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Kees Mandemakers Les Grandes Bases de Données et l’Histoire Sociale des Populations Bordeaux, Université Michel de Montagne, 7-9 th of February 2008 Development,

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Presentation on theme: "Kees Mandemakers Les Grandes Bases de Données et l’Histoire Sociale des Populations Bordeaux, Université Michel de Montagne, 7-9 th of February 2008 Development,"— Presentation transcript:

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2 Kees Mandemakers Les Grandes Bases de Données et l’Histoire Sociale des Populations Bordeaux, Université Michel de Montagne, 7-9 th of February 2008 Development, database and results of the Historical Sample of the Netherlands

3 HSN -What’s the HSN ? -GENLIAS-index of civil certificates -Best practices of large databases -International data model -Historical Sample of Europe

4 HSN -What’s the HSN ? -Sources and development database -Projects - Results

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7 HSN Five periods of Investment Conceptual stage Pilot project province of Utrecht Extension pilot, first collaboratory projects Extension to the whole country Life courses 1850/

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14 Parental family On the road lodger maid servant soldier Own family Typical Sequence of Entries in Population Registers

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16 HSN IN CONNECTION WITH OUTPUT REGISTER Adding Personal Card/List RP Adding Marriage Certificates RP

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18 HSN Collaboratory projects Extension datasets -Other kind of data -Other (related) persons Upkeeping HSN-infrastructure Widening circle HSN-users

19 Migration Dutch East Indies 1820 – 1940 Ulbe Bosma Retrieving HSN-research persons - Indian archives (Directories) - Registers Military, Civil Servants - Shipping Lists etc

20 Migration Dutch East Indies 1820 – 1940 Ulbe Bosma Comparison Indian and Dutch Careers (HSN Control Group)

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24 HSN Unique position HSN.Sampling birth certificates.A whole nation (not regional).Following persons all over the country

25 HSN Spanning Past and Present (SPAN).Combination NKPS (sample ).Completing Families RP’s. Sampling and Following Siblings.Sampling from Period Reinforcement technical infrastructure (e.g. integrated SPAN-database)

26 HSN Future. Life courses Back into 18th century.Simulating census New sources: land registers, tax registers, poor law files, personal records army.Enrichment geo-referencing all addresses

27 HSN Standard HSN-data P A R E N T A L family OWN family Life career RP

28 HSN Collaboratory projects P A R E N T A L family 1st generation Life career RP 2nd generation Life career 2nd RP

29 HSN P A R E N T A L family OWN family Life career 2nd RP OWN family Life career 1st RP Collaboratory projects

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31 Index names from 2,5 million marriage certificates % 4,0 million death certificates % 2,0 million birth certificates % 0,6 million from sources before 1812

32 Coverage by index of marriage certificates N O T C O V E R E D

33 With occupational titles

34 Bride and groom Lastname, First name, Age at marriage Parents of bride and groom Lastname, First name Marriage certificates

35 Linking parents of bride and groom with their own certificate between 15 and 50 years earlier matching on combination of two persons (last name and first name) Marriage certificates

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44 Linking three or more generations ??

45 They have already been linked !!!

46 BUT HOW ?????

47 EASILY

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51 A B [= A] C [=B]

52 Chains of three generations Research on social mobility Marriages of cousins Marriages of uncles/aunts with nieces/newphews.Passing down of the age of marriage Marriage certificates

53 HSN Standard HSN-data P A R E N T A L family OWN family Life career RP

54 HSN P A R E N T A L family OWN family Life career RP

55 HSN P A R E N T A L family OWN family Life career RP

56 HSN P A R E N T A L family OWN family Life career RP

57 HSN P A R E N T A L family 1st generation Life career RP 2nd generation 3rd generation Life career 2nd RP Life career 3rd RP

58 Best practices with large databases on historical populations Historical Methods 37 (2004), nr. 1, History and Computing 13 (2001, published 2004), 2, Kees Mandemakers and Lisa Dillon

59 Best practices with large databases Purpose of the rules -Articulate standards -Trustworthy results -Benefit from previous experience -Quality standard -Read as list of recommendations

60 Best practices with large databases Three stages database-building ADefinition object and content BData entry, integration, standardization CEnrichment and release data

61 Best practices with large databases ADefinition object and content A1Description universe database A2Whole source, unless… A3Documentation each included source A4Specific rules in case of samples

62 Best practices with large databases B Data entry, integration, standardization Components Database SOURCES CENTRAL DATABASE DATA RELEASE

63 Best practices with large databases B Data entry, integration, standardization B5Distinction original and corrected data B6Clearly distinction of inferred data B7Archiving in simple format (ASCI) B8Good back-up system

64 Best practices with large databases C Enrichment and release data Values C5Standardized and original values (international standards, e.g. HISCO) C6Negative standard values missing values C7Geo-referenced data

65 Best practices with large databases C Enrichment and release Documentation C8 List of model studies C9 Easy user versions (for ‘beginners’) C10 DDI-based meta-data C11 Website database C12 Progress reports

66 HSN P A R E N T A L family OWN family Life career RP RELEASES Dissemination data

67 HSN P A R E N T A L family OWN family Life career RP EASY to handle????

68 HSN P A R E N T A L family OWN family Life career RP NO, dynamic output

69 HSN

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74 Tough nuts Dynamic output Uncertain dates Cohort/period Definition household Linking research persons

75 Dynamic Output

76 HSN UNCERTAIN DATES

77 HSN Over 20 CODES on day number 33 Arrival date based on interpretation 35 Estimated declaration occupational title, religion etc 42 Estimated change of address 44 Estimated departure (group departing) 46 Estimated departure (based on census date)

78 HSN COHORT & PERIOD

79 HSN Life career RP

80 HSN DEFINITION HOUSEHOLD or where is my RP?

81 HSN P A R E N T A L family OWN family Life career 1st RP

82 HSN P A R E N T A L family OWN family OWN family Life career 1st RP Life career 2nd RP

83 HSN P A R E N T A L family OWN family OWN family Life career 1st RP Life career 2nd RP OWN family Life career 3th RP

84 HSN P A R E N T A L family OWN family OWN family Life career 1st RP Life career 2nd RP OWN family OWN family Life career 3th RP

85 HSN Complicated but TWOSOLUTIONS Internationalising Simplifying

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96 TASK EACH DATABASE

97 LINKING appearances of persons to individuals TASK EACH DATABASE

98 LINKING appearances of persons to individuals DATING attributes TASK EACH DATABASE

99 LINKING appearances of persons to individuals DATING attributes STANDARDIZING attributes (HISCO, GIS, etc) TASK EACH DATABASE

100 LINKING appearances of persons to individuals DATING attributes STANDARDIZING attributes (HISCO, GIS, etc) ALL META-DATA TASK EACH DATABASE

101 LINKING appearances of persons to individuals DATING attributes STANDARDIZING attributes (HISCO, GIS, etc) ALL META-DATA TASK EACH DATABASE at least

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103 HSN Simplifying with HSN data-machine flat structure only main data no uncertainty documentation per variable

104 HSN Simplifying HSN data machine with Umeå Historical Sample of Europe [Clio_infra project]

105 Historical Sample of the Netherlands International Institute for Social History

106 Problems for researcher Problem of time-dependent data - more values same variable - changing environment (family structure cause as such) - age / period /cohort

107 Problems for researcher. Selection (movers / stayers/ disappearing). Fuzzy or no dating. Household definition. Multi-level data. Need for rectangularization. Analysing in a comparative way

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