The Barcelona Historical Marriage Database and the Baix Llobregat Demographic Database. From Algorithms for Handwriting Recognition to Individual-Level Demographic and Socioeconomic Data

J. Pujadas-Mora, A. Fornés, Oriol Ramos Terrades, J. Lladós, Jialuo Chen, M. Valls-Fígols, A. Cabré
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引用次数: 1

Abstract

The Barcelona Historical Marriage Database (BHMD) gathers records of the more than 600,000 marriages celebrated in the Diocese of Barcelona and their taxation registered in Barcelona Cathedral's so-called Marriage Licenses Books for the long period 1451–1905 and the BALL Demographic Database brings together the individual information recorded in the population registers, censuses and fiscal censuses of the main municipalities of the county of Baix Llobregat (Barcelona). In this ongoing collection 263,786 individual observations have been assembled, dating from the period between 1828 and 1965 by December 2020. The two databases started as part of different interdisciplinary research projects at the crossroads of Historical Demography and Computer Vision. Their construction uses artificial intelligence and computer vision methods as Handwriting Recognition to reduce the time of execution. However, its current state still requires some human intervention which explains the implemented crowdsourcing and game sourcing experiences. Moreover, knowledge graph techniques have allowed the application of advanced record linkage to link the same individuals and families across time and space. Moreover, we will discuss the main research lines using both databases developed so far in historical demography.
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巴塞罗那历史婚姻数据库和Baix Llobregat人口数据库。从手写识别算法到个人层面的人口统计和社会经济数据
巴塞罗那历史婚姻数据库(BHMD)收集了1451年至1905年期间在巴塞罗那教区庆祝的60多万次婚姻及其在巴塞罗那大教堂所谓的婚姻许可证簿中登记的纳税记录,Baix Llobregat县(巴塞罗那)主要市镇的人口普查和财政普查。在这一正在进行的收集中,截至2020年12月,收集了263786份1828年至1965年期间的个人观测结果。这两个数据库最初是历史人口学和计算机视觉交叉点上不同跨学科研究项目的一部分。他们的构建使用了人工智能和计算机视觉方法,如手写识别,以减少执行时间。然而,它目前的状态仍然需要一些人为干预,这解释了实施的众包和游戏包体验。此外,知识图技术允许应用高级记录链接,在时间和空间上连接相同的个人和家庭。此外,我们将讨论使用迄今为止在历史人口学中开发的两个数据库的主要研究路线。
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CiteScore
2.20
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0.00%
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审稿时长
30 weeks
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