Tag Archives: images

Introducing Whiiif – Full text searching across image-based collections

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Background

For historical collections digitisation projects inside the library, we are increasingly looking to provide OCR transcriptions of the documents alongside the digital images. In many cases, this can enhance the usability of the images significantly. For example, the volumes in the Session Papers Project are large and often without index, making locating specific text inside difficult (see the previous blog post about this challenge here: http://libraryblogs.is.ed.ac.uk/librarylabs/2017/06/23/automated-item-data-extraction-from-old-manuscripts/) unless one is in possession of copious amounts of free time and dedication.

Our implementation of IIIF as the primary delivery method for digital images at Edinburgh (some highlights of our IIIF collections at the bottom of Scott’s blog here: http://libraryblogs.is.ed.ac.uk/librarylabs/2018/12/13/edinburgh-hosts-international-iiif-event/) opens up a vector for not just providing the OCR text alongside the images, but also to enable native searching within the volume images inside an IIIF viewer such as UniversalViewer or Mirador.

IIIF Search

Currently searching is usually performed before and outside of the viewing experience, with the chosen result then loaded in a viewer. Searching within a volume therefore offers different possibilities for the end-user during their journies across the collections. This is achieved by using a service that is capable of providing the IIIF Search API.

So far, not many such services exist in the open source world, with the IIIF Awesome list having just one entry under Content Search Services: NCSU Libraries’ Ocracoke project, which is a Rails-based full workflow solution that can also process and OCR the documents prior to serving them via IIIF. Whilst other institutions do provide IIIF Search on their holdings, these implementations can be an integral part of their digital delivery stack and not easily seperable for release, internal only projects, instances of Ocracoke, etc.

As the OCR here at Edinburgh falls under a different part of our workflow (of which more in a future blogpost) and we are primarily working with PHP and Python, I decided to implement a simple Python service capable of supporting the Search API. The project is written using Flask, a lightweight Python web framework and backed by Apache Solr to provide the text-searching. A simple service needed a simple name, and so Whiiif (Word Highlighting for IIIF) was born.

Whiiif v1

Initially, I adopted the model used by Ocracoke: indexing the text of each whole page in Solr, and using an array of word->co-ordinate mappings for each page image. When a search is made in Solr, each document is returned using the native Highlighting feature of Solr, which returns a fragment of text, with the matching words bracketed by <em> tags.

The word-co-ordinate mappings for each page are extracted from the ALTO-XML generated by the Tesseract OCR process and stored in Solr as JSON, alongside the raw text. Producing the IIIF Search API response then becomes a case of extracting the matched words from the Solr highlight result, popping the co-ordinates for each word, and generating the response JSON for the client. The initial version of Whiiif using this approach can be found on the Whiiif Github repo at commit af8a903.

This version was deployed and during testing raised issues when handling some of the documents in our collection:

  • Text-dense images, such as the Session Papers volumes, tended to have multiple instances of individual words on a page. Whilst this was not a problem for single-term searches (all instances would be found and the co-ordinates loaded), it caused a problem for phrase-based searching, where a word from the phrase could appear elsewhere on the page, before the match for the phrase, leading to incorrect word co-ordinates being retrieved from the array.
  • Some words were modified by Solr’s language processing during the ingest process, meaning matches were being returned for which the corresponding co-ordinates (generated from the pre-processed, raw text) could not be found.

There were approaches to solving these problems, such as forcing Solr to return the entire page text via the Highlighter, so that the correct instance of repeated words could be ascertained. However, this led to a significant increase in the processing time required to generate the response for each hit, as well as greater resource requirements for Solr and I decided to try a different approach.

Whiiif v2

For the second iteration of Whiiif, I decided to investigate how feasible it would be to have Solr return the matching fragment from the ALTO-XML document, which would mean having the co-ordinates for the hits already in the Solr response. This ran into difficulties, as Solr is designed for working with text, and will not easily index or search an XML document, in fact usually stripping all the XML data (that we wanted to try and preserve) by using the HTMLStripCharFilter during the indexing process. Even with the filtering removed from the processing chain, basic abilities such as phrase searching were lost due to the format of the text being searched being “word<xml fragment>word<xml fragment>word<xml fragment>…”, and false hits for words appearing inside the ALTO-XML format such as “page”, “line”, “word”, etc.

Via the IIIF Slack, I was pointed towards the work of Johannes Baiter and the MDZ Digital Library team at the Bavarian State Library, who are developing a Solr plugin to resolve these various issues (available at https://github.com/dbmdz/solr-ocrhighlighting). I reworked the Solr controller for Whiiif to use the functionality of this plugin, keeping the work already done to provide IIIF Search API responses.

Following a couple of weeks of testing, and some very useful collaborative bug-fixing work with Johannes (primarily fixing some regexp bugs and improving the handling of ALTO files) and thanks to his speedy implementation of a feature request, Whiiif v2 was moved into internal production for some in-development project websites.

I then implemented a secondary feature in Whiiif: the ability to search across a collection as a whole, and have document hits, with snippets of page images returned (complete with visual highlighting), to complement the existing “Search Within” functionality of the IIIF Search API. This feature is also powered by the OCR Highlighting plugin, but returns a custom JSON format (although similar to the IIIF Search response format), allowing the front end controller of a collections site to customise the display of results to fit each individual site design.

The version of Whiiif with these capabilities is currently available on the “withplugin” branch of the Whiiif github repo, although this is still in heavy development and will become the master branch in the future when it is a bit tidier!

Next Steps

The next steps with the Whiiif experiment are to prepare a formal release of Whiiif v2, with updated documentation, install instructions and full unit-test coverage, keep an eye out here or on the github repo for news. In the meantime, please feel free to clone the repo and experiment. Issues and PRs always welcome and you can also contact me on the IIIF slack (as mbennett) or via email: mike.bennett@ed.ac.uk.

I’d love to hear from anyone playing around with Whiiif, or suggestions for other features. Experimental support for the “hits” property of IIIF Search v1 will arrive shortly, along with some updates to make use of the latest features of the Solr plugin.

Until next time 🙂
Mike

CSV Mind-Blow(ve)n!

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PSV Eindhoven - Eredivisie champions
Never waste a football-related pun. It’s been a good week for both PSV and CSV.

I was lucky enough to have a paper accepted to Csv,conf,2* in Berlin on the 3rd-4th of May, which was great to do, but it also got me through the door to see loads of great things going on in data and its surrounding technology. Yes, there was heavy mention made of CSV and Spreadsheets; in fact, at times it was akin to an AA meeting ,with people guiltily admitting their love of Excel. This left me feeling- quite worryingly- vindicated in a lot of the things I do.

As is always the case with any conference review blogpost, it’s not viable to list every link or ruminate on the message of every talk, so I’ll just home in on a few highlights. The talks (available in slide or video form) are appearing over at Lanyrd.com, and they’ll give a lot more depth to what was spoken about.

My own reason for being there- as far as my talk was concerned- was to look at better ways of processing workflow, enriching data, and improving engagement with our collections. Afterwards, I had some interesting conversations: I was alerted to the tool NeuralTalk2  by Maciej Gryka of rainforestqa.com, a company that specialises in cleaning data using mechanical turks and crowdsourced test-cases. Neural Talk, though, is a captioning tool, which will attempt to visually recognise what your image is “of”. I’m sure it fails as much as it succeeds, but, as I pointed out, we’ve not really used this kind of tech to enhance our metadata, so there’d be no harm in running some of our images through and seeing what it comes up with.  Another chat, with a lady from UC Santa Cruz, made it clear that we are quite liberal with our approach to crowdsourced data. Where we have generally decided it’s fine to surface as long as it is properly marked as such, they are proceeding rather slowly, due to a particularly strict metadata librarian.

The keynotes were deliberately intended to cover a range of disciplines that might be new to most people at this highly eclectic conference. Resultantly, there were interesting talks on technology and activism (including visualisations of the Ebola crisis and police brutality); ethics in technology and workflows to give your consent without clicking on unreadable terms and conditions (do you know what SmartBins are taking from you as you pass?); dealing with messy spreadsheets (the Enron crisis showed this institution to manage them terribly), and open data with neuroscience (a lot of mouse brains in action).

Some other tools that we could be looking at:

Zegami – great for exploring large banks of images and spotting patterns across them. Can it work with IIIF, I wonder?

OpenRefine– a tool that we perhaps should have been using for some time to rationalise spreadsheet data, which could certainly save lots of time. Our former colleague, Richard Jones of cottagelabs, is a great advocate of these kinds of tools, as his talk made clear.

DataBaker– created in collaboration between the Office of National Statistics and ScraperWiki. This Python application can convert any ‘pretty’ spreadsheet into usable source data in CSV.

CSV Rinse and Repeat– built in Paris by Mathieu Jacomy of the Paris MediaLab, this is a JavaScript tool which intends to cut down the distance between data, coding and visualisation. Basically you take your data, spot patterns, recode to surface interesting things, and generate a visualisation out the end, in an iterative process.

Wikipedia Googlesheets– I am not sure if we would have a use for this specifically, but it was fascinating to see a plugin which serves up spreadsheet formulae coded in Google Apps JavaScript, which can then be used to interrogate any Wikipedia pages. Particularly of note is the ability to combine category pages and pageviews, to see if real-time events are influenced by Wikipedia and vice-versa. Developed by Thomas Steiner at Google.

Finally, here are three interesting observations, which certainly struck a chord with me:

  • It is now deemed quite acceptable, as a symptom of rapid development, perhaps, that the CSV is used as the master dataset; perhaps the file-based database’s day is not over. I certainly found out about some interesting applications built in this way.
  • I heard no-one but myself talk about Excel macros- at a spreadsheet conference, no less! It is far more fashionable these days to read your data as csv, and code against it using JavaScript, R, or Python. I clearly need to get out of the 1990s.
  • EVERYONE suffers from problems with diacritics, glyphs, badly formatted data and what happens when you import a CSV into a spreadsheet tool that tries to be too clever. It is not just me.

All in all, an excellent couple of days, which have filled me with ideas for improvements for existing workflows. Hopefully the likes of the DIU will reap some benefits!

Berlin Dom und Fernsehturm
Insert standard caption regarding “old content meets new technology to surface it”!

Scott Renton, Digital Developer

*The commas are intentional, by the way!

Library Digital Development investigate IIIF

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Quick caveat: this post is a partner to the one Claire Knowles has written about our signing up to the IIIF Consortium, so the explanation of the acronym will not be explained here!

The Library Digital Development team decided to investigate the standard due to its appearance at every Cultural Heritage-related conference we’d attended in 2015, and we thought it would be apposite to update everyone with our progress.

First things first: we have managed to make some progress on displaying IIIF formatting to show what it does. Essentially, the standard allows us to display a remotely-served image on a web page, with our choice of size, rotation, mirroring and cropped section without needing to write CSS, HTML, or use Photoshop to manipulate the image; everything is done through the URL. The Digilib IIIF Server was very simple to get up and running (for those that are interested, it is distributed as a Java webapp that runs under Apache Tomcat), so here it is in action, using the standard IIIF URI syntax of [http://[server domain]/[webapp location]/[specific image identifier]/[region]/[size]/[mirror][rotation]/[quality].[format]]!

The URL for the following (image 0070025c.jpg/jp2) would be:

[domain]/0070025/full/full/0/default.jpg

Poster

This URL is saying, “give me image 0070025 (in this case an Art Collection poster), at full resolution, uncropped, unmirrored and unrotated: the standard image”.

[domain]/0070025/300,50,350,200/200,200/!236/default.jpg

posterbit

This URL says, “give me the same image, but this time show me co-ordinates 300px in from the left, 50 down from the top, to 350 in from the left, to 200 down from the top (of the original); return it at a resolution of 200px x 200px, rotate it at an angle of 236 degrees, and mirror it”.

The server software is only one part of the IIIF Image API: the viewer is very important too. There are a number of different viewers around which will serve up high-resolution zooming of IIIF images, and we tried integrating OpenSeaDragon with our Iconics collection to see how it could look when everything is up and running (this is not actually using IIIF interaction at this time, rather Microsoft DeepZoom surrogates, but it shows our intention). We cannot show you the test site, unfortunately, but our plan is that all our collections.ed.ac.uk sites, such as Art and Mimed, which have a link to the LUNA image platform, can have that replaced with an embedded high-res image like this. At that point, we will be able to hide the LUNA collection from the main site, thus saving us from having to maintain metadata in two places.

deepzoom

We have also met, as Claire says, the National Library’s technical department to see how they are doing with IIIF. They have implemented rather a lot using Klokan’s IIIFServer and we have investigated using this, with its integrated viewer on both Windows and Docker. We have only done this locally, so cannot show it here, but it is even easier to set up and configure than Digilib. Here’s a screenshot, to show we’re not lying.

eyes

Our plan to implement the IIIF Image API involves LUNA though. We already pay them for support and have a good working relationship with them. They are introducing IIIF in their next release so we intend to use that as a IIIF Server. It makes sense- we use LUNA for all our image management, it saves us having to build new systems, and because the software generates JP2K zoomable images, we don’t need to buy anything to do that (this process is not open, no matter how Open Source the main IIIF software may be!). We expect this to be available in the next month or so, and the above investigation has been really useful, as the experience with other servers will allow us to push back to LUNA to say “we think you need to implement this!”. Here’s a quick prospective screenshot of how to pick up a IIIF URL from the LUNA interface.

IIIFMenu

We still need to investigate more viewers (for practical use) and servers (for investigation), and we need to find out more about the Presentation API, annotations etc., but we feel we are making good progress nonetheless.

Scott Renton, Digital Developer

IIIF – International Image Interoperability Framework

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The next big thing
Inspirational quote on the side of a University of Ghent building, St. Pietersnieuwstraat 33.

The adoption of IIIF (International Image Interoperability Framework) has been gaining momentum over the past few years for digitised images. Adoption of IIIF for serving images allows users to rotate, zoom, crop, and compare images from different institutions side by side. Scott and I attended the IIIF conference in Ghent earlier this month to learn more about IIIF, so we can decide how we can move forward at the University of Edinburgh to adopt IIIF for our images.

On the Monday we attended a technical meeting at the University of Ghent Library, this session really helped us to understand the architecture of the two IIIF APIs (image and presentation) and speak to others who have implemented IIIF at their institutions.

The main event was on Tuesday at the beautiful Ghent Opera House, where there were lots of short presentations about different use-cases for IIIF adoption and the different applications that have been developed. If you are interested in adoption IIIF at your institution I recommend looking at Glen Robson’s slides on how the National Library of Wales has implemented IIIF. I can see myself coming back to these slides again and again, along with those on the two APIs.

Whilst we were in Ghent there was a timely update from LUNA Imaging, whose application we use as an imaging repository on their plans to support IIIF.

Thanks to everyone we met in Ghent who was willing to share with us their experiences of implementing IIIF and to the organisers for a great event in a beautiful city (and our stickers).

IIIF Meeting in Ghent Opera House
IIIF Meeting in Ghent Opera House

If you want to keep up to date with IIIF development please join the Google Group iiif-discuss@googlegroups.com

Claire Knowles and Scott Renton

Library Digital Development Team

 

 

‘Innovation’: the Emperor’s new clothes?

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Scott and I travelled down to Cambridge last week to speak at the Museum Computer Group’s Spring Meeting, ‘Innovation’: the Emperor’s new clothes? It was a very informative day that began with Peter Pavement, SurfaceImpression, giving us a history of digital innovation in museums. Including the first audio guides and the Senster, which was the first robotic sculpture to be controlled by a computer.

First Museum Audio Guides from Loic Tallon Flickr

First Museum Audio Guides

Peter discussing the Hype Cycle, where would you place new technological innovations?

The Hype Cycle

Sejul Malde, Culture 24, followed on from Peter. He discussed using existing assets and content, as well as small ‘process focused’ innovation rather than innovation through giant leaps. His emphasis on creating a rhythm for change made me reflect on how short sprints enabled us to get Collections.ed online. (Looking at our Github commit history highlights sprint deadlines.)

Scott and I then discussed the work we have being doing at Edinburgh to get our collections online through Collections.ed, which has been an iterative process starting off with four online collections launched May 2014, we now have eight collections online following the recent launch of our Iconics collection. We have also recently made a first import into Collections.ed of  776 unique crowdsourced tags we have obtained through Library Labs Metadata Games and those entered into Tiltfactor‘s metadata games.

The tags can been seen online in these two examples:
Charles Darwin’s Class Card
Bond M., White House in Warm Perthshire Valley

The slides from our presentation are available on ERA http://hdl.handle.net/1842/10415 and have a film theme running through them.

The new Iconics home page (I think it is my favourite so far):

iconicswithborder

In the afternoon Lizzie Edwards, Samsung Digital Discovery Centre, British Museum, lead a practical session where we had to think about how we could use new technologies in Museums. Jessica Suess, Oxford University Museums, spoke about their ‘Innovation Fund’ programme and how it had led to new ways of working and new collaborations with colleagues. She mentioned one project using Ipads as Art Sketchbooks http://www.ashmolean.org/education/dsketchbooks/ which was also showcased in a lightning talk.

Lightning talks and a Q&A session with HLF and Nesta finished off the day, you can find out more from Liz Hide’s storify of the day: https://storify.com/TheMuseumOfLiz/the-emperor-s-new-clothes

Claire Knowles and Scott Renton, Library Digital Development Team

Metadata Fun and Games

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MetadataGames1

Earlier this week we ran a 1980s-inspired crowdsourcing ‘Metadata Game’ to enhance the description of items within our online image collection http://images.is.ed.ac.uk. The good folk of Library and University Collections rallied to the cause and ten hardy volunteers surrendered their lunch breaks to take part in the session, sustained only by coffee, biscuits and a will to succeed.

Each participant was provided with a series of random images and received one ‘crowdsourcing point’ for every person, object or location they tagged. Can you spot a familiar face in one of the randomly-generated images below?

MetadataGames 2

Once the tagging was complete, the group then moderated the submitted terms and further points were awarded for approved tags. In the course of the session, 264 images were tagged a total of 631 times and, although time ran out during the moderation phase because of issues with load on the software, we learned a lot about the programme and received useful feedback for future sessions.

Norman Rodger from the Projects & Innovations team ran out the clear winner on this occasion, with 221 points, but he was pushed all the way by Sandi Phillips and Clare Button, who finished second and third with 155 and 146 points respectively.

We’ll be setting up the game again at the Pop Up Library during Freshers’ Week so come along and find us if you’re interested in having a go for yourself! Or if you’re anxious to have a shot now, please email gavin.willshaw@ed.ac.uk or scott.renton@ed.ac.uk and we’d be happy to send you the link. Maybe you can even set a new high score…