Summary information

Study title

Dutch Ships and Sailors - VOC Opvarenden as RDF

Creator

L. Heerma van Voss (Huygens ING)
V. de Boer (VU University Amsterdam)
M. van Rossum (VU University Amsterdam)
J. Leinenga (Huygens ING)
C.A. Davids (VU University Amsterdam)
J. Lucassen (International Institute of Social History (IISH) / VU University Amsterdam)
J.C.A. Schokkenbroek (The National Maritime Museum)
R. Hoekstra (Huygens ING)

Study number / PID

doi:10.17026/dans-z57-kfkq (DOI)

Dutch Ships and Sailors (DSS)

easy-dataset:57623 (DANS-KNAW)

Data access

Information not available

Series

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Abstract

Dutch Ships and Sailors is a project that aims to provide an infrastructure for maritime historical datasets, linking correlating data through semantic web technology. It brings together datasets related to recruitment and shipping in the East-India trade (mainly 18th century) and in the shipping of the northern provinces of the Netherlands (mainly 19th century). For the northern provinces, the database contains data on the personnel recruited, the ships, and other variables (muster rolls of the northern provinces of the Netherlands).

Dutch Ships and Sailors is a Clarin IV-project, hosted by Huygens ING in collaboration with VU University Amsterdam, the International Institute of Social History and Scheepvaartmuseum Amsterdam.

The data from this project are divided over 5 datasets. See the ‘Thematic collection: Dutch Ships and Sailors’ dataset for a full overview.

This dataset is a RDF/Turtle conversion of EASY dataset: "Velzen, Drs A.J.M. van; Gaastra, Prof.dr. F.S. (2012-01-26), VOC Opvarenden, versie 6 - januari 2012; VOC Sea Voyagers", Persistent Identifier: urn:nbn:nl:ui:13-gupf-pd. This source dataset contains digitized 18th century personnel administration of the VOC (Dutch East India Company) collected from archival data and processed in a relational database.

The source dataset was split into three separate parts: ‘opvarenden’, ‘soldijboeken’ and ‘begunstigden’ (voyagers, salary books and benificiaries). This substructuring was left intact in the subsequent conversions.

Topics

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Methodology

Data collection period

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Country

Time dimension

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Analysis unit

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Universe

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Sampling procedure

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Kind of data

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Data collection mode

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Access

Publisher

DANS Data Station Social Sciences and Humanities

Publication year

2014

Terms of data access

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Related publications

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