of captains and related occupations
DESCRIPTION
Final presentation for the statistics exercise during the VU Semantic Web outing 2014TRANSCRIPT
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Davide’s Group:Davide, Veruska, Martine, Chris, Victor
Of Captains and related things
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Linked data
• CEDAR 1889 census (occupations)• Dutch Ships and Sailors -> Monsterrollen
database (1800-1900)
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One SPARQL query to rule them allSELECT * WHERE { ?obs <http://cedar.example.org/ns#occupation> ?occ. ?obs <http://cedar.example.org/ns#city> ?city. ?obs <http://cedar.example.org/ns#populationSize> ?num. ?city rdfs:label ?lab1. ?rank skos:exactMatch ?occ. ?pc mdb:rang ?occ. ?pc mdb:rang mdb:rang-kapitein. ?pc mdb:persoon ?pers. ?pers mdb:woonplaats ?wp. ?wp rdfs:label ?lab2. FILTER (lcase(str(?lab2)) = ?lab1)}
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Results
city cedar mdbbolsward 0 6deventer 486 1edam 192 1haarlem 642 11harlingen 0 95kampen 612 7leeuwarden 0 1middelburg 264 1norg 81 1oude pekela 1456 1279scheemda 1678 18sloten 126 2winschoten 414 95zaandam 1266 2
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Analysis in R
So.. the amount of people embarking as captains on ships during the 19th century is a bit correlated with the number of captain’s found in the 1889 census: CAPTAIN Cities!
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But where there’s sailors, there’s…
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Lichtekooien!!
(en: Public Women)
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Sparql query PREFIX cedar: <http://cedar.example.org/ns#>PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>PREFIX qb: <http://purl.org/linked-data/cube#>PREFIX cedardata: <http://cedar.example.org/resource/>PREFIX dim: <http://purl.org/linked-data/sdmx/2009/dimension#>
select ?sex (SUM(?populationSize) AS ?totalSize) where { ?x cedar:occupation cedar:hisco-54040 . ?x cedar:populationSize ?populationSize. ?x dim:sex ?sex. ?x qb:dataSet cedardata:VT-1849 } GROUP BY ?sexorder by ?totalSize
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Results
• 2260 “PUBLIC WOMEN”,
• TOTAL WOMEN 17.069.797
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Results
• 2260 “PUBLIC WOMEN”, 35 PUBLIC MEN
• TOTAL WOMEN 17.069.797
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Some Real Statistics (Martine)
H0: The percentage of ‘public women’ in 1889 in the total female population is 0.013% (based on 1849 data)
census data from 1889
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Some Real Statistics
H0: The percentage of ‘public women’ in 1889 in the total female population is 0.013% (based on 1849 data)
census data from 1889
0 PUBLIC WOMEN, 0 PUBLIC MENTOTAL WOMEN 13343598
p-value < 2.2e-16 so smaller than threshold 0.05alternative hypothesis: true p is not equal to 0.0001323976so percentage public women is NOT the same as in 1849
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Great Prostitute fire of 186X..?