Difference between revisions of "Lab: Web APIs and JSON-LD"

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=Lab 12: Accessing and lifting Web APIs (RESTful web services)=
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=Lab 5: Accessing and lifting Web APIs (RESTful web services)=
  
 
==Topics==  
 
==Topics==  
Programming regular (non-semantic) as well as semantic Web APIs (RESTful web services) with JSON and JSON-LD.
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Programming regular (non-semantic) Web APIs (RESTful web services) with JSON-LD.
 +
 
 +
We will use Web APIs to retrieve regular JSON data, parse them programmatically, where possible link the resources to established DBpedia ones and finally create a RDFLib graph with the data.
  
 
==Imports==
 
==Imports==
 +
* import json
 +
* import rdflib
 
* import requests
 
* import requests
* import json
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* import spotlight
* import pprint
 
  
 
==Tasks==
 
==Tasks==
===Regular JSON web APIs===
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=== Task 1 ===
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)).
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Write a small program that queries the Open Notify Astros API (link below) for the people currently in space. Create a graph from the response connecting each astronaut to the craft they are currently on, for instance using http://example.com/onCraft as a property. Also as the space station is not too big, it is safe to assume that two people who spent time on it at the same time know each other, so add this to the graph.
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").
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* Astros API url: http://api.open-notify.org/astros.json
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* Documentation: http://open-notify.org/Open-Notify-API/People-In-Space/
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* Requests Quickstart: https://docs.python-requests.org/en/latest/user/quickstart/
  
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 .
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The response from the API follows the format
  
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.  
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<syntaxhighlight>
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{
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    "message": "success",
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    "number": 7,
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    "people": [
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        {
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            "craft": "ISS",
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            "name": "Sergey Ryzhikov"
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        },
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        {
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            "craft": "ISS",
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            "name": "Kate Rubins"
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        },
 +
        ...
 +
    ]
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}
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</syntaxhighlight>
  
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):
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We only need to think about whats inside the list of the "people"-value.
{\"postalcodes\":[{\"adminCode2\":\"V\",\"adminCode1\":\"VC\",\"adminName2\":\"Valencia\",\"lng\":-0.377386808395386,\"countryCode\":\"ES\",\"postalcode\":\"46020\",\"adminName1\":\"Comunidad Valenciana\",\"placeName\":\"Valencia\",\"lat\":39.4697524227712}]}"
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To create the graph you can iteratively extract the values of craft and name and add them. As none of the names or craft is a valid URI, they can be crated using the example-namespace.
  
===Lifting JSON to JSON-LD===
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=== Task 2 ===
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Serialise the graph to JSON-LD, set the context of the JSON-LD object to represent the properties for knows and onCraft.
  
In python we can represent JSON objects as dictionaries ({}) and JSON Arrays as lists ([]).
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To do this you need to pip install the json-ld portion of rdflib if you have not already:
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<syntaxhighlight>
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pip install rdflib-jsonld
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</syntaxhighlight>
  
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.  
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=== If you have more time ===
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DBpedia Spotlight is a tool for automatically annotating mentions of DBpedia resources in text, providing a solution for linking unstructured information sources to the Linked Open Data cloud through DBpedia.
  
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".
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Build upon the program using the DBpedia Spotlight API (example code below) to use a DBpedia-resource in your graph if one is available. You can add some simple error-handling for cases where no DBpedia resource is found - use an example-entity in stead. Keep in mind that some resources may represent other people with the same name, so try to change the types-parameter so you only get astronauts in return, the confidence-parameter might also help you with this.
  
Add this pair too to the context object: "postalcodes" and "http://dbpedia.org/ontology/postalCode".  
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The response from DBpedia Spotlight is a list of dictionaries, where each dictionary contains the URI of the resource, its types and some other metadata we will not use now. Set the type of the resouce to the types listed in the response.
  
Add more string pairs, using existing or inventing new terms as you go along, to the context object.
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==== Example code for DBpedia Spotlight query ====
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First pip install <b>pyspotlight</b>
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<syntaxhighlight>
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import spotlight
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# Note that althoug we import spotlight in python, we need to pip install pyspotlight to get the correct package
  
In addition to expand, try the compact and flatten operations on the JSON object. What do they do?
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SERVER = "https://api.dbpedia-spotlight.org/en/annotate"
 
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annotations = spotlight.annotate(SERVER, "str_to_be_annotated")
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:
 
<syntaxhighlight>
 
pip install rdflib-jsonld
 
 
</syntaxhighlight>
 
</syntaxhighlight>
  
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()).
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==Useful Reading==
 
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* [https://stackabuse.com/reading-and-writing-json-to-a-file-in-python/ Reading and writing with JSON - stackabuse.com]
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")
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* [https://wiki.uib.no/info216/index.php/Python_Examples Examples]
 
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* [https://realpython.com/python-requests/ Requests - realpython.com]
 
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* [https://www.dbpedia-spotlight.org/api Spotlight Documentation]
===Useful Reading===
 
[https://stackabuse.com/reading-and-writing-json-to-a-file-in-python/ - Reading and writing with JSON - stackabuse.com]
 

Latest revision as of 14:20, 22 February 2022

Lab 5: Accessing and lifting Web APIs (RESTful web services)

Topics

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

We will use Web APIs to retrieve regular JSON data, parse them programmatically, where possible link the resources to established DBpedia ones and finally create a RDFLib graph with the data.

Imports

  • import json
  • import rdflib
  • import requests
  • import spotlight

Tasks

Task 1

Write a small program that queries the Open Notify Astros API (link below) for the people currently in space. Create a graph from the response connecting each astronaut to the craft they are currently on, for instance using http://example.com/onCraft as a property. Also as the space station is not too big, it is safe to assume that two people who spent time on it at the same time know each other, so add this to the graph.

The response from the API follows the format

{
    "message": "success",
    "number": 7,
    "people": [
        {
            "craft": "ISS",
            "name": "Sergey Ryzhikov"
        },
        {
            "craft": "ISS",
            "name": "Kate Rubins"
        },
        ...
    ]
}

We only need to think about whats inside the list of the "people"-value. To create the graph you can iteratively extract the values of craft and name and add them. As none of the names or craft is a valid URI, they can be crated using the example-namespace.

Task 2

Serialise the graph to JSON-LD, set the context of the JSON-LD object to represent the properties for knows and onCraft.

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

pip install rdflib-jsonld

If you have more time

DBpedia Spotlight is a tool for automatically annotating mentions of DBpedia resources in text, providing a solution for linking unstructured information sources to the Linked Open Data cloud through DBpedia.

Build upon the program using the DBpedia Spotlight API (example code below) to use a DBpedia-resource in your graph if one is available. You can add some simple error-handling for cases where no DBpedia resource is found - use an example-entity in stead. Keep in mind that some resources may represent other people with the same name, so try to change the types-parameter so you only get astronauts in return, the confidence-parameter might also help you with this.

The response from DBpedia Spotlight is a list of dictionaries, where each dictionary contains the URI of the resource, its types and some other metadata we will not use now. Set the type of the resouce to the types listed in the response.

Example code for DBpedia Spotlight query

First pip install pyspotlight

import spotlight
# Note that althoug we import spotlight in python, we need to pip install pyspotlight to get the correct package

SERVER = "https://api.dbpedia-spotlight.org/en/annotate"
annotations = spotlight.annotate(SERVER, "str_to_be_annotated")

Useful Reading