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About Maritime careers

Seafarers are a fascinating class of workers. They form part of a dynamic labour force, characterised over the past 400 years by varying levels of internationalisation.

On this website we showcase the results of our research into the functioning of maritime labour markets and the characteristics of the seagoing workforce, and the changes these underwent over time. We’re interested in question such as: how did skill levels of seamen develop over the centuries? How international was the maritime sector? And what changes in the level of internationalisation do we witness over time? What differences can we observe between careers of native and migrant sailors?

Haven met zeilschepen en zeelieden op de kade, Reinier Nooms, 1656 - Rijksmuseum
Haven met zeilschepen en zeelieden op de kade, Reinier Nooms, 1656 – Rijksmuseum Amsterdam
Time span and sources

Currently, most of our research covers the 18th century and is based on two major datasets: Prize Papers and Dutch East India Company’s personnel records but we will also discuss other sources and aim to extent our research into the 19th and 20th century.

While Jelle van Lottum frequently posts short updates of ongoing work on his Twitter feed (also displayed on this page), this website provides more background on our research projects and the historical sources used, to be supplemented in due time with discussion of our results and links to the research data.

Grant awarded for new research into maritime careers

Samenwerkende Maritieme Fondsen (SMF), a body of six historical maritime foundations, have kindly awarded us a grant of just over € 100,000 to do new research into the life and careers of Dutch sailors. We will use this money to broaden our focus to the late nineteenth and twentieth centuries, allowing us to tell new stories about sailors (on this blog, but also in a sailors of the Dutch merchant marine), make some more cool maps, and draw lines through history. Watch this blog and Jelle’s Twitter feed for updates on the project (2019-2023).

Jelle’s Twitter announcement of the SMF grant

Visualizing networks and careers

We mostly post map visualizations of our historical data on sailors, but we’re working on other visualizations to gain insight into our data as well.

Markov models

We’ve teamed up with DHLab and Marijn Koolen (@marijnkoolen) of the KNAW-Humanities Cluster to do a thorough analysis of sailor’s careers. As a first step, Marijn produced Markov model visualization of all steps in the career data we reconstructed from the digitized VOC pay ledgers. These visualizations give very good insight into the data. The one pictured below, for example, shows the various ranks from which crew members were promoted to ‘skipper or master’ and the most frequent career steps after having served as a ‘skipper or master’ on a Dutch East Indiaman (most often: ‘end of VOC career’). It also suggests that senior boatswains always climbed up in the hierarchy to become a skipper. This is a remarkable fact, even though we have only four senior boatswains in our career clusters. Thanks to this visualization, we now know that we need to look into our data again to find out whether senior boatswains were indeed without exception very highly skilled, or that something is wrong with these clusters.

Markov model showing careers steps to and from ‘skipper or master’
Markov model showing careers steps to and from ‘skipper or master’

Network visualizations

We’re also working together with Veruska Zamborlini and Al Idrissou. They are experts on automated methods for linking entities from various datasets and subsequently validating the links. We did a pilot on our VOC career data to see if we could devise a way to automatically validate our career reconstructions, which consist of multiple observations from the digitized VOC pay ledgers: is our clustering correct, or did we sometimes wrongly link observations to one individual?

We experimented with networks around captains. They were the highest officials on board and had a significant say in the hiring of crew members. Our hypothesis was that it is likely that a captain would hire sailors that he’d sailed with on an earlier voyage to the East Indies, and that these recurring patterns would help us to validate clusters. Veruska and Al produced network visualizations like the one pictured below. So far, alas, evidence from the network analysis is too sketchy. But the experiment has inspired us to test other crew network hypotheses, so there’s more on this to come.

Recurring captain-sailor relations in Jacob Onkruijt’s network
Recurring captain-sailor relations in Jacob Onkruijt’s network

Daniel Engel: a maritime career reconstructed

Daniel Engel was a young man from ‘Dantsig’ (modern-day Gdańsk in Poland) who travelled to the Dutch Republic in the mid-18th century to apply for a job with the Dutch East India Company (VOC). We’ve written about him before (in this blog post, where we introduced the Company’s pay ledgers, one of our main data sources) and now come back to him once more. Not that Engel is so special–on the contrary, there were thousands of men like him in the ranks of the VOC–but because his story is a good case in point for illustrating our work on reconstructing maritime careers.

1766: first journey to the East Indies
Entry Daniel Engel in VOC pay ledger (1766)
Entry of Daniel Engel in the pay ledger of Dutch East Indiaman Vrouwe Anthoinetta Koenrardina (1766)

A clerk of the Delft chamber of the VOC recorded Engel’s name and birthplace in the pay ledger of a brand new ship called Vrouwe Anthoinetta Koenrardina, that would set sail for the East Indies on 1 October 1766. The VOC hired Engel as a common sailor, on a wage of seven guilders per month. This is all we can infer about the life of Daniel Engel from his employment record, but we do know more about the environment in which he would work en route to Asia. There were 300 men on board, mostly Dutchmen, as can be seen from the map below, but also quite a few men from the German lands and the Southern Netherlands, as well as a number of individuals from the coastal areas of southern Scandinavia, Malta and Batavia (modern-day Jakarta).

Birthplaces of the crew members of the 1766 journey to the East Indies of VOC ship Vrouwe Anthoinetta Koenrardina. Blue markers: sailors and maritime officers. Green markers: military personnel. Visualisation: Triply

This is an interactive map; clicking on a marker reveals employment details of a crew member. By default, the map only shows one marker per geographic location, and the Gdańsk marker is not linked to Daniel Engel. By clicking on the expand button (^) located just above the map, and changing the map setting to ‘Grouped’, it becomes visible that Engel was joined on board by one other man from his home town: Christiaan Cornelis Gerlach, who was employed as a soldier. While Engel returned to Europe on the same ship in 1768, Gerlach stayed behind in Asia, where he died on 3 August 1770.

Interrogated by the English

More than ten years later, in 1781, shortly after the beginning of the Fourth Anglo-Dutch War, a Daniel Engel from ‘Dantzick’ was taken to the Fountain Tavern in Plymouth to be interrogated after his ship had been captured by the English privateer ship Defiance (see this blog post for more on privateering during wartime). He told his questioners that he was 28 years old, worked as a boatswain on a vessel called De Keyser Josephus, and that he had lived in Rotterdam for the past thirteen years. It is likely that this Daniel Engel is the same person as the one who sailed to Asia in 1766, even though he would have been only thirteen or fourteen years old back then. He had switched to the merchant marine: De Keyser Josephus was en route from Curacao to Rotterdam, carrying a cargo of wood, hides, sugar, tobacco, cocoa, coffee and tea.

Report of interrogation of Daniel Engel. National Archives, HCA 32/383-1. Courtesy Brill.
To Asia again

It seems Daniel Engel switched back to the ranks of the VOC in the late 1780s: there are mentions of a Daniel Engel from Dantzig in VOC pay ledgers from 1788 and 1792. While he worked as a boatswain’s mate on his second voyage to the East Indies and back (he returned in the Dutch Republic in 1791), he was an able seamen on his third, from which he did not come back: Engel died in Asia, on 2 October 1798, when the VOC was already in a state of bankruptcy.

Daniel Engel did not rise high through the ranks of the VOC and the merchant marine–he died as an able seamen. By zooming out from Engel, and reconstructing careers of many more sailors, our future research will point out whether it is likely that he lacked the skills to get promoted or changing labour market conditions were to blame.

Newspaper article

Daniel Engel also featured in an article on the Dutch Prize Papers project in Dutch national newspaper Trouw!

Walking through the Prize Paper Dataset

This video provides a tour through the Prize Paper dataset using Kepler. Kepler is an amazing open source geospatial analysis tool for large-scale data sets.

Here I’ve used it get an impression of the geographical scope of the Prize Paper Dataset – focusing on the shipping connections. Every line represents the journey of an 18th century merchant ship. As you can see the main connections are intra-European and Transatlantic. We’ll make the dataset available (hopefully) sometime early next year. Please look at my twitter feed for any updates and other visualisation (maps in particular), using this dataset.

Data: Prize Papers

One of the best early-modern maritime sources is the Prize Paper Archive, an archive held at the National Archives in Kew (London). In a project that started at the University of Oxford in 2011 and later moved to Birmingham, we’ve collected data from this amazing archive to get an insight in maritime migration in the 18th century. But what are the Prize Papers, and how can we use this source to reconstruct early-modern migration patterns?

Archival box with Prize Paper documents
A box full of evidence
Lawful loot

When a Royal Navy vessel or a private man-of-war captured an enemy ship, a court needed to establish whether the vessel was in fact a lawful prize: in other words whether the ship, crew or cargo belonged to an enemy state. To determine this they collected all documents aboard a ship, as they could serve as evidence. But they also cross-examined crew members (if necessary with the help of a sworn-in interpreter) about all matters relating to the ownership of the ship and its cargo. Commonly, three crew members were questioned, usually a cross section of the ranks aboard. Furthermore, because it involved a court case, supporting material, such as the ship’s papers and other administration is also present in the same file as the corresponding interrogation (see above for a collection of documents belonging to one ship).

The captured ships and sailors

From these interrogations (the picture below shows an example), we have created a relational database, containing all the information required by the interrogation rubric and therefore consistently present in the interrogations. The database comprises two tables, one of which deals with information about the ship, such as geographical markers of its ports of origin and destination, its tonnage, the number of nationalities aboard and information about its owner. This is linked to information about the crew, since there was normally more than one crew member interrogated per vessel. The crew table includes demographic information about the individual interrogated (including place of birth, residence and location of the employer, which allows one to determine if the person in question was a migrant or not), an indicator of his literacy, his rank and the length and nature of his relationship with the master of the vessel.

Picture of the report of an interrogation of a crew member
An example of an interrogation
Insights from the crew interrogations

The interrogations exist from the end of the seventeenth up until the beginning of the nineteenth century, and are clustered around the various wars during this time frame, but such conflicts were regularly spread across the period, meaning that we can analyse change over time by looking at similar variables and comparable numbers of vessels in three clusters of years. The first cluster runs from c. 1702 to 1712, the second between 1776 an 1783, and the last between 1793 and 1803. As a consequence of this, our data on migration and mobility in the early-modern period ideally captures the growth in international trade and the increased integration of European labour markets during the eighteenth and early nineteenth centuries.

We hope to publish to dataset in 2019, but in the meantime will show some visualisations based on it! Watch this space, or follow Jelle’s twitter feed!

Presentation at the 2018 World Economic History Congress

Today we presented the paper ‘Maritime careers in the Dutch Republic: some preliminary findings’ at the 2018 World Economic History Congress (WEHC) in Boston MA. It was great to show our findings to an international audience at the session ‘Factor Costs in the Expansion of Pre-Modern Ocean Shipping: Labor, Capital, and Knowledge Transfer, 1300-1700’, organized by Maryanne Kowaleski (Fordham University).

Good career opportunities for migrant sailors

Based on quantitative analysis of our Dutch East India Company’s sailors’ careers database, we argued that the tightening native labor supply in the 18th-century Dutch Republic necessitated an influx of skilled migrant workers, and that these migrant workers were given equal opportunities compared to natives. Indeed, as shown by the graph on slide 16 (see presentation below), from the mid-18th-century, migrant workers gained (proportionally) more promotions to an officer’s rank than their Dutch counterparts.

Here are the slides we showed at the conference. Unfortunately, the animated map images on slides 6 – 8 have been rendered static when converted to SlideShare; the proper, dynamic images can be found in this blog post.

Slides shown at 2018 WEHC

How do we reconstruct sailors’ careers?

We published a paper on our methodology of reconstructing sailors’ careers in the HUMIGEC project. It’s called ‘Small Lives, Big Meanings. Expanding the Scope of Biographical Data through Entity Linkage and Disambiguation’ and was co-authored by Lodewijk Petram, Jelle van Lottum, Rutger van Koert, and Sebastiaan Derks.

The paper was originally presented at the 2017 edition of the Biographical Data in a Digital World conference, held in Linz, Austria. The maritime dataset and career reconstruction methodology serve as a use case to introduce the Huygens ING digital biographical data policy.

Where the VOC crews came from

The pay ledgers of the Dutch East India Company (VOC) are an important data source for our projects (we tell more about this source in this blog post). The following dynamic heatmaps give a good impression of the regions where the sailors on board of the ships headed for Asia originated.

Regions of origin of VOC sailors, 1630-1795
Regions of origin of VOC sailors, 1630-1795
Regions of origin of VOC soldiers, 1630-1795
Regions of origin of VOC soldiers, 1630-1795
Regions of origin of VOC naval officers, 1630-1795
Regions of origin of VOC naval (i.e. not military) officers, 1630-1795

For clarity reasons, crew members from one of the six VOC towns (Amsterdam, Delft, Enkhuizen, Hoorn, Middelburg and Rotterdam) were excluded from these maps.

Data: VOC maritime personnel records

Our research on the careers of maritime workers is based on a number of data sources, which we’ll introduce in separate blog posts. First up is a database containing the maritime personnel records of the Dutch East India Company (VOC).

In the period 1602-1795, just under 5,000 Dutch East India Company ships sailed from the Dutch Republic to Asia. Each of these kept a pay ledger, in which personal particulars and salary information for all paid crew members were registered. Not all pay ledgers have survived until today, but for the late 17th and, especially, the 18th century, the ledgers give a very good view of the (highly international) workforce of the company.

All 774,200 records in the surviving ledgers were entered into a database in a collaborative project in which a number of archives (Delft, RotterdamZeeuws archiefWestfries Archief) and the history departments of  Leiden and Ghent universities participated. The database was subsequently published on the website of the Dutch National Archives

Daniel Engel from Gdańsk

Each record contains, among other things, data on a sailor’s name, place of birth, rank on board, as well as start and end dates of the employment, and the reason why the employment ended. The image above (large version) shows the entry of Daniel Engel from ‘Dantsig’ (modern-day Gdańsk in Poland), who signed up with the Delft branch of the VOC on the first of October, 1766. He worked as an ordinary seaman during the seven-month journey to Batavia (now Jakarta), stayed there for nine months and then sailed back to Europe on the same ship. He was paid 7 guilders per month by the company. Engel was probably illiterate, as he signed with a cross.

150,000 uniquely spelled birth places

The pay ledgers were literally transcribed, resulting in the fact that the database contains more than 150,000 unique place name attestations. The Hague occurs in no less than 333 variations.

When a sailor survived the journey to Asia and back, and later re-joined the VOC, a new entry in a new pay ledger was made. Therefore, to reconstruct careers from this database, we had to link records that are (in all likelihood) related to the same individual. To facilitate the linkage (we explain our linkage methodology in this post) we tried to standardize as many place name attestations as possibly—mostly by hand. We will share the standardized birth places of more than 80 percent of the records (reconciled to GeoNames and thus also geo-referenced) at a later stage; plotted on a map, they look like this:

Map showing the global recruitment of the Dutch East India Company (VOC). Locations are weighted by number of records.
Map showing the European recruitment of the Dutch East India Company (VOC). Locations are weighted by number of records.