Lab: Web APIs and JSON-LD

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Lab 12: Accessing and lifting Web APIs (RESTful web services)

Topics

Programming regular (non-semantic) as well as semantic Web APIs (RESTful web services) with JSON and JSON-LD.

Imports

  • import requests
  • import json
  • import pprint

Tasks

Regular JSON web APIs

Write a small program that accesses a regular (non-semantic) web API and download the result. The "json" library in python can be used to load a json string as a json object (json.loads(data)). Use the the prettyprint import to print a readable version of the json object.

The GeoNames web API (http://www.geonames.org/export/ws-overview.html) offers many services. For example, you can use this URL to access more information about Ines' neighbourhood in Valencia: http://api.geonames.org/postalCodeLookupJSON?postalcode=46020&country=ES&username=demo (register to get your own username instead of "demo").

You do not have to use the GeoNames web API. There are lots and lots of other web APIs out there. But we want something simple that does not require extensive registration (HTTPS can also make things more complex when the certificates are outdated). Here are some examples to get you started if you want to try out other APIs: http://opendata.app.uib.no/ , http://data.ssb.no/api , http://ws.audioscrobbler.com/2.0/ , http://www.last.fm/api /intro , http://wiki.musicbrainz.org/Development/JSON_Web_Service .

While you are testing and debugging things, it is good to make measures so that you do not need to call the GeoNames or other API over and over. A solution can be writing the returned data to a file, or copying it into a variable.

Here is an example of a results string you can use, if you have trouble connecting to GeoNames (note that you have to escape all the quotation marks inside the Java string): {\"postalcodes\":[{\"adminCode2\":\"V\",\"adminCode1\":\"VC\",\"adminName2\":\"Valencia\",\"lng\":-0.377386808395386,\"countryCode\":\"ES\",\"postalcode\":\"46020\",\"adminName1\":\"Comunidad Valenciana\",\"placeName\":\"Valencia\",\"lat\":39.4697524227712}]}"

Lifting JSON to JSON-LD

In python we can represent JSON objects as dictionaries ({}) and JSON Arrays as lists ([]).

So far we have only used plain JSON. Now we want to move to JSON-LD, the semantic version of JSON. Make a new JSON object (dictionary/{} in python) called context. Put a single entry into this map, with "@context" as the key and another object ({}) as the value. It is this second map that contains the actual mappings.


Put at least one pair of strings into it. For example, if you used the postcode API, the pair "lat" and "http://www.w3.org/2003/01/geo/wgs84_pos#lat". You can also put the pair "lng" and "http://www.w3.org/2003/01/geo/wgs84_pos#long".

Add this pair too to the context object: "postalcodes" and "http://dbpedia.org/ontology/postalCode".

Add more string pairs, using existing or inventing new terms as you go along, to the context object.

In addition to expand, try the compact and flatten operations on the JSON object. What do they do?

Go back to the RDF/RDFS programs your wrote in labs 2 and 3. Extend the program so that it adds further information about the post codes of every person in your graph.

We will now make a RDFlib Graph from the JSON-LD object.

First you need to pip install the json-ld portion of rdflib if you have not already:

pip install rdflib-jsonld

Now, create a new Graph. Then convert the JSON-LD object to a string (use json.dumps() and write it to a file). Then parse the file with Rdflib (g.parse()).

Congratulations - you have now gone through the steps of accessing a web API over the net, lifting the results using JSON-LD, manipulating the in JSON-LD and reading them into a RDF Graph. Of course, it is easy to convert the RDFlib graph back into JSON-LD using g.serialize("json-ld")


Useful Reading

- Reading and writing with JSON - stackabuse.com