Week 19 of Lockdown, and it was a short week for me as the Monday was the Glasgow Fair holiday. I spent a couple of days this week continuing to add features to the content management system for the Books and Borrowing project. I have now implemented the ‘normalised occupations’ part of the CMS. Originally occupations were just going to be a set of keywords, allowing one or more keyword to be associated with a borrower. However, we have been liaising with another project that has already produced a list of occupations and we have agreed to share their list. This is slightly different as it is hierarchical, with a top-level ‘parent’ containing multiple main occupations. E.g. ‘Religion and Clergy’ features ‘Bishop’. However, for our project we needed a third hierarchical level do differentiate types of minister/priest, so I’ve had to add this in too. I’ve achieved this by means of a parent occupation ID in the database, which is ‘null’ for top-level occupations and contains the ID of the parent category for all other occupations.
I completed work on the page to browse occupations, arranging the hierarchical occupations in a nested structure that features a count of the number of borrowers associated with the occupation to the right of the occupation name. These are all currently zero, but once some associations are made the numbers will go up and you’ll be able to click on the count to bring up a list of all associated borrowers, with links through to each borrower. If an occupation has any child occupations a ‘+’ icon appears beside it. Press on this to view the child occupations, which also have counts. The counts for ‘parent’ occupations tally up all of the totals for the child occupations, and clicking on one of these counts will display all borrowers assigned to all child occupations. If an occupation is empty there is a ‘delete’ button beside it. As the list of occupations is going to be fairly fixed I didn’t add in an ‘edit’ facility – if an occupation needs editing I can do it directly through the database, or it can be deleted and a new version created. Here’s a screenshot showing some of the occupations in the ‘browse’ page:
I also created facilities to add new occupations. You can enter an occupation name and optionally specify a parent occupation from a drop-down list. Doing so will add the new occupation as a child of the selected category, either at the second level if a top level parent is selected (e.g. ‘Agriculture’) or at the third level if a second level parent is selected (e.g. ‘Farmer’). If you don’t include a parent the occupation will become a new top-level grouping. I used this feature to upload all of the occupations, and it worked very well.
I then updated the ‘Borrowers’ tab in the ‘Browse Libraries’ page to add ‘Normalised Occupation’ to the list of columns in the table. The ‘Add’ and ‘Edit’ borrower facilities also now feature ‘Normalised Occupation’, which replicates the nested structure from the ‘browse occupations’ page, only features checkboxes beside each main occupation. You can select any number of occupations for a borrower and when you press the ‘Upload’ or ‘Edit’ button your choice will be saved. Deselecting all ticked checkboxes will clear all occupations for the borrower. If you edit a borrower who has one or more occupations selected, in addition to the relevant checkboxes being ticked, the occupations with their full hierarchies also appear above the list of occupations, so you can easily see what is already selected. I also updated the ‘Add’ and ‘Edit’ borrowing record pages so that whenever a borrower appears in the forms the normalised occupations feature also appears.
I also added in the option to view page images. Currently the only ledgers that have page images are the three Glasgow ones, but more will be added in due course. When viewing a page in a ledger that includes a page image you will see the ‘Page Image’ button above the table of records. Press on this and a new browser tab will open. It includes a link through to the full-size image of the page if you want to open this in your browser or download it to open in a graphics package. It also features the ‘zoom and pan’ interface that allows you to look at the image in the same manner as you’d look at a Google Map. You can also view this full screen by pressing on the button in the top right of the image.
Also this week I made further tweaks to the script I’d written to update lexeme start and end dates in the Historical Thesaurus based on citation dates in the OED. I’d sent a sample output of 10,000 rows to Fraser last week and he got back to me with some suggestions and observations. I’m going to have to rerun the script I wrote to extract the more than 3 million citation dates from the OED as some of the data needs to be processed differently, but as this script will take several days to run and I’m on holiday next week this isn’t something I can do right now. However, I managed to change the way the date matching script runs to fix some bugs and make the various processes easier to track. I also generated a list of all of the distinct labels in the OED data, with counts of the number of times these appear. Labels are associated with specific citation dates, thankfully. Only a handful are actually used lots of times, and many of the others appear to be used as a ‘notes’ field rather than as a more general label.
In addition to the above I also had a further conversation with Heather Pagan about the data management plan for the AND’s new proposal, responded to a query from Kathryn Cooper about the website I set up for her at the end of last year, responded to a couple of separate requests from post-grad students in Scottish Literature, spoke to Thomas Clancy about the start date for his Place-Names of Iona project, which got funded recently, helped with some issues with Matthew Creasy’s Scottish Cosmopolitanism website and spoke to Carole Hough about making a few tweaks to the Berwickshire Place-names website for REF.
I’m going to be on holiday for the next two weeks, so there will be no further updates from me for a while.
This was week 18 of Lockdown, which is now definitely easing here. I’m still working from home, though, and will be for the foreseeable future. I took Friday off this week, so it was a four-day week for me. I spent about half of this time on the Books and Borrowing project, during which time I returned to adding features to the content management system, after spending recent weeks importing datasets. I added a number of indexes to the underlying database which should speed up the loading of certain pages considerably. E.g. the browse books, borrowers and author pages. I then updated the ‘Books’ tab when viewing a library (i.e. the page that lists all of the book holdings in the library) so that it now lists the number of book holdings in the library above the table. The table itself now has separate columns for all additional fields that have been created for book holdings in the library and it is now possible to order the table by any of the headings (pressing on a heading a second time reverses the ordering). The count of ‘Borrowing records’ for each book in the table is now a button and pressing on it brings up a popup listing all of the borrowing records that are associated with the book holding record, and from this pop-up you can then follow a link to view the borrowing record you’re interested in. I then made similar changes to the ‘Borrowers’ tab when viewing a library (i.e. the page that lists all of the borrowers the library has). It also now displays the total number of borrowers at the top. This table already allowed the reordering by any column, so that’s not new, but as above, the ‘Borrowing records’ count is now a link that when clicked on opens a list of all of the borrowing records the borrower is associated with.
The big new feature I implemented this week was borrower cross references. These can be added via the ‘Borrowers’ tab within a library when adding or editing a borrower on this page. When adding or editing a borrower there is now a section of the form labelled ‘Cross-references to other borrowers’. If there are any existing cross references these will appear here, with a checkbox beside each that you can tick if you want to delete the cross reference (the user can tick the box then press ‘Edit’ to edit the borrower and the reference will be deleted). Any number of new cross references can be added by pressing on the ‘Add a cross-reference’ button (multiple times, if required). Doing so adds two fields to the form, one for a ‘description’, which is the text that shows how the current borrower links to the referenced borrowing record, and one for ‘referenced borrower’, which is an auto-complete. Type in a name or part of a name and any borrower that matches in any library will be listed. The library appears in brackets after the borrower’s name to help differentiate records. Select a borrower and then when the ‘Add’ or ‘Edit’ button is pressed for the borrower the cross reference will be made.
Cross-references work in both directions – if you add a cross reference from Borrower A to Borrower B you don’t then need to load up the record for Borrower B to add a reference back to Borrower A. The description text will sit between the borrower whose form you make the cross reference on and the referenced borrower you select, so if you’re on the edit form for Borrower A and link to Borrower B and the description is ‘is the son of’ then the cross reference will appear as ‘Borrower A is the son of Borrower B’. If you then view Borrower B the cross reference will still be written in this order. I also updated the table of borrowers to add in a new ‘X-Refs’ column that lists all cross-references for a borrower.
I spent the remainder of my working week completing smaller tasks for a variety of projects, such as updating the spreadsheet output of duplicate child entries for the DSL people, getting an output of the latest version of the Thesaurus of Old English data for Fraser, advising Eleanor Lawson on ‘.ac.uk’ domain names and having a chat with Simon Taylor about the pilot Place-names of Fife project that I worked on with him several years ago. I also wrote a Data Management Plan for a new AHRC proposal the Anglo-Norman Dictionary people are putting together, which involved a lengthy email correspondence with Heather Pagan at Aberystwyth.
Finally, I returned to the ongoing task of merging data from the Oxford English Dictionary with the Historical Thesaurus. We are currently attempting to extract citation dates from OED entries in order to update the dates of usage that we have in the HT. This process uses the new table I recently generated from the OED XML dataset which contains every citation date for every word in the OED (more than 3 million dates). Fraser had prepared a document listing how he and Marc would like the HT dates to be updated (e.g. if the first OED citation date is earlier than the HT start date by 140 years or more then use the OED citation date as the suggested change). Each rule was to be given its own type, so that we could check through each type individually to make sure the rules were working ok.
It took about a day to write an initial version of the script, which I ran on the first 10,000 HT lexemes as a test. I didn’t split the output into different tables depending on the type, but instead exported everything to a spreadsheet so Marc and Fraser could look through it.
In the spreadsheet if there is no ‘type’ for a row it means it didn’t match any of the criteria, but I included these rows anyway so we can check whether there are any other criteria the rows should match. I also included all the OED citation dates (rather than just the first and last) for reference. I noted that Fraser’s document doesn’t seem to take labels into consideration. There are some labels in the data, and sometimes there’s a new label for an OED start or end date when nothing else is different, e.g. htid 1479 ‘Shore-going’: This row has no ‘type’ but does have new data from the OED.
Another issue I spotted is that as the same ‘type’ variable is set when a start date matches the criteria and then when an end date matches the criteria, the ‘type’ as set during start date is then replaced with the ‘type’ for end date. I think, therefore, that we might have to split the start and end processes up, or append the end process type to the start process type rather than replacing it (so e.g. type 2-13 rather than type 2 being replaced by type 13). I also noticed that there are some lexemes where the HT has ‘current’ but the OED has a much earlier last citation date (e.g. htid 73 ‘temporal’ has 9999 in the HT but 1832 in the OED. Such cases are not currently considered.
Finally, according to the document, Antes and Circas are only considered for update if the OED and HT date is the same, but there are many cases where the start / end OED date is picked to replace the HT date (because it’s different) and it has an ‘a’ or ‘c’ and this would then be lost. Currently I’m including the ‘a’ or ‘c’ in such cases, but I can remove this if needs be (e.g. HT 37 ‘orb’ has HT start date 1601 (no ‘a’ or ‘c’) but this is to be replaced with OED 1550 that has an ‘a’. Clearly the script will need to be tweaked based on feedback from Marc and Fraser, but I feel like we’re finally making some decent progress with this after all of the preparatory work that was required to get to this point.
Next Monday is the Glasgow Fair holiday, so I won’t be back to work until the Tuesday.
Week 16 of Lockdown and still working from home. I continued working on the data import for the Books and Borrowers project this week. I wrote a script to import data from Haddington, which took some time due to the large number of additional fields in the data (15 across Borrowers, Holdings and Borrowings), but are executing it resulted in a further 5,163 borrowing records across 2 ledgers and 494 pages being added, including 1399 book holding records and 717 borrowers.
I then moved onto the datasets from Leighton and Wigtown. Leighton was a much smaller dataset, with just 193 borrowing records over 18 pages in one ledger and involving 18 borrowers and 71 books. As before, I have just created book holding records for these (rather than project-wide edition records), although in this case there are authors for books too, which I have also created. Wigtown was another smaller dataset. The spreadsheet has three sheets, the first is a list of borrowers, the second a list of borrowings and the third a list of books. However, no unique identifiers are used to connect the borrowers and books to the information in the borrowings sheet and there’s no other field that matches across the sheets to allow the data to be automatically connected up. For example, in the Books sheet there is the book ‘History of Edinburgh’ by author ‘Arnot, Hugo’ but in the borrowings tab author surname and forename are split into different columns (so ‘Arnot’ and ‘Hugo’ and book titles don’t match (in this case the book appears as simply ‘Edinburgh’ in the borrowings). Therefore I’ve not been able to automatically pull in the information from the books sheet. However, as there are only 59 books in the books sheet it shouldn’t take too much time to manually add the necessary data when created Edition records. It’s a similar issue with Borrowers in the first sheet – they appear with name in one column (e.g. ‘Douglas, Andrew’) but in the Borrowings sheet the names are split into separate forename and surname columns. There are also instances of people with the same name (e.g. ‘Stewart, John’) but without unique identifiers there’s no way to differentiate these. There are only 110 people listed in the Borrowers sheet, and only 43 in the actual borrowing data, so again, it’s probably better if any details that are required are added in manually.
I imported a total of 898 borrowing records for Wigtown. As there is no page or ledger information in the data I just added these all to one page in a made-up ledger. It does however mean that the page can take quite a while to load in the CMS. There are 43 associated borrowers and 53 associated books, which again have been created as Holding records only and have associated authors. However, there are multiple Book Items created for many of these 53 books – there are actually 224 book items. This is because the spreadsheet contains a separate ‘Volume’ column and a book may be listed with the same title but a different volume. In such cases a Holding record is made for the book (e.g. ‘Decline and Fall of Rome’) and an Item is made for each Volume that appears (in this case 12 items for the listed volumes 1-12 across the dataset). With these datasets imported I have now processed all of the existing data I have access to, other than the Glasgow Professors borrowing records, but these are still being worked on.
I did some other tasks for the project this week as well, including reviewing the digitisation policy document for the project, which lists guidelines for the team to follow when they have to take photos of ledger pages themselves in libraries where no professional digitisation service is available. I also discussed how borrower occupations will be handled in the system with Katie.
In addition to the Books and Borrowers project I found time to work on a number of other projects this week too. I wrote a Data Management Plan for an AHRC Networking proposal that Carolyn Jess-Cooke in English Literature is putting together and I had an email conversation with Heather Pagan of the Anglo-Norman Dictionary about the Data Management Plan she wants me to write for a new AHRC proposal that Glasgow will be involved with. I responded to a query about a place-names project from Thomas Clancy, a query about App certification from Brian McKenna in IT Services and a query about domain name registration from Eleanor Lawson at QMU. Also (outside of work time) I’ve been helping my brother-in-law set up Beacon Genealogy, through which he offers genealogy and family history research services.
Also this week I worked with Jennifer Smith to make a number of changes to the content of the SCOSYA website (https://scotssyntaxatlas.ac.uk/) to provide more information about the project for REF purposes and I added a new dataset to the interactive map of Burns Suppers that I’m creating for Paul Malgrati in Scottish Literature. I also went through all of the WordPress sites I manage and upgraded them to the most recent version of WordPress.
Finally, I spent some time writing scripts for the DSL people to help identify child entries in the DOST and SND datasets that haven’t been properly merged with main entries when exported from their editing software. In such cases the child entries have been added to the main entries, but then they haven’t been removed as separate entries in the output data, meaning the child entries appear twice. When attempting to process the SND data I discovered there were some errors in the XML file (mismatched tags) that prevented my script from processing the file, so I had to spend some time tracking these down and fixing them. But once this had been done my script could do through the entire dataset, look for an ID that appeared as a URL in one entry and as an ID of another entry and in such cases pull out the IDs and the full XML of each entry and export it into an HTML table. There were about 180 duplicate child entries in DOST but a lot more in SND (the DOST file is about 1.5mb, the SND one is about 50mb). Hopefully once the DSL people have analysed the data we can then strip out the unnecessary child entries and have a better dataset to import into the new editing system the DSL is going to be using.
This was week 15 of Lockdown, which I guess is sort of coming to an end now, although I will still be working from home for the foreseeable future and having to juggle work and childcare every day. I continued to work on the Books and Borrowing project for much of this week, this time focussing on importing some of the existing datasets from previous transcription projects. I had previously written scripts to import data from Glasgow University library and Innerpeffray library, which gave us 14,738 borrowing records. This week I began by focussing on the data from St Andrews University library.
The St Andrews data is pretty messy, reflecting the layout and language of the original documents, so I haven’t been able to fully extract everything and it will require a lot of manual correcting. However, I did manage to migrate all of the data to a test version of the database running on my local PC and then updated the online database to incorporate this data.
The data I’ve got are CSV and HTML representations of transcribed pages that come from an existing website with pages that look like this: https://arts.st-andrews.ac.uk/transcribe/index.php?title=Page:UYLY205_2_Receipt_Book_1748-1753.djvu/100. The links in the pages (e.g. Locks Works) lead through to further pages with information about books or borrowers. Unfortunately the CSV version of the data doesn’t include the links or the linked to data, and as I wanted to try and pull in the data found on the linked pages I therefore needed to process the HTML instead.
I wrote a script that pulled in all of the files in the ‘HTML’ directory and processed each in turn. From the filenames my script could ascertain the ledger volume, its dates and the page number. For example ‘Page_UYLY205_2_Receipt_Book_1748-1753.djvu_10.html’ is ledger 2 (1748-1753) page 10. The script creates ledgers and pages, and adds in the ‘next’ and ‘previous’ page links to join all the pages in a ledger together.
The actual data in the file posed further problems. As you can see from the linked page above, dates are just too messy to automatically extract into our strongly structured borrowed and returned date system. Often a record is split over multiple rows as well (e.g. the borrowing record for ‘Rollins belles Lettres’ is actually split over 3 rows). I could have just grabbed each row and inserted it as a separate borrowing record, which would then need to be manually merged, but I figured out a way to do this automatically. The first row of a record always appears to have a code (the shelf number) in the second column (e.g. J.5.2 for ‘Rollins’) whereas subsequent rows that appear to belong to the same record don’t (e.g. ‘on profr Shaws order by’ and ‘James Key’). I therefore set up my script to insert new borrowing records for rows that have codes, and to append any subsequent rows that don’t have codes to this record until a row with a code is reached again.
I also used this approach to set up books and borrowers too. If you look at the page linked to above again you’ll see that the links through to things are not categorised – some are links to books and others to borrowers, with no obvious way to know which is which. However, it’s pretty much always the case that it’s a book that appears in the row with the code and it’s people that are linked to in the other rows. I could therefore create or link to existing book holding records for links in the row with a code and create or link to existing borrower records for links in rows without a code. There are bound to be situations where this system doesn’t quite work correctly, but I think the majority of rows do fit this pattern.
The next thing I needed to do was to figure out which data from the St Andrews files should be stored as what in our system. I created four new ‘Additional Fields’ for St Andrews as follows:
- Original Borrowed date: This contains the full text of the first column (e.g. Decr 16)
- Code: This contains the full text of the second column (e.g. J.5.2)
- Original Returned date: This contains the full text of the fourth column (e.g. Jan. 5)
- Original returned text: This contains the full date of the fifth column (e.g. ‘Rollins belles Lettres V. 2d’)
In the borrowing table the ‘transcription’ field is set to contain the full text of the ‘borrowed’ column, but without links. Where subsequent rows contain data in this column but no code, this data is then appended to the transcription. E.g. the complete transcription for the third item on the page linked to above is ‘Rollins belles Lettres Vol 2<sup>d</sup> on profr Shaws order by James Key’.
The contents of all pages linked to in the transcriptions are added to the ‘editors notes’ field for future use if required. Both the page URL and the page content are included, separated by a bar (|) and if there are multiple links these are separated by five dashes. E.g. for the above the notes field contains:
‘Rollins_belles_Lettres| <p>Possibly: De la maniere d’enseigner et d’etuder les belles-lettres, Par raport à l’esprit & au coeur, by Charles Rollin. (A Amsterdam : Chez Pierre Mortier, M. DCC. XLV. ) <a href=”http://library.st-andrews.ac.uk/record=b2447402~S1″>http://library.st-andrews.ac.uk/record=b2447402~S1</a></p>
—– profr_Shaws| <p><a href=”https://arts.st-andrews.ac.uk/biographical-register/data/documents/1409683484″>https://arts.st-andrews.ac.uk/biographical-register/data/documents/1409683484</a></p>
—– James_Key| <p>Possibly James Kay: <a href=”https://arts.st-andrews.ac.uk/biographical-register/data/documents/1389455860″>https://arts.st-andrews.ac.uk/biographical-register/data/documents/1389455860</a></p>
As mentioned earlier, the script also generates book and borrower records based on the linked pages too. I’ve chosen to set up book holding rather than book edition records as the details are all very vague and specific to St Andrews. In the holdings table I’ve set the ‘standardised title’ to be the page link with underscores replaced with dashes (e.g. ‘Rollins belles Lettres’) and the page content is stored in the ‘editors notes’ field. One book item is created for each holding to be used to link to the corresponding borrowing records.
For borrowers a similar process is followed, with the link added to the surname column (e.g. Thos Duncan) and the page content added to the ‘editors notes’ field (e.g. <p>Possibly Thomas Duncan: <a href=”https://arts.st-andrews.ac.uk/biographical-register/data/documents/1377913372″>https://arts.st-andrews.ac.uk/biographical-register/data/documents/1377913372</a></p>’). All borrowers are linked to records as ‘Main’ borrowers.
During the processing I noticed that the fourth ledger had a slightly different structure to the others, with entire pages devoted to a particular borrower, whose name then appeared in a heading row in the table. I therefore updated my script to check for the existence of this heading row, and if it exists my script then grabs the borrower name, creates the borrower record if it doesn’t already exist and then links this borrower to every borrowing item found on the page. After my script had finished running we had 11147 borrowing records, 996 borrowers and 6395 book holding records for St Andrew in the system.
I then moved onto looking at the data for Selkirk library. This data was more nicely structured than the St Andrews data, with separate spreadsheets for borrowings, borrowers and books and borrowers and books connected to borrowings via unique identifiers. Unfortunately the dates were still transcribed as they were written rather than being normalised in any way, which meant it was not possible to straightforwardly generate structured dates for the records and these will need to be manually generated. The script I wrote to import the data took about a day to write, and after running it we had a further 11,431 borrowing records across two registers and 415 pages entered into our database.
As with St Andrews, I created book records as Holding records only (i.e. associated specifically with the library rather than being project-wide ‘Edition’ records. There are 612 Holding records for Selkirk. I also processed the borrower records, resulting in 86 borrower records being added. I added the dates as originally transcribed to an additional field named ‘Original Borrowed Date’ and the only other additional field is in the Holding records for ‘Subject’, that will eventually be merged with our ‘Genre’ when this feature becomes available.
Also this week I advised Katie on a file naming convention for the digitised images of pages that will be created for the project. I recommended that the filenames shouldn’t have spaces in them as these can be troublesome on some operating systems and that we’d want a character to use as a delimiter between the parts of the filename that wouldn’t appear elsewhere in the filename so it’s easy to split up the filename. I suggested that the page number should be included in the filename and that it should reflect the page number as it will be written into the database – e.g. if we’re going to use ‘r’ and ‘v’ these would be included. Each page in the database will be automatically assigned an auto-incrementing ID, and the only means of linking a specific page record in the database with a specific image will be via the page number entered when the page is created, so if this is something like ‘23r’ then ideally this should be represented in the image filename.
Katie had wondered about using characters to denote ledgers and pages in the filename (e.g. ‘L’ and ‘P’) but if we’re using a specific delimiting character to separate parts of the filename then using these characters wouldn’t be necessary and I suggested it would be better to not use ‘L’ as a lower case ‘l’ is very easy to confuse with a ‘1’ or a capital ‘I’ which might confuse future human users.
Instead I suggested using a ‘-‘ instead of spaces and a ‘_’ as a delimiter and pointed out that we should ensure that no other non-alphanumeric characters are ever used in the filename – no apostrophes, commas, colons, semi-colons, ampersands etc and to make sure the ‘-‘ is really a minus sign and not one of the fancy dashes (–) that get created by MS Office. This shouldn’t be an issue when entering a filename, but might be if a list of filenames is created in Word and then pasted into the ‘save as’ box, for example.
Finally, I suggested that it might be best to make the filenames entirely lower case, as some operating systems are case sensitive and if we don’t specify all lower case then there may be variation in the use of case. Following these guidelines the filenames would look something like this:
In addition to the Books and Borrowing project I worked on a number of other projects this week. I gave Matthew Creasy some further advice on using forums in his new project website, and ‘Scottish Cosmopolitanism at the Fin de Siècle’ website is now available here: https://scoco.glasgow.ac.uk/.
I also worked a bit more on using dates from the OED data in the Historical Thesaurus. Fraser had sent me a ZIP file containing the entire OED dataset as 240 XML files and I began analysing these to figure out how we’d extract these dates so that we could use them to update the dates associated with the lexemes in the HT. I needed to extract the quotation dates as these have ‘ante’ and ‘circa’ notes, plus labels. I noted that in addition to ‘a’ and ‘c’ a question mark is also used, somethings with an ‘a’ or ‘c’ and sometimes without. I decided to process things as follows:
- ?a will just be ‘a’
- ?c will just be ‘c’
- ? without an ‘a’ or ‘c’ will be ‘c’.
I also noticed that a date may sometimes be a range (e.g. 1795-8) so I needed to include a second date column in my data structure to accommodate this. I also noted that there are sometimes multiple Old English dates, and the contents of the ‘date’ tag vary depending on the date – sometimes the content is ‘OE’ and othertimes ‘lOE’ or ‘eOE’. I decided to process any OE dates for a lexeme as being 650 and to have only one OE date stored, so as to align with how OE dates are stored in the HT database (we don’t differentiate between date for OE words).
While running my date extraction script over one of the XML files I also noticed that there were lexemes in the OED data that were not present in the OED data we had previously extracted. This presumably means the dataset Fraser sent me is more up to date than the dataset I used to populate our online OED data table. This will no doubt mean we’ll need to update our online OED table, but as we link to the HT lexeme table using the OED catid, refentry, refid and lemmaid fields if we were to replace the online OED lexeme table with the data in these XML files the connections from OED to HT lexemes would be retained without issue (hopefully), but any matching processes we performed would need to be done again for the new lexemes.
I set my extraction script running on the OED XML files on Wednesday and processing took a long time. The script didn’t complete until sometime during Friday night, but after it had finished it had processed 238,699 categories, 754,285 lexemes, generating 3,893,341 date rows. It also found 4,062 new words in the OED data that it couldn’t process because they don’t exist in our OED lexeme database.
I also spent a bit more time working on some scripts for Fraser’s Scots Thesaurus project. The scripts now ignore ‘additional’ entries and only include ‘n.’ entries that match an HT ‘n’ category. Variant spellings are also removed (these were all tagged with <form> and I removed all of these). I also created a new field to store only the ‘NN_’ tagged words and remove all others.
The scripts generated three datasets, which I saved as spreadsheets for Fraser. The first (postagged-monosemous-dost-no-adds-n-only) contains all of the content that matches the above criteria. The second (postagged-monosemous-dost-no-adds-n-only-catheading-match) lists those lexemes where a postagged word fully matches the HT category heading. The final (postagged-monosemous-dost-no-adds-n-only-catcontents-match) lists those lexemes where a postagged word fully matches a lexeme in the HT category. For this table I’ve also added in the full list of lexemes for each HT category too.
I also spent a bit of time working on the Data Management Plan for the new project for Jane Stuart-Smith and Eleanor Lawson at QMU and arranged for a PhD student to get access to the TextGrid files that were generated for the audio records for the SCOTS Corpus project.
Finally, I investigated the issue the DSL people are having with duplicate child entries appearing in their data. This was due to something not working quite right in a script Thomas Widmann had written to extract the data from the DSL’s editing system before he left last year, and Ann had sent me some examples of where the issue was cropping up.
I have the data that was extracted from Thomas’s script last July as two XML files (dost.xml and snd.xml) and I looked through these for the examples Ann had sent. The entry for snd13897 contains the following URLs:
The first is the ID for the main entry and the other two are child entries. If I search for the second one (snds3788) this is the only occurrence of the ID in the file, as the child entry has been successfully merged. But if I search for the third one (sndns2217) I find a separate entry with this ID (with more limited content). The pulling in of data into a webpage in the V3 site uses URLs stored in a table linked to entry IDs. These were generated from the URLs in the entries in the XML file (see the <url> tags above). For the URL ‘sndns2217’ the query finds multiple IDs, one for the entry snd13897 and another for the entry sdnns2217. But it finds snd13897 first, so it’s the content of this entry that is pulled into the page.
The entry for dost16606 contains the following URLs:
(in addition to headword URLs). Searching for the second one discovers a separate entry with the ID dost50272 (with more limited content). As with SND, searching the URL table for this URL finds two IDs, and as dost16606 appears first this is the entry that gets displayed.
What we need to do is remove the child entries that still exist as separate entries in the data. To do this I could is write a script that would go through each entry in the dost.xml and snd.xml files. It would then pick out every <url> that is not the same as the entry ID and search the file to see if any entry exists with this ID. If it does then presumably this is a duplicate that should then be deleted. I’m waiting to hear back from the DSL people to see how we should proceed with this.
As you can no doubt gather from the above, this was a very busy week but I do at least feel that I’m getting on top of things again.