Final presentation for the statistics exercise during the VU Semantic Web outing 2014

1. Davide’s Group:
Davide, Veruska, Martine, Chris, Victor
Of Captains and
related things

2. Linked data
• CEDAR 1889 census (occupations)
• Dutch Ships and Sailors -> Monsterrollen
database (1800-1900)

3. One SPARQL query to rule them all
SELECT * 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)
}

4. Results
city cedar mdb
bolsward 0 6
deventer 486 1
edam 192 1
haarlem 642 11
harlingen 0 95
kampen 612 7
leeuwarden 0 1
middelburg 264 1
norg 81 1
oude pekela 1456 1279
scheemda 1678 18
sloten 126 2
winschoten 414 95
zaandam 1266 2

5. 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!

6. But where there’s sailors, there’s…

7. Lichtekooien!!

8. 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 ?sex
order by ?totalSize

9. Results
• 2260 “PUBLIC WOMEN”,
• TOTAL WOMEN 17.069.797

10. Results
• 2260 “PUBLIC WOMEN”, 35 PUBLIC MEN
• TOTAL WOMEN 17.069.797

11. 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

12. 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 MEN
TOTAL WOMEN 13343598
p-value < 2.2e-16 so smaller than threshold 0.05
alternative hypothesis: true p is not equal to 0.0001323976
so percentage public women is NOT the same as in 1849

13. Great Prostitute fire of 186X..?