I think I’ve probably left it too late to think up some sort of hack for the UK Discovery developer competition, but here’s a fragment that might provide a starting point for someone else… How to use a Yahoo pipe to grab a list of photos in a particular flickr set (such as one of the sets posted by the UK National Archive to the flickr commons)
The recipe makes use of two calls to the flickr api: one to get the a list of photos in a particular set, the second, repeatedly made call, to grab details down for each photo in the set.
In pseudo-code, we would write the algorithm along the lines of:
get list of photos in a given flickr set for each photo in the set: get the details for the photo
Here’s the pipe:
The first step is construct a call to the flickr API to pull down the photos in a given set. The API is called via a URI of the form:
The API returns a JSON object containing separate items identifying each photo in the set.
The rename block constructs a new attribute for each photo item (detailURI) containing the corresponding photo ID. The RegEx block applies a regular expression to each item’s detailURI attribute to transform it to a URI that calls the flickr API for details of a particular phot, by photo id. The call this time is of the form:
Finally, the Loop block runs through each item in the original set, calls the flickr API using the detailURI to get the details for the corresponding photo, and replaces each item with the full details of each photo.
You can find the pipe here: grabbing photo details for photos in a flickr set
An obvious next step might be to enrich the phot decriptions with semantic tags using something like the Reuters OpenCalais service. On a quick demo, this didn’t seem to work in the pipes context (I wonder if there is Calais API throttling going on, or maybe a timeout?) but I’ve previously posted a recipe using Python that shows how to call the Open Calais service in a Python context: Augmenting OU/BBC Co-Pro Programme Data With Semantic Tags.
Again in pseudo code, we might do something like:
get JSON feed out of Yahoo pipe for each item: call the Calais API against the description element
We could then index the description, title, and semantic tags for each photo and use them to support search and linking between items in the set.
Other pivots potentially arise from identifying whether photos are members of other sets, and using the metadata associated with those other sets to support discovery, as well as information contained within comments associate with each photo.