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.

Version: 1.0.0

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.

Version: 1.0.0

An ontology to capture the use of OWL 2 semantics in RDF knowledge graphs.

Version: 1.0.0

Named Graphs is the idea that having multiple RDF graphs in a single document/repository and naming them with URIs provides useful additional functionality built on top of the RDF Recommendations.

Named Graphs and corresponding technologies are currently developed by participants of the Semantic Web Interest Group. The intent is to introduce them into the W3C process in an appropriate way once initial versions are finished.

Version: 1.0.0

SDMX vocabulary describing the core statistical concepts.

Version: 1.0.0

The World Factbook, also known as the CIA World Factbook, is a reference resource produced by the Central Intelligence Agency with almanac-style information about the countries of the world.

Version: 1.0.0

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 do to start a SPARQL service.

  1. Go to the Services page and you'll see a form to create a SPARQL service.
  2. To Create a SPARQL service you fill in a name for your service and select SPARQL from the three options.
  3. Press Create service to confirm your choices and a SPARQL service will be started.
  4. Wait until the status of the service changed to running.
  5. A new option called SPARQL will 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.

  1. Go to the Graphs page and click on import a new graph
  2. Click on Add data from an existing dataset
  3. Type in DBpedia and select DBpedia-association / dbpedia from the dropdown menu.
  4. The page should now change and there is now one graph selected. This graph consist out of 369.205.380 statements and is the full DBpedia dataset.
  5. To import this into your dataset you can click import 1 graphs. This will add the DBpedia graph into your dataset.
  6. You've now imported the DBpedia graph into your dataset. You can now use the browser and see more information about DBpedia resources.
  7. To remove the DBpedia graph from your dataset you can go the graphs page and remove the dataset by clicking on the X behind the https://triplydb.com/wikimedia/dbpedia/graphs/default graph. 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.

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 do to start a SPARQL service.

  1. Go to the Services page and you'll see a form to create a SPARQL service.
  2. To Create a SPARQL service you fill in a name for your service and select SPARQL from the three options.
  3. Press Create service to confirm your choices and a SPARQL service will be started.
  4. Wait until the status of the service changed to running.
  5. A new option called SPARQL will 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.

  1. Go to the Graphs page and click on import a new graph
  2. Click on Add data from an existing dataset
  3. Type in DBpedia and select DBpedia-association / dbpedia from the dropdown menu.
  4. The page should now change and there is now one graph selected. This graph consist out of 369.205.380 statements and is the full DBpedia dataset.
  5. To import this into your dataset you can click import 1 graphs. This will add the DBpedia graph into your dataset.
  6. You've now imported the DBpedia graph into your dataset. You can now use the browser and see more information about DBpedia resources.
  7. To remove the DBpedia graph from your dataset you can go the graphs page and remove the dataset by clicking on the X behind the https://triplydb.com/wikimedia/dbpedia/graphs/default graph. 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.

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 do to start a SPARQL service.

  1. Go to the Services page and you'll see a form to create a SPARQL service.
  2. To Create a SPARQL service you fill in a name for your service and select SPARQL from the three options.
  3. Press Create service to confirm your choices and a SPARQL service will be started.
  4. Wait until the status of the service changed to running.
  5. A new option called SPARQL will 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.

  1. Go to the Graphs page and click on import a new graph
  2. Click on Add data from an existing dataset
  3. Type in DBpedia and select DBpedia-association / dbpedia from the dropdown menu.
  4. The page should now change and there is now one graph selected. This graph consist out of 369.205.380 statements and is the full DBpedia dataset.
  5. To import this into your dataset you can click import 1 graphs. This will add the DBpedia graph into your dataset.
  6. You've now imported the DBpedia graph into your dataset. You can now use the browser and see more information about DBpedia resources.
  7. To remove the DBpedia graph from your dataset you can go the graphs page and remove the dataset by clicking on the X behind the https://triplydb.com/wikimedia/dbpedia/graphs/default graph. 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.

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 do to start a SPARQL service.

  1. Go to the Services page and you'll see a form to create a SPARQL service.
  2. To Create a SPARQL service you fill in a name for your service and select SPARQL from the three options.
  3. Press Create service to confirm your choices and a SPARQL service will be started.
  4. Wait until the status of the service changed to running.
  5. A new option called SPARQL will 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.

  1. Go to the Graphs page and click on import a new graph
  2. Click on Add data from an existing dataset
  3. Type in DBpedia and select DBpedia-association / dbpedia from the dropdown menu.
  4. The page should now change and there is now one graph selected. This graph consist out of 369.205.380 statements and is the full DBpedia dataset.
  5. To import this into your dataset you can click import 1 graphs. This will add the DBpedia graph into your dataset.
  6. You've now imported the DBpedia graph into your dataset. You can now use the browser and see more information about DBpedia resources.
  7. To remove the DBpedia graph from your dataset you can go the graphs page and remove the dataset by clicking on the X behind the https://triplydb.com/wikimedia/dbpedia/graphs/default graph. 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.

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 do to start a SPARQL service.

  1. Go to the Services page and you'll see a form to create a SPARQL service.
  2. To Create a SPARQL service you fill in a name for your service and select SPARQL from the three options.
  3. Press Create service to confirm your choices and a SPARQL service will be started.
  4. Wait until the status of the service changed to running.
  5. A new option called SPARQL will 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.

  1. Go to the Graphs page and click on import a new graph
  2. Click on Add data from an existing dataset
  3. Type in DBpedia and select DBpedia-association / dbpedia from the dropdown menu.
  4. The page should now change and there is now one graph selected. This graph consist out of 369.205.380 statements and is the full DBpedia dataset.
  5. To import this into your dataset you can click import 1 graphs. This will add the DBpedia graph into your dataset.
  6. You've now imported the DBpedia graph into your dataset. You can now use the browser and see more information about DBpedia resources.
  7. To remove the DBpedia graph from your dataset you can go the graphs page and remove the dataset by clicking on the X behind the https://triplydb.com/wikimedia/dbpedia/graphs/default graph. 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.

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 do to start a SPARQL service.

  1. Go to the Services page and you'll see a form to create a SPARQL service.
  2. To Create a SPARQL service you fill in a name for your service and select SPARQL from the three options.
  3. Press Create service to confirm your choices and a SPARQL service will be started.
  4. Wait until the status of the service changed to running.
  5. A new option called SPARQL will 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.

  1. Go to the Graphs page and click on import a new graph
  2. Click on Add data from an existing dataset
  3. Type in DBpedia and select DBpedia-association / dbpedia from the dropdown menu.
  4. The page should now change and there is now one graph selected. This graph consist out of 369.205.380 statements and is the full DBpedia dataset.
  5. To import this into your dataset you can click import 1 graphs. This will add the DBpedia graph into your dataset.
  6. You've now imported the DBpedia graph into your dataset. You can now use the browser and see more information about DBpedia resources.
  7. To remove the DBpedia graph from your dataset you can go the graphs page and remove the dataset by clicking on the X behind the https://triplydb.com/wikimedia/dbpedia/graphs/default graph. 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.

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 do to start a SPARQL service.

  1. Go to the Services page and you'll see a form to create a SPARQL service.
  2. To Create a SPARQL service you fill in a name for your service and select SPARQL from the three options.
  3. Press Create service to confirm your choices and a SPARQL service will be started.
  4. Wait until the status of the service changed to running.
  5. A new option called SPARQL will 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.

  1. Go to the Graphs page and click on import a new graph
  2. Click on Add data from an existing dataset
  3. Type in DBpedia and select DBpedia-association / dbpedia from the dropdown menu.
  4. The page should now change and there is now one graph selected. This graph consist out of 369.205.380 statements and is the full DBpedia dataset.
  5. To import this into your dataset you can click import 1 graphs. This will add the DBpedia graph into your dataset.
  6. You've now imported the DBpedia graph into your dataset. You can now use the browser and see more information about DBpedia resources.
  7. To remove the DBpedia graph from your dataset you can go the graphs page and remove the dataset by clicking on the X behind the https://triplydb.com/wikimedia/dbpedia/graphs/default graph. 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.

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 do to start a SPARQL service.

  1. Go to the Services page and you'll see a form to create a SPARQL service.
  2. To Create a SPARQL service you fill in a name for your service and select SPARQL from the three options.
  3. Press Create service to confirm your choices and a SPARQL service will be started.
  4. Wait until the status of the service changed to running.
  5. A new option called SPARQL will 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.

  1. Go to the Graphs page and click on import a new graph
  2. Click on Add data from an existing dataset
  3. Type in DBpedia and select DBpedia-association / dbpedia from the dropdown menu.
  4. The page should now change and there is now one graph selected. This graph consist out of 369.205.380 statements and is the full DBpedia dataset.
  5. To import this into your dataset you can click import 1 graphs. This will add the DBpedia graph into your dataset.
  6. You've now imported the DBpedia graph into your dataset. You can now use the browser and see more information about DBpedia resources.
  7. To remove the DBpedia graph from your dataset you can go the graphs page and remove the dataset by clicking on the X behind the https://triplydb.com/wikimedia/dbpedia/graphs/default graph. 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.

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 do to start a SPARQL service.

  1. Go to the Services page and you'll see a form to create a SPARQL service.
  2. To Create a SPARQL service you fill in a name for your service and select SPARQL from the three options.
  3. Press Create service to confirm your choices and a SPARQL service will be started.
  4. Wait until the status of the service changed to running.
  5. A new option called SPARQL will 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.

  1. Go to the Graphs page and click on import a new graph
  2. Click on Add data from an existing dataset
  3. Type in DBpedia and select DBpedia-association / dbpedia from the dropdown menu.
  4. The page should now change and there is now one graph selected. This graph consist out of 369.205.380 statements and is the full DBpedia dataset.
  5. To import this into your dataset you can click import 1 graphs. This will add the DBpedia graph into your dataset.
  6. You've now imported the DBpedia graph into your dataset. You can now use the browser and see more information about DBpedia resources.
  7. To remove the DBpedia graph from your dataset you can go the graphs page and remove the dataset by clicking on the X behind the https://triplydb.com/wikimedia/dbpedia/graphs/default graph. 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.

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 do to start a SPARQL service.

  1. Go to the Services page and you'll see a form to create a SPARQL service.
  2. To Create a SPARQL service you fill in a name for your service and select SPARQL from the three options.
  3. Press Create service to confirm your choices and a SPARQL service will be started.
  4. Wait until the status of the service changed to running.
  5. A new option called SPARQL will 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.

  1. Go to the Graphs page and click on import a new graph
  2. Click on Add data from an existing dataset
  3. Type in DBpedia and select DBpedia-association / dbpedia from the dropdown menu.
  4. The page should now change and there is now one graph selected. This graph consist out of 369.205.380 statements and is the full DBpedia dataset.
  5. To import this into your dataset you can click import 1 graphs. This will add the DBpedia graph into your dataset.
  6. You've now imported the DBpedia graph into your dataset. You can now use the browser and see more information about DBpedia resources.
  7. To remove the DBpedia graph from your dataset you can go the graphs page and remove the dataset by clicking on the X behind the https://triplydb.com/wikimedia/dbpedia/graphs/default graph. 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.

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 do to start a SPARQL service.

  1. Go to the Services page and you'll see a form to create a SPARQL service.
  2. To Create a SPARQL service you fill in a name for your service and select SPARQL from the three options.
  3. Press Create service to confirm your choices and a SPARQL service will be started.
  4. Wait until the status of the service changed to running.
  5. A new option called SPARQL will 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.

  1. Go to the Graphs page and click on import a new graph
  2. Click on Add data from an existing dataset
  3. Type in DBpedia and select DBpedia-association / dbpedia from the dropdown menu.
  4. The page should now change and there is now one graph selected. This graph consist out of 369.205.380 statements and is the full DBpedia dataset.
  5. To import this into your dataset you can click import 1 graphs. This will add the DBpedia graph into your dataset.
  6. You've now imported the DBpedia graph into your dataset. You can now use the browser and see more information about DBpedia resources.
  7. To remove the DBpedia graph from your dataset you can go the graphs page and remove the dataset by clicking on the X behind the https://triplydb.com/wikimedia/dbpedia/graphs/default graph. 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.

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 do to start a SPARQL service.

  1. Go to the Services page and you'll see a form to create a SPARQL service.
  2. To Create a SPARQL service you fill in a name for your service and select SPARQL from the three options.
  3. Press Create service to confirm your choices and a SPARQL service will be started.
  4. Wait until the status of the service changed to running.
  5. A new option called SPARQL will 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.

  1. Go to the Graphs page and click on import a new graph
  2. Click on Add data from an existing dataset
  3. Type in DBpedia and select DBpedia-association / dbpedia from the dropdown menu.
  4. The page should now change and there is now one graph selected. This graph consist out of 369.205.380 statements and is the full DBpedia dataset.
  5. To import this into your dataset you can click import 1 graphs. This will add the DBpedia graph into your dataset.
  6. You've now imported the DBpedia graph into your dataset. You can now use the browser and see more information about DBpedia resources.
  7. To remove the DBpedia graph from your dataset you can go the graphs page and remove the dataset by clicking on the X behind the https://triplydb.com/wikimedia/dbpedia/graphs/default graph. 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.

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 do to start a SPARQL service.

  1. Go to the Services page and you'll see a form to create a SPARQL service.
  2. To Create a SPARQL service you fill in a name for your service and select SPARQL from the three options.
  3. Press Create service to confirm your choices and a SPARQL service will be started.
  4. Wait until the status of the service changed to running.
  5. A new option called SPARQL will 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.

  1. Go to the Graphs page and click on import a new graph
  2. Click on Add data from an existing dataset
  3. Type in DBpedia and select DBpedia-association / dbpedia from the dropdown menu.
  4. The page should now change and there is now one graph selected. This graph consist out of 369.205.380 statements and is the full DBpedia dataset.
  5. To import this into your dataset you can click import 1 graphs. This will add the DBpedia graph into your dataset.
  6. You've now imported the DBpedia graph into your dataset. You can now use the browser and see more information about DBpedia resources.
  7. To remove the DBpedia graph from your dataset you can go the graphs page and remove the dataset by clicking on the X behind the https://triplydb.com/wikimedia/dbpedia/graphs/default graph. 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.

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 do to start a SPARQL service.

  1. Go to the Services page and you'll see a form to create a SPARQL service.
  2. To Create a SPARQL service you fill in a name for your service and select SPARQL from the three options.
  3. Press Create service to confirm your choices and a SPARQL service will be started.
  4. Wait until the status of the service changed to running.
  5. A new option called SPARQL will 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.

  1. Go to the Graphs page and click on import a new graph
  2. Click on Add data from an existing dataset
  3. Type in DBpedia and select DBpedia-association / dbpedia from the dropdown menu.
  4. The page should now change and there is now one graph selected. This graph consist out of 369.205.380 statements and is the full DBpedia dataset.
  5. To import this into your dataset you can click import 1 graphs. This will add the DBpedia graph into your dataset.
  6. You've now imported the DBpedia graph into your dataset. You can now use the browser and see more information about DBpedia resources.
  7. To remove the DBpedia graph from your dataset you can go the graphs page and remove the dataset by clicking on the X behind the https://triplydb.com/wikimedia/dbpedia/graphs/default graph. 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.

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 do to start a SPARQL service.

  1. Go to the Services page and you'll see a form to create a SPARQL service.
  2. To Create a SPARQL service you fill in a name for your service and select SPARQL from the three options.
  3. Press Create service to confirm your choices and a SPARQL service will be started.
  4. Wait until the status of the service changed to running.
  5. A new option called SPARQL will 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.

  1. Go to the Graphs page and click on import a new graph
  2. Click on Add data from an existing dataset
  3. Type in DBpedia and select DBpedia-association / dbpedia from the dropdown menu.
  4. The page should now change and there is now one graph selected. This graph consist out of 369.205.380 statements and is the full DBpedia dataset.
  5. To import this into your dataset you can click import 1 graphs. This will add the DBpedia graph into your dataset.
  6. You've now imported the DBpedia graph into your dataset. You can now use the browser and see more information about DBpedia resources.
  7. To remove the DBpedia graph from your dataset you can go the graphs page and remove the dataset by clicking on the X behind the https://triplydb.com/wikimedia/dbpedia/graphs/default graph. 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.

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 do to start a SPARQL service.

  1. Go to the Services page and you'll see a form to create a SPARQL service.
  2. To Create a SPARQL service you fill in a name for your service and select SPARQL from the three options.
  3. Press Create service to confirm your choices and a SPARQL service will be started.
  4. Wait until the status of the service changed to running.
  5. A new option called SPARQL will 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.

  1. Go to the Graphs page and click on import a new graph
  2. Click on Add data from an existing dataset
  3. Type in DBpedia and select DBpedia-association / dbpedia from the dropdown menu.
  4. The page should now change and there is now one graph selected. This graph consist out of 369.205.380 statements and is the full DBpedia dataset.
  5. To import this into your dataset you can click import 1 graphs. This will add the DBpedia graph into your dataset.
  6. You've now imported the DBpedia graph into your dataset. You can now use the browser and see more information about DBpedia resources.
  7. To remove the DBpedia graph from your dataset you can go the graphs page and remove the dataset by clicking on the X behind the https://triplydb.com/wikimedia/dbpedia/graphs/default graph. 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.

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 do to start a SPARQL service.

  1. Go to the Services page and you'll see a form to create a SPARQL service.
  2. To Create a SPARQL service you fill in a name for your service and select SPARQL from the three options.
  3. Press Create service to confirm your choices and a SPARQL service will be started.
  4. Wait until the status of the service changed to running.
  5. A new option called SPARQL will 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.

  1. Go to the Graphs page and click on import a new graph
  2. Click on Add data from an existing dataset
  3. Type in DBpedia and select DBpedia-association / dbpedia from the dropdown menu.
  4. The page should now change and there is now one graph selected. This graph consist out of 369.205.380 statements and is the full DBpedia dataset.
  5. To import this into your dataset you can click import 1 graphs. This will add the DBpedia graph into your dataset.
  6. You've now imported the DBpedia graph into your dataset. You can now use the browser and see more information about DBpedia resources.
  7. To remove the DBpedia graph from your dataset you can go the graphs page and remove the dataset by clicking on the X behind the https://triplydb.com/wikimedia/dbpedia/graphs/default graph. 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.

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 do to start a SPARQL service.

  1. Go to the Services page and you'll see a form to create a SPARQL service.
  2. To Create a SPARQL service you fill in a name for your service and select SPARQL from the three options.
  3. Press Create service to confirm your choices and a SPARQL service will be started.
  4. Wait until the status of the service changed to running.
  5. A new option called SPARQL will 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.

  1. Go to the Graphs page and click on import a new graph
  2. Click on Add data from an existing dataset
  3. Type in DBpedia and select DBpedia-association / dbpedia from the dropdown menu.
  4. The page should now change and there is now one graph selected. This graph consist out of 369.205.380 statements and is the full DBpedia dataset.
  5. To import this into your dataset you can click import 1 graphs. This will add the DBpedia graph into your dataset.
  6. You've now imported the DBpedia graph into your dataset. You can now use the browser and see more information about DBpedia resources.
  7. To remove the DBpedia graph from your dataset you can go the graphs page and remove the dataset by clicking on the X behind the https://triplydb.com/wikimedia/dbpedia/graphs/default graph. 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.

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 do to start a SPARQL service.

  1. Go to the Services page and you'll see a form to create a SPARQL service.
  2. To Create a SPARQL service you fill in a name for your service and select SPARQL from the three options.
  3. Press Create service to confirm your choices and a SPARQL service will be started.
  4. Wait until the status of the service changed to running.
  5. A new option called SPARQL will 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.

  1. Go to the Graphs page and click on import a new graph
  2. Click on Add data from an existing dataset
  3. Type in DBpedia and select DBpedia-association / dbpedia from the dropdown menu.
  4. The page should now change and there is now one graph selected. This graph consist out of 369.205.380 statements and is the full DBpedia dataset.
  5. To import this into your dataset you can click import 1 graphs. This will add the DBpedia graph into your dataset.
  6. You've now imported the DBpedia graph into your dataset. You can now use the browser and see more information about DBpedia resources.
  7. To remove the DBpedia graph from your dataset you can go the graphs page and remove the dataset by clicking on the X behind the https://triplydb.com/wikimedia/dbpedia/graphs/default graph. 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.