What?
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:
Why?
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.
How?
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
-
Download Virtuoso installer archive(s). You
must deploy the Personal or Enterprise Edition; the Open Source
Edition does not support Shared-Nothing Cluster Deployment.
-
Obtain a Virtuoso Cluster license.
-
Install Virtuoso.
-
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
-
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.
-
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.
-
Start the Virtuoso Cluster with this command:
virtuoso-start.sh
-
Stop the Virtuoso Cluster with this command:
virtuoso-stop.sh
Using the DBpedia + BBC Combo dataset
-
Navigate to your installation directory.
-
Download the combo dataset installer script — bbc-dbpedia-install.sh
.
-
For best results, set the downloaded script to fully executable
using this command:
chmod 755
bbc-dbpedia-install.sh
-
Shut down any Virtuoso instances that may be currently
running.
-
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/
-
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:
-
Verify that the Virtuoso Conductor (HTTP-based Admin UI) is in
place via:
http://localhost:[port]/conductor
-
Verify that the Virtuoso SPARQL endpoint is in place via:
http://localhost:[port]/sparql
-
Verify that the Precision Search & Find UI is in place
via:
http://localhost:[port]/fct
-
Verify that the Virtuoso hosted PivotViewer is in place via:
http://localhost:[port]/PivotViewer
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