000728326 000__ 05019cam\a2200457Ii\4500 000728326 001__ 728326 000728326 005__ 20230306141006.0 000728326 006__ m\\\\\o\\d\\\\\\\\ 000728326 007__ cr\cn\nnnunnun 000728326 008__ 150727s2015\\\\sz\a\\\\o\\\\\000\0\eng\d 000728326 020__ $$a9783319198842$$qelectronic book 000728326 020__ $$a331919884X$$qelectronic book 000728326 020__ $$z9783319198835 000728326 035__ $$aSP(OCoLC)ocn914472074 000728326 035__ $$aSP(OCoLC)914472074 000728326 040__ $$aN$T$$beng$$erda$$epn$$cN$T$$dGW5XE$$dN$T$$dOCLCO$$dIDEBK$$dYDXCP$$dAZU 000728326 049__ $$aISEA 000728326 050_4 $$aHB871 000728326 08204 $$a304.6072$$223 000728326 24500 $$aPopulation reconstruction$$h[electronic resource] /$$cGerrit Bloothooft, Peter Christen, Kees Mandemakers, Marijn Schraagen, editors. 000728326 264_1 $$aCham :$$bSpringer,$$c2015. 000728326 300__ $$a1 online resource (x, 302 pages) :$$billustrations 000728326 336__ $$atext$$btxt$$2rdacontent 000728326 337__ $$acomputer$$bc$$2rdamedia 000728326 338__ $$aonline resource$$bcr$$2rdacarrier 000728326 500__ $$aIncludes index. 000728326 5050_ $$aPart I Data quality: cleaning and standardization -- 1 The Danish Demographic Database -- principles and methods for cleaning and standardization of data -- 2 Dutch historical toponyms in the Semantic Web -- 3 Automatic methods for coding historical occupation descriptions to standard classifications -- 4 Learning name variants from inexact high-confidence matches -- Part II Record linkage and validation -- 5 Advanced record linkage methods and privacy aspects for population reconstruction -- a survey and case studies -- 6 Reconstructing historical populations from genealogical data files -- 7 Multi-source entity resolution for genealogical data -- 8 Record linkage in the Historical Population Registry for Norway -- 9 Record linkage in Medieval and early modern texts -- Part III Life course reconstruction -- 10 Reconstructing lifespans through historical marriage records of Barcelona from the 16th and 17th centuries -- 11 Dancing with dirty data: Problems in the extraction of life-course evidence from historical censuses -- 12 Using the Canadian censuses of 1852 and 1881 for automatic data linkage: a case study of intergenerational social mobility -- 13 Introducing 'movers' into community reconstructions: linking civil registers of vital events to local and national census data: a Scottish experiment -- 14 Linking strategies for building a life course dataset from Australian convict records; Founders & Survivors: Australian Life Courses in Historical Context, 1803-1920. 000728326 506__ $$aAccess limited to authorized users. 000728326 520__ $$aThis book addresses the problems that are encountered, and solutions that have been proposed, when we aim to identify people and to reconstruct populations under conditions where information is scarce, ambiguous, fuzzy and sometimes erroneous. The process from handwritten registers to a reconstructed digitized population consists of three major phases, reflected in the three main sections of this book. The first phase involves transcribing and digitizing the data while structuring the information in a meaningful and efficient way. In the second phase, records that refer to the same person or group of persons are identified by a process of linkage. In the third and final phase, the information on an individual is combined into a reconstruction of their life course. The studies and examples in this book originate from a range of countries, each with its own cultural and administrative characteristics, and from medieval charters through historical censuses and vital registration, to the modern issue of privacy preservation. Despite the diverse places and times addressed, they all share the study of fundamental issues when it comes to model reasoning for population reconstruction and the possibilities and limitations of information technology to support this process. It is thus not a single discipline that is involved in such an endeavor. Historians, social scientists, and linguists represent the humanities through their knowledge of the complexity of the past, the limitations of sources, and the possible interpretations of information. The availability of big data from digitized archives and the need for complex analyses to identify individuals calls for the involvement of computer scientists. With contributions from all these fields, often in direct cooperation, this book is at the heart of the digital humanities, and will hopefully offer a source of inspiration for future investigations. 000728326 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed July 29, 2015). 000728326 650_0 $$aDemography. 000728326 650_0 $$aDemography$$xMethodology. 000728326 650_0 $$aPopulation research. 000728326 7001_ $$aBloothooft, Gerrit,$$eeditor. 000728326 7001_ $$aChristen, Peter,$$eeditor. 000728326 7001_ $$aMandemakers, Kees,$$eeditor. 000728326 7001_ $$aSchraagen, Marijn,$$eeditor. 000728326 852__ $$bebk 000728326 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-19884-2$$zOnline Access$$91397441.1 000728326 909CO $$ooai:library.usi.edu:728326$$pGLOBAL_SET 000728326 980__ $$aEBOOK 000728326 980__ $$aBIB 000728326 982__ $$aEbook 000728326 983__ $$aOnline 000728326 994__ $$a92$$bISE