Entering Stage Two: Mapping Parishes in Lothian and Tweeddale, 1560-1689

With Stage One of Mapping the Scottish Reformation nearing completion, we now have a large dataset of ministers, detailing their movements and important moments of their careers. We have parsed over 9,000 pages of manuscripts from presbyteries across the region of Lothian and Tweeddale. With these significant task complete, we can now turn our attentions to how we intend to present this data in Stage Two of the project.

Stage Two of Mapping the Scottish Reformation is generously funded by the Strathmartine Trust and will see us explore our user interfaces for the first time. Up to now, we have deposited our data onto Wikidata and used the built-in tools to test our material, to see the locations of gaps, and to create quick mock-up visuals that we think users might find useful. You can read more about our use of Wikidata mapping tools and how we structure our dataset here.

A screen grab of using the mapping tools built into the Wikidata Query Service.

Followers of the project will have seen some of the demos we have been able to quickly put together that visualise the breadth of our data and hint at some of the ways we can put it to work. Critically, Stage Two of Mapping the Scottish Reformation will use even more powerful mapping technologies to create visualisations that load faster, run more smoothly and show even more data. Before we formally embark on this process, we have spent the last couple of weeks dipping our toes into some of these more powerful mapping technologies.

The Wikidata Query Service — and the SPARQL queries we write to ask questions of our data — sits at the heart of our project. It allows our data to be open for other researchers to use (and build on) in the future, but it can also be quickly exported and patched into other programmes/services. The first stage of testing more powerful maps is to take the result of a SPARQL query, add a few modifications to the code, and export it into a TSV (tab-separated values) file.

The Wikidata Query Service allows the results of queries to be exported into various file formats

We exported a SPARQL query that shows all of the parishes in the Synod of Lothian and Tweeddale between 1560 and 1689, as well as a label that showed in which presbytery each parish sat. This has the fewest values of any of our datasets so we thought it would be an easy place to start! The resulting TSV file is effectively a huge spreadsheet: and as much as I like spreadsheets, I think it would be stretch to call it attractive or user friendly. The key thing here is that we have the latitude and longitude data in separate columns and have the key bits of information we want to display to users. Our test file included around 120 lines.

The resulting TSV file is functional, if unappealing

Formatted correctly, a TSV file like this one can be imported into GeoJSON, an open format mapping service that allows users to input geographical data and show them on maps (note: have you noticed our constant use of open source and access services?!! It’s no coincidence!). Users can either add points manually or, critically for us, add geo-referenced locations in bulk. Having uploaded the file, the result is a much more appealing map that includes more attractive and comprehensive icons and the ability to select different mapping layers. We can even add different mapping tiles, using a service like Map Tiler, enabling us to test different backgrounds.

The beauty about GeoJSON is that it transforms that ugly TSV file into something more machine readable. Unfortunately, GeoJSON doesn’t allow you to automatically export your map or embed it into a website like this one. This is where Leaflet.JS comes in.

Leaflet is quietly taking over the world of internet mapping applications, but its huge functionality comes at a significant technical cost: we aren’t in the world of drag and drop or ‘what you see is what you get’ editing anymore. The benefits of a little perseverance, however, are huge.

Leaflet demands an understanding of CSS, or at least an understanding of what to swap into lines of code cribbed from GitHub and when. This process was made infinitely easier by Leaflet’s own tutorials and, in particular, by this superb tutorial on YouTube by Eduonix. The key here is to take the code generated by GeoJSON and to copy it into our HTML file (shown below in Sublime Text markup editor). You can see how the data from GeoJSON is shown just below the various lines of code for headers etc.

After generating our map, a few fairly simply lines of code allows Leaflet to then take the data from GeoJSON and display it, as well as adding a custom mapping layer and popup menus that are, in theory, infinitely customisable. The resulting map can be exported to HTML and embedded into a website. And because the database values were all pasted into Leaflet, at least for the moment, Leaflet doesn’t have to request the info each time the page loads. The result is that the embedded map loads almost immediately.

You can play with this simple demo, showing all of the parishes of Lothian and Tweeddale between 1560 and 1689, below.

Notice that we have made use of the NLS Historical Maps API to plot the points on a historical map. This dynamically adjusts to a different background map depending on how far a user zooms in or out of the map.

If this seems like a tremendous amount of effort to go to in order to embed a map, then I suppose you’re right. What’s important here is that we have demonstrated that the data we manually took from manuscripts within the National Records of Scotland, passed into Wikidata, and then queried using SPARQL and the Wikidata Query Service, can be exported, customised and presented in a way that it as visually friendly as we can make it!

This is just a test, but it reflects the process we will go through during Stage Two of Mapping the Scottish Reformation, with colleagues from our international Advisory Board and our technical friends and colleagues at the University of Edinburgh. Ultimately, this process will allow us to create a number of interactive visualisations that will distill the months we have spent looking at handwritten archival material and make it more accessible. So while we’ve been recording, storing and querying the Scottish Reformation up to now, Stage Two of this project will allow us to start intricately mapping the Scottish Reformation.

Chris R. Langley

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