The DBpedia + BBC Combo Linked Dataset is a preconfigured Virtuoso Cluster (4 Virtuoso Cluster Nodes, each comprised of one Virtuoso Instance; initial deployment is to a single Cluster Host, but license may be converted for physically distributed deployment), available via the Amazon EC2 Cloud, preloaded with the following datasets:


The BBC has been publishing Linked Data from its Web Data Space for a number of years. In line with best practices for injecting Linked Data into the World Wide Web (Web), the BBC datasets are interlinked with other datasets such as DBpedia and MusicBrainz.

Typical follow-your-nose exploration using a Web Browser (or even via sophisticated SPARQL query crawls) isn't always practical once you get past the initial euphoria that comes from comprehending the Linked Data concept. As your queries get more complex, the overhead of remote sub-queries increases its impact, until query results take so long to return that you simply give up.

Thus, maximizing the effects of the BBC's efforts requires Linked Data that shares locality in a Web-accessible Data Space — i.e., where all Linked Data sets have been loaded into the same data store or warehouse. This holds true even when leveraging SPARQL-FED style virtualization — there's always a need to localize data as part of any marginally-decent locality-aware cost-optimization algorithm.

This DBpedia + BBC dataset, exposed via a preloaded and preconfigured Virtuoso Cluster, delivers a practical point of presence on the Web for immediate and cost-effective exploitation of Linked Data at the individual and/or service specific levels.


To work through this guide, you'll need to start with 90 GB of free disk space. (Only 41 GB will be consumed after you delete the installer archives, but starting with 90+ GB ensures enough work space for the installation.)

Install Virtuoso

  1. Download Virtuoso installer archive(s). You must deploy the Personal or Enterprise Edition; the Open Source Edition does not support Shared-Nothing Cluster Deployment.

  2. Obtain a Virtuoso Cluster license.

  3. Install Virtuoso.

  4. Set key environment variables and start the OpenLink License Manager, using command (this may vary depending on your shell and install directory):

    . /opt/virtuoso/virtuoso-enterprise.sh
  5. Optional: To keep the default single-server configuration file and demo database intact, set the VIRTUOSO_HOME environment variable to a different directory, e.g.,

    export VIRTUOSO_HOME=/opt/virtuoso/cluster-home/

    Note: You will have to adjust this setting every time you shift between this cluster setup and your single-server setup. Either may be made your environment's default through the virtuoso-enterprise.sh and related scripts.

  6. Set up your cluster by running the mkcluster.sh script. Note that initial deployment of the DBpedia + BBC Combo requires a 4 node cluster, which is the default for this script.

  7. Start the Virtuoso Cluster with this command:

  8. Stop the Virtuoso Cluster with this command:


Using the DBpedia + BBC Combo dataset

  1. Navigate to your installation directory.

  2. Download the combo dataset installer script — bbc-dbpedia-install.sh.

  3. For best results, set the downloaded script to fully executable using this command:

    chmod 755 bbc-dbpedia-install.sh
  4. Shut down any Virtuoso instances that may be currently running.

  5. Optional: As above, if you have decided to keep the default single-server configuration file and demo database intact, set the VIRTUOSO_HOME environment variable appropriately, e.g.,

    export VIRTUOSO_HOME=/opt/virtuoso/cluster-home/
  6. Run the combo dataset installer script with this command:

    sh bbc-dbpedia-install.sh

Verify installation

The combo dataset typically deploys to EC2 virtual machines in under 90 minutes; your time will vary depending on your network connection speed, machine speed, and other variables.

Once the script completes, perform the following steps:

  1. Verify that the Virtuoso Conductor (HTTP-based Admin UI) is in place via:

  2. Verify that the Virtuoso SPARQL endpoint is in place via:

  3. Verify that the Precision Search & Find UI is in place via:

  4. Verify that the Virtuoso hosted PivotViewer is in place via: