This week I completed work on a first version of the textbase search facilities for the Anglo-Norman Dictionary. I’ve been working on this over the past three weeks and it’s now fully operational, quick to use and does everything that was required of it. I completed work on the KWIC ordering facilities, adding in a drop-down list that enables the user to order the results either by the term or any word to the left or right of the term. When results are ordered by a word to the left or right of the search term that word is given a yellow highlight so you can easily get your eye on the word that each result is being ordered by. I ran into a few difficulties with the ordering, for example accented initial characters were being sorted after ‘z’, and upper case characters were all sorted before lower case characters, but I’ve fixed these issues. I also updated the textbase page so that when you load a text from the results a link back to the search results appears at the top of the page. You can of course just use the ‘back’ button to return to the search results. Also, all occurrences of the search term throughout the text are highlighted in yellow. There are possibly some further enhancements that could be made here (e.g. we could have a box that hovers on the screen like the ‘Top’ button that contains a summary of your search and a link back to the results, or options to load the next or previous result) but I’ll leave things as they are for now as what’s there might be good enough. I also fixed some bugs that were cropping up, such as an exact search term not appearing in the search box when you return to refine your results (caused by double quotes needing to be changed to the code ‘%22’).
I then began thinking about the development of a proximity search for the textbase. As with the old site, this will allow the user to enter two search terms and specify the maximum number of words before or after the first term the second one appears. The results will then be displayed in a KWIC form with both terms highlighted. It took quite some time to think through the various possibilities for this feature. The simplest option from a technical point of view would be to process the first term as with the regular search, retrieve the KWIC for each result and then search this for the second term. However, this wouldn’t allow the user to search for an exact match for the second term, or use wildcards, as the KWIC only contains the full text as written, complete with punctuation. Instead I decided to make the proximity search as similar to and as consistent with the regular textbase search as possible. This means the user will be able to enter the two terms with wildcards and two lists of possible exact matches will be displayed, from which the user can select term 1 and term 2. Then at this point the exact matches for term 1 will be returned and in each case a search will be performed to see whether term 2 is found however number of words specified before or after term 1. This will rely on the ‘word order’ column that I already added to the database, but will involve some complications when term 1 is near the very start or end of a page (as the search will then need to look at the preceding or following page). I ran a few tests of this process directly via the database and it seemed to work ok, but I’ll just need to see whether there are any speed issues when running such queries on potentially thousands of results.
Also this week I had an email from Bryony Randall about her upcoming exhibition for her New Modernist Editing project. The exhibition will feature a live website (https://www.blueandgreenproject.com/) running on a tablet in the venue and Bryony was worried that the wifi at the venue wouldn’t be up to scratch. She asked whether I could create a version of the site that would run locally without an internet connection, and I spent some time working on this.
I continued to work on my replica of the site, getting all of the content transferred over. This took longer than I anticipated, as some of the pages are quite complicated (artworks including poetry, images, text and audio) but I managed to get everything done before the end of the week. In the end it turned out that the wifi at the venue was absolutely fine so my replica site wasn’t needed, but it was still a good opportunity to learn about hosting a site on an Android device and to hone my Bootstrap skills.
Also this week I helped Katie Halsey of the Books and Borrowing project with a query about access to images, had a look through the final version of Kirsteen McCue’s AHRC proposal and spoke to Eleanor Lawson about creating some mockups of the interface to the STAR project websites, which I will start on next week.
I’d taken last week off as our final break of the summer, and we spent it on the Kintyre peninsula. We had a great time and were exceptionally lucky with the weather. The rains began as we headed home and I returned to a regular week of work. My major task for the week was to begin work on the search facilities for the Anglo-Norman Dictionary’s textbase, a collection of almost 80 lengthy texts for which I had previously created facilities to browse and view texts. The editors wanted me to replicate the search options that were available through the old site, which enabled a user to select which texts to search (either individual texts or groups of texts arranged by genre), enter a single term to search (either a full match or partial match at the beginning or end of a word), select a specific term from a list of possible matches and then view each hit via a keyword in context (KWIC) interface, showing a specific number of words before and after the hit, with a link through to the full text opened at that specific point.
This is a pretty major development and I decided initially that I’d have two major tasks to tackle. I’d have to categorise the texts by their genre and I’d have to research how best to handle full text searching including limiting to specific texts, KWIC and reordering KWIC, and linking through to specific pages and highlighting the results. I reckoned it was potentially going to be tricky as I don’t have much experience with this kind of searching. My initial thought was to see whether Apache Solr might be able to offer the required functionality. I used this for the DSL’s advanced search, which searches the full text of the entries and returns snippets featuring the word, with the word highlighted and the word then highlighted throughout the entry when an entry in the results is loaded (e.g. https://dsl.ac.uk/results/dreich/fulltext/withquotes/both/). This isn’t exactly what is required here, but I hoped that there might be further options I can explore. Failing that I wondered whether I could repurpose the code for the Scottish Corpus of Texts and Speech. I didn’t create this site, but I redeveloped it significantly a few years ago and may be able to borrow parts from the concordance search. E.g. https://scottishcorpus.ac.uk/advanced-search/ and select ‘general’ then ‘word search’ then ‘word / phrase (concordance)’ then search for ‘haggis’ and scroll down to the section under the map. When opening a document you can then cycle through the matching terms, which are highlighted, e.g. https://scottishcorpus.ac.uk/document/?documentid=1572&highlight=haggis#match1.
After spending some further time with the old search facility and considering the issues I realised there are a lot of things to be considered regarding preparing the texts for search purposes. I can’t just plug the entire texts in as only certain parts of them should be used for searching – no front or back matter, no notes, textual apparatus or references. In addition, in order to properly ascertain which words follow on from each other all XML tags need to be removed too, and this introduces issues where no space has been entered between tags but a space needs to exist between the contents of the tags, e.g. ‘dEspayne</item><item>La charge’ would otherwise become ‘dEspayneLa charge’.
As I’d need to process the texts no matter which search facility I end up using I decided to focus on this first, and set up some processing scripts and a database on my local PC to work with the texts. Initially I managed to extract the page contents for each required page, remove notes etc and strip the tags and line breaks so that the page content is one continuous block of text.
I realised that the old search seems to be case sensitive, which doesn’t seem very helpful. E.g. search for ‘Leycestre’ and you find nothing – you need to enter ‘leycestre’, even though all 264 occurrences actually have a capital L. I decided to make the new search case insensitive – so searching for ‘Leycestre’, ‘leycestre’ or ‘LEYCESTRE’ will bring back the same results. Also, the old search limits the keyword in context display to pages. E.g. the first ‘Leycestre’ hit has no text after it as it’s the last word on the page. I’m intending to take the same approach as I’m processing text on a page-by-page basis. I may be able to fill out the KWIC with text from the preceding / subsequent page if you consider this to be important, but it would be something I’d have to add in after the main work is completed. The old search also limits the KWIC to text that’s on the same line, e.g. in a search for ‘arcevesque’ the result ‘L’arcevesque puis metre en grant confundei’ has no text before because it’s on a different line (it also chops off the end of ‘confundeisun’ for some reason). The new KWIC will ignore breaks in the text (other than page breaks) when displaying the context. I also realised that I need to know what to do about words that have apostrophes in them. The old search splits words on the apostrophe, so for example you can search for arcevesque but not l’arcevesque. I’m intending to do the same. The old search retains both parts before and after the apostrophe as separate search terms, so for example in “qu’il” you can search for “qu” and “il” (but not “qu’il”).
After some discussions with the editor, I updated my system to include textual apparatus, stored in a separate field to the main page text. With all of the text extracted I decided that I’d just try and make my own system initially, to see whether it would be possible. I therefore created a script that would take each word from the extracted page and textual apparatus fields and store this in a separate table, ensuring that words with apostrophes in them are split into separate words and for search purposes all non-alphanumeric characters are removed and the text is stored as lower-case. I also needed to store the word as it actually appears in the text, the word order on the page and whether the word is a main page word or in the textual apparatus. This is because after finding a word I’ll need to extract those around it for the KWIC display. After running my script I ended up with around 3.5 million rows in the ‘words’ table, and this is where I ran into some difficulties.
I ran some test queries on the local version of the database and all looked pretty promising, but after copying the data to the server and running the same queries it appeared that the server is unusably slow. On my desktop a query to find all occurrences of ‘jour’, with the word table joined to the page table and then to the text table completed in less than 0.5 seconds but on the server the same query took more than 16 seconds, so about 32 times slower. I tried the same query a couple of times and the results are roughly the same each time. My desktop PC is a Core i5 with 32GB of RAM, and the database is running on an NVMe M.2 SSD, which no doubt makes things quicker, but I wouldn’t expect it to be 32 times quicker.
I then did some further experiments with the server. When I query the table containing the millions of rows on its own the query is fast (much less than a second). I added a further index to the column that is used for the join to the page table (previously it was indexed, but in combination with other columns) and then when limiting the query to just these two tables the query runs at a fairly decent speed (about 0.5 seconds). However, the full query involving all three tables still takes far too long, and I’m not sure why. It’s very odd as there are indexes on the joining columns and the additional table is not big – it only has 77 rows. I read somewhere that ordering the results by a column in the joined table can make things slower, as can using descending order on a column, so I tried updating the ordering but this has had no effect. It’s really weird – I just can’t figure out why adding the table has such a negative effect on the performance and I may end up just having to incorporate some of the columns from the text table into the page table, even though it will mean duplicating data. I also still don’t know why the performance is so different on my local PC either.
One final thing I tried was to change the database storage type. I noticed that the three tables were set to use MyISAM storage rather than InnoDB, which the rest of the database was set to. I migrated the tables to InnoDB in the hope that this might speed things up, but it’s actually slowed things down, both on my local PC and the server. The two-table query now takes several seconds while the three-table query now takes about the same, so is quicker, but still too slow. On my desktop PC the speed has doubled to about 1 second. I therefore reverted back to using MyISAM.
Also this week I had a chat with Eleanor Lawson about the STAR project that has recently begun. There was a project meeting last week that unfortunately I wasn’t able to attend due to my holiday, so we had an email conversation about some of the technical issues that were raised at the meeting, including how it might be possible to view videos side by side and how a user may choose to select multiple videos to be played automatically one after the other.
I also fixed a couple of minor formatting issues for the DSL people and spoke to Katie Halsey, PI of the Books and Borrowing project about the development of the API for the project and the data export facilities. I also received further feedback from Kirsteen McCue regarding the Data Management Plan for her AHRC proposal and went through this, responding to the comments and generating a slightly tweaked version of the plan.
This was my second and final week staying at my parents’ house in Yorkshire, where I’m working a total of four days over the two weeks. This week I had an email conversation with Eleanor Lawson about her STAR project, which will be starting very shortly. We discussed the online presence for the project, which will be split between a new section on the Seeing Speech website and an entirely new website, the project’s data and workflows and my role over the 24 months of the project. I also created a script to batch process some of the Edinburgh registers for the Books and Borrowing project. The page images are double spreads and had been given a number for both the recto and the verso (e.g. 1-2, 3-4), but the student registers only ever use the verso page. I was therefore asked to write a script to renumber all of these (e.g. 1-2 becomes 1, 3-4 becomes 2), which I created and executed on a test version of the site before applying to the live data.
I also continued to make tweaks to the front-ends for the Comparative Kingship project. I fixed a bug with the Elements glossary of the Irish site, which was loading the Scottish version instead. I also contacted Chris Fleet at NLS Maps to enquire about using a couple of their historical Irish maps with the site. I also fixed the ‘to top’ button in the CMSes not working; the buttons now actually scroll the page to the top as they should. I also fixed some issues relating to parish names no longer being unique in the system (e.g. the parish of Gartly is in the system twice due to it changing county at some point). This was causing issues with the browse option as data was being grouped by parish name. Changing the grouping to the parish ID thankfully fixed the issue.
I also had a chat with Ann Fergusson at the DSL about multi-item bibliographical entries in the existing DSL data. These are being split into individual items, and a new ‘sldid’ attribute in the new data will be used to specify which item in the old entry the new entry corresponds to. We agreed that I would figure out a way to ensure that these IDs can be used in the new website once I receive the updated data.
My final task of the week was to investigate a problem with Rob Maslen’s City of Lost Books blog (https://thecityoflostbooks.glasgow.ac.uk/) when went offline this week and only displayed a ‘database error’. Usually when this happens it’s a problem with the MySQL database and it takes down all of the sites on the server, but this time it was only Rob’s site that was being affected. I tried accessing the WP admin pages and this gave a different error about the database being corrupted. I needed to update the wordpress config file to add the line define(‘WP_ALLOW_REPAIR’, true); and upon reloading the page WordPress attempted to fix the database. After doing so it stated that “The wp_options table is not okay. It is reporting the following error: Table is marked as crashed and last repair failed. WordPress will attempt to repair this table… Failed to repair the wp_options table. Error: Wrong block with wrong total length starting at 10356”. WordPress appeared to regenerate the table, as after this the table existed and was populated with data and the blog went online again and could be logged into. I’ll have to remember this if it happens again in future.
Next week I’ll be back in Glasgow.