Week Beginning 10th January 2022

I continued to work on the Books and Borrowing project for a lot of this week, completing some of the tasks I began last week and working on some others.  We ran out of server space for digitised page images last week, and although I freed up some space by deleting a bunch of images that were no longer required we still have a lot of images to come.  The team estimates that a further 11,575 images will be required.  If the images we receive for these pages are comparable to the ones from the NLS, which average around 1.5Mb each, then 30Gb should give us plenty of space.  However, after checking through the images we’ve received from other digitisation units it turns out that the  NLS images are a vit of an outlier in term of file size and generally 8-10Mb is more usual.  If we use this as an estimate then we would maybe require 120Gb-130Gb of additional space.  I did some experiments with resizing and changing the image quality of one of the larger images, managing to bring an 8.4Mb image down to 2.4Mb while still retaining its legibility.  If we apply this approach to the tens of thousands of larger images we have then this would result in a considerable saving of storage.  However, Stirling’s IT people very kindly offered to give us a further 150Gb of space for the images so this resampling process shouldn’t be needed for now at least.

Another task for the project this week was to write a script to renumber the folio numbers for the 14 volumes from the Advocates Library that I noticed had irregular numbering.  Each of the 14 volumes had different issues with their handwritten numbering, so I had to tailor my script to each volume in turn, and once the process was complete the folio numbers used to identify page images in the CMS (and eventually in the front-end) entirely matched the handwritten numbers for each volume.

My next task for the project was to import the records for several volumes from the Royal High School of Edinburgh but I ran into a bit of an issue.  I had previously been intending to extract the ‘item’ column and create a book holding record and a single book item record for each distinct entry in the column.  This would then be associated with all borrowing records in RHS that also feature this exact ‘item’.  However, this is going to result in a lot of duplicate holding records due to the contents of the ‘item’ column including information about different volumes of a book and/or sometimes using different spellings.

For example, in SL137142 the book ‘Banier’s Mythology’ appears four times as follows (assuming ‘Banier’ and ‘Bannier’ are the same):

  1. Banier’s Mythology v. 1, 2
  2. Banier’s Mythology v. 1, 2
  3. Bannier’s Myth 4 vols
  4. Bannier’s Myth. Vol 3 & 4

My script would create one holding and item record for ‘Banier’s Mythology v. 1, 2’ and associate it with the first two borrowing records but the 3rd and 4th items above would end up generating two additional holding / item records which would then be associated with the 3rd and 4th borrowing records.

No script I can write (at least not without a huge amount of work) would be able to figure out that all four of these books are actually the same, or that there are actually 4 volumes for the one book, each requiring its own book item record, and that volumes 1 & 2 need to be associated with borrowing records 1&2 while all 4 volumes need to be associated with borrowing record 3 and volumes 3&4 need to be associated with borrowing record 4.  I did wonder whether I might be able to automatically extract volume data from the ‘item’ column but there is just too much variation.

We’re going to have to tackle the normalisation of book holding names and the generation of all required book items for volumes at some point and this either needs to be done prior to ingest via the spreadsheets or after ingest via the CMS.

My feeling is that it might be simpler to do it via the spreadsheets before I import the data.  If we were to do this then the ‘Item’ column would become the ‘original title’ and we’d need two further columns, one for the ‘standardised title’ and one listing the volumes, consisting of a number of each volume separated with a comma.  With the above examples we would end up with the following (with a | representing a column division):

  1. Banier’s Mythology v. 1, 2 | Banier’s Mythology | 1,2
  2. Banier’s Mythology v. 1, 2 | Banier’s Mythology | 1,2
  3. Bannier’s Myth 4 vols | Banier’s Mythology | 1,2,3,4
  4. Bannier’s Myth. Vol 3 & 4 | Banier’s Mythology | 3,4

If each sheet of the spreadsheet is ordered alphabetically by the ‘item’ column it might not take too long to add in this information.  The additional fields could also be omitted where the ‘item’ column has no volumes or different spellings.  E.g. ‘Hederici Lexicon’ may be fine as it is.  If the ‘standardised title’ and ‘volumes’ columns are left blank in this case then when my script reaches the record it will know to use ‘Hederici Lexicon’ as both original and standardised titles and to generate one single unnumbered book item record for it.  We agreed that normalising the data prior to ingest would be the best approach and I will therefore wait until I receive updated data before I proceed further with this.

Also this week I generated a new version of a spreadsheet containing the records for one register for Gerry McKeever, who wanted borrowers, book items and book holding details to be included in addition to the main borrowing record.  I also made a pretty major update to the CMS to enable books and borrower listings for a library to be filtered by year of borrowing in addition to filtering by register.  Users can either limit the data by register or year (not both).  They need to ensure the register drop-down is empty for the year filter to work, otherwise the selected register will be used as the filter.  On either the ‘books’ or ‘borrowers’ tab in the year box they can add either a single year (e.g. 1774) or a range (e.g. 1770-1779).  Then when ‘Go’ is pressed the data displayed is limited to the year or years entered.  This also includes the figures in the ‘borrowing records’ and ‘Total borrowed items’ columns.  Also, the borrowing records listed when a related pop-up is opened will only feature those in the selected years.

I also worked with Raymond in Arts IT Support and Geert, the editor of the Anglo-Norman Dictionary to complete the process of migrating the AND website to the new server.  The website (https://anglo-norman.net/) is now hosted on the new server and is considerably faster than it was previously.  We also took the opportunity the launch the Anglo-Norman Textbase, which I had developed extensively a few months ago.  Searching and browsing can be found here: https://anglo-norman.net/textbase/ and this marks the final major item in my overhaul of the AND resource.

My last major task of the week was to start work on a database of ultrasound video files for the Speech Star project.  I received a spreadsheet of metadata and the video files from Eleanor this week and began processing everything.  I wrote a script to export the metadata into a three-table related database (speakers, prompts and individual videos of speakers saying the prompts) and began work on the front-end through which this database and the associated video files will be accessed.  I’ll be continuing with this next week.

In addition to the above I also gave some advice to the students who are migrating the IJOSTS journal over the WordPress, had a chat with the DSL people about when we’ll make the switch to the new API and data, set up a WordPress site for Joanna Kopaczyk for the International Conference on Middle English, upgraded all of the WordPress sites I manage to the latest version of WordPress, made a few tweaks to the 17th Century Symposium website for Roslyn Potter, spoke to Kate Simpson in Information Studies about speaking to her Digital Humanities students about what I do and arranged server space to be set up for the Speak For Yersel project website and the Speech Star project website.  I also helped launch the new Burns website: https://burnsc21-letters-poems.glasgow.ac.uk/ and updated the existing Burns website to link into it via new top-level tabs.  So a pretty busy week!

Week Beginning 3rd January 2022

This was my first week back after the Christmas holidays, and it was a three-day week.  I spent the days almost exclusively on the Books and Borrowing project.  We had received a further batch of images for 23 library registers from the NLS, which I needed to download from the NLS’s server and process.  This involved renaming many thousands of images via a little script I’d written in order to give the images more meaningful filenames and stripping out several thousand images of blank pages that had been included but are not needed by the project.  I then needed to upload the images to the project’s web server and then generate all of the necessary register and page records in the CMS for each page image.

I also needed up update the way folio numbers were generated for the registers.  For the previous batch of images from the NLS I had just assigned the numerical part of the image’s filename as the folio number, but it turns out that most of the images have a hand-written page number in the top-right which starts at 1 for the first actual page of borrowing records.  There are usually a few pages before this, and these need to be given Roman numerals as folio numbers.  I therefore had to write another script that would take into consideration the number of front-matter pages in each register, assign Roman numerals as folio numbers to them and then begin the numbering of borrowing record pages from 1 after that, incrementing through the rest of the volume.

I guess it was inevitable with data of this sort, but I ran into some difficulties whilst processing it.  Firstly, there were some problems with the Jpeg images the NLS had sent for two of the volumes.  These didn’t match the Tiff images for the volumes, with each volume having an incorrect number of files.  Thankfully the NLS were able to quickly figure out what had gone wrong and were able to supply updated images.

The next issue to crop up occurred when I began to upload the images to the server.  After uploading about 5Gb of images the upload terminated, and soon after that I received emails from the project team saying they were unable to log into the CMS.  It turns out that the server had run out of storage.  Each time someone logs into the CMS the server needs a tiny amount of space to store a session variable, but there wasn’t enough space to store this, meaning it was impossible to log in successfully.  I emailed the IT people at Stirling (Where the project server is located) to enquire about getting some further space allocated but I haven’t heard anything back yet.  In the meantime I deleted the images from the partially uploaded volume which freed up enough space to enable the CMS to function again.  I also figured out a way to free up some further space:  The first batch of images from the NLS also included images of blank pages across 13 volumes – several thousand images.  It was only after uploading these and generating page records that we had decided to remove the blank pages, but I only removed the CMS records for these pages – the image files were still stored on the server.  I therefore wrote another script to identify and delete all of the blank page images from the first batch that was uploaded, which freed up 4-5Gb of space from the server, which was enough to complete the upload of the second batch of registers from the NLS.  We will still need more space, though, as there are still many thousands of images left to add.

I also took the opportunity to update the folio numbers of the first batch of NLS registers to bring them into line with the updated method we’d decided on for the second batch (Roman numerals for front-matter and then incrementing page numbers from the first page of borrowing records).  I wrote a script to renumber all of the required volumes, which was mostly a success.

However, I also noticed that the automatically generated folio numbers often became out of step with the hand-written folio numbers found in the top-right corner of the images.  I decided to go through each of the volumes to identify all that became unaligned and to pinpoint on exactly which page or pages the misalignment occurred.  This took some time as there were 32 volumes that needed checked, and each time an issue was spotted I needed to look back through the pages and associated images from the last page until I found the point where the page numbers correctly aligned.  I discovered that there were numbering issues with 14 of the 32 volumes, mainly due to whoever wrote the numbers in getting muddled.  There are occasions where a number is missed, or a number is repeated.  In once volume the page numbers advance by 100 from one page to the next.  It should be possible for me to write a script that will update the folio numbers to bring them into alignment with the erroneous handwritten numbers (for example where a number is repeated these will be given ‘a’ and ‘b’ suffixes).  I didn’t have time to write the script this week but will do so next week.

Also for the project this week I looked through the spreadsheet of borrowing records from the Royal High School of Edinburgh that one of the RAs has been preparing.  I had a couple of questions about the spreadsheet, and I’m hoping to be able to process it next week.  I also exported the records from one register for Gerry McKeever to work on, as these records now need to be split across two volumes rather than one.

Also this week I had an email conversation with Marc Alexander about a few issues, during which he noted that the Historical Thesaurus website was offline.  Further investigation revealed that the entire server was offline, meaning several other websites were down too.  I asked Arts IT Support to look into this, which took a little time as it was a physical issue with the hardware and they were all still working remotely.  However, the following day they were able to investigate and address the issue, which they reckon was caused by a faulty network port.

Week Beginning 20th December 2021

This was the last week before Christmas and it’s a four-day week as the University has generously given us all an extra day’s holiday on Christmas Eve.  I also lost a bit of time due to getting my Covid booster vaccine on Wednesday.  I was booked in for 9:50 and got there at 9:30 to find a massive queue snaking round the carpark.  It took an hour to queue outside, plus about 15 minutes inside, but I finally got my booster just before 11.  The after-effects kicked in during Wednesday night and I wasn’t feeling great on Thursday, but I managed to work.

My major task of the week was to deal with the new Innerpeffray data for the Books and Borrowing project.  I’d previously uploaded data from an existing spreadsheet in the early days of the project, but it turns out that there were quite a lot of issues with the data and therefore one of the RAs has been creating a new spreadsheet containing reworked data.  The RA Kit got back to me this week after I’d checked some issues with her last week and I therefore began the process of deleting the existing data and importing the new data.

I was a pretty torturous process but I managed to finish deleting the existing Innerpeffray data and imported the new data.  This required a pretty complex amount of processing and checking via a script I wrote this week.  I managed to retain superscript characters in the transcriptions, something that proved to be very tricky as there is no way to find and replace superscript characters in Excel.  Eventually I ended up copying the transcription column into Word, then saving the table as HTML, stripping out all of the rubbish Word adds in when it generates an HTML file and then using this resulting file alongside the main spreadsheet file that I saved as a CSV.  After several attempts at running the script on my local PC, then fixing issues, then rerunning, I eventually reckoned the script was working as it should – adding page, borrowing, borrower, borrower occupation, book holding and book item records as required.  I then ran the script on the server and the data is now available via the CMS.

There were a few normalised occupations that weren’t right and I updated these.  There were also 287 standardised titles that didn’t match any existing book holding records in Innerpeffray.  For these I created a new holding record and (if there’s an ESTC number) linked to a corresponding edition.

Also this week I completed work on the ‘Guess the Category’ quizzes for the Historical Thesaurus.  Fraser had got back to me about the spreadsheets of categories and lexemes that might cause offence and should therefore never appear in the quiz.  I added a new ‘inquiz’ column to both the category and lexeme table which has been set to ‘N’ for each matching category and lexeme.  I also updated the code behind the quiz so that only categories and lexemes with ‘inquiz’ set to ‘Y’ are picked up.

The category exclusions are pretty major – a total of 17,111 are now excluded.  This is due to including child categories where noted, and 8340 of these are within ’03.08 Faith’.  For lexemes there are a total of 2174 that are specifically noted as excluded based on both tabs of the spreadsheet (but note that all lexemes in excluded categories are excluded by default – a total of 69099).  The quiz picks a category first and then a lexeme within it, so there should never be a case where a lexeme in an excluded category is displayed.  I also ensured that when a non-noun category is returned if there isn’t a full trail of categories (because there isn’t a parent in the same part of speech) then the trail is populated from the noun categories instead.

The two quizzes (a main one and an Old English one) are now live and can be viewed here:

https://ht.ac.uk/guess-the-category/

https://ht.ac.uk/guess-the-oe-category/

Also this week I made a couple of tweaks to the Comparative Kingship place-names systems, adding in Pictish as a language and tweaking how ‘codes’ appear in the map.  I also helped Raymond migrate the Anglo-Norman Dictionary to the new server that was purchased earlier this year.  We had to make a few tweaks to get the site to work at a temporary URL but it’s looking good now.  We’ll update the DNS and make the URL point to the new server in the New Year.

That’s all for this year.  If there is anyone reading this (doubtful, I know) I wish you a merry Christmas and all the best for 2022!

Week Beginning 13th December 2021

My big task of the week was to return to working for the Speak For Yersel project after a couple of weeks when my services haven’t been required.  I had a meeting with PI Jennifer Smith and RA Mary Robinson on Monday where we discussed the current status of the project and the tasks I should focus on next.  Mary had finished work on the geographical areas we are going to use.  These are based on postcode areas but a number of areas have been amalgamated.  We’ll use these to register where a participant is from and also to generate a map marker representing their responses at a random location within their selected area based on the research I did a few weeks ago about randomly positioning a marker in a polygon.

The original files that Mary sent me were plus two exports from ArcGIS as JSON and GeoJSON.  Unfortunately both files used a different coordinates system rather than latitude and longitude, the GeoJSON file didn’t include any identifiers for the areas so couldn’t really be used and while the JSON file looked promising when I tried to use it in Leaflet it gave me an ‘invalid GeoJSON object’ error.  Mary then sent me the original ArcGIS file for me to work with and I spent some time in ArcGIS figuring out how to export the shapefile data as GeoJSON with latitude and longitude.

Using ArcGIS I exported the data by typing in ‘to json’ in the ‘Geoprocessing’ pane on the right of the map then selecting ‘Features to JSON’.  I selected ‘output to GeoJSON’ and also checked ‘Project to WGS_1984’ which converts the ArcGIS coordinates to latitude and longitude.  When not using the ‘formatted JSON option’ (which adds in line breaks and tabs) this gave me a file size of 115Mb.  As a starting point I created a Leaflet map that uses this GeoJSON file but I ran into a bit of a problem:  the data takes a long time to load into the map – about 30-60 seconds for me – and the map feels a bit sluggish to navigate around even after it’s loaded in. And this is without there being any actual data.  The map is going to be used by school children, potentially on low-spec mobile devices connecting to slow internet services (or even worse, mobile data that they may have to pay for per MB).  We may have to think about whether using these areas is going to be feasible.  A option might be to reduce the detail in the polygons, which would reduce the size of the JSON file.  The boundaries in the current file are extremely detailed and each twist and turn in the polygon requires a latitude / longitude pair in the data, and there are a lot of twists and turns.  The polygons we used in SCOSYA are much more simplified (see for example https://scotssyntaxatlas.ac.uk/atlas/?j=y#9.75/57.6107/-7.1367/d3/all/areas) but would still suit our needs well enough.  However, manually simplifying each and every polygon would be a monumental and tedious task.  But perhaps there’s a method in ArcGIS that could do this for us.  There’s a tool called ‘Simplify Polygon’: https://desktop.arcgis.com/en/arcmap/latest/tools/cartography-toolbox/simplify-polygon.htm which might work.

I spoke to Mary about this and she agreed to experiment with the tool.  Whilst she worked on this I continued to work with the data.  I extracted all of the 411 areas and stored these in a database, together with all 954 postcode components that are related to these areas.  This will allow us to generate a drop-down list of options as the user types – e.g.  type in ‘G43’ and options ‘G43 2’ and ‘G43 3’ will appear, and both of these are associated with ‘Glasgow South’.

I also wrote a script to generate sample data for each of the 411 areas using the ‘turf.js’ script I’d previously used.  For each of the 411 areas a random number of markers between 0 and 100 are generated and stored in the database, each with a random rating of between 1 and 4.  This has resulted in 19946 sample ratings, which I then added to the map along with the polygonal area data, as you can see here:

Currently these are given the colours red=1, orange=2, light blue=3, dark blue=4, purely for test purposes.  As you can see, including almost 20,000 markers swamps the map when it’s zoomed out, but when you zoom in things look better.  I also realised that we might not even need to display the area boundaries to users.  They can be used in the background to work out where a marker should be positioned (as is the case with the map above) but perhaps they’re not needed for any other reasons?  It might be sufficient to include details of area in a popup or sidebar and if so we might not need to rework the areas at all.

However, whilst working on this Mary had created four different versions of the area polygons using four different algorithms.  These differ in how the simplify the polygons and therefore result in different boundaries – some missing out details such as lochs and inlets.  All four versions were considerably smaller in file size than the original, ranging from 4Mb to 20Mb.  I created new maps for each of the four simplified polygon outputs.  For each of these I regenerated new random marker data.  For algorithms ‘DP’ and ‘VW’ I limited the number of markers to between 0 and 20 per area, giving around 4000 markers in each map.  For ‘WM’ and ‘ZJ’ I limited the number to between 0 and 50 per area, giving around 10,000 markers per map.

All four new maps look pretty decent to me, with even the smaller JSON files (‘DP’ and ‘VW’) containing a remarkable level of detail.  I think the ‘DP’ one might be the one to go for.  It’s the smallest (just under 4MB compared to 115MB for the original) yet also seems to have more detail than the others.  For example for the smaller lochs to the east of Loch Ness the original and ‘DP’ include the outline of four lochs while the other three only include two.  ‘DP’ also includes more of the smaller islands around the Outer Hebrides.

We decided that we don’t need to display the postcode areas on the map to users but instead we’ll just use these to position the map markers.  However, we decided that we do want to display the local authority area so people have a general idea of where the markers are positioned.  My next task was to add these in.  I downloaded the administrative boundaries for Scotland from here: https://raw.githubusercontent.com/martinjc/UK-GeoJSON/master/json/administrative/sco/lad.json as referenced on this website: https://martinjc.github.io/UK-GeoJSON/ and added them into my ‘DP’ sample map, giving the boundaries a dashed light green that turns a darker green when you hover over the area, as you can see from the screenshot below:

Also this week I added in a missing text to the Anglo-Norman Dictionary’s Textbase.  To do this I needed to pass the XML text through several scripts to generate page records and all of the search words and ‘keyword in context’ data for search purposes.  I also began to investigate replacing the Innerpeffray data for Books and Borrowing with a new dataset that Kit has worked on.  This is going to be quite a large and complicated undertaking and after working through the data I had a set of questions to ask Kit before I proceeded to delete any of the existing data.  Unfortunately she is currently on jury duty so I’ll need to wait until she’s available again before I can do anything further.  Also this week a huge batch of images became available to us from the NLS and I spent some time downloading these and moving them to an external hard drive as they’d completely filled up the hard drive of my PC.

I also spoke to Fraser about the new radar diagrams I had been working on for the Historical Thesaurus and also about the ‘guess the category’ quiz that we’re hoping to launch soon.  Fraser sent on a list of categories and words that we want to exclude from the quiz (anything that might cause offence) but I had some questions about this that will need clarification before I take things further.  I’d suggested to Fraser that I could update the radar diagrams to include not only the selected category but also all child categories and he thought this would be worth investigating so I spent some time updating the visualisations.

I was a little worried about the amount of processing that would be required to include child categories but thankfully things seem pretty speedy, even when multiple top-level categories are chosen.  See for example the visualisation of everything within ‘Food and drink’, ‘Faith’ and ‘Leisure’:

This brings back many tens of thousands of lexemes but doesn’t take too long to generate.  I think including child categories will really help make the visualisations more useful as we’re now visualising data at a scale that’s very difficult to get a grasp on simply by looking at the underlying words.  It’s interesting to note in the above visualisation how ‘Leisure’ increases in size dramatically throughout the time periods while ‘Faith’ shrinks in comparison (but still grows overall).  With this visualisation the ‘totals’ rather than the ‘percents’ view is much more revealing.

Week Beginning 6th December 2021

I spent a bit of time this week writing as second draft of a paper for DH2022 after receiving feedback from Marc.  This one targets ‘short papers’ (500-750 words) and I managed to get it submitted before the deadline on Friday.  Now I’ll just need to see if it gets accepted – I should find out one way or the other in February.  I also made some further tweaks to the locution search for the Anglo-Norman Dictionary, ensuring that when a term appears more than once the result is repeated for each occurrence, appearing in the results grouped by each word that matches the term.  So for example ‘quatre tempres, tens’ now appears twice, once amongst the ‘tempres’ and once amongst the ‘tens’ results.

I also had a chat with Heather Pagan about the Irish Dictionary eDIL (http://www.dil.ie/) who are hoping to rework the way they handle dates in a similar way to the AND.  I said that it would be difficult to estimate how much time it would take without seeing their current data structure and getting more of an idea of how they intend to update it, and also what updates would be required to their online resource to incorporate the updated date structure, such as enhanced search facilities and whether further updates to their resource would also be part of the process.  Also whether any back-end systems would also need to be updated to manage the new data (e.g. if they have a DMS like the AND).

Also this week I helped out with some issues with the Iona place-names website just before their conference started on Thursday.  Someone had reported that the videos of the sessions were only playing briefly and then cutting out, but they all seemed to work for me, having tried them on my PC in Firefox and Edge and on my iPad in Safari.  Eventually I managed to replicate the issue in Chrome on my desktop and in Chrome on my phone, and it seemed to be an issue specifically related to Chrome, and didn’t affect Edge, which is based on Chrome.  The video file plays and then cuts out due to the file being blocked on the server.  I can only assume that the way Chrome accesses the file is different to other browsers and it’s sending multiple requests to the server which is then blocking access due to too many requests being sent (the console in the browser shows a 403 Forbidden error).  Thankfully Raymond at Arts IT Support was able to increase the number of connections allowed per browser and this fixed the issue.  It’s still a bit of a strange one, though.

I also had a chat with the DSL people about when we might be able to replace the current live DSL site with the ‘new’ site, as the server the live site is on will need to be decommissioned soon.  I also had a bit of a catch-up with Stevie Barrett, the developer in Celtic and Gaelic, and had a video call with Luca and his line-manager Kirstie Wild to discuss the current state of Digital Humanities across the College of Arts.  Luca does a similar job to me at college-level and it was good to meet him and Kirstie to see what’s been going on outside of Critical Studies.  I also spoke to Jennifer Smith about the Speak For Yersel project, as I’d not heard anything about it for a couple of weeks.  We’re going to meet on Monday to take things further.

I spent the rest of the week working on the radar diagram visualisations for the Historical Thesaurus, completing an initial version.  I’d previously created a tree browser for the thematic headings, as I discussed last week.  This week I completed work on the processing of data for categories that are selected via the tree browser.  After the data is returned the script works out which lexemes have dates that fall into the four periods (e.g. a word with dates 650-9999 needs to appear in all four periods).  Words are split by Part of speech, and I’ve arranged the axes so that N, V, Aj and Av appear first (if present), with any others following on.  All verb categories have also been merged.

I’m still not sure how widely useful these visualisations will be as they only really work for categories that have several parts of speech.  But there are some nice ones.  See for example a visualisation of ‘Badness/evil’, ‘Goodness, acceptability’ and ‘Mediocrity’ which shows words for ‘Badness/evil’ being much more prevalent in OE and ME while ‘Mediocrity’ barely registers, only for it and ‘Goodness, acceptability’ to grow in relative size EModE and ModE:

I also added in an option to switch between visualisations which use total counts of words in each selected category’s parts of speech and visualisations that use percentages.  With the latter the scale is fixed at a maximum of 100% across all periods and the points on the axes represent the percentage of the total words in a category that are in a part of speech in your chosen period.  This means categories of different sizes are more easy to compare, but does of course mean that the relative sizes of categories is not visualised.  I could also add a further option that fixes the scale at the maximum number of words in the largest POS so the visualisation still represents relative sizes of categories but the scale doesn’t fluctuate between periods (e.g. if there are 363 nouns for a category across all periods then the maximum on the scale would stay fixed at 363 across all periods, even if the maximum number of nouns in OE (for example) is 128.  Here’s the above visualisation using the percentage scale:

The other thing I did was to add in a facility to select a specific category and turn off the others.  So for example if you’ve selected three categories you can press on a category to make it appear bold in the visualisation and to hide the other categories.  Pressing on a category a second time reverts back to displaying all.  Your selection is remembered if you change the scale type or navigate through the periods.  I may not have much more time to work on this before Christmas, but the next thing I’ll do is to add in access to the lexeme data behind the visualisation.  I also need to fix a bug that is causing the ModE period to be missing a word in its counts sometimes.

 

Week Beginning 29th November 2021

I participated in the UCU strike action on Wednesday to Friday this week, so it was a two-day working week for me.  During this time I gave some help to the students who are migrating the International Journal of Scottish Theatre and Screen and talked to Gerry Carruthers about another project he’s hoping to put together.  I also passed on information about the DNS update to the DSL’s IT people, added a link to the DSL’s new YouTube site to the footer of the DSL site and dealt with a query regarding accessing the DSL’s Google Analytics data.  I also spoke with Luca about arranging a meeting with him and his line manager to discuss digital humanities across the college and updated the listings for several Android apps that I created a few years ago that had been taken down due to their information being out of date.  As central IT services now manages the University Android account I hadn’t received notifications that this was going to take place.  Hopefully the updates have done the trick now.

Other than this I made some further updates to the Anglo-Norman Dictionary’s locution search that I created last week.  This included changing the ordering to list results by the word that was search for rather than by headword, changing the way the search works so that a wildcard search such as ‘te*’ now matches the start of any word in the locution phrase rather than just the first work and fixing a number of bugs that had been spotted.

I spent the rest of my available time starting to work on an interactive version of the radar diagram for the Historical Thesaurus.  I’d made a static version of this a couple of months ago which looks at a the words in an HT category by part of speech and visualises how the numbers of words in each POS change over time.  What I needed to do was find a way to allow users to select their own categories to visualise.  We had decided to use the broader Thematic Categories for the feature rather than regular HT categories so my first task was to create a Thematic Category browser from ‘AA The World’ to ‘BK Leisure’.  It took a bit of time to rework the existing HT category browser to work with thematic categories, and also to then enable the selection of multiple categories by pressing on the category name.  Selected categories appear to the right of the browser, and I added in an option to remove a selected category if required.  With this in place I began work on the code to actually grab and process the data for the selected categories.  This finds all lexemes and their associated dates for each lexeme in each HT category in each of the selected thematic categories.  For now the data is just returned and I’m still in the middle of processing the dates to work out which period each word needs to appear in.  I’ll hopefully find some time to continue with this next week.  Here’s a screenshot of the browser:

Week Beginning 22nd November 2021

I spent a bit of time this week writing an abstract for the DH2022 conference.  I wrote about how I rescued the data for the Anglo-Norman Dictionary in order to create the new AND website.  The DH abstracts are actually 750-1000 words long so it took a bit of time to write.  I have sent it on to Marc for feedback and I’ll need to run it by the AND editors before submission as well (if it’s worth submitting).  I still don’t know whether there would be sufficient funds for me to attend the event, plus the acceptance rate for papers is very low, so I’ll just need to see how this develops.

Also this week I participated in a Zoom call for the DSL about user feedback and redeveloping the DSL website.  It was a pretty lengthy call, but it was interesting to be a part of.  Marc mentioned a service called Hotjar (https://www.hotjar.com/) that allows you to track how people use your website (e.g. tracking their mouse movements) and this seemed like an interesting way of learning about how an interface works (or doesn’t).  I also had a conversation with Rhona about the updates to the DSL DNS that need to be made to improve the security or their email systems.  Somewhat ironically, recent emails from their IT people had ended up in my spam folder and I hadn’t realised they were asking me for further changes to be made, which unfortunately has caused a delay.

I spoke to Gerry Carruthers about another new project he’s hoping to set up, and we’ll no doubt be having a meeting about this in the coming weeks.  I also gave some advice to the students who are migrating the IJOSTS articles to WordPress too and made some updates to the Iona Placenames website in preparation for their conference.

For the Anglo-Norman Dictionary I fixed an issue with one of the textbase texts that had duplicate notes in one of its pages and then I worked on a new feature for the DMS that enables the editors to search the phrases contained in locutions in entries.  Editors can either match locution phrases beginning with a term (e.g. ta*), ending with a term (e.g. *de) or without a wildcard the term can appear anywhere in the phrase.  Other options found on the public site (e.g. single character wildcards and exact matches) are not included in this search.

The first time a search is performed the system needs to query all entries to retrieve only those that feature a locution.  These results are then stored in the session for use the next time a search is performed.  This means subsequent searches in a session should be quicker, and also means if the entries are updated between sessions to add or remove locutions the updates will be taken into consideration.

Search results work in a similar way to the old DMS option:  Any matching locution phrases are listed, together with their translations if present (if there are multiple senses / subsenses for a locution then all translations are listed, separated by a ‘|’ character).  Any cross references appear with an arrow and then the slug of the cross referenced entry.  There is also a link to the entry the locution is part of, which opens in a new tab on the live site.  A count of the total number of entries with locutions, the number of entries your search matched a phrase in and the total number of locutions is displayed above the results.

I spent the rest of the week working on the Speak For Yersel project.  We had a Zoom call on Monday to discuss the mockups I’d been working on last week and to discuss the user interface that Jennifer and Mary would like me to develop for the site (previous interfaces were just created for test purposes).  I spent the rest of my available time developing a further version of the grammar exercise with the new interface, that included logos, new fonts and colour schemes, sections appearing in different orders and an overall progress bar for the full exercise rather than individual ones for the questionnaire and the quiz sections.

I added in UoG and AHRC logos underneath the exercise area and added both an ‘About’ and ‘Activities’ menu items with ‘Activities’ as the active item.  The active state of the menu wasn’t mentioned in the document but I gave it a bottom border and made the text green not blue (but the difference is not hugely noticeable).  This is also used when hovering over a menu item.  I made the ‘Let’s go’ button blue not green to make it consistent with the navigation button in subsequent stages.  When a new stage loads the page now scrolls to the top as on mobile phones the content was changing but the visible section remained as it was previously, meaning the user had to manually scroll up.  I also retained the ‘I would never say that!’ header in the top-left corner of all stages rather than having ‘activities’ so it’s clearer what activity the user is currently working on.  For the map in the quiz questions I’ve added the ‘Remember’ text above the map rather than above the answer buttons as this seemed more logical and on the quiz the map pane scrolls up and scrolls down when the next question loads so as to make it clearer that it’s changed.  Also, the quiz score and feedback text now scroll down one after the other and in the final ‘explore’ page the clicked on menu item now remains highlighted to make it clearer which map is being displayed.  Here’s a screenshot of how the new interface looks:

Week Beginning 15th November 2021

I had an in-person meeting for the Historical Thesaurus on Tuesday this week – the first such meeting I’ve had since the first lockdown began.  It was a much more enjoyable experience than Zoom-based calls and we had some good discussions about the current state of the HT and where we will head next.  I’m going to continue to work on my radar chart visualisations when I have the time and we will hopefully manage to launch a version of the quiz before Christmas.  There has also been some further work on matching categories and we’ll be looking into this in the coming months.

We also discussed the Digital Humanities conference, which will be taking place in Tokyo next summer.  This is always a really useful conference for me to attend and I wondered about writing a paper about the redevelopment of the Anglo-Norman Dictionary.  I’m not sure at this point whether we would be able to afford to send me to the conference, and the deadline for paper submission is the end of this month.  I did start looking through these blog posts and I extracted all of the sections that relate to the redevelopment of the site.  It’s almost 35,000 words over 74 pages, which shows you how much effort has gone into the redevelopment process.

I also had a meeting with Gerry Carruthers and others about the setting up of an archive for the International Journal of Scottish Theatre and Screen.  I’d set up a WordPress site for this and explored how the volumes, issues and articles could be migrated over from PDFs.  We met with the two students who will now do the work.  I spent the morning before the meeting preparing an instruction document for the students to follow and at the meeting I talked through the processes contained in the document.  Hopefully it will be straightforward for the students to migrate the PDFs, although I suspect it may take them an article or two before they get into the swing of things.

Also this week I fixed an issue with the search results tabs in the left-hand panel of the entry page on the DSL website.  There’s a tooltip on the ‘Up to 1700’ link, but on narrow screens the tooltip was ending up positioned over the link, and when you pressed on it the code was getting confused as to whether you’d pressed on the link or the tooltip.  I repositioned the tooltips so they now appear above the links, meaning they should no longer get in the way on narrow screens.  I also looked into an issue with the DSL’s Paypal account, which wasn’t working.  This turned out to be an issue on the Paypal side rather than with the links through from the DSL’s site.

I also had to rerun the varlist date scripts for the AND as we’d noticed that some quotations had a structure that my script was not set up to deal with.  The expected structure is something like this:

<quotation>ou ses orribles pates paracrosçanz <varlist><ms_var id=””V-43aaf04a”” usevardate=””true””><ms_form>par acros</ms_form><ms_wit>BN</ms_wit><ms_date post=””1300″” pre=””1399″”>s.xiv<sup>in</sup></ms_date></ms_var></varlist> e par ateinanz e par encrés temptacions</quotation>

Where there is one varlist in the quotation, containing one or more ms_var tags.  But the entry ‘purprestur’ has multiple separate varlists in the quotation:

<quotation>Endreit de purprestures voloms qe les nusauntes <varlist><ms_var id=””V-66946b02″”><ms_form>nusantes porprestures</ms_form><ms_wit>W</ms_wit><ms_date>s.xiv</ms_date></ms_var></varlist> soint ostez a coustages de ceux qi lé averount fet <varlist><ms_var id=””V-67f91f67″”><ms_form>des provours</ms_form><ms_wit>A</ms_wit><ms_date>s.xiv</ms_date></ms_var><ms_var id=””V-ea466d5e””><ms_form>des fesours</ms_form><ms_wit>W</ms_wit><ms_date>s.xiv</ms_date></ms_var><ms_var id=””V-88b4b5c2″” usevardate=””true””><ms_form>dé purpresturs</ms_form><ms_wit>M</ms_wit><ms_date post=””1300″” pre=””1310″”>s.xiv<sup>in</sup></ms_date></ms_var><ms_var id=””V-769400cd””><ms_form>des purpernours</ms_form><ms_wit>C</ms_wit><ms_date>s.xiv<sup>1/3</sup></ms_date></ms_var></varlist> </quotation>

I wasn’t aware that this was a possibility, so my script wasn’t set up to catch such situations.  It therefore only looks at the first <varlist>. And the <ms_var> that needs to be used for dating isn’t contained in this, so gets missed.  I therefore updated the script and have run both spreadsheets through it again.  I also updated the DMS so that quotations with multiple varlists can be processed.

Also this week I updated all of the WordPress sites I manage and helped set up the Our Heritage, Our Stories site, and had a further discussion with Sofia about the conference pages for the Iona place-names project.

I spent the rest of the week continuing to work on the mockups for the Speak For Yerself project, creating a further mockup of the grammar quiz that now features all of the required stages.  The ‘word choice’ type of question now has a slightly different layout, with buttons closer together in a block, and after answering the second question there is now an ‘Explore the answers’ button under the map.  Pressing on this loads the summary maps for each question, which are not live maps yet, and underneath the maps is a button for starting the quiz.  There isn’t enough space to have a three-column layout for the quiz so I’ve placed the quiz above the summary maps.  The progress bar also gets reinstated for the quiz and I’ve added the  text ‘Use the maps below to help you’ just to make it clearer what those buttons are for.  The ‘Q1’, ‘Q2’ IDs will probably need to be altered as it just makes it look like the map refers to a particular question in the quiz, which isn’t the case.  It’s possible to keep a map open between quiz questions, and when you press an answer button the ones you didn’t press get greyed out.  If your choice is correct you get a tick, and if not you get a cross and the correct answer gets a tick.  The script keeps track of what questions have been answered correctly in the background and I haven’t implemented a timer yet.  After answering all of the questions (there doesn’t need to be 6 – the code will work with any number) you can finish the section, which displays your score and the ranking.  Here is a screenshot of how the quiz currently looks:

Week Beginning 8th November 2021

I spent a bit of time this week working for the DSL.  I needed to act as the go-between for the DSL’s new IT people who are updating their email system and the University’s IT people who manage the DNS record on behalf of the DSL.  IT took a few attempts before the required changes were successfully in place.  I also read through a document that had been prepared about automatically ‘fixing’ the DSL’s dates to make them machine readable, and gave some feedback on the many different procedures that will need to be performed on the various date forms to produce the desired structure.

I also looked into an issue with cross references within citations that work in the live site but are not functioning in the new site or in the DSL’s editing system.  After some investigation it seems like it’s another case of the original API ‘fixing’ the XML in some way each time it’s processed in order for these links to work.  The XML for ‘put_v’ stored in the original API is as follows:

<cit><cref><date>1591</date> <title>Edinb. B. Rec.</title> V 41 (see <ref>Putting</ref> <i>vbl. n.</i> 1 (1)).</cref></cit>

There is a <ref> tag but no other information in this tag.  This is the same for the XML exported from DPS and used in the new dsl site (which has an additional bibliographic reference in):

<cit><cref refid=”bib013153″><date>1591</date> <title>Edinb. B. Rec.</title> V 41 (see <ref>Putting</ref> <i>vbl. n.</i> 1 (1)).</cref></cit>

The XSLT for both the live and new sites doesn’t include anything to process a <ref> that doesn’t include any attributes so both the live and new sites shouldn’t be displaying a link through to ‘putting’.  But of course the live site does.  I had generated and stored the XML that the original API (which I did not develop) outputs whenever the live site asks for an entry.  When looking at this I found the following:

<cit><cref ref=”db674″><date>1591</date> <title>Edinb. B. Rec.</title> V 41 (see <ref action=”link” href=”dost/putting”>Putting</ref> <i>vbl. n.</i> 1 (1)).</cref></cit>

You can see that the original API is injecting both a bibliographical cross-reference and the ‘putting’ reference.  The former we previously identified and sorted but the latter unfortunately hasn’t, although references that are not in citations do seem to have been fixed.  I updated the XSLT on the new dsl site to process the <ref> so the link now works, however this is not an approach that can be relied upon as all the XSLT is currently doing is taking the contents of the tag (Putting) and making a link out of it.  If the ‘slug’ of the entry doesn’t match the display form then the link is not going to work.  The original API includes a table containing cross references, but this doesn’t differentiate ones in citations from regular ones, and as the ‘putting_v’ entry contains 83 references it’s not going to be easy to pick out from this the ones that still need to be added.  This will need further discussion with the editors.

Continuing on a dictionary theme, I also did some further work for the Anglo-Norman Dictionary.  Last week I processed entries where a varlist date needed to be used as the citation date, but we noticed that the earliest date for entries hadn’t been updated in many cases where it should have been.  This week I figured out what went wrong.  My script only updated the entry’s date if the new date from the varlist was earlier than the existing earliest date for the entry.  This is obviously not what we want as in the majority of cases the varlist date will be later and should replace the earlier date that is erroneous.  Thankfully it was easy to pick out all of the entries that have a ‘usevardate’ and I then reran a corrected version of the script that checks and replaces an entry’s earliest date.

The editor spotted a couple of entries that still hadn’t been updated after this process and I then had to investigate them.  One of them had an error in the edited markup that was preventing the update from being applied.  For the other I realised that my code to update the XML wasn’t looking at all senses, just the first in each entry.  My script was attempting to loop through all senses as follows:

foreach($xml->main_entry->sense -> attestation as $a){

//process here

}

Which unfortunately only loops through all attestations in the first sense.  What I needed to do was:

 

foreach($xml->main_entry->sense as $s){

foreach($s->attestation as $a){

//process here

}

}

As the sense that needed updating for ‘aspreté’ was the last one the XML wasn’t getting changed, this meant ‘usevardate’ wasn’t present in the XML therefore my update to regenerate the earliest dates didn’t catch this entry (despite all dates for citations being successfully updated in the database for the entry).  I then fixed my script and regenerated all data again, including fixing the data so the ones with XML errors were updated.  I then ran a further spreadsheet containing entries that needed updated through the fixed script, resulting in a further 257 citations that had their dates updated.

Finally, I updated the Dictionary Management System so that ‘usevardate’ dates are taken into consideration when processing and publishing uploaded XML files.  If a ‘usevardate’ is found then this date is used for the attestation, which automatically affects the earliest date that is generated for the entry and also the dates used for attestations for search purposes.  I tried this out by downloading the XML for ‘admirable’, which features a ‘usevardate’.  I then edited the XML to remove the ‘usevardate’ before uploading and publishing this version.  As expected the dates for the attestation and the entry’s earliest date were affected by this change.  I then edited the XML to reinstate the ‘usevardate’ and uploaded and published this version, which took into consideration the ‘usevardate’ when generating the entry’s earliest date and attestation dates and returned the entry to the way it was before the test.

Also this week I set up a WordPress site that will be used for the archive of the International Journal of Scottish Theatre and Screen and migrated one of the issues to WordPress, which required me to do the following:

  1. Open the file in a PDF viewer for reference (e.g. Adobe Acrobat)
  2. Open the file in MS Word, which converts it into an editable format
  3. Create a WordPress page for the article with the article’s title as the page title and setting the page ‘parent’ as Volume 1
  4. Copy and paste the article contents from Word into WordPress
  5. Go through the article in WordPress, referencing the file in Acrobat, and manually fixing any issues that I spotted (e.g. fixing the display of headings, fixing some line breaks that were erroneously added). Footnotes proved to be particularly tricky as their layout was not handled very well by Word.  It’s possible that some footnotes are not quite right, especially with the ‘Trainspotting’ article that has more than 70(!) footnotes.
  6. Publish the WordPress page and update the ‘Volume 1’ page to add a link to it.

None of this was particularly difficult to do, but it was somewhat time-consuming.  There are a further 18 issues left to do (as far as I can tell), although some of these will take longer as they contain more articles, and some of these are more structurally complicated (e.g. including images).  Gerry Carruthers is getting a couple of students to do the rest and we have a meeting scheduled next week where I’ll talk through the process.

I also made some further tweaks to the WordPress site for the ‘Our Heritage, Our Stories’ site and dealt with renewing the domain for TheGlasgowStory.com site, which is now safe for a further nine years.  I also generated an Excel spreadsheet of the full lexical dataset from Mapping Metaphor for Wendy Anderson after she had a request for the data from some researchers in Germany.

I spent the rest of the week working for the Speak For Yersel project, continuing to generate mockups of the interactive exercises.  I completed an initial version of the overall structure for both the accessibility and word choice question types for the grammar exercise, so it will be possible to just ‘plug in’ any number of other questions that fit these templates.  What I haven’t done yet is incorporate the maps, the post-questionnaire ‘explore’ or the final quiz, as these need more content.  Here’s how things currently look:

I used another different font for the heading (Slackey), with the same one used for the ‘Question x of y’ text too’.  I also used CSS gradients quite a bit in this version, as the team seemed quite keen on these.  There’s a subtle diagonal gradient in the header and footer backgrounds, and a more obvious  top-to-bottom one in the answer buttons.  I used different combinations of colours too.  I created a progress bar, which works, but with only two questions in the system it’s not especially obvious what it does.  Rather than having people click an answer and then click a ‘next’ button to continue I’ve made it so that clicking an answer automatically loads the next step, and clicking an answer loads a panel with a ‘map’ – this is just a static image for now.  It also loads a ‘next’ button if there is a next question.  Clicking the ‘next’ button slides up the map panel, loads the next question in and advances the progress bar.  Users will be accessing this on many different screen sizes and I’ve tested it out on my Android phone and my iPad in both portrait and landscape orientations and all seems to work well to me.  However, the map panel will be displayed below rather than beside the questions on narrower screens.

I then began experimenting with randomly positioned markers in polygonal areas.  Initially I wanted to see whether this would be possible in ArcGIS, and a bit of Googling suggested it would be, see for example this post: http://gis.mtu.edu/?p=127 which is 10 years old, so the instructions don’t in any way match up to how things work in the current version of ArcGIS, but it at least showed it should be possible.  I loaded the desktop version of ArcGIS up via Glasgow Anywhere and after some experimentation and a fair bit of exasperation I managed to create a polygon shape and add 100 randomly placed marker points to it, which you can see here:

Something we will have to bear in mind is how such points will look when zoomed:

This is just 100 points over a pretty large geographical area.  We might end up with thousands of points, which might make this approach unusable.  Another issue is it took ArcGIS more than a minute to generate and process these 100 random points.  I don’t know how much of this is down to running the software via Glasgow Anywhere, but if we’re dealing with tens of polygons and hundreds or thousands of data points this is just not going to be feasible.

An issue of greater concern is that as far as I can tell (after more than an hour of investigation) the ‘create random points’ option is not available via ArcGIS Online, which is the tool we would need to use to generate maps to share online (if we choose to use ArcGIS).  The online version seems to be really pared back in terms of functionality compared to the desktop version and I just couldn’t see any way of incorporating the random points system.  However, I discovered a way of generating random points using Leaflet and another javascript based geospatial library called turf.js (http://turfjs.org/).  The information about how to go about it is here:  https://gis.stackexchange.com/questions/163044/mapbox-how-to-generate-a-random-coordinate-inside-a-polygon

I created a test map using the SCOSYA area for Campbeltown and the SCOSYA base map.  As a solution I’d say it’s working pretty well – it’s very fast and seems to do what we want it to.  You can view an example of the script output here:

The script generates 100 randomly placed markers each time you load the page.  At zoomed out levels the markers are too big, but I can make them smaller – this is just an initial test.  There is unfortunately going to be some clustering of markers as well, due to the nature of the random number generator.  This may give people to wrong impression.  I could maybe update the code to reject markers that are in too close proximity to another one, but I’d need to see about that.  I’d say it’s looking promising, anyway!

Week Beginning 1st November 2021

I spent most of my time working on the Speak For Yersel project this week, including Zoom calls on Tuesday and Friday.  Towards the start of the week I created a new version of the exercise I created last week.  This version uses a new sound file and transcript and new colours based on the SCOSYA palette.  It also has different fonts, and has a larger margin on the left and right of the screen.  I’ve also updated the way the exercise works to allow you to listen to the clip up to three times, with the ‘clicks’ on subsequent listens adding to rather than replacing the existing ones.  I’ve had to add in a new ‘Finish’ button as information can no longer be processed automatically when the clip finishes.  I’ve moved the ‘Play’ and ‘Finish buttons to a new line above the progress bar as on a narrow screen the buttons on one line weren’t working well.  I’ve also replaced the icon when logging a ‘click’ and added in ‘Press’ instead of ‘Log’ as the button text.  Here’s a screenshot of the mockup in action:

I then gave some thought to the maps, specifically what data we’ll be generating from the questions and how it might actually form a heatmap or a marker-based map.  I haven’t seen any documents yet that actually go into this and it’s something we need to decide upon if I’m going to start generating maps.  I wrote a document detailing how data could be aggregated and sent it to the team for discussion.  I’m going to include the full text here so I’ve got a record of it:

The information we will have about users is:

  1. Rough location based on the first part of their postcode (e.g. G12) from which we will ascertain a central latitude / longitude point
  2. Which one of the 12 geographical areas this point is in (e.g. Glasgow)

There will likely be many (tens, hundreds or more) users with the same geographical information (e.g. an entire school over several years).  If we’re plotting points on a map this means one point will need to represent the answers of all of these people.

We are not dealing with the same issues as the Manchester Voices heatmaps.  Their heatmaps represent one single term, e.g. ‘Broad’ and the maps represent a binary choice – for a location the term is either there or it isn’t.  What we are dealing with in our examples are multiple options.

For the ‘acceptability’ question such as ‘Gonnae you leave me alone’ we have four possible answers: ‘I’d say this myself’, ‘I wouldn’t say this, but people where I live do’, ‘I’ve heard some people say this (outside my area, on TV etc)’ and ‘I’ve never heard anyone say this’.  If we could convert these into ratings (0-3 with ‘I’d say this myself’ being 3 and ‘I’ve never heard anyone say this’ being 0) then we could plot a heatmap with the data.

However, we are not dealing with comparable data to Manchester, where users draw areas and the intersects of these areas establish the pattern of the heatmap.  What we have are distinct geographical areas (e.g. G12) with no overlap between these areas and possibly hundreds of respondents within each area.  We would need to aggregate the data for each area to get a single figure for it but as we’re not dealing with a binary choice this is tricky.  E.g. if it was like the Manchester study and we were looking for the presence of ‘broad’ and there were 15 respondents at location Y and 10 had selected ‘broad’ then we could generate the percentage and say that 66% of respondents here used ‘broad’.

Instead what we might have for our 15 respondents is 8 said ‘I’d say this myself’ (53%), 4 said ‘I wouldn’t say this, but people where I live do’ (26%), 2 said ‘I’ve heard some people say this (outside my area, on TV etc)’ (13%) and 1 said ‘I’ve never heard anyone say this’ (7%).  So four different figures.  How would we convert this into a single figure that could then be used?

If we assign a rating of 0-3 to the four options then we can multiply the percentages by the rating score and then add all four scores together to give one overall score out of a maximum score of 300 (if 100% of respondents chose the highest rating of 3).  In the example here the scores would be 53% x 3 = 159, 26% x 2 = 52, 13% x 1 = 13 and 7% x 0 = 0, giving a total score of 224 out of 300, or 75% – one single figure for the location that can then be used to give a shade to the marker or used in a heatmap.

For the ‘Word Choice’ exercises (whether we allow a single or multiple words to be selected) we need to aggregate and represent non-numeric data, and this is going to be trickier.  For example, if person A selects ‘Daftie’ and ‘Bampot’ and person B selects ‘Daftie’, ‘Gowk’ and ‘Eejit’ and both people have the same postcode then how are these selections to be represented at the same geographical point on the map?

We could pick out the most popular word at each location and translate it into a percentage.  E.g. at location Y 10 people selected ‘Daftie’, 6 selected ‘Bampot’, 2 selected ‘Eejit’ and 1 selected ‘Gowk’ out of a total of 15 participants.  We then select ‘Daftie’ as the representative term with 66% of participants selecting it.  Across the map wherever ‘Daftie’ is the representative term the marker is given a red colour, with darker shades representing higher percentages.  For areas where ‘Eejit’ is the representative term it could be given shades of blue etc.  We could include a popup or sidebar that gives the actual data, including other words and their percentages at each location, either tabular or visually (e.g. a pie chart).  This approach would work as individual points or could possibly work as a heatmap with multiple colours, although it would then be trickier to include a popup or sidebar.  The overall approach would be similar to the NYT ice-hockey map:

Note, however, that for the map itself we would be ignoring everything other than the most commonly selected term at each location.

Alternatively, we could have individual maps or map layers for each word as a way of representing all selected words rather than just the top-rated one.  We would still convert the selections into a percentage (e.g. out of 15 participants at Location Y 10 people selected ‘Daftie’, giving us a figure of 66%) and assign a colour and shade to each form (e.g. ‘Daftie’ is shades of red with a darker shade meaning a higher percentage) but you’d be able to switch from the map for one form to that of another to show how the distribution changes (e.g. the ‘Daftie’ map has darker shades in the North East, the ‘Eejit’ map has darker shades in the South West), or look at a series of small maps for each form side by side to compare them all at once.  This approach would be comparable to the maps shown towards the end of the Manchester YouTube video for ‘Strong’, ‘Soft’ and ‘Broad’ (https://www.youtube.com/watch?v=ZosWTMPfqio):

Another alternative is we could have clusters of markers at each location, with one marker per term.  So for example if there are 6 possible terms each location on the map would consist of a cluster of 6 markers, each of a different colour representing the term, and each a different shade representing the percentage of people who selected the term at the location.  However, this approach would risk getting very cluttered, especially at zoomed out levels, and may present the user with too much information, and is in many ways similar to the visualisations we investigated and decided not to use for SCOSYA.  For example:

look at the marker for Arbroath.  This could be used to show four terms and the different sizes of each section would show the relative percentages of respondents who chose each.

A further thing to consider is whether we actually want to use heatmaps at all.  A choropleth map might work better.  From this page: https://towardsdatascience.com/all-about-heatmaps-bb7d97f099d7  here is an explanation:

“Choropleth maps are sometimes confused with heat maps. A choropleth map features different shading patterns within geographic boundaries to show the proportion of a variable of interest². In contrast, a heat map does not correspond to geographic boundaries. Choropleth maps visualize the variability of a variable across a geographic area or within a region. A heat map uses regions drawn according to the variable’s pattern, rather than the a priori geographic areas of choropleth maps¹. The Choropleth is aggregated into well-known geographic units, such as countries, states, provinces, and counties.”

An example of a choropleth map is:

We are going to be collecting the postcode area for every respondent and we could use this as the basis for our maps.  GeoJSON encoded data for postcode areas is available.  For example, here are all of the areas for the ‘G’ postcode: https://github.com/missinglink/uk-postcode-polygons/blob/master/geojson/G.geojson

Therefore we could generate choropleth maps comparable to the US one above based on these postcode areas (leaving areas with no respondents blank).  But perhaps postcode districts are too small an area and we may not get sufficient coverage.

There is an interesting article about generating bivariate choropleth maps here:

https://www.joshuastevens.net/cartography/make-a-bivariate-choropleth-map/

These enable two datasets to be displayed on one map, for example the percentage of people selecting ‘Daftie’ split into 25% chunks AND the percentage of people selecting ‘Eejit’ similarly split into 25% chunks, like this (only it would be 4×4 not 3×3):

However, there is a really good reply about why cramming a lot of different data into one map is a bad idea here: https://ux.stackexchange.com/questions/87941/maps-with-multiple-heat-maps-and-other-data and it’s well worth a read (despite calling a choropleth map a heat map).

After circulating the document we had a further meeting and it turns out the team don’t want to aggregate the data as such – what they want to do is have individual markers for each respondent, but to arrange them randomly throughout the geographical area the respondent is from to give a general idea of what the respondents in an area are saying without giving their exact location.  It’s an interesting approach and I’ll need to see whether I can find a way to randomly position markers to cover a geoJSON polygon.

Moving on to other projects, I also worked on the Books and Borrowers project, running a script to remove blank pages from all of the Advocates registers and discussing some issues with the Innerpeffray data and how we might deal with this.  I also set up the initial infrastructure for the ‘Our Heritage, Our Stories’ project website for Marc Alexander and Lorna Hughes and dealt with some requests from the DSL’s IT people about updating the DNS record for the website.  I also had an email conversation with Gerry Carruthers about setting up a website for the archive of the International Journal of Scottish Theatre and Screen and made a few minor tweaks to the mockups for the STAR project.

Finally, I continued to work on the Anglo-Norman Dictionary, firstly sorting out an issue with Greek characters not displaying properly and secondly working on the redating of citations where a date from a varlist tag should be used as the citation date.  I wrote a script that picked out the 465 entries that had been marked as needing updated in a spreadsheet and processed them, firstly updating each entry’s XML to replace the citation with the updated one, then replacing the date fields for the citation and then finally regenerating the earliest date for an entry if the update in citation date has changed this.  The script seemed to run perfectly on my local PC, based on a number of entries I checked, therefore I ran the script on the live database.  All seemed to work fine, but it looks like the earliest dates for entries haven’t been updated as often as expected, so I’m going to have to do some further investigation next week.