mirror of
https://github.com/gsi-upm/sitc
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Add RDF/Turtle exercise
This commit is contained in:
J. Fernando Sánchez
parent
8913c5ecde
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"name": "python",
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"name": "python",
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"nbconvert_exporter": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"pygments_lexer": "ipython3",
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"version": "3.6.4"
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"version": "3.7.2"
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}
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}
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},
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},
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"nbformat": 4,
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"nbformat": 4,
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875
rdf/RDF.ipynb
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rdf/RDF.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"deletable": false,
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"editable": false,
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"nbgrader": {
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"checksum": "1fba29f718bbaa14890b305223712474",
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"grade": false,
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"grade_id": "cell-2bd9e19ffed99f81",
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"locked": true,
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"schema_version": 1,
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"solution": false
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}
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},
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"source": [
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"<header style=\"width:100%;position:relative\">\n",
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" <div style=\"width:80%;float:right;\">\n",
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" <h1>Course Notes for Learning Intelligent Systems</h1>\n",
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" <h3>Department of Telematic Engineering Systems</h3>\n",
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" <h5>Universidad Politécnica de Madrid</h5>\n",
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" </div>\n",
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" <img style=\"width:15%;\" src=\"../logo.jpg\" alt=\"UPM\" />\n",
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"</header>"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"deletable": false,
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"editable": false,
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"nbgrader": {
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"checksum": "59c5cb46c9d722f691206e766e5af557",
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"grade": false,
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"grade_id": "cell-51338a0933103db9",
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"locked": true,
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"schema_version": 1,
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"solution": false
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}
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},
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"source": [
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"# Introduction\n",
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"\n",
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"The goal of this exercise is to understand the usefulness of semantic annotation and the Linked Open Data initiative, by solving a practical use case.\n",
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"\n",
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"The student will achieve the goal through:\n",
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"\n",
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"* Analyzing the sequence of tasks required to generate and publish semantic data\n",
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"* Extending their knowledge using the set of additional documents and specifications\n",
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"* Creating a partial semantic definition using the Turtle format\n",
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"\n",
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"\n",
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"# Objectives\n",
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"\n",
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"The main objective is to learn how annotations can be unified on the web, by following the Linked Data principles.\n",
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"\n",
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"\n",
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"These concepts will be applied in a practical use case: obtaining a Graph of information about hotels and reviews about them.\n",
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"\n",
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"\n",
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"# Tools\n",
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"\n",
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"This notebook is self-contained, but it requires some python libraries.\n",
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"To install them, simply run the following line"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"deletable": false,
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"editable": false,
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"nbgrader": {
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"checksum": "387f9c38b548f29b56ae5ef5ae76fd4f",
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"grade": false,
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"grade_id": "cell-d7f1ea9c021693b8",
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"locked": true,
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"schema_version": 1,
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"solution": false
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}
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},
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"outputs": [],
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"source": [
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"!pip install --user -r requirements.txt"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Linked Data, RDF and Turtle\n",
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"\n",
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"\n",
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"The term [Linked Data](https://www.w3.org/wiki/LinkedData) refers to a set of best practices for publishing structured data on the Web.\n",
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"These principles have been coined by Tim Berners-Lee in the design issue note Linked Data.\n",
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"The principles are:\n",
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"\n",
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"1. Use URIs as names for things\n",
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"2. Use HTTP URIs so that people can look up those names\n",
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"3. When someone looks up a URI, provide useful information\n",
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"4. Include links to other URIs, so that they can discover more things\n",
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"\n",
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"The [RDF](https://www.w3.org/RDF/) is a standard model for data interchange on the Web.\n",
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"It formalizes some concepts behind Linked Data into a specification, which can be used to develop applications and store information.\n",
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"\n",
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"Explaining RDF is out of the scope of this notebook.\n",
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"The [resources section](#Useful-resources) contains some links if you wish to learn about RDF.\n",
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"\n",
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"The main idea behind RDF is that information is encoded in the form of triples:\n",
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"\n",
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"```turtle\n",
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"<subject> <predicate> <object>\n",
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"```\n",
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"\n",
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"Each of these, (`<subject>`, `<predicate>` and `<object>`) should be unique identifiers.\n",
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"\n",
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"For example, to say Timmy is a 6 year-old whose dog is Tobby, we would write:\n",
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"\n",
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"```turtle\n",
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"<http://example.org/Timmy> <http://example.org/hasDog> <http://example.org/Tobby>\n",
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"<http://example.org/Timmy> <http://example.org/age> 7\n",
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"```\n",
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"\n",
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"Note that we are not referring to \"any Timmy\", but to a *very specific* Timmy.\n",
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"We could learn more about this particular boy using that URI.\n",
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"The same goes for the dog, and for the concept of \"having a dog\", which we unambiguously encode as `<http://example.org/hasDog>`.\n",
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"This concept may be described as taking care of a dog, for example, whereas a different property `<http://yourwebsite.com/hasDog>` could be described as being the legal owner of the dog.\n",
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"\n",
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"\n",
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"RDF can be used to embed annotation in many places, including HTML document, using any compatible format.\n",
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"The options include including RDFa, XML, JSON-LD and [Turtle](https://www.w3.org/TR/turtle/).\n",
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"\n",
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"\n",
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"In the exercises, we will be using turtle notation, because it is very readable.\n",
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"\n",
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"Here's an example of document in Turtle, taken from the Turtle specification:\n",
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"\n",
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"```turtle\n",
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"@base <http://example.org/> .\n",
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"@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .\n",
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"@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .\n",
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"@prefix foaf: <http://xmlns.com/foaf/0.1/> .\n",
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"@prefix rel: <http://www.perceive.net/schemas/relationship/> .\n",
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"\n",
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"<#green-goblin>\n",
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" rel:enemyOf <#spiderman> ;\n",
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" a foaf:Person ; # in the context of the Marvel universe\n",
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" foaf:name \"Green Goblin\" .\n",
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"\n",
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"<#spiderman>\n",
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" rel:enemyOf <#green-goblin> ;\n",
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" a foaf:Person ;\n",
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" foaf:name \"Spiderman\", \"Человек-паук\"@ru .\n",
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"```\n",
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"\n",
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"\n",
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"The second exercise will show you how to extract this information from any website."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Vocabularies and schema.org\n",
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"\n",
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"Concepts (predicates, types, etc.) can be defined in vocabularies.\n",
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"These vocabularies can be reused in several applications.\n",
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"In the example above, we used the concept of person from an external vocabulary (`foaf:Person`, i.e. http://xmlns.com/foaf/0.1/Person).\n",
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"That way, we do not need to redefine the concept of Person in every application.\n",
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"There are several well known vocabularies, such as:\n",
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"\n",
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"* Dublin core, for metadata: http://dublincore.org/\n",
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"* FOAF (Friend-of-a-friend) for social networks: http://www.foaf-project.org/\n",
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"* SIOC for online communities: https://www.w3.org/Submission/sioc-spec/\n",
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"\n",
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"Using the same vocabularies also makes it easier to automatically process and classify information.\n",
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"\n",
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"\n",
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"That was the motivation behind Schema.org, a collaboration between Google, Microsoft, Yahoo and Yandex.\n",
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"They aim to provide schemas for structured data annotation of Web sites, e-mails, etc., which can be leveraged by search engines and other automated processes.\n",
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"\n",
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"They rely on RDF for representation, and provide a set of common vocabularies that can be shared by every web developer.\n",
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"\n",
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"\n",
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"There are thousands of properties in the schema.org vocabulary, and they offer a very comprehensive documentation.\n",
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"\n",
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"As an example, this is the documentation for hotels:\n",
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"\n",
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"* List of properties for the Hotel type: https://schema.org/Hotel\n",
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"* Documentation for hotels: https://schema.org/docs/hotels.html\n",
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"\n",
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"\n",
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"You can use the documentation to find properties (e.g. `checkinTime`), as well as the type of that property (e.g. `Datetime`)."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"deletable": false,
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"editable": false,
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"nbgrader": {
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"checksum": "fe9a246ba580c71385e9b83d414a1216",
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"grade": false,
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"grade_id": "cell-a1b60daabb1a9d00",
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"locked": true,
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"schema_version": 1,
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"solution": false
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}
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},
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"source": [
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"# Exercises"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"deletable": false,
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"editable": false,
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"nbgrader": {
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"checksum": "63879c425ec11742c95c728a578d109e",
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"grade": false,
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"grade_id": "cell-d9289e96b2b0f265",
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"locked": true,
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"schema_version": 1,
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"solution": false
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}
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},
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"source": [
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"## Instructions"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"deletable": false,
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"editable": false,
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"nbgrader": {
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"checksum": "e0b6464bce9263fb35543acf4acb31da",
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"grade": false,
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"grade_id": "cell-bb418e9bae1fef1a",
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"locked": true,
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"schema_version": 1,
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"solution": false
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}
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},
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"source": [
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"First of all, run the line below.\n",
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"It will import everything you need for the exercises."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"deletable": false,
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"editable": false,
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"nbgrader": {
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"checksum": "bf98cea45f42e3d0f1ab158693b40da7",
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"grade": false,
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"grade_id": "cell-4a1b60bd9974bbb1",
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"locked": true,
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"schema_version": 1,
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"solution": false
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}
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},
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"outputs": [],
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"source": [
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"from helpers import *\n",
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"from rdflib import term, RDF, Namespace"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"deletable": false,
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"nbgrader": {
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"checksum": "3e23398d5277f2db2b3b5fb84f9623d6",
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"grade": true,
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"grade_id": "cell-da88c2f8170436fe",
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"locked": false,
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"points": 0,
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"schema_version": 1,
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"solution": true
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}
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},
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"source": [
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"You have to fill in the parts marked:\n",
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"\n",
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"```\n",
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"# YOUR ANSWER HERE\n",
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"```\n",
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"\n",
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"To make sure everything is working, try the following example.\n",
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"The solution is:\n",
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"\n",
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"```turtle\n",
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"@prefix foaf: <http://xmlns.com/foaf/0.1/> .\n",
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"@prefix geo: <http://www.w3.org/2003/01/geo/wgs84_pos#> .\n",
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"@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .\n",
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"\n",
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"<http://purl.org/net/bsletten> \n",
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" a foaf:Person;\n",
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" foaf:interest <http://www.w3.org/2000/01/sw/>;\n",
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" foaf:based_near [\n",
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" geo:lat \"34.0736111\" ;\n",
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" geo:lon \"-118.3994444\"\n",
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" ] .\n",
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"```\n",
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"\n",
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"Fill in the answer and run the test code."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"deletable": false,
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"nbgrader": {
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"checksum": "69182e8fadb9c9751f76786e0fcb8803",
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"grade": false,
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"grade_id": "cell-808cfcbf3891f39f",
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"locked": false,
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"schema_version": 1,
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"solution": true
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}
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},
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"outputs": [],
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"source": [
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"%%ttl example\n",
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"\n",
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"# YOUR ANSWER HERE"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"deletable": false,
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"editable": false,
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"nbgrader": {
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"checksum": "5982ca82090e267401af135ca1f371a8",
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"grade": true,
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"grade_id": "cell-23e61b9f48d597fc",
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"locked": true,
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"points": 1,
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"schema_version": 1,
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"solution": false
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}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"g = solution('example')\n",
|
||||||
|
"test('Some triples have been loaded',\n",
|
||||||
|
" len(g))\n",
|
||||||
|
"test('A person has been defined',\n",
|
||||||
|
" g.subjects(RDF.type, term.URIRef('http://xmlns.com/foaf/0.1/Person')))\n",
|
||||||
|
"print('All tests passed. Well done!')"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"editable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"checksum": "a64acf02625b48b3c65b6e1bc1ba6c1a",
|
||||||
|
"grade": false,
|
||||||
|
"grade_id": "cell-e73f1933742f7ab3",
|
||||||
|
"locked": true,
|
||||||
|
"schema_version": 1,
|
||||||
|
"solution": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"source": [
|
||||||
|
"## Exercise 1: Definition of a Hotel"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"We will define some basic information about a hotel, and some reviews.\n",
|
||||||
|
"This should be the same type of information that some aggregators (e.g. TripAdvisor) offer in their websites.\n",
|
||||||
|
"\n",
|
||||||
|
"Namely, you need to define at least two hotels (you may add more than one), with the following information:\n",
|
||||||
|
"* Description\n",
|
||||||
|
"* Address\n",
|
||||||
|
"* Contact information\n",
|
||||||
|
"* City and country (location)\n",
|
||||||
|
"* Email\n",
|
||||||
|
"* logo\n",
|
||||||
|
"* Opening hours\n",
|
||||||
|
"* Price range\n",
|
||||||
|
"* Amenities (optional)\n",
|
||||||
|
"* Geolocation (optional)\n",
|
||||||
|
"* Images (optional)\n",
|
||||||
|
"\n",
|
||||||
|
"You should also add at least three reviews about hotels, with the following information:\n",
|
||||||
|
"* Name of the user that reviewed the Hotel\n",
|
||||||
|
"* Rating\n",
|
||||||
|
"* Date\n",
|
||||||
|
"* Replies by other users (optional)\n",
|
||||||
|
"* Aspects rated in each review (cleanliness, staff, etc...) (optional)\n",
|
||||||
|
"* Information about the user (name, surname, date the account was created) (optional)\n",
|
||||||
|
"\n",
|
||||||
|
"\n",
|
||||||
|
"You can check any hotel website for inspiration, like this [review of a hotel in TripAdvisor](https://www.tripadvisor.es/Hotel_Review-g1437655-d1088667-Reviews-Hotel_Spa_La_Salve-Torrijos_Province_of_Toledo_Castile_La_Mancha.html)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"To make sure we are following Principles 1 and 2, we should use URIs that can be queried.\n",
|
||||||
|
"For the sake of this exercise, you have two options:\n",
|
||||||
|
" \n",
|
||||||
|
"* Use the made-up `http://example/sitc/` as base for our URIs.\n",
|
||||||
|
"Hence, the URIs of our hotels will look like this: `http://example/sitc/my-fancy-hotel`.\n",
|
||||||
|
"These URIs can not be queried, **and should not be used in real annotations**, but we will see how to fix that in a future exercise.\n",
|
||||||
|
"* Use (blank nodes)[https://en.wikipedia.org/wiki/Blank_node] (e.g. `_:my-fancy-hotel`), which cannot be used by other people, but can be re-used in your annotations.\n",
|
||||||
|
"\n",
|
||||||
|
"\n",
|
||||||
|
"We will use the vocabularies defined in https://schema.org e.g.:\n",
|
||||||
|
" * https://schema.org/Review defines properties about reviews\n",
|
||||||
|
" * https://schema.org/Hotel defines properties about hotels\n",
|
||||||
|
" \n",
|
||||||
|
"\n",
|
||||||
|
"Your definition has to be included in the following cell.\n",
|
||||||
|
"\n",
|
||||||
|
"**Tip**: Define the schema prefix first, to avoid repeating `<http://schema.org/...>`."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"checksum": "44f8be14db3d3e42b5b85f0485206346",
|
||||||
|
"grade": false,
|
||||||
|
"grade_id": "definition",
|
||||||
|
"locked": false,
|
||||||
|
"schema_version": 1,
|
||||||
|
"solution": true
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"%%ttl hotel\n",
|
||||||
|
"\n",
|
||||||
|
"@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .\n",
|
||||||
|
"@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .\n",
|
||||||
|
"@prefix sitc: <http://example/sitc/> .\n",
|
||||||
|
"\n",
|
||||||
|
"\n",
|
||||||
|
"<http://example/sitc/GSIHOTEL> a <http://schema.org/Hotel> ;\n",
|
||||||
|
" <http://schema.org/description> \"This is just an example to get you started.\" .\n",
|
||||||
|
"\n",
|
||||||
|
"\n",
|
||||||
|
"# YOUR ANSWER HERE"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"editable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"checksum": "4f54963163a64f46058c86be139e5543",
|
||||||
|
"grade": true,
|
||||||
|
"grade_id": "definition-tests",
|
||||||
|
"locked": true,
|
||||||
|
"points": 10,
|
||||||
|
"schema_version": 1,
|
||||||
|
"solution": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"g = solution('hotel')\n",
|
||||||
|
"test('Some triples are loaded',\n",
|
||||||
|
" len(g))\n",
|
||||||
|
"\n",
|
||||||
|
"hotels = set(g.subjects(RDF.type, schema['Hotel']))\n",
|
||||||
|
"test('At least 2 hotels are loaded',\n",
|
||||||
|
" hotels,\n",
|
||||||
|
" 2,\n",
|
||||||
|
" atLeast)\n",
|
||||||
|
"\n",
|
||||||
|
"for hotel in hotels:\n",
|
||||||
|
" if 'GSIHOTEL' in hotel: # Do not check the example hotel\n",
|
||||||
|
" continue\n",
|
||||||
|
" props = g.predicates(hotel)\n",
|
||||||
|
" test('Each hotel has all required properties',\n",
|
||||||
|
" props,\n",
|
||||||
|
" list(schema[i] for i in ['description', 'email', 'logo', 'priceRange']),\n",
|
||||||
|
" func=containsAll)\n",
|
||||||
|
"\n",
|
||||||
|
"reviews = set(g.subjects(RDF.type, schema['Review']))\n",
|
||||||
|
"test('At least 3 reviews are loaded',\n",
|
||||||
|
" reviews,\n",
|
||||||
|
" 3,\n",
|
||||||
|
" atLeast)\n",
|
||||||
|
"\n",
|
||||||
|
"for review in reviews:\n",
|
||||||
|
" props = g.predicates(review)\n",
|
||||||
|
" test('Each review has all required properties',\n",
|
||||||
|
" props,\n",
|
||||||
|
" list(schema[i] for i in ['itemReviewed', 'reviewBody', 'reviewRating']),\n",
|
||||||
|
" func=containsAll)\n",
|
||||||
|
" ratings = list(g.objects(review, schema['reviewRating']))\n",
|
||||||
|
" for rating in ratings:\n",
|
||||||
|
" value = g.value(rating, schema['ratingValue'])\n",
|
||||||
|
" test('The review should have ratings', value)\n",
|
||||||
|
"\n",
|
||||||
|
"authors = set(g.objects(None, schema['author']))\n",
|
||||||
|
"for author in authors:\n",
|
||||||
|
" for prop in g.predicates(author, None):\n",
|
||||||
|
" if 'name' in str(prop).lower():\n",
|
||||||
|
" break\n",
|
||||||
|
"else:\n",
|
||||||
|
" assert \"At least a reviewer has a name (surname, givenName...)\"\n",
|
||||||
|
"\n",
|
||||||
|
"print('All tests passed. Congratulations!')\n",
|
||||||
|
"print()\n",
|
||||||
|
"print('Now you can try to add the optional properties')"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Exercise 2: Explore existing data"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"The goal of this exercise is to explore and compare annotations from existing websites.\n",
|
||||||
|
"\n",
|
||||||
|
"Semantic annotations are very useful on the web, because they allow `robots` to extract information about resources, and how they relate to other resources.\n",
|
||||||
|
"\n",
|
||||||
|
"For example, `schema.org` annotations on a website allow Google to show summaries and useful information (e.g. price and location of a hotel) in their results.\n",
|
||||||
|
"A similar technology powers their knowledge graph and the \"related search\". i.e. when you look for a famous actor, it will first show you their filmography, and a list of related actors.\n",
|
||||||
|
"\n",
|
||||||
|
"The information has to be provided using the official standards (RDF), to comply with the 3rd principle of linked data.\n",
|
||||||
|
"\n",
|
||||||
|
"To follow the 4<sup>th</sup> principle of linked data, the annotations should include links to known sources (e.g. DBpedia) whenever possible."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"Let us explore some semantic annotations from popular websites.\n",
|
||||||
|
"\n",
|
||||||
|
"First, start with hotel reviews and websites. Here are some examples:\n",
|
||||||
|
"\n",
|
||||||
|
"* TripAdvisor hotels\n",
|
||||||
|
"* Trivago\n",
|
||||||
|
"* Kayak\n",
|
||||||
|
"* Specific hotel reviews\n",
|
||||||
|
"\n",
|
||||||
|
"\n",
|
||||||
|
"These are just two examples:"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"print_data('http://www.hotellasalve.com/')"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"print_data('https://www.mandarinoriental.com/madrid/hotel-ritz/luxury-hotel')"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"editable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"checksum": "a29112f51cc3299c7cae27841feb7410",
|
||||||
|
"grade": false,
|
||||||
|
"grade_id": "cell-9bf9c7d7516fae75",
|
||||||
|
"locked": true,
|
||||||
|
"schema_version": 1,
|
||||||
|
"solution": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"source": [
|
||||||
|
"Once you've extracted and analyzed different sources, answer the following questions:\n",
|
||||||
|
"\n",
|
||||||
|
"\n",
|
||||||
|
"### Questions:\n",
|
||||||
|
"\n",
|
||||||
|
"What type of data do they offer?"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"checksum": "2a7a6ab7d69f7ca5db64233128260045",
|
||||||
|
"grade": true,
|
||||||
|
"grade_id": "cell-17508ecf96884653",
|
||||||
|
"locked": false,
|
||||||
|
"points": 0,
|
||||||
|
"schema_version": 1,
|
||||||
|
"solution": true
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"source": [
|
||||||
|
"# YOUR ANSWER HERE"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"editable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"checksum": "531928c9e3b8462baddd4d700c240995",
|
||||||
|
"grade": false,
|
||||||
|
"grade_id": "cell-d36826d6323c96e8",
|
||||||
|
"locked": true,
|
||||||
|
"schema_version": 1,
|
||||||
|
"solution": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"source": [
|
||||||
|
"What vocabularyes and ontologies do they use?"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"checksum": "f100004eceae0c8159ade9d713af47e7",
|
||||||
|
"grade": true,
|
||||||
|
"grade_id": "cell-17508ecf96884655",
|
||||||
|
"locked": false,
|
||||||
|
"points": 0,
|
||||||
|
"schema_version": 1,
|
||||||
|
"solution": true
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"source": [
|
||||||
|
"# YOUR ANSWER HERE"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"What are the similarities between sites"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"checksum": "3d9ad086580ee27d93395dac8c16551d",
|
||||||
|
"grade": true,
|
||||||
|
"grade_id": "cell-30797c9ac87cc7e1",
|
||||||
|
"locked": false,
|
||||||
|
"points": 0,
|
||||||
|
"schema_version": 1,
|
||||||
|
"solution": true
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"source": [
|
||||||
|
"# YOUR ANSWER HERE"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"What are the similarities between sites"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"checksum": "4c03ad45eb1234cadccab2b468a69123",
|
||||||
|
"grade": true,
|
||||||
|
"grade_id": "answer-similarities",
|
||||||
|
"locked": false,
|
||||||
|
"points": 0,
|
||||||
|
"schema_version": 1,
|
||||||
|
"solution": true
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"source": [
|
||||||
|
"# YOUR ANSWER HERE"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"What are the biggest differences"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"checksum": "6ccc2db2be4826a146a6c34bc54f00de",
|
||||||
|
"grade": true,
|
||||||
|
"grade_id": "cell-17508ecf96884657",
|
||||||
|
"locked": false,
|
||||||
|
"points": 0,
|
||||||
|
"schema_version": 1,
|
||||||
|
"solution": true
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"source": [
|
||||||
|
"# YOUR ANSWER HERE"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"editable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"checksum": "33e1ec78415c85a795e86211d88316c2",
|
||||||
|
"grade": false,
|
||||||
|
"grade_id": "cell-5f922dc14ad3236a",
|
||||||
|
"locked": true,
|
||||||
|
"schema_version": 1,
|
||||||
|
"solution": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"source": [
|
||||||
|
"Are all properties from Exercise 1 given by the websites? What's missing?"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"checksum": "e0b4d9f1a2dfe5a7ab835f7349aa3796",
|
||||||
|
"grade": true,
|
||||||
|
"grade_id": "answer-missing",
|
||||||
|
"locked": false,
|
||||||
|
"points": 0,
|
||||||
|
"schema_version": 1,
|
||||||
|
"solution": true
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"source": [
|
||||||
|
"# YOUR ANSWER HERE"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"editable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"checksum": "26eb04e562aa6c7d29efa8318982a337",
|
||||||
|
"grade": false,
|
||||||
|
"grade_id": "cell-7a3c1553c4d6a9b7",
|
||||||
|
"locked": true,
|
||||||
|
"schema_version": 1,
|
||||||
|
"solution": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"source": [
|
||||||
|
"## Optional\n",
|
||||||
|
"\n",
|
||||||
|
"There is nothing special about review sites.\n",
|
||||||
|
"You can get information about any website.\n",
|
||||||
|
"\n",
|
||||||
|
"Verify this running checking:\n",
|
||||||
|
"\n",
|
||||||
|
"* News sites: e.g. https://edition.cnn.com/\n",
|
||||||
|
"* CMS: e.g. http://www.etsit.upm.es\n",
|
||||||
|
"* Twitter profiles: e.g. https://www.twitter.com/cif\n",
|
||||||
|
"* Mastodon (a Twitter alternative) profiles: e.g. https://mastodon.social/@Gargron/\n",
|
||||||
|
"* Twitter status pages: e.g. http://mobile.twitter.com/TBLInternetBot/status/1054438951237312514\n",
|
||||||
|
"* Mastodon (a Twitter alternative) status pages: e.g. https://mastodon.social/@Gargron/101202440923902326\n",
|
||||||
|
"* Wikipedia entries: e.g. https://es.wikipedia.org/wiki/Tim_Berners-Lee\n",
|
||||||
|
"* Facebook groups: e.g. https://www.facebook.com/universidadpolitecnicademadrid/"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"print_data('https://mastodon.social/@Gargron')"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"editable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"checksum": "cffc12120c51a7d994063f66d788570a",
|
||||||
|
"grade": false,
|
||||||
|
"grade_id": "cell-ec8df1a53c3d3f23",
|
||||||
|
"locked": true,
|
||||||
|
"schema_version": 1,
|
||||||
|
"solution": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"source": [
|
||||||
|
"# Useful resources\n",
|
||||||
|
"\n",
|
||||||
|
"* TTL validator: http://ttl.summerofcode.be/\n",
|
||||||
|
"* RDF-turtle specification: https://www.w3.org/TR/turtle/\n",
|
||||||
|
"* Schema.org documentation: https://schema.org\n",
|
||||||
|
"* Wikipedia entry on the Turtle syntax: https://en.wikipedia.org/wiki/Turtle_(syntax)\n",
|
||||||
|
"* RDFLib, the most popular python library for RDF (we use it in the tests): https://rdflib.readthedocs.io/"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"# Bibliography\n",
|
||||||
|
"\n",
|
||||||
|
"* W3C website on Linked Data: https://www.w3.org/wiki/LinkedData\n",
|
||||||
|
"* W3C website on RDF: https://www.w3.org/RDF/\n",
|
||||||
|
"* Turtle W3C recommendation: https://www.w3.org/TR/turtle/"
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"kernelspec": {
|
||||||
|
"display_name": "Python 3",
|
||||||
|
"language": "python",
|
||||||
|
"name": "python3"
|
||||||
|
},
|
||||||
|
"language_info": {
|
||||||
|
"codemirror_mode": {
|
||||||
|
"name": "ipython",
|
||||||
|
"version": 3
|
||||||
|
},
|
||||||
|
"file_extension": ".py",
|
||||||
|
"mimetype": "text/x-python",
|
||||||
|
"name": "python",
|
||||||
|
"nbconvert_exporter": "python",
|
||||||
|
"pygments_lexer": "ipython3",
|
||||||
|
"version": "3.7.2"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"nbformat": 4,
|
||||||
|
"nbformat_minor": 2
|
||||||
|
}
|
||||||
148
rdf/helpers.py
Normal file
148
rdf/helpers.py
Normal file
@ -0,0 +1,148 @@
|
|||||||
|
import sys
|
||||||
|
import operator
|
||||||
|
import types
|
||||||
|
from future.standard_library import install_aliases
|
||||||
|
install_aliases()
|
||||||
|
|
||||||
|
from urllib import request, parse
|
||||||
|
from rdflib import Graph, term, Namespace, BNode
|
||||||
|
from lxml import etree
|
||||||
|
|
||||||
|
import IPython
|
||||||
|
js = "IPython.CodeCell.options_default.highlight_modes['magic_turtle'] = {'reg':[/^%%ttl/]};"
|
||||||
|
IPython.core.display.display_javascript(js, raw=True)
|
||||||
|
|
||||||
|
|
||||||
|
from IPython.core.magic import (register_line_magic, register_cell_magic,
|
||||||
|
register_line_cell_magic)
|
||||||
|
from IPython.display import HTML, display, Image, Markdown
|
||||||
|
|
||||||
|
|
||||||
|
schema = Namespace('http://schema.org/')
|
||||||
|
|
||||||
|
DEFINITIONS = {}
|
||||||
|
|
||||||
|
def solution(exercise='default'):
|
||||||
|
if exercise not in DEFINITIONS:
|
||||||
|
raise Exception('Solution for {} not found'.format(exercise))
|
||||||
|
return DEFINITIONS[exercise]
|
||||||
|
|
||||||
|
|
||||||
|
@register_cell_magic
|
||||||
|
def ttl(line, cell):
|
||||||
|
'''
|
||||||
|
TTL magic command for ipython. It can be used in a cell like this:
|
||||||
|
|
||||||
|
```
|
||||||
|
%%ttl
|
||||||
|
|
||||||
|
... Your TTL definition ...
|
||||||
|
|
||||||
|
```
|
||||||
|
The definition will be loaded into a DEFINITION variable, using RDFlib.
|
||||||
|
This definition can then be used for evaluation.
|
||||||
|
'''
|
||||||
|
g = Graph()
|
||||||
|
msg = '''Error on line {line}
|
||||||
|
|
||||||
|
Reason: {reason}
|
||||||
|
|
||||||
|
If you don\'t know what this error means, try an online validator: http://ttl.summerofcode.be/
|
||||||
|
'''
|
||||||
|
global DEFINITIONS
|
||||||
|
key = line or 'default'
|
||||||
|
try:
|
||||||
|
DEFINITIONS[key] = g.parse(data=cell,
|
||||||
|
format="ttl")
|
||||||
|
except SyntaxError as ex:
|
||||||
|
return Markdown(msg.format(line=ex.lines, reason=ex._why))
|
||||||
|
except Exception as ex:
|
||||||
|
return Markdown(msg.format(line='?', reason=ex))
|
||||||
|
return Markdown('File loaded!')
|
||||||
|
|
||||||
|
return HTML('Loaded!') #HTML('<code>{}</code>'.format(cell))
|
||||||
|
|
||||||
|
|
||||||
|
def extract_data(url):
|
||||||
|
g = Graph()
|
||||||
|
try:
|
||||||
|
g.parse(url, format='rdfa')
|
||||||
|
except Exception:
|
||||||
|
print('Could not get rdfa data', file=sys.stderr)
|
||||||
|
try:
|
||||||
|
g.parse(url, format='microdata')
|
||||||
|
except Exception:
|
||||||
|
print('Could not get microdata', file=sys.stderr)
|
||||||
|
|
||||||
|
|
||||||
|
def sanitize_triple(t):
|
||||||
|
"""Function to remove bad URIs from the graph that would otherwise
|
||||||
|
make the serialization fail."""
|
||||||
|
def sanitize_triple_item(item):
|
||||||
|
if isinstance(item, term.URIRef) and ' ' in item:
|
||||||
|
return term.URIRef(parse.quote(str(item)))
|
||||||
|
return item
|
||||||
|
|
||||||
|
return (sanitize_triple_item(t[0]),
|
||||||
|
sanitize_triple_item(t[1]),
|
||||||
|
sanitize_triple_item(t[2]))
|
||||||
|
|
||||||
|
|
||||||
|
with request.urlopen(url) as response:
|
||||||
|
# Get all json-ld objects embedded in the html file
|
||||||
|
html = response.read().decode('utf-8', errors='ignore')
|
||||||
|
parser = etree.XMLParser(recover=True)
|
||||||
|
root = etree.fromstring(html.encode(), parser=parser)
|
||||||
|
if root is not None and len(root):
|
||||||
|
for jsonld in root.findall(".//script[@type='application/ld+json']"):
|
||||||
|
g.parse(data=jsonld.text, publicID=BNode(), format='json-ld')
|
||||||
|
|
||||||
|
|
||||||
|
fixedgraph = Graph()
|
||||||
|
fixedgraph += [sanitize_triple(s) for s in g]
|
||||||
|
|
||||||
|
# print(g.serialize(format='turtle').decode('utf-8', errors='ignore'))
|
||||||
|
return fixedgraph
|
||||||
|
|
||||||
|
def turtle(g):
|
||||||
|
return Markdown('''
|
||||||
|
Results:
|
||||||
|
|
||||||
|
```turtle
|
||||||
|
{}
|
||||||
|
```
|
||||||
|
'''.format(g.serialize(format='turtle').decode('utf-8', errors='ignore')))
|
||||||
|
|
||||||
|
def print_data(url):
|
||||||
|
g = extract_data(url)
|
||||||
|
return turtle(g)
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
def test(description, got, expected=None, func=None):
|
||||||
|
if isinstance(got, types.GeneratorType):
|
||||||
|
got = set(got)
|
||||||
|
try:
|
||||||
|
if expected is None:
|
||||||
|
func = func or operator.truth
|
||||||
|
expected = True
|
||||||
|
assert func(got)
|
||||||
|
else:
|
||||||
|
func = func or operator.eq
|
||||||
|
assert func(got, expected)
|
||||||
|
except AssertionError:
|
||||||
|
print('Test failed: {}'.format(description), file=sys.stderr)
|
||||||
|
print('\tExpected: {}'.format(expected), file=sys.stderr)
|
||||||
|
print('\tGot: {}'.format(got), file=sys.stderr)
|
||||||
|
raise Exception('Test failed: {}'.format(description))
|
||||||
|
|
||||||
|
|
||||||
|
def atLeast(lst, number):
|
||||||
|
return len(set(lst))>=number
|
||||||
|
|
||||||
|
def containsAll(lst, other):
|
||||||
|
for i in other:
|
||||||
|
if i not in lst:
|
||||||
|
print('{} not found'.format(i), file=sys.stderr)
|
||||||
|
return False
|
||||||
|
return True
|
||||||
Loading…
Reference in New Issue
Block a user