This session will be about managing RDF data programmatically. We will set up an RDF data base (also called a triplestore). We will convert existing, non-RDF data, into RDF, programmatically, then load it to the triplestore.
These instructions assume that you are programming in Java, preferably with Eclipse, using the Apache Jena libraries. You may also use RDF4J in Java, RDFlib in Python, or Redland RDF libary in C, or dotNetRDF in C♯, or EasyRDF for PHP, or N3.js for JavaScript, or Ruby RDF for Ruby, or SWI-Prolog Semantic Web Library, etc.
These operations should get you started with Apacha Jena and Eclipse. With a different IDE for Java, the only difference will be the initial settings for a Mavan project. If you are using a different library, look at the documentation.
File -> New -> Java Project...
.Next >
.Next >
.fr.emse.master
. In the Artifact's Artifact Id, write semweb
. Click Finish
.pom.xml
. Double click on this file.pom.xml
. If you used a different groupId
or artifactId
, change it accordingly.Now you will generate RDF data from non-RDF sources. Read the Jena tutorial to familiarise yourself with the API and learn how to generate an RDF graph programmatically. Once you are done with the tutorial, follow the instructions below.
stops.txt
in the dataset you downloaded. It just describes the names and location of train stations. What is relevant is the stop_id
, stop_name
, stop_lat
and stop_lon
.rdf:type
) of the class http://www.w3.org/2003/01/geo/wgs84_pos#SpatialThing
, usually abbreviated as geo:SpatialThing
. The WGS84 Geo Positioning vocabulary also provides RDF properties for latitude (geo:lat
) and longitude (geo:long
). Generate IRIs for each stops based on their stop_id
.@prefix ex: <http://www.example.com/> . @prefix geo: <http://www.w3.org/2003/01/geo/wgs84_pos#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix xsd: <http://www.w3.org/2001/XMLSchema#> . ex:StopArea:OCE80194035 a geo:SpatialThing; rdfs:label "gare de Neustadt (Weinstr) Hbf"@fr; geo:lat "49.35006155"^^xsd:decimal; geo:long "8.14067588"^^xsd:decimal .
There are many triplestores. The simplest to set up is probably Fuseki.
fuseki-server.bat
for Windows systems, fuseki-server
for Unix-based systems. Execute it. The server will be running in the background.http://localhost:3030
. This interface allows you to manage your data.In the exercise of the first part, you can generate all the data at once in a large Jena Model and serialise it as RDF, or you can fill in a triplestore little by little. If you want to add data to a triplestore such as Jena Fuseki, you can send update queries like this:
Model model = ModelFactory.createDefaultModel();
// ... build the model
String datasetURL = "http://localhost:3030/dataset";
String sparqlEndpoint = datasetURL + "/sparql";
String sparqlUpdate = datasetURL + "/update";
String graphStore = datasetURL + "/data";
RDFConnection conneg = RDFConnectionFactory.connect(sparqlEndpoint,sparqlUpdate,graphStore);
conneg.load(model); // add the content of model to the triplestore
conneg.update("INSERT DATA { <test> a <TestClass> }"); // add the triple to the triplestore
If you finish fast, you can then try to define a vocabulary for GTFS and transform all the SNCF data to RDF. Your vocabulary can also distinguish between train stations and coach stations, relate stations (StopArea) to more specific locations (StopPoint), etc.
To interact with a Linked Data Platform as in practical session 3 programmatically, you need to rely on an HTTP library in your programming language. You may use the Apache HTTP Client in Java (which is also a Jena dependency), or URLlib in Python, etc. Instead of using cURL, you send POST
requests with appropriate Turtle payload via the programming interfaces.
Write a program that reproduces the steps of practical session 3 (Publishing data on a Linked Data Platform).