Serendipity and readability - Building an engaging online collection site with limited resources
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The Sarjeant Gallery's online collection site makes careful use of staff time and computer vision tools to provide multiple ways for visitors to explore their collection. The slides are a joint presentation from Paul Rowe and Jennifer Taylor Moore.
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Serendipity and readability - Building an engaging online collection site with limited resources
- 1. Serendipity and Readability: Building an Engaging Online Collection Site with Limited Resources Paul Rowe, Vernon Systems, @armchair_caver Jennifer Taylor Moore, Sarjeant Gallery Te Whare o Rehua Whanganui Museums and the Web, Apr 2018
- 2. Sarjeant Gallery Te Whare o Rehua Whanganui, New Zealand
- 3. The main collection store
- 5. Small budget ($US15,000) and timeframe
- 6. Did not have time for any major rework of the collection data
- 8. Open access: Publishing the whole collection
- 9. Open access: allowing re-use wherever possible
- 10. Open access: filtering by image rights
- 12. Considering visitor types Explorers Facilitators • Website should be easy to browse • Simple options to filter the collection • Explore options: colour, image orientation, time, subject, object type • Highlight works on display at the Gallery • Connect ‘visit planning’ pages where relevant Experience Seekers Rechargers • Explore by colour • Connect works by keywords • Provide highlight sets to showcase groups of works • Provide a clean, uncluttered website where the artworks are the focus Professional/Hobbyist • Provide advanced search options
- 13. Computer vision: Creating new data
- 14. Quick wins: adding nationality
- 15. Generating natural sentences based on object type, production place and date
- 16. Adding links to related Wikipedia and Te Ara pages
- 17. Referencing significant sub- collections from Wikipedia
- 18. Separate microsite for the online collection
- 19. Microsite: lower cost and more flexible design
- 20. Prototyping: used an unbranded “working wireframe” as the starting point
- 21. Prototyping: features in action
- 22. User testing: worthwhile even at a small scale
- 24. Adding shortcuts for exploring the collection
- 25. Making the best use of the data we had
- 27. Ensuring search engines can get to every page
- 29. Google Cloud Vision subject tags
- 31. Colour Analysis: extracting the raw colours was the easy part
- 32. Mapping to a smaller palette was hard
- 33. Indexing the colour names
- 34. Accessibility compliance Alternative text for images Responsive design for different devices Support for browser zooming to resize content
- 35. Prototype ideas not implemented: Changing background colour based on each artwork image
- 36. … but the background colours didn’t always work
- 37. Prototype ideas not implemented: Most popular colours by decade
- 38. Nationalmuseum, Sweden: Painting Madonna with child Prototype ideas not implemented: Full sentence captions
- 39. Create once, publish everywhere (COPE)
- 40. Collection Focus: Digital/Physical Parallels
- 41. Options for sharing on social media
- 42. What’s next: Monitoring with Google Analytics Page views by explore option: 35% via a curated highlight set 23% via an object type link 12% via a colour swatch
- 43. What’s next rights clearance interpretive descriptions regular changes to home page content
- 44. What’s next quantitative displays of data (acquisitions by decade for example) better highlighting of works on display Peoples’ Choice series
- 45. National award and praise from visitors
- 46. Combine it all and find “house AND white AND landscape”
- 47. Related links Blog posts Looking at the Sarjeant Gallery’s collection through robot eyes: https://medium.com/@armchair_caver/looking-at-sarjeant-gallerys- collection-through-robot-eyes-c7fd0281814e Building an accessible online collection for Sarjeant Gallery: https://medium.com/@armchair_caver/building-an-accessible-online- collection-for-sarjeant-gallery-48cbcac4fdb6 Websites Cogapp image tagging test site: http://labs.cogapp.com/iiif-ml/ Sarjeant Gallery: https://collection.sarjeant.org.nz Tools Color Thief: http://lokeshdhakar.com/projects/color-thief/ Google Cloud Vision API: https://cloud.google.com/vision/docs/
- 48. Paul Rowe, Vernon Systems Jennifer Taylor Moore, Sarjeant Gallery Te Whare o Rehua Whanganui Thank you!
Editor's Notes
- Kia ora, I’m Jennifer Taylor Moore, the Curator of Collections at the Sarjeant Gallery Te Whare o Rehua Whanganui – and I’m Paul Rowe, the CEO of Vernon Systems. We’re here to tell you about how we made the most of our online collection project with limited resources.
- The Sarjeant Gallery is located in a regional centre in the lower North Island of New Zealand. The Gallery has a small team of about 11 staff with no in-house IT or design staff. The Gallery building which opened in 1919 is a Category I listed heritage building.
- The Sarjeant Gallery’s nationally significant collection comprises of over 8,000 artworks and archival items spanning four centuries of European and New Zealand art history and is one of the country’s most comprehensive surveys of NZ art history in a regional centre.
- In 2014 the Gallery’s heritage building was identified as an ‘earthquake-prone’ building and closed to the public. We relocated to a smaller temporary site, called Sarjeant on the Quay, to maintain public programs during fundraising for earthquake strengthening of the heritage building. During this time there was an urgent need for online access to the collection as the temporary exhibition space is significantly restricted.
- We had a goal of launching a website for the online collection within four months of the start of the project, with a budget of USD$15,000. We were keen to build a website that provided open access to the collection and offered a variety of options for visitors to explore the collection online.
- The Gallery’s operating budget is very modest and any large funds that might have been available for this project had already been channelled towards fundraising for the redevelopment. The budget constraints meant that there were not enough resources to spend hours retrospectively inputting relevant data and keywords into the collection records, so we had to look for ways to quickly clean up the data and prioritise copyright clearance with the artists.
- Our collection was already catalogued in Vernon Systems’ collection management database and Vernon Systems offered to work in partnership with us to develop the new website. Vernon Systems’ provided the software and development resources we needed.
- We made the decision to put the entire collection online, including records where the image was not yet available. The full collection provided many more records to connect and online access is now helping us spot data that can be improved. The online access is also helping us reach copyright holders that we weren’t previously able to contact.
- The images have been put online even if they’re not perfect, as in this example where the image will be cropped when we have time to do so. We’ve allowed re-use of the images wherever possible and clearly mark images for which there are no known copyright restrictions.
- Search results can also be filtered by the current rights for each artwork, making it easy to find images for re-use. Here you can see our main rights categories.
- The site uses responsive templates to provide layouts for mobile, tablet, and desktop screens. For example, on smaller screens we display smaller image sizes. This also helps with speed over slower connections.
- We used John Falk’s research on museum visitor types as one way to assess our potential features. For example, we wanted to allow users to browse the collection by attributes such as colour or subject tags and this best fitted the ‘Explorer’ type visitors, but we still planned an advanced search screen to meet the needs of ‘Professionals’ researching the collection.
- We made a commitment to using computer vision, software that can automatically analyse images and adds more detailed information. We used a couple of products: Google Cloud Vision and Color Thief.
- We looked at what we could do quickly with the limited staff time that was available. With only an hour of work, we filled in the nationalities for the 40 countries of birth recorded in the system. We were able to display nationality as a search option for the majority of the artists in the collection. For example, if the birth place was Japan, then we display Japanese in the Nationality field.
- Many of the works did not have a description in the catalogue. By combining the object type, production place and date metadata we were able to generate natural sounding sentences. The website automatically checks how many other works there are online of the same type, giving the user a sense of scale within the online collection. The sentence also provides links to jump to other works with the same production place or object type. In this example we see a typical generated sentence. “This is one of 1,832 photographs in our collection. It was made in Whanganui circa 1907”.
- Two hours were spent matching the most common artists in the Gallery’s collection to Wikipedia and Te Ara (the encyclopaedia of New Zealand). About one third of the collection now connects to these additional resources. We felt it was essential that the online collection was not isolated from the rest of the web.
- We’ve also added links from Wikipedia back to the artist pages in cases where the Gallery has significant holdings. Again, by concentrating on the collection’s most important artists, this was a quick process. As time permits the Gallery will also add Wikipedia pages where they are missing for prominent artists.
- We made the decision to keep the online collection separate from the main website. This allowed us to build upon an existing working online collection product rather than trying to fit within the Gallery’s content management system. (WordPress). Online collections are complex to develop, so building from scratch was certainly not an option for us.
- The key disadvantages of a separate site are that you can’t search the collection from the main site and there’s a separate user interface for the visitor to understand. However, the site layout can focus on how best to present the collection, and we were able to incorporate many features that wouldn’t otherwise have been possible within the budget. The online collection site is also less likely to be affected by changes to the design of the main site in the future.
- Prototyping potential features was an essential step in deciding whether features were viable and how they could be best implemented. We started with an unbranded version of our online collection product and this became a working wireframe where we could test out ideas on layout and use of the data. Here for example we tried showing colour swatches in circles to evoke an artist’s palette. Some users didn’t realise that these were swatches they could click on to navigate to other artworks, and so the design was altered.
- The colour analysis took many iterations. For example, we were initially looking at the hue of the original colour and finding the closest matching colour from our smaller palette. Through the prototype we realised we needed to consider colour brightness and saturation to avoid cases like the false greens in this screenshot using test data in an early prototype.
- Even on a tight budget, user testing is essential in development projects. We made use of staff at Vernon Systems and Sarjeant Gallery who were not otherwise involved in the project, and asked for volunteers from people outside of our organisation. Our testers covered a range of ages and interests and they helped us spot problems and potential design improvements.
- The user testing helped us find areas where we could use plainer language, such on the terms of use page that is linked from wherever the image rights are displayed. We introduced the open and closed padlock icon to make it clearer which rights types allowed open access.
- The website includes several options for exploring the collection. In the testing we found users sometimes missed these options, so we added shortcuts at the top of the home page and in the menu so that these options are always above the fold.
- Through the prototype we also explored what we could do with the data we had, rather than data we wished we had. For example, the object type data was consistent, so we’ve used this on the home page as an explore option and we display counts for each category to again give the visitor a sense of scale within the online collection. We can immediately see for example that there are 1800 drawings in the collection.
- Similarly, we use data on the artwork page to avoid dead-ends, by always providing options to jump to related records, such as other artworks that depict the same subject or include the same colour.
- In the prototyping we looked at how features might serve more than one purpose. For example, we added an option to get a simple listing of all artists represented in the collection and this also provided search engines with links to get to every artist and artwork page on the website.
- The last part of the project looked at what computer generated data we could use. We could easily determine the image orientation from the file (landscape, portrait or square), so we’ve provided orientation as one option for filtering search results. For example, here are all of the Gretchen Albrecht works in landscape orientation.
- We used Google Cloud Vision to automatically add subject tags. Image analysis isn’t easy, and we do see examples of problematic keywords. We had to build tools for staff to manage the tags – either deleting a tag for a single record or deleting it across the whole site. For example, many of the photographs were tagged by Google as “Stock Photography” which wouldn’t have gone down well with the artists, so this tag was completely removed.
- But the automated tags don’t have to be perfect to create interesting results. All of these works have been tagged as ‘circle’. Most of them aren’t strictly circles, but the tags provide new connections to other works with similar shapes and lines.
- We used an open source tool called Color Thief to extract the most dominant colours from the original 16 million colour palette in the image. However, unless your collection is enormous, hardly any images will share the same exact colour with such a huge palette.
- These original colours needed to be matched to a smaller palette – in our case we used the 140 named web colours. With a smaller palette, more images share the same matching colour. However, as the palette gets smaller the colours you are displaying are gradually getting further away from the original precise image colours.
- Because we’re using named colours, all of the colours we detect can be added to the text search index. We index the colour name, such as crimson, along with the colour group, such as red. This allows people to type in a text search that includes colour words not referenced in the original cataloguing.
- We’ve also considered how the site can meet accessibility guidelines, making sure it works on different devices, adding alternative text for images, considering contrast levels, and allowing for zooming within a browser to easily change the size of the content.
- During the prototyping there were some features we decided not to go ahead with, and I’ll give a few examples of this. We considered automatically changing the background colour on the page to match the artwork as we can see on this page.
- However, for some artworks the background colour became distracting and it was hard to write generic enough rules to avoid this becoming a problem. In this screenshot you can also see mockup text for the generated description (on the right), as at this stage in the prototype we hadn’t yet written the code to do it for real.
- We also looked at showing how the dominant colours in collection changed over time. We pulled out the most popular colours for each production decade, but we were disappointed to find we ended up with fifty shades of beige. This concept may still be worth revisiting if we first remove the neutral colours from the palette in this display.
- We also considered generating a full sentence caption. However, this is particularly complex and I think it’s the weakest element in the computer vision tools available to us. We looked at a prototype that the web development company Cogapp made public and decided from this that full sentence captions were too variable in quality to use at this stage.
- With the finished website we have embraced the concept of Create once, publish everywhere. Gallery staff are using the online collection to engage the public in different ways, such as this example where the Gallery shared a set of works featuring moustaches as part of the Movember event. This was grouping of works was possible because of the Google subject tags.
- We’ve developed a Collection Focus series highlighting works by a featured artist from the collection. This is accompanied by a physical exhibition and the website provides digital access to the selected works.
- We have also included simple options for visitors to share a page on common social media platforms. This is done using the Open Graph metadata standard, which ensures the correct title, description and image from the page are carried over into the user’s social media post.
- We’re now planning what we can do next. Google Analytics is a valuable tool for assessing use of the website. We can see we’re reaching a much wider audience, with only 5% of visits coming from New Zealand. We can also see what parts of the site are the most used. For example, what options for exploring the site are people accessing.
- Gallery staff are currently working steadily through requesting copyright permission from artists and copyright holders to increase the number of images that can be displayed on the site. Every artist approached so far has responded positively. We’re also adding more interpretive descriptions to the catalogue and adding more carefully curated sets as another path into the collection.
- We had some ideas that didn’t make it to the prototype stage, such as presenting more visual displays of the breakdown of the collection. This is a concept we hope to look at further in a second development phase. We can also see that we need to better highlight on the artwork page when an artwork is on display in the gallery. We’re also developing a monthly series to be launched next year called My Choice where members of the public, using social media, can make collection selections from which we will choose a few to highlight on the website as virtual exhibitions.
- There has been very positive feedback from the artists and the visitors. We were fortunate to win the New Zealand cultural heritage sector’s annual award for the best new digital exhibition or collection.
- I’ll finish with one final example of what we have achieved. Visitors can search on several elements together, such as keywords, colour names, and image orientation. Here’s a search on “house AND white AND landscape” where all of these results were missing at least one of these descriptive elements in the original catalogue record.
- We’ve added a slide with references to related blog posts, websites and tools and the slides will be uploaded to SlideShare.
- We’ve focused our staff time on a few areas where data could be improved with minimal effort, and on the larger task of rights clearance. By carefully selecting and testing potential features we’ve completed the project on time and within budget. The current state of image analysis isn’t perfect, but computer vision has made it easier to discover the images and has opened up new connections within the collection. Thank you!