Triply has converted the famous Iris flower dataset to linked data! It is a multivariate dataset that quantifies the morphologic variation of Iris flowers of three different species, measured in four different properties. In this data cube, each species of Iris occurs 50 times and this linked data version uses the RDF Data Cube Vocabulary.
How to start a SPARQL service
TriplyDB allows you to expose your dataset through SPARQL. Exposing your data via SPARQL gives you the opportunity to create SPARQL queries and datastories over your own dataset or datasets from others. On TriplyDB you can already find a several examples of SPARQL queries. But creating your own SPARQL queries requires you to first start a SPARQL service over your dataset. The following step by step guide helps you to start a SPARQL service.
- Go to the Services page and you'll see a form to create a SPARQL service.
- To Create a SPARQL service you fill in a name for your service and select SPARQL from the three options.
Create serviceto confirm your choices and a SPARQL service will be started.
- Wait until the status of the service changed to
- A new option called
SPARQLwill appear in the sidebar. Clicking the button opens the SPARQL editor where you can write queries over your dataset.
How to import DBpedia
The iris dataset reuses classes, properties and resources from DBpedia. This not only reduces the amount of maintenance, but by reusing objects from DBpedia we can make use of the links that DBpedia already created. But before you can use the objects from DBpedia you'll first need to import DBpedia into the Iris dataset. The following step by step guide helps you do exactly that.
- Go to the Graphs page and click on
import a new graph
- Click on
Add data from an existing dataset
- Type in
DBpedia-association / dbpediafrom the dropdown menu.
- The page should now change and there is now one graph selected. This graph consist out of
369.205.380statements and is the full DBpedia dataset.
- To import this into your dataset you can click
import 1 graphs. This will add the DBpedia graph into your dataset.
- You've now imported the DBpedia graph into your dataset. You can now use the browser and see more information about DBpedia resources.
- To remove the DBpedia graph from your dataset you can go the graphs page and remove the dataset by clicking on the
https://triplydb.com/wikimedia/dbpedia/graphs/defaultgraph. This will remove your local connection to DBpedia.
PS: It is not allowed to start or sync a service when DBpedia is added as a graph. To start a service you will first need to remove the DBpedia graph by following step 7.
The Covid Statistics Profile data consists of the up to date Covid-19 Daily Statistics as well as the Profile of Covid-19 Daily Statistics for Ireland, as reported by the Health Surveillance Protection Centre. The Covid-19 Daily Statistics are updated on a daily basis, with the latest record reporting the counts recorded at 1pm the same day. The further breakdown of these counts (age, gender, transmission, etc.) is part of a Daily Statistics Profile of Covid-19, an analysis that utilises the data that dates back to 12am two days previous to help identify patterns and trends.
The Covid County Statistics data consists of Covid-19 Daily Statistics for Ireland by County as reported by the Health Surveillance Protection Centre. This data links into the OSi county geospatial Linked Data through the Unique Geospatial Identifier (UGI) for each each county.