Showing posts with label html. Show all posts
Showing posts with label html. Show all posts
In the previous post I introduced our Discover the Queenslander project for the SLQ, and mentioned that we used the AngularJS web framework. That process has got me thinking about some of the technical challenges in creating rich collection interfaces, and the different approaches in play, and I'll report on these in the next two posts. In this one I'll focus on AngularJS, and in the next, some broader questions on working with collection data on the client side.
AngularJS is a Javascript-based framework that focuses on extending HTML to deal with dynamic content. Angular "binds" data to HTML elements; so change the data, and the HTML updates. Even better, the bindings are two-way: interacting with an HTML element can also change its bound data. Angular implements a MVC (Model View Controller) architecture, where the data structure is the Model, the HTML document is the View, and a Javascript Controller links the two together.
Our previous web-based collections projects (TroveMosaic, Manly Images, Prints and Printmaking) were built in plain JS and jQuery. The general approach is pretty straightforward: load and manipulate some collection metadata (either from an API or a static JSON file), then build the HTML dynamically (adding and styling elements according to the data). jQuery makes handling interactions with the HTML pretty straightforward. It also (in my experience) makes for a verbose mess. Because all the HTML is built dynamically there's a lot of code devoted to creating elements, setting attributes, then stuffing them into the DOM. Code that loads and munges data gets tangled with code that builds the document and code handling interactions. Some elements get styled with static CSS, others are styled with hard-coded attributes. It all works fine - jQuery is very robust - but under the surface, it's bad code.
AngularJS tidies this process up quite a bit. Here's a quick example showing how straightforward it is to bind some collection data to some HTML. Say we have a JSON array items where each item looks something like:
Angular lets us iterate over a list of elements with the ng-repeat directive; it will simply generate a <li> for each element in the items array. Attributes of each item i are easily bound to the HTML using the {{moustache}} notation - so the item title will appear inside the h1. Apart from the compact, HTML-based rendering syntax, the killer feature here is that the HTML stays bound to the data: in order to change the display, we simply change the contents of items. No jQuery-style DOM manipulation; the data drives the document.
So rendering items in a list is trivially easy; but what about more complex displays? It's a matter of creating the data structures you need, then binding them to HTML in the same way. The Queenslander grid interface (above) includes a histogram showing items per year. In HTML this is simply another list, where each column is a list element. To create the data structure we sort the items into a new array where each element contains both the year, and a count of its items. Then as in the example, we run through the array with Angular building an element (this time a column) for each year. Angular's ng-style directive lets us create a custom height for each element, based on the number of items in the year list. With an array yearTable, where each year y has a totalCount
Hopefully this gives a hint of how AngularJS can be applied to cultural collection interfaces. From a developer's perspective, there are a number of big advantages. Compared to our previous jQuery process, Angular simplifies the page-building process immensely; the templating approach encourages a separation of concerns and more organised, maintainable code. Angular's data-centric binding also provides some big wins. Data structures (models) become more important; Angular requires that you get your data organised before binding it to the DOM. Coming from the free-wheeling procedural world of jQuery, this data-centric approach was the biggest conceptual challenge. The bottom line is: manipulate the data, not the HTML. The payoff is that the work of keeping the HTML and the data coordinated just disappears. Angular's modular architecture and active developer community also bring benefits: in the Queenslander project for example we used ngStorage, a module that made the favourites incredibly easy to build.
Compared to standard web interfaces, the big difference here is that all the collection data (in this case some 1000 items worth) is in the browser, on the client side. No server calls, pulling down a few items at a time - instead we load the whole set up front, and build the interface dynamically based on that data. The biggest payoff for this approach is responsiveness - filtering and exploration are lightning fast - but there are problems too; search engines can't index this dynamic content, and it requires modern browsers with fast JS engines. Some would argue that this approach is just plain wrong; abusing the client/server architecture of the web. I'm more of a pragmatist, but there are certainly some technical issues to consider, and in the next post I'll go a bit deeper into this notion of client-side data for digital cultural collections.
AngularJS is a Javascript-based framework that focuses on extending HTML to deal with dynamic content. Angular "binds" data to HTML elements; so change the data, and the HTML updates. Even better, the bindings are two-way: interacting with an HTML element can also change its bound data. Angular implements a MVC (Model View Controller) architecture, where the data structure is the Model, the HTML document is the View, and a Javascript Controller links the two together.
Our previous web-based collections projects (TroveMosaic, Manly Images, Prints and Printmaking) were built in plain JS and jQuery. The general approach is pretty straightforward: load and manipulate some collection metadata (either from an API or a static JSON file), then build the HTML dynamically (adding and styling elements according to the data). jQuery makes handling interactions with the HTML pretty straightforward. It also (in my experience) makes for a verbose mess. Because all the HTML is built dynamically there's a lot of code devoted to creating elements, setting attributes, then stuffing them into the DOM. Code that loads and munges data gets tangled with code that builds the document and code handling interactions. Some elements get styled with static CSS, others are styled with hard-coded attributes. It all works fine - jQuery is very robust - but under the surface, it's bad code.
AngularJS tidies this process up quite a bit. Here's a quick example showing how straightforward it is to bind some collection data to some HTML. Say we have a JSON array items where each item looks something like:
{ "id":"702692-19340823-s002b",
"title":"Illustrated advertisement from The Queenslander, 23 August, 1934",
"description":["Caption: Practical garments","An Advertisement for women's clothing sewing patterns acquired through mail order from The Queenslander Pattern Service."],
"subjects":["women's clothing & accessories","advertisements"],
"thumbURL":"702692-19340823-s002.jpg",
"year":"1934"
}
To create a HTML list where each item appears as a list element:
<ul>
<li ng-repeat="i in items">
<h1>{{i.title}}</h1>
<img ng-src="{{i.thumbURL}}"/>
</li>
</ul>
Angular lets us iterate over a list of elements with the ng-repeat directive; it will simply generate a <li> for each element in the items array. Attributes of each item i are easily bound to the HTML using the {{moustache}} notation - so the item title will appear inside the h1. Apart from the compact, HTML-based rendering syntax, the killer feature here is that the HTML stays bound to the data: in order to change the display, we simply change the contents of items. No jQuery-style DOM manipulation; the data drives the document.
So rendering items in a list is trivially easy; but what about more complex displays? It's a matter of creating the data structures you need, then binding them to HTML in the same way. The Queenslander grid interface (above) includes a histogram showing items per year. In HTML this is simply another list, where each column is a list element. To create the data structure we sort the items into a new array where each element contains both the year, and a count of its items. Then as in the example, we run through the array with Angular building an element (this time a column) for each year. Angular's ng-style directive lets us create a custom height for each element, based on the number of items in the year list. With an array yearTable, where each year y has a totalCount
<ul>
<li ng-repeat="y in yearTable">
<div ng-style="{height: y.totalCount+'px'}"
ng-click="setYearFilter(y.year);" >
</li>
</ul>
Here Angular is doing some rudimentary data vis, linking variables in the data to the dimensions of each HTML element. Note also that each column element has an ng-click directive, calling a function that filters the items displayed. The term clouds for subjects and creators work the same way.Hopefully this gives a hint of how AngularJS can be applied to cultural collection interfaces. From a developer's perspective, there are a number of big advantages. Compared to our previous jQuery process, Angular simplifies the page-building process immensely; the templating approach encourages a separation of concerns and more organised, maintainable code. Angular's data-centric binding also provides some big wins. Data structures (models) become more important; Angular requires that you get your data organised before binding it to the DOM. Coming from the free-wheeling procedural world of jQuery, this data-centric approach was the biggest conceptual challenge. The bottom line is: manipulate the data, not the HTML. The payoff is that the work of keeping the HTML and the data coordinated just disappears. Angular's modular architecture and active developer community also bring benefits: in the Queenslander project for example we used ngStorage, a module that made the favourites incredibly easy to build.
Compared to standard web interfaces, the big difference here is that all the collection data (in this case some 1000 items worth) is in the browser, on the client side. No server calls, pulling down a few items at a time - instead we load the whole set up front, and build the interface dynamically based on that data. The biggest payoff for this approach is responsiveness - filtering and exploration are lightning fast - but there are problems too; search engines can't index this dynamic content, and it requires modern browsers with fast JS engines. Some would argue that this approach is just plain wrong; abusing the client/server architecture of the web. I'm more of a pragmatist, but there are certainly some technical issues to consider, and in the next post I'll go a bit deeper into this notion of client-side data for digital cultural collections.
Over the past twelve months we have been developing some new approaches to the challenge of providing rich, revealing interfaces to cultural collections. The key idea here is the notion of generous interfaces - an argument that we can (and should) show more of these collections than the search box normally allows; and that there's a zone between conventional web design and interactive data visualisation, where generous interfaces might happen. There's more on this concept in my NDF 2011 presentation, or (in a more formal mode) in the paper I presented at the recent ICA conference.
Here I want to introduce an experimental "generous interface" prototype. Manly Images is an explorer for the Manly Local Studies Image Library - a collection hosted by the Manly Library. This is a collection of around 7000 images, documenting the history of the Manly region from the 1800s to the 1990s. The aim here was to develop a "generous," exploratory, non-search interface to the collection, delivered in HTML.
The original intention here was simply to adapt our CommonsExplorer work into HTML - CommonsExplorer uses a linked combination of thumbnails and title words to provide a dense overview of an image collection. But to "show everything" would mean 7000 elements, a stretch even for modern browsers; and I wanted to experiment with some new approaches to overview which remains the key problem here - a really juicy one. Given 7000 images with titles and little else, how can we provide a compact but revealing representation of the whole collection?
Here, the strategy was to break the collection into smaller segments based on either terms in the title, or date, and to draw each segment as a simple HTML div, where the size of the box reflects the number of items in that segment. These segments also act as navigational elements, opening a "slider" type display for browsing through specific records, and finally a lightbox for larger images, with links to canonical URLs on both Trove and the Manly site.
As a visualisation, it's a bit like a treemap (without the heirarchy), or a reconfigured histogram. But a collection like this is more than a list of quantities; the texture and character of the images is crucial. So as well as showing quantity, the segments become windows revealing (fragments of) the images inside them in a rolling slideshow. We get a visual core-sample of each segment, revealing the character of that group; and across the collection as a whole, a shifting mosaic that reveals diversity (and consistency), and invites further exploration. An interesting side effect is that it becomes possible to surf through the whole collection without doing a thing; it will (eventually) just roll past. This might not be realistic in a traditional browser context, but that traditional, "sit-forward" user model is not what it used to be - as Marian Dork argues, the leisurely drift of the information flaneur might be more apt.
So, a rich exploratory interface to 7000 images, without search, and delivered entirely in HTML; we have shown that it's possible, but is it any good? I'll write up my own evaluation with some technical documentation shortly; meantime, feedback on the prototype is very welcome - and if you are interested in building on it, or adapting it for other collections, the source is up on GitHub.
Finally some acknowledgements: this project was funded by the State Library of New South Wales and supported by Cameron Morley and Ellen Forsyth; thanks to John Taggart of Manly Library for permission to use the image collection. The collection data is harvested from the excellent Trove API, developed by the National Library of Australia.
Here I want to introduce an experimental "generous interface" prototype. Manly Images is an explorer for the Manly Local Studies Image Library - a collection hosted by the Manly Library. This is a collection of around 7000 images, documenting the history of the Manly region from the 1800s to the 1990s. The aim here was to develop a "generous," exploratory, non-search interface to the collection, delivered in HTML.
The original intention here was simply to adapt our CommonsExplorer work into HTML - CommonsExplorer uses a linked combination of thumbnails and title words to provide a dense overview of an image collection. But to "show everything" would mean 7000 elements, a stretch even for modern browsers; and I wanted to experiment with some new approaches to overview which remains the key problem here - a really juicy one. Given 7000 images with titles and little else, how can we provide a compact but revealing representation of the whole collection?
Here, the strategy was to break the collection into smaller segments based on either terms in the title, or date, and to draw each segment as a simple HTML div, where the size of the box reflects the number of items in that segment. These segments also act as navigational elements, opening a "slider" type display for browsing through specific records, and finally a lightbox for larger images, with links to canonical URLs on both Trove and the Manly site.
As a visualisation, it's a bit like a treemap (without the heirarchy), or a reconfigured histogram. But a collection like this is more than a list of quantities; the texture and character of the images is crucial. So as well as showing quantity, the segments become windows revealing (fragments of) the images inside them in a rolling slideshow. We get a visual core-sample of each segment, revealing the character of that group; and across the collection as a whole, a shifting mosaic that reveals diversity (and consistency), and invites further exploration. An interesting side effect is that it becomes possible to surf through the whole collection without doing a thing; it will (eventually) just roll past. This might not be realistic in a traditional browser context, but that traditional, "sit-forward" user model is not what it used to be - as Marian Dork argues, the leisurely drift of the information flaneur might be more apt.
So, a rich exploratory interface to 7000 images, without search, and delivered entirely in HTML; we have shown that it's possible, but is it any good? I'll write up my own evaluation with some technical documentation shortly; meantime, feedback on the prototype is very welcome - and if you are interested in building on it, or adapting it for other collections, the source is up on GitHub.
Finally some acknowledgements: this project was funded by the State Library of New South Wales and supported by Cameron Morley and Ellen Forsyth; thanks to John Taggart of Manly Library for permission to use the image collection. The collection data is harvested from the excellent Trove API, developed by the National Library of Australia.
