

See 1 more Smart Citation

Detecting Articles in a Digitized Finnish Historical Newspaper Collection 1771-1929

Kettunen

Ruokolainen

Liukkonen

et al. 2019

Proceedings of the 3rd International Conference on Digital Access to Textual Cultural Heritage

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“…The digitisation project for the 1961 Census for England and Wales [1] [12] was conducted by the authors for the UK's Office for National Statistics (ONS) [13]. The goal was to produce a complete integrated digital dataset for publication by ONS, containing as much information as could possibly be extracted and validated from a set of approximately 140,000 digital images of computer printouts (via microfilm) of tables from the unpublished and almost entirely inaccessible 1961 Census Small Area Statistics.…”

Section: The 1961 Census Digitisation Projectmentioning

confidence: 99%

Crowdsourcing Historical Tabular Data

Clausner

Hayes

Antonacopoulos

2019

Proceedings of the 5th International Workshop on Historical Document Imaging and Processing

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C r o w d s o u r ci n g hi s t o ri c al t a b ul a r d a t a : 1 9 6 1 c e n s u s of E n gl a n d a n d Wal e s Cl a u s n er, C, H a y e s, J a n d Anto n a c o p o ulo s, A h t t p:// dx. d oi.o r g/ 1 0. 1 1 4 5/ 3 3 5 2 6 3 1. 3 3 5 2 6 4 3 Ti t l e C r o w d s o u r ci n g hi s t o ri c al t a b ul a r d a t a : 1 9 6 1 c e n s u s of E n gl a n d a n d Wal e s A u t h o r s Cl a u s n er, C, H a y e s , J a n d Anto n a c o p o ulo s, A Typ e Book S e c tio n U RL This ve r sio n is a v ail a bl e a t : h t t p:// u sir.s alfo r d. a c. u k/id/ e p ri n t/ 5 3 0 1 4/ P u b l i s h e d D a t e 2 0 1 9 U SIR is a di git al c oll e c tio n of t h e r e s e a r c h o u t p u t of t h e U niv e r si ty of S alfo r d. W h e r e c o py ri g h t p e r mi t s, full t e x t m a t e ri al h el d in t h e r e p o si to ry is m a d e fr e ely a v ail a bl e o nli n e a n d c a n b e r e a d , d o w nlo a d e d a n d c o pi e d fo r n o nc o m m e r ci al p riv a t e s t u dy o r r e s e a r c h p u r p o s e s . Pl e a s e c h e c k t h e m a n u s c ri p t fo r a n y fu r t h e r c o py ri g h t r e s t ri c tio n s. Fo r m o r e info r m a tio n, in cl u di n g o u r p olicy a n d s u b mi s sio n p r o c e d u r e , pl e a s e c o n t a c t t h e R e p o si to ry Te a m a t: u si r@ s alfo r d. a c. u k .ABSTRACT This paper describes how crowdsourcing can be incorporated as an integral part of a comprehensive technical workflow to identify, extract and validate data from large volumes of printed tabular statistics, and transform them into operable digital datasets using current structural and descriptive standards. The recently completed digitisation project for the 1961 Census of England and Wales (commissioned by the UK's Office for National Statistics) is used to provide details on data processing, crowdsourcing platform and tasks, crowd interaction, and validation of results. The multi-modal approach employed was very successful, delivering far more complete and validated data than automated processes alone could produce (due to the challenging nature of the source material).

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Ontology and Framework for Semantic Labelling of Document Data and Software Methods

Clausner

Antonacopoulos

2018

2018 13th IAPR International Workshop on Document Analysis Systems (DAS)

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Abstract-We present a metadata labelling framework for datasets, software tools, and workflows. An ontology for document image analysis was developed with deep support for historical data. An accompanying open source software framework was implemented to enable ontology editing, data and method annotation, workflow composition, and semantic search. A wide range of examples is used to illustrate realworld application.

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Unearthing the Recent Past

Cited by 4 publications

References 7 publications

Detecting Articles in a Digitized Finnish Historical Newspaper Collection 1771-1929

Detecting Articles in a Digitized Finnish Historical Newspaper Collection 1771-1929

Crowdsourcing Historical Tabular Data

Ontology and Framework for Semantic Labelling of Document Data and Software Methods

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