e60bea17c26dc33f1d607c387e3b2176 document.pdf 5a0c8337c59ace273fbd5208323dfdec2c8cdb78 document.pdf 0b6f4d91a901744cc0fde2f8f2528ea464d5ce4c8c7428c249f7f6d0a9414ccd document.pdf Title: The Barcelona Historical Marriage Database and the Baix Llobregat Demographic Database. From Algorithms for Handwriting Recognition to Individual-Level Demographic and Socioeconomic Data Subject: 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. Author: Joana Maria Pujadas-Mora Creator: Adobe InDesign 16.4 (Windows) Producer: Adobe PDF Library 16.0 CreationDate: Tue Jun 21 11:59:33 2022 CEST ModDate: Thu Feb 2 13:02:52 2023 CET Tagged: no UserProperties: no Suspects: no Form: none JavaScript: no Pages: 37 Encrypted: no Page size: 595 x 842 pts (A4) Page rot: 0 File size: 1872007 bytes Optimized: no PDF version: 1.4 name type encoding emb sub uni object ID ------------------------------------ ----------------- ---------------- --- --- --- --------- NNHUVR+Verdana-Bold TrueType MacRoman yes yes no 9795 0 GPVEQG+Verdana TrueType MacRoman yes yes no 9796 0 NATPIF+Verdana TrueType MacRoman yes yes no 9797 0 QJAAHF+Verdana-Italic TrueType MacRoman yes yes no 9798 0 KGETXF+Calibri TrueType WinAnsi yes yes yes 9799 0 JYTSZL+SyntaxLTStd-Roman Type 1C Custom yes yes yes 9674 0 DAOYTX+SyntaxLTStd-Italic Type 1C Custom yes yes yes 9675 0 GNUGJR+SyntaxLTStd-Bold Type 1C WinAnsi yes yes yes 9682 0 GNUGJR+SyntaxLTStd-Bold Type 1C WinAnsi yes yes yes 13 0 JYTSZL+SyntaxLTStd-Roman Type 1C WinAnsi yes yes yes 15 0 JYTSZL+SyntaxLTStd-Roman Type 1C Custom yes yes yes 148 0 AHRMDD+SyntaxLTStd-Bold-SC700 Type 1C WinAnsi yes yes yes 154 0 JYTSZL+SyntaxLTStd-Roman Type 1C WinAnsi yes yes yes 150 0 UGNXXP+TimesNewRomanPSMT TrueType WinAnsi yes yes yes 158 0 PWATFZ+SymbolMT CID TrueType Identity-H yes yes yes 160 0 JYTSZL+SyntaxLTStd-Roman Type 1C Custom yes yes yes 162 0 JYTSZL+SyntaxLTStd-Roman Type 1C WinAnsi yes yes yes 166 0 Jhove (Rel. 1.22.1, 2019-04-17) Date: 2023-03-16 02:36:11 CET RepresentationInformation: document.pdf ReportingModule: PDF-hul, Rel. 1.12.1 (2019-04-17) LastModified: 2023-02-02 13:03:51 CET Size: 1872007 Format: PDF Version: 1.4 Status: Well-Formed, but not valid SignatureMatches: PDF-hul ErrorMessage: Annotation object is not a dictionary Offset: 128738 MIMEtype: application/pdf PDFMetadata: Objects: 9821 FreeObjects: 9375 IncrementalUpdates: 2 DocumentCatalog: ViewerPreferences: HideToolbar: false HideMenubar: false HideWindowUI: false FitWindow: false CenterWindow: false DisplayDocTitle: false NonFullScreenPageMode: UseNone Direction: L2R ViewArea: CropBox ViewClip: CropBox PrintArea: CropBox PageClip: CropBox PageLayout: SinglePage PageMode: UseNone Language: en-US Outlines: Item: Title: _GoBack Item: Title: _heading=h.1fob9te Item: Title: _heading=h.sa3fz3fp7rga Item: Title: _heading=h.tyjcwt Item: Title: _Hlk82090085 Item: Title: _Hlk98230110 Item: Title: _heading=h.3dy6vkm Info: Title: The Barcelona Historical Marriage Database and the Baix Llobregat Demographic Database. From Algorithms for Handwriting Recognition to Individual-Level Demographic and Socioeconomic Data Author: Joana Maria Pujadas-Mora Subject: 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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See http://creativecommons.org/licenses/. Individual demographic databases Computer vision Record linkage Social mobility Inequality Migration Word spotting Handwriting recognition Local censuses Marriage licences The Barcelona Historical Marriage Database and the Baix Llobregat Demographic Database. From Algorithms for Handwriting Recognition to Individual-Level Demographic and Socioeconomic Data Joana Maria Pujadas-Mora Alícia Fornés Oriol Ramos Terrades Josep Lladós Jialuo Chen Miquel Valls-Fígols Anna Cabré 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. 2022-06-21T11:59:33+02:00 2023-02-02T13:02:52+01:00 2023-02-02T13:02:52+01:00 Adobe InDesign 16.4 (Windows) uuid:1e4d1048-c4a5-0e4e-a4d4-2c8650f55af1 xmp.did:018011740720681188C69A9F660B4633 xmp.id:fa936a05-7be0-1e4c-a382-0ccfb69b70be proof:pdf xmp.iid:5129e016-18d3-324b-9abc-f03e5263b5ae xmp.did:978598d4-65b8-2744-978a-897a2a4d1228 xmp.did:018011740720681188C69A9F660B4633 default converted from application/x-indesign to application/pdf Adobe InDesign 16.4 (Windows) / 2022-06-21T11:59:33+02:00 https://creativecommons.org/licenses/by/4.0/ False Adobe PDF Library 16.0 False Checksum: 851836b8 Type: CRC32 Checksum: e60bea17c26dc33f1d607c387e3b2176 Type: MD5 Checksum: 5a0c8337c59ace273fbd5208323dfdec2c8cdb78 Type: SHA-1