Seven Tips for Using the Trading Consequences Database and Visualization Tools

The strengths of the Trading Consequences relational database and visualization tools lie in the information they convey about the geospatial history of particular commodities. There are a variety of ways to explore the database and visualizations. But for someone unfamiliar with the tools and the information they make available, Trading Consequences can be a bit overwhelming at first. In order to help first time users and non-specialists, here’s a list of tips to help you use the tools.

Start with a commodity, not a location. Interesting information is available for specific places, but is much more limited than the information available for specific commodities. Using location searches can be useful, but only after some initial work has been done to explore a commodity.

Tip #1 – Do a Wikipedia search

It helps to have a basic familiarity with the history of the commodity you’re searching. In most cases, if you don’t already know the basics of your commodity’s history, a Wikipedia search will provide more than enough information to get the background (where it came from, what it was used for, where it was consumed/bought).

Tip #2 – Start with the big picture

After choosing a commodity to explore, start with the Location Cloud Visualization search bar. For example, here’s the result if Ivory is entered.

Ivory main

Every location listed in the cloud is a place associated with Ivory in the entire corpus of documents. Each column represents a different decade between 1800 and 1910 (left to right). Locations are listed in alphabetical order, with the largest font representing the most frequently mentioned locations for that decade.

In this case, immediately obvious is the large number of mentions related to Havana. Your initial inclination might be to pursue what appears to be an abnormal result. But hold off on that for now!

Tip #3 – Isolate individual continents

Apart from the largest words in the cloud, it’s hard to make sense of all the information on display. To begin with, use the world map at the top of the screen to isolate the results for individual continents. Hovering the mouse over different continents will highlight locations from each continent in different colours. For example, hovering the mouse over Europe will highlight in green all the places in Europe associated with Ivory in the documents. Similarly, hovering the mouse over Africa will highlight in purple all the places in Africa associated with Ivory in the documents. Ivory Africa (hover)

Hovering the mouse over a continent will also display the total number of mentions of Ivory associated with that continent in a small text box next to the mouse (e.g. the total number of mentions for Africa is 3,137).

Actually clicking on an individual continent will control the location cloud to display only the places from that continent. For example, clicking on Africa will eliminate all locations other than places in Africa.

Ivory Africa

This will make it easier to search for patterns in the location cloud. Once you’ve finished exploring one continent, simply click on the continent again to disengage the control and return to the full location cloud. You can click on any number of continents to control for different combinations (clicking on both Europe and Africa, for example, will eliminate all other continents and display locations for places in Europe and Africa alone).

Try isolating for each continent individually as well as different combinations of continents.

Tip #4 – Isolate for specific places

It may still be difficult to identify potential patterns from the location cloud for an individual continent. Hovering the mouse over particular location names in the cloud will allow you to isolate spatial and temporal patterns. Moreover, hovering the mouse over location names in the cloud reveals the number of mentions of Ivory associated with that specific place in that decade. For example, hovering the mouse over Mozambique in the location cloud reveals there are 42 mentions of Ivory during the 1850s. More importantly, most mentions of Ivory associated with Mozambique occur during the 1840s and 1850s. Ivory Mozambique (hover)

Similarly, hovering the mouse over Zanzibar (off the coast of Tanzania) reveals there are 67 mentions of Ivory during the 1900s and that most mentions of Ivory associated with Zanzibar occur between the 1870s and the 1910s.

Ivory Zanzibar (hover)

This suggests that the ivory trade was important in Mozambique during the early nineteenth century, but that trade through Zanzibar became more important toward the end of the century.

Actually clicking on a specific location in a particular decade brings up a window display of the timeline distribution of mentions of Ivory associated with that place (normalized by all commodity/location mentions from 1800-1920), as well as a short list of selected sentences from documents that feature Ivory and that location during the decade chosen.

Ivory Zanzibar (distribution)

This visualization will give you a clearer sense of the changing trends in mentions of Ivory associated with that location (in this case Zanzibar).

Tip #5 – Explore excerpts from the documents

Once you have identified what you think are likely significant trends, it makes sense to follow up your hypothesis with a quick look through excerpts from the primary source documents in which the mentions occurred. Included in the window that pops up when you click on a specific place in one of the location cloud columns is a link to a list of documents that feature Ivory and the chosen location.

For example, clicking on the Mozambique location in 1850s column of the location cloud brings up a window with a distribution of mentions and a list of selected sentences. Clicking on the link to the full document list in the pop up window opens a new page with a list of primary source documents. By clicking on the small box next to the name of the document, you can explore the sentences that feature Ivory and Mozambique in that document. The larger the box, the more mentions that document includes.

Ivory Mozambique (docs list)

Reading through these documents allows you to determine a more accurate picture of the nature of the relationship between Ivory and Mozambique during the 1850s.

Tip #6 – Explore the other end of the commodity chain

If you started with the production end of the commodity chain (i.e. Ivory comes from Africa), try exploring the consumption side of the commodity chain (i.e. places where Ivory ended up).

Instead of isolating Africa, try isolating Europe or North America. Look for similar types of patterns using the same methods described above and then follow up with the primary sources by clicking on promising-looking specific locations on the location cloud.

For example, isolating Europe in the location cloud reveals a high number of mentions associated with Lisbon (Portugal) earlier in the nineteenth century,

Ivory Lisbon (distribution)


followed by a rise in the number of mentions associated with Germany toward the end of the century.

Ivory Germany (distribution)

During the nineteenth century, Mozambique was a Portuguese colony and Germany held imperial interests (along with Britain) in Zanzibar. The patterns of mentions of Ivory in Europe, therefore, suggest a strong correlation with the patterns of mentions of Ivory associated with Africa.

Indeed a quick reading of excerpts from the documents confirms this to be the case.

In this list of documents from the 1850s, Lisbon is mentioned in relation to Mozambique and Ivory several times.

Ivory Lisbon (docs list)

Similarly, an 1888 document dealing with relations between Germany and Zanzibar mentions Ivory as a commodity key to peace negotiations.

Ivory Germany (docs list)

Tip #7 – Cross-reference with a full corpus commodity search

A separate Commodity search bar allows you to cross-reference the information obtained from your exploration of the commodity-location patterns in the Location Cloud Visualization.

For example, here’s the result if Ivory is entered.

Ivory commodity search

The list on the right contains all the documents in which Ivory is mentioned (use the ‘next’ button at the bottom to advance to the next page). This list can be narrowed down into ten year blocks by clicking on a specific decade at the bottom left (the number in brackets next to each decade denotes the number of mentions of Ivory in that decade).

Hopefully these tips will help get you started using the database and visualization tools. Trading Consequences is a great resource with a lot to offer anyone interested in global commodity flows during the nineteenth century. To use these tools effectively, however, requires several sessions in between which users must be spend time reading through the literature to confirm results and determine new avenues of enquiry to guide further use of Trading Consequences.

A Quick Exploration of Ten Nineteenth Century British Imports

During the 19th century, Britain imported hundreds of commodities from all over the world. Ten of the most important were cotton, wool, wheat, sugar, tea, butter, silk, flax, rice and guano. Below are graphs depicting the number of mentions of each of these commodities by decade and pie charts breaking down the number of mentions of each commodity by continent.

The Trading Consequences relational database and visualization tools represent extraordinary new research opportunities for historians and historical geographers. A large amount of data is presented at a glance, allowing researchers to pursue obvious lines of further inquiry as well as more obscure connections that might otherwise have been missed. The visualization component is also complemented by the ability to follow up curious or novel relationships with a read of the primary sources that populate the visualizations.

Let’s take a look at the ten commodities listed above to get a sense for what these visualizations can tell us. Both in terms of what is commonly understood about these trade items, but also in terms of new research questions, the Trading Consequences database and visualization tools provide exciting insights – even at just a glance.

A couple of notes should be borne in mind when reviewing the graphs and pie charts below. First of all, the sources are all in English. The provenance of the sources means the statistics related to mentions tend to privilege places in Britain and North America. Because most of the sources were created in Britain and North America, they also tend to privilege the consumption end of the commodity chain.

Second, the main corpus of documents used to populate the database relate to the years 1800-1900. Several collections of documents include sources from earlier and later dates, but mentions related to years before 1800 and especially after 1900 are unreliable. A decline in the number of mentions after 1900 reflects the smaller number of documents after 1900, not necessarily a decline in the significance of a given commodity.


For a little context, below is a graph depicting the top twenty commodity imports to Britain ranked by value during the second half of the nineteenth century. Some commodities, such as wool and wheat are consistently in the top twenty. Others, such as guano, appear just once. Cotton remained the most important commodity by value throughout this period, while others declined (flax) or rose (butter).

top twenty

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