OpenLink Community Blog

What is SPARQL?

A declarative query language from the W3C for querying structured propositional data (in the form of 3-tuple [triples] or 4-tuple [quads] records) stored in a deductive database (colloquially referred to as triple or quad stores in Semantic Web and Linked Data parlance).

SPARQL is inherently platform independent. Like SQL, the query language and the backend database engine are distinct. Database clients capture SPARQL queries which are then passed on to compliant backend databases.

Why is it important?

Like SQL for relational databases, it provides a powerful mechanism for accessing and joining data across one or more data partitions (named graphs identified by IRIs). The aforementioned capability also enables the construction of sophisticated Views, Reports (HTML or those produced in native form by desktop productivity tools), and data streams for other services.

Unlike SQL, SPARQL includes result serialization formats and an HTTP based wire protocol. Thus, the ubiquity and sophistication of HTTP is integral to SPARQL i.e., client side applications (user agents) only need to be able to perform an HTTP GET against a URL en route to exploiting the power of SPARQL.

How do I use it, generally?

1. Locate a SPARQL endpoint (DBpedia, LOD Cloud Cache, Data.Gov, URIBurner, others), or;
2. Install a SPARQL compliant database server (quad or triple store) on your desktop, workgroup server, data center, or cloud (e.g., Amazon EC2 AMI)
3. Start the database server
4. Execute SPARQL Queries via the SPARQL endpoint.

How do I use SPARQL with Virtuoso?

What follows is a very simple guide for using SPARQL against your own instance of Virtuoso:

1. Software Download and Installation
2. Data Loading from Data Sources exposed at Network Addresses (e.g. HTTP URLs) using very simple methods
3. Actual SPARQL query execution via SPARQL endpoint.

Installation Steps

1. Download Virtuoso Open Source or Virtuoso Commercial Editions
2. Run installer (if using Commercial edition of Windows Open Source Edition, otherwise follow build guide)
3. Follow post-installation guide and verify installation by typing in the command: virtuoso -? (if this fails check you've followed installation and setup steps, then verify environment variables have been set)
4. Start the Virtuoso server using the command: virtuoso-start.sh
5. Verify you have a connection to the Virtuoso Server via the command: isql localhost (assuming you're using default DB settings) or the command: isql localhost:1112 (assuming demo database) or goto your browser and type in: http://<virtuoso-server-host-name>:[port]/conductor (e.g. http://localhost:8889/conductor for default DB or http://localhost:8890/conductor if using Demo DB)
6. Go to SPARQL endpoint which is typically -- http://<virtuoso-server-host-name>:[port]/sparql
7. Run a quick sample query (since the database always has system data in place): select distinct * where {?s ?p ?o} limit 50 .

Troubleshooting

1. Ensure environment settings are set and functional -- if using Mac OS X or Windows, so you don't have to worry about this, just start and stop your Virtuoso server using native OS services applets
2. If using the Open Source Edition, follow the getting started guide -- it covers PATH and startup directory location re. starting and stopping Virtuoso servers.
3. Sponging (HTTP GETs against external Data Sources) within SPARQL queries is disabled by default. You can enable this feature by assigning "SPARQL_SPONGE" privileges to user "SPARQL". Note, more sophisticated security exists via WebID based ACLs.

Data Loading Steps

1. Identify an RDF based structured data source of interest -- a file that contains 3-tuple / triples available at an address on a public or private HTTP based network
2. Determine the Address (URL) of the RDF data source
3. Go to your Virtuoso SPARQL endpoint and type in the following SPARQL query: DEFINE GET:SOFT "replace" SELECT DISTINCT * FROM <RDFDataSourceURL> WHERE {?s ?p ?o}
4. All the triples in the RDF resource (data source accessed via URL) will be loaded into the Virtuoso Quad Store (using RDF Data Source URL as the internal quad store Named Graph IRI) as part of the SPARQL query processing pipeline.

Note: the data source URL doesn't even have to be RDF based -- which is where the Virtuoso Sponger Middleware comes into play (download and install the VAD installer package first) since it delivers the following features to Virtuoso's SPARQL engine:

1. Transformation of data from non RDF data sources (file content, hypermedia resources, web services output etc..) into RDF based 3-tuples (triples)
2. Cache Invalidation Scheme Construction -- thus, subsequent queries (without the define get:soft "replace" pragma will not be required bar when you forcefully want to override cache).
3. If you have very large data sources like DBpedia etc. from CKAN, simply use our bulk loader .

SPARQL Endpoint Discovery

Public SPARQL endpoints are emerging at an ever increasing rate. Thus, we've setup up a DNS lookup service that provides access to a large number of SPARQL endpoints. Of course, this doesn't cover all existing endpoints, so if our endpoint is missing please ping me.

Here are a collection of commands for using DNS-SD to discover SPARQL endpoints:

1. dns-sd -B _sparql._tcp sparql.openlinksw.com -- browse for services instances
2. dns-sd -Z _sparql._tcp sparql.openlinksw.com -- output results in Zone File format

Related

1. Using HTTP from Ruby -- you can just make SPARQL Protocol URLs re. SPARQL
2. Using SPARQL Endpoints via Ruby -- Ruby example using DBpedia endpoint
3. Interactive SPARQL Query By Example (QBE) tool -- provides a graphical user interface (as is common in SQL realm re. query building against RDBMS engines) that works with any SPARQL endpoint
4. Other methods of loading RDF data into Virtuoso
5. Virtuoso Sponger -- architecture and how it turns a wide variety of non RDF data sources into SPARQL accessible data
6. Using OpenLink Data Explorer (ODE) to populate Virtuoso -- locate a resource of interest; click on a bookmarklet or use context menus (if using ODE extensions for Firefox, Safari, or Chrome); and you'll have SPARQL accessible data automatically inserted into your Virtuoso instance.
7. W3C's SPARQLing Data Access Ingenuity -- an older generic SPARQL introduction post
8. Collection of SPARQL Query Examples -- GoodRelations (Product Offers), FOAF (Profiles), SIOC (Data Spaces -- Blogs, Wikis, Bookmarks, Feed Collections, Photo Galleries, Briefcase/DropBox, AddressBook, Calendars, Discussion Forums)
9. Collection of Live SPARQL Queries against LOD Cloud Cache -- simple and advanced queries.

What is SPARQL?

A declarative query language from the W3C for querying structured propositional data (in the form of 3-tuple [triples] or 4-tuple [quads] records) stored in a deductive database (colloquially referred to as triple or quad stores in Semantic Web and Linked Data parlance).

SPARQL is inherently platform independent. Like SQL, the query language and the backend database engine are distinct. Database clients capture SPARQL queries which are then passed on to compliant backend databases.

Why is it important?

Like SQL for relational databases, it provides a powerful mechanism for accessing and joining data across one or more data partitions (named graphs identified by IRIs). The aforementioned capability also enables the construction of sophisticated Views, Reports (HTML or those produced in native form by desktop productivity tools), and data streams for other services.

Unlike SQL, SPARQL includes result serialization formats and an HTTP based wire protocol. Thus, the ubiquity and sophistication of HTTP is integral to SPARQL i.e., client side applications (user agents) only need to be able to perform an HTTP GET against a URL en route to exploiting the power of SPARQL.

How do I use it, generally?

1. Locate a SPARQL endpoint (DBpedia, LOD Cloud Cache, Data.Gov, URIBurner, others), or;
2. Install a SPARQL compliant database server (quad or triple store) on your desktop, workgroup server, data center, or cloud (e.g., Amazon EC2 AMI)
3. Start the database server
4. Execute SPARQL Queries via the SPARQL endpoint.

How do I use SPARQL with Virtuoso?

What follows is a very simple guide for using SPARQL against your own instance of Virtuoso:

1. Software Download and Installation
2. Data Loading from Data Sources exposed at Network Addresses (e.g. HTTP URLs) using very simple methods
3. Actual SPARQL query execution via SPARQL endpoint.

Installation Steps

1. Download Virtuoso Open Source or Virtuoso Commercial Editions
2. Run installer (if using Commercial edition of Windows Open Source Edition, otherwise follow build guide)
3. Follow post-installation guide and verify installation by typing in the command: virtuoso -? (if this fails check you've followed installation and setup steps, then verify environment variables have been set)
4. Start the Virtuoso server using the command: virtuoso-start.sh
5. Verify you have a connection to the Virtuoso Server via the command: isql localhost (assuming you're using default DB settings) or the command: isql localhost:1112 (assuming demo database) or goto your browser and type in: http://<virtuoso-server-host-name>:[port]/conductor (e.g. http://localhost:8889/conductor for default DB or http://localhost:8890/conductor if using Demo DB)
6. Go to SPARQL endpoint which is typically -- http://<virtuoso-server-host-name>:[port]/sparql
7. Run a quick sample query (since the database always has system data in place): select distinct * where {?s ?p ?o} limit 50 .

Troubleshooting

1. Ensure environment settings are set and functional -- if using Mac OS X or Windows, so you don't have to worry about this, just start and stop your Virtuoso server using native OS services applets
2. If using the Open Source Edition, follow the getting started guide -- it covers PATH and startup directory location re. starting and stopping Virtuoso servers.
3. Sponging (HTTP GETs against external Data Sources) within SPARQL queries is disabled by default. You can enable this feature by assigning "SPARQL_SPONGE" privileges to user "SPARQL". Note, more sophisticated security exists via WebID based ACLs.

Data Loading Steps

1. Identify an RDF based structured data source of interest -- a file that contains 3-tuple / triples available at an address on a public or private HTTP based network
2. Determine the Address (URL) of the RDF data source
3. Go to your Virtuoso SPARQL endpoint and type in the following SPARQL query: DEFINE GET:SOFT "replace" SELECT DISTINCT * FROM <RDFDataSourceURL> WHERE {?s ?p ?o}
4. All the triples in the RDF resource (data source accessed via URL) will be loaded into the Virtuoso Quad Store (using RDF Data Source URL as the internal quad store Named Graph IRI) as part of the SPARQL query processing pipeline.

Note: the data source URL doesn't even have to be RDF based -- which is where the Virtuoso Sponger Middleware comes into play (download and install the VAD installer package first) since it delivers the following features to Virtuoso's SPARQL engine:

1. Transformation of data from non RDF data sources (file content, hypermedia resources, web services output etc..) into RDF based 3-tuples (triples)
2. Cache Invalidation Scheme Construction -- thus, subsequent queries (without the define get:soft "replace" pragma will not be required bar when you forcefully want to override cache).
3. If you have very large data sources like DBpedia etc. from CKAN, simply use our bulk loader .

SPARQL Endpoint Discovery

Public SPARQL endpoints are emerging at an ever increasing rate. Thus, we've setup up a DNS lookup service that provides access to a large number of SPARQL endpoints. Of course, this doesn't cover all existing endpoints, so if our endpoint is missing please ping me.

Here are a collection of commands for using DNS-SD to discover SPARQL endpoints:

1. dns-sd -B _sparql._tcp sparql.openlinksw.com -- browse for services instances
2. dns-sd -Z _sparql._tcp sparql.openlinksw.com -- output results in Zone File format

Related

1. Using HTTP from Ruby -- you can just make SPARQL Protocol URLs re. SPARQL
2. Using SPARQL Endpoints via Ruby -- Ruby example using DBpedia endpoint
3. Interactive SPARQL Query By Example (QBE) tool -- provides a graphical user interface (as is common in SQL realm re. query building against RDBMS engines) that works with any SPARQL endpoint
4. Other methods of loading RDF data into Virtuoso
5. Virtuoso Sponger -- architecture and how it turns a wide variety of non RDF data sources into SPARQL accessible data
6. Using OpenLink Data Explorer (ODE) to populate Virtuoso -- locate a resource of interest; click on a bookmarklet or use context menus (if using ODE extensions for Firefox, Safari, or Chrome); and you'll have SPARQL accessible data automatically inserted into your Virtuoso instance.
7. W3C's SPARQLing Data Access Ingenuity -- an older generic SPARQL introduction post
8. Collection of SPARQL Query Examples -- GoodRelations (Product Offers), FOAF (Profiles), SIOC (Data Spaces -- Blogs, Wikis, Bookmarks, Feed Collections, Photo Galleries, Briefcase/DropBox, AddressBook, Calendars, Discussion Forums)
9. Collection of Live SPARQL Queries against LOD Cloud Cache -- simple and advanced queries.

What is SPARQL?

A declarative query language from the W3C for querying structured propositional data (in the form of 3-tuple [triples] or 4-tuple [quads] records) stored in a deductive database (colloquially referred to as triple or quad stores in Semantic Web and Linked Data parlance).

SPARQL is inherently platform independent. Like SQL, the query language and the backend database engine are distinct. Database clients capture SPARQL queries which are then passed on to compliant backend databases.

Why is it important?

Like SQL for relational databases, it provides a powerful mechanism for accessing and joining data across one or more data partitions (named graphs identified by IRIs). The aforementioned capability also enables the construction of sophisticated Views, Reports (HTML or those produced in native form by desktop productivity tools), and data streams for other services.

Unlike SQL, SPARQL includes result serialization formats and an HTTP based wire protocol. Thus, the ubiquity and sophistication of HTTP is integral to SPARQL i.e., client side applications (user agents) only need to be able to perform an HTTP GET against a URL en route to exploiting the power of SPARQL.

How do I use it, generally?

1. Locate a SPARQL endpoint (DBpedia, LOD Cloud Cache, Data.Gov, URIBurner, others), or;
2. Install a SPARQL compliant database server (quad or triple store) on your desktop, workgroup server, data center, or cloud (e.g., Amazon EC2 AMI)
3. Start the database server
4. Execute SPARQL Queries via the SPARQL endpoint.

How do I use SPARQL with Virtuoso?

What follows is a very simple guide for using SPARQL against your own instance of Virtuoso:

1. Software Download and Installation
2. Data Loading from Data Sources exposed at Network Addresses (e.g. HTTP URLs) using very simple methods
3. Actual SPARQL query execution via SPARQL endpoint.

Installation Steps

1. Download Virtuoso Open Source or Virtuoso Commercial Editions
2. Run installer (if using Commercial edition of Windows Open Source Edition, otherwise follow build guide)
3. Follow post-installation guide and verify installation by typing in the command: virtuoso -? (if this fails check you've followed installation and setup steps, then verify environment variables have been set)
4. Start the Virtuoso server using the command: virtuoso-start.sh
5. Verify you have a connection to the Virtuoso Server via the command: isql localhost (assuming you're using default DB settings) or the command: isql localhost:1112 (assuming demo database) or goto your browser and type in: http://<virtuoso-server-host-name>:[port]/conductor (e.g. http://localhost:8889/conductor for default DB or http://localhost:8890/conductor if using Demo DB)
6. Go to SPARQL endpoint which is typically -- http://<virtuoso-server-host-name>:[port]/sparql
7. Run a quick sample query (since the database always has system data in place): select distinct * where {?s ?p ?o} limit 50 .

Troubleshooting

1. Ensure environment settings are set and functional -- if using Mac OS X or Windows, so you don't have to worry about this, just start and stop your Virtuoso server using native OS services applets
2. If using the Open Source Edition, follow the getting started guide -- it covers PATH and startup directory location re. starting and stopping Virtuoso servers.
3. Sponging (HTTP GETs against external Data Sources) within SPARQL queries is disabled by default. You can enable this feature by assigning "SPARQL_SPONGE" privileges to user "SPARQL". Note, more sophisticated security exists via WebID based ACLs.

Data Loading Steps

1. Identify an RDF based structured data source of interest -- a file that contains 3-tuple / triples available at an address on a public or private HTTP based network
2. Determine the Address (URL) of the RDF data source
3. Go to your Virtuoso SPARQL endpoint and type in the following SPARQL query: DEFINE GET:SOFT "replace" SELECT DISTINCT * FROM <RDFDataSourceURL> WHERE {?s ?p ?o}
4. All the triples in the RDF resource (data source accessed via URL) will be loaded into the Virtuoso Quad Store (using RDF Data Source URL as the internal quad store Named Graph IRI) as part of the SPARQL query processing pipeline.

Note: the data source URL doesn't even have to be RDF based -- which is where the Virtuoso Sponger Middleware comes into play (download and install the VAD installer package first) since it delivers the following features to Virtuoso's SPARQL engine:

1. Transformation of data from non RDF data sources (file content, hypermedia resources, web services output etc..) into RDF based 3-tuples (triples)
2. Cache Invalidation Scheme Construction -- thus, subsequent queries (without the define get:soft "replace" pragma will not be required bar when you forcefully want to override cache).
3. If you have very large data sources like DBpedia etc. from CKAN, simply use our bulk loader .

SPARQL Endpoint Discovery

Public SPARQL endpoints are emerging at an ever increasing rate. Thus, we've setup up a DNS lookup service that provides access to a large number of SPARQL endpoints. Of course, this doesn't cover all existing endpoints, so if our endpoint is missing please ping me.

Here are a collection of commands for using DNS-SD to discover SPARQL endpoints:

1. dns-sd -B _sparql._tcp sparql.openlinksw.com -- browse for services instances
2. dns-sd -Z _sparql._tcp sparql.openlinksw.com -- output results in Zone File format

Related

1. Using HTTP from Ruby -- you can just make SPARQL Protocol URLs re. SPARQL
2. Using SPARQL Endpoints via Ruby -- Ruby example using DBpedia endpoint
3. Interactive SPARQL Query By Example (QBE) tool -- provides a graphical user interface (as is common in SQL realm re. query building against RDBMS engines) that works with any SPARQL endpoint
4. Other methods of loading RDF data into Virtuoso
5. Virtuoso Sponger -- architecture and how it turns a wide variety of non RDF data sources into SPARQL accessible data
6. Using OpenLink Data Explorer (ODE) to populate Virtuoso -- locate a resource of interest; click on a bookmarklet or use context menus (if using ODE extensions for Firefox, Safari, or Chrome); and you'll have SPARQL accessible data automatically inserted into your Virtuoso instance.
7. W3C's SPARQLing Data Access Ingenuity -- an older generic SPARQL introduction post
8. Collection of SPARQL Query Examples -- GoodRelations (Product Offers), FOAF (Profiles), SIOC (Data Spaces -- Blogs, Wikis, Bookmarks, Feed Collections, Photo Galleries, Briefcase/DropBox, AddressBook, Calendars, Discussion Forums)
9. Collection of Live SPARQL Queries against LOD Cloud Cache -- simple and advanced queries.

Motivation for this post arose from a series of Twitter exchanges between Tony Hirst and I, in relation to his blog post titled: So What Is It About Linked Data that Makes it Linked Data™ ?

At the end of the marathon session, it was clear to me that a blog post was required for future reference, at the very least :-)

What is Linked Data?

"Data Access by Reference" mechanism for Data Objects (or Entities) on HTTP networks. It enables you to Identify a Data Object and Access its structured Data Representation via a single Generic HTTP scheme based Identifier (HTTP URI). Data Object representation formats may vary; but in all cases, they are hypermedia oriented, fully structured, and negotiable within the context of a client-server message exchange.

Why is it Important?

Information makes the world tick!

Information doesn't exist without data to contextualize.

Information is inaccessible without a projection (presentation) medium.

All information (without exception, when produced by humans) is subjective. Thus, to truly maximize the innate heterogeneity of collective human intelligence, loose coupling of our information and associated data sources is imperative.

How is Linked Data Delivered?

Linked Data is exposed to HTTP networks (e.g. World Wide Web) via hypermedia resources bearing structured representations of data object descriptions. Remember, you have a single Identifier abstraction (generic HTTP URI) that embodies: Data Object Name and Data Representation Location (aka URL).

How are Linked Data Object Representations Structured?

A structured representation of data exists when an Entity (Datum), its Attributes, and its Attribute Values are clearly discernible. In the case of a Linked Data Object, structured descriptions take the form of a hypermedia based Entity-Attribute-Value (EAV) graph pictorial -- where each Entity, its Attributes, and its Attribute Values (optionally) are identified using Generic HTTP URIs.

Examples of structured data representation formats (content types) associated with Linked Data Objects include:

• text/html
• text/turtle
• text/n3
• application/json
• application/rdf+xml
• Others

How Do I Create Linked Data oriented Hypermedia Resources?

You markup resources by expressing distinct entity-attribute-value statements (basically these a 3-tuple records) using a variety of notations:

• (X)HTML+RDFa,
• JSON,
• Turtle,
• N3,
• TriX,
• TriG,
• RDF/XML, and
• Others (for instance you can use Atom data format extensions to model EAV graph as per OData initiative from Microsoft).

You can achieve this task using any of the following approaches:

• Notepad
• WYSIWYG Editor
• Transformation of Database Records via Middleware
• Transformation of XML based Web Services output via Middleware
• Transformation of other Hypermedia Resources via Middleware
• Transformation of non Hypermedia Resources via Middleware
• Use a platform that delivers all of the above.

Practical Examples of Linked Data Objects Enable

• Describe Who You Are, What You Offer, and What You Need via your structured profile, then leave your HTTP network to perform the REST (serendipitous discovery of relevant things)
• Identify (via map overlay) all items of interest based on a 2km+ radious of my current location (this could include vendor offerings or services sought by existing or future customers)
• Share the latest and greatest family photos with family members *only* without forcing them to signup for Yet Another Web 2.0 service or Social Network
• No repetitive signup and username and password based login sequences per Web 2.0 or Mobile Application combo
• Going beyond imprecise Keyword Search to the new frontier of Precision Find - Example, Find Data Objects associated with the keywords: Tiger, while enabling the seeker disambiguate across the "Who", "What", "Where", "When" dimensions (with negation capability)
• Determine how two Data Objects are Connected - person to person, person to subject matter etc. (LinkedIn outside the walled garden)
• Use any resource address (e.g blog or bookmark URL) as the conduit into a Data Object mesh that exposes all associated Entities and their social network relationships
• Apply patterns (social dimensions) above to traditional enterprise data sources in combination (optionally) with external data without compromising security etc.

How Do OpenLink Software Products Enable Linked Data Exploitation?

Our data access middleware heritage (which spans 16+ years) has enabled us to assemble a rich portfolio of coherently integrated products that enable cost-effective evaluation and utilization of Linked Data, without writing a single line of code, or exposing you to the hidden, but extensive admin and configuration costs. Post installation, the benefits of Linked Data simply materialize (along the lines described above).

Our main Linked Data oriented products include:

• OpenLink Data Explorer -- visualizes Linked Data or Linked Data transformed "on the fly" from hypermedia and non hypermedia data sources
• URIBurner -- a "deceptively simple" solution that enables the generation of Linked Data "on the fly" from a broad collection of data sources and resource types
• OpenLink Data Spaces -- a platform for enterprises and individuals that enhances distributed collaboration via Linked Data driven virtualization of data across its native and/or 3rd party content manager for: Blogs, Wikis, Shared Bookmarks, Discussion Forums, Social Networks etc
• OpenLink Virtuoso -- a secure and high-performance native hybrid data server (Relational, RDF-Graph, Document models) that includes in-built Linked Data transformation middleware (aka. Sponger).

Related

• Hypertext Transfer Protocol 1.1 RFC
• Open Data Protocol Glossary
• Simple Explanation of RDF and Linked Data Dynamics
• Collection of post from the past about Linked Data
• Are We There Yet Re. Web++? -- includes link to podcast conversation with Jon Udell
• Web of Linked Data Pivoting Demo from TED -- by Microsoft's Gary Flake
• Microsoft Pivot atop Virtuoso Quad Store's Faceted Browser Engine-- My Demonstration of EAV model transcending data representation variations (i.e., RDF's EAV data model data served up in Microsoft CXML data representation format).

Motivation for this post arose from a series of Twitter exchanges between Tony Hirst and I, in relation to his blog post titled: So What Is It About Linked Data that Makes it Linked Data™ ?

At the end of the marathon session, it was clear to me that a blog post was required for future reference, at the very least :-)

What is Linked Data?

"Data Access by Reference" mechanism for Data Objects (or Entities) on HTTP networks. It enables you to Identify a Data Object and Access its structured Data Representation via a single Generic HTTP scheme based Identifier (HTTP URI). Data Object representation formats may vary; but in all cases, they are hypermedia oriented, fully structured, and negotiable within the context of a client-server message exchange.

Why is it Important?

Information makes the world tick!

Information doesn't exist without data to contextualize.

Information is inaccessible without a projection (presentation) medium.

All information (without exception, when produced by humans) is subjective. Thus, to truly maximize the innate heterogeneity of collective human intelligence, loose coupling of our information and associated data sources is imperative.

How is Linked Data Delivered?

Linked Data is exposed to HTTP networks (e.g. World Wide Web) via hypermedia resources bearing structured representations of data object descriptions. Remember, you have a single Identifier abstraction (generic HTTP URI) that embodies: Data Object Name and Data Representation Location (aka URL).

How are Linked Data Object Representations Structured?

A structured representation of data exists when an Entity (Datum), its Attributes, and its Attribute Values are clearly discernible. In the case of a Linked Data Object, structured descriptions take the form of a hypermedia based Entity-Attribute-Value (EAV) graph pictorial -- where each Entity, its Attributes, and its Attribute Values (optionally) are identified using Generic HTTP URIs.

Examples of structured data representation formats (content types) associated with Linked Data Objects include:

• text/html
• text/turtle
• text/n3
• application/json
• application/rdf+xml
• Others

How Do I Create Linked Data oriented Hypermedia Resources?

You markup resources by expressing distinct entity-attribute-value statements (basically these a 3-tuple records) using a variety of notations:

• (X)HTML+RDFa,
• JSON,
• Turtle,
• N3,
• TriX,
• TriG,
• RDF/XML, and
• Others (for instance you can use Atom data format extensions to model EAV graph as per OData initiative from Microsoft).

You can achieve this task using any of the following approaches:

• Notepad
• WYSIWYG Editor
• Transformation of Database Records via Middleware
• Transformation of XML based Web Services output via Middleware
• Transformation of other Hypermedia Resources via Middleware
• Transformation of non Hypermedia Resources via Middleware
• Use a platform that delivers all of the above.

Practical Examples of Linked Data Objects Enable

• Describe Who You Are, What You Offer, and What You Need via your structured profile, then leave your HTTP network to perform the REST (serendipitous discovery of relevant things)
• Identify (via map overlay) all items of interest based on a 2km+ radious of my current location (this could include vendor offerings or services sought by existing or future customers)
• Share the latest and greatest family photos with family members *only* without forcing them to signup for Yet Another Web 2.0 service or Social Network
• No repetitive signup and username and password based login sequences per Web 2.0 or Mobile Application combo
• Going beyond imprecise Keyword Search to the new frontier of Precision Find - Example, Find Data Objects associated with the keywords: Tiger, while enabling the seeker disambiguate across the "Who", "What", "Where", "When" dimensions (with negation capability)
• Determine how two Data Objects are Connected - person to person, person to subject matter etc. (LinkedIn outside the walled garden)
• Use any resource address (e.g blog or bookmark URL) as the conduit into a Data Object mesh that exposes all associated Entities and their social network relationships
• Apply patterns (social dimensions) above to traditional enterprise data sources in combination (optionally) with external data without compromising security etc.

How Do OpenLink Software Products Enable Linked Data Exploitation?

Our data access middleware heritage (which spans 16+ years) has enabled us to assemble a rich portfolio of coherently integrated products that enable cost-effective evaluation and utilization of Linked Data, without writing a single line of code, or exposing you to the hidden, but extensive admin and configuration costs. Post installation, the benefits of Linked Data simply materialize (along the lines described above).

Our main Linked Data oriented products include:

• OpenLink Data Explorer -- visualizes Linked Data or Linked Data transformed "on the fly" from hypermedia and non hypermedia data sources
• URIBurner -- a "deceptively simple" solution that enables the generation of Linked Data "on the fly" from a broad collection of data sources and resource types
• OpenLink Data Spaces -- a platform for enterprises and individuals that enhances distributed collaboration via Linked Data driven virtualization of data across its native and/or 3rd party content manager for: Blogs, Wikis, Shared Bookmarks, Discussion Forums, Social Networks etc
• OpenLink Virtuoso -- a secure and high-performance native hybrid data server (Relational, RDF-Graph, Document models) that includes in-built Linked Data transformation middleware (aka. Sponger).

Related

• Hypertext Transfer Protocol 1.1 RFC
• Open Data Protocol Glossary
• Simple Explanation of RDF and Linked Data Dynamics
• Collection of post from the past about Linked Data
• Are We There Yet Re. Web++? -- includes link to podcast conversation with Jon Udell
• Web of Linked Data Pivoting Demo from TED -- by Microsoft's Gary Flake
• Microsoft Pivot atop Virtuoso Quad Store's Faceted Browser Engine-- My Demonstration of EAV model transcending data representation variations (i.e., RDF's EAV data model data served up in Microsoft CXML data representation format).

Motivation for this post arose from a series of Twitter exchanges between Tony Hirst and I, in relation to his blog post titled: So What Is It About Linked Data that Makes it Linked Data™ ?

At the end of the marathon session, it was clear to me that a blog post was required for future reference, at the very least :-)

What is Linked Data?

"Data Access by Reference" mechanism for Data Objects (or Entities) on HTTP networks. It enables you to Identify a Data Object and Access its structured Data Representation via a single Generic HTTP scheme based Identifier (HTTP URI). Data Object representation formats may vary; but in all cases, they are hypermedia oriented, fully structured, and negotiable within the context of a client-server message exchange.

Why is it Important?

Information makes the world tick!

Information doesn't exist without data to contextualize.

Information is inaccessible without a projection (presentation) medium.

All information (without exception, when produced by humans) is subjective. Thus, to truly maximize the innate heterogeneity of collective human intelligence, loose coupling of our information and associated data sources is imperative.

How is Linked Data Delivered?

Linked Data is exposed to HTTP networks (e.g. World Wide Web) via hypermedia resources bearing structured representations of data object descriptions. Remember, you have a single Identifier abstraction (generic HTTP URI) that embodies: Data Object Name and Data Representation Location (aka URL).

How are Linked Data Object Representations Structured?

A structured representation of data exists when an Entity (Datum), its Attributes, and its Attribute Values are clearly discernible. In the case of a Linked Data Object, structured descriptions take the form of a hypermedia based Entity-Attribute-Value (EAV) graph pictorial -- where each Entity, its Attributes, and its Attribute Values (optionally) are identified using Generic HTTP URIs.

Examples of structured data representation formats (content types) associated with Linked Data Objects include:

• text/html
• text/turtle
• text/n3
• application/json
• application/rdf+xml
• Others

How Do I Create Linked Data oriented Hypermedia Resources?

You markup resources by expressing distinct entity-attribute-value statements (basically these a 3-tuple records) using a variety of notations:

• (X)HTML+RDFa,
• JSON,
• Turtle,
• N3,
• TriX,
• TriG,
• RDF/XML, and
• Others (for instance you can use Atom data format extensions to model EAV graph as per OData initiative from Microsoft).

You can achieve this task using any of the following approaches:

• Notepad
• WYSIWYG Editor
• Transformation of Database Records via Middleware
• Transformation of XML based Web Services output via Middleware
• Transformation of other Hypermedia Resources via Middleware
• Transformation of non Hypermedia Resources via Middleware
• Use a platform that delivers all of the above.

Practical Examples of Linked Data Objects Enable

• Describe Who You Are, What You Offer, and What You Need via your structured profile, then leave your HTTP network to perform the REST (serendipitous discovery of relevant things)
• Identify (via map overlay) all items of interest based on a 2km+ radious of my current location (this could include vendor offerings or services sought by existing or future customers)
• Share the latest and greatest family photos with family members *only* without forcing them to signup for Yet Another Web 2.0 service or Social Network
• No repetitive signup and username and password based login sequences per Web 2.0 or Mobile Application combo
• Going beyond imprecise Keyword Search to the new frontier of Precision Find - Example, Find Data Objects associated with the keywords: Tiger, while enabling the seeker disambiguate across the "Who", "What", "Where", "When" dimensions (with negation capability)
• Determine how two Data Objects are Connected - person to person, person to subject matter etc. (LinkedIn outside the walled garden)
• Use any resource address (e.g blog or bookmark URL) as the conduit into a Data Object mesh that exposes all associated Entities and their social network relationships
• Apply patterns (social dimensions) above to traditional enterprise data sources in combination (optionally) with external data without compromising security etc.

How Do OpenLink Software Products Enable Linked Data Exploitation?

Our data access middleware heritage (which spans 16+ years) has enabled us to assemble a rich portfolio of coherently integrated products that enable cost-effective evaluation and utilization of Linked Data, without writing a single line of code, or exposing you to the hidden, but extensive admin and configuration costs. Post installation, the benefits of Linked Data simply materialize (along the lines described above).

Our main Linked Data oriented products include:

• OpenLink Data Explorer -- visualizes Linked Data or Linked Data transformed "on the fly" from hypermedia and non hypermedia data sources
• URIBurner -- a "deceptively simple" solution that enables the generation of Linked Data "on the fly" from a broad collection of data sources and resource types
• OpenLink Data Spaces -- a platform for enterprises and individuals that enhances distributed collaboration via Linked Data driven virtualization of data across its native and/or 3rd party content manager for: Blogs, Wikis, Shared Bookmarks, Discussion Forums, Social Networks etc
• OpenLink Virtuoso -- a secure and high-performance native hybrid data server (Relational, RDF-Graph, Document models) that includes in-built Linked Data transformation middleware (aka. Sponger).

Related

• Hypertext Transfer Protocol 1.1 RFC
• Open Data Protocol Glossary
• Simple Explanation of RDF and Linked Data Dynamics
• Collection of post from the past about Linked Data
• Are We There Yet Re. Web++? -- includes link to podcast conversation with Jon Udell
• Web of Linked Data Pivoting Demo from TED -- by Microsoft's Gary Flake
• Microsoft Pivot atop Virtuoso Quad Store's Faceted Browser Engine-- My Demonstration of EAV model transcending data representation variations (i.e., RDF's EAV data model data served up in Microsoft CXML data representation format).

Motivation for this post arose from a series of Twitter exchanges between Tony Hirst and I, in relation to his blog post titled: So What Is It About Linked Data that Makes it Linked Data™ ?

At the end of the marathon session, it was clear to me that a blog post was required for future reference, at the very least :-)

What is Linked Data?

"Data Access by Reference" mechanism for Data Objects (or Entities) on HTTP networks. It enables you to Identify a Data Object and Access its structured Data Representation via a single Generic HTTP scheme based Identifier (HTTP URI). Data Object representation formats may vary; but in all cases, they are hypermedia oriented, fully structured, and negotiable within the context of a client-server message exchange.

Why is it Important?

Information makes the world tick!

Information doesn't exist without data to contextualize.

Information is inaccessible without a projection (presentation) medium.

All information (without exception, when produced by humans) is subjective. Thus, to truly maximize the innate heterogeneity of collective human intelligence, loose coupling of our information and associated data sources is imperative.

How is Linked Data Delivered?

Linked Data is exposed to HTTP networks (e.g. World Wide Web) via hypermedia resources bearing structured representations of data object descriptions. Remember, you have a single Identifier abstraction (generic HTTP URI) that embodies: Data Object Name and Data Representation Location (aka URL).

How are Linked Data Object Representations Structured?

A structured representation of data exists when an Entity (Datum), its Attributes, and its Attribute Values are clearly discernible. In the case of a Linked Data Object, structured descriptions take the form of a hypermedia based Entity-Attribute-Value (EAV) graph pictorial -- where each Entity, its Attributes, and its Attribute Values (optionally) are identified using Generic HTTP URIs.

Examples of structured data representation formats (content types) associated with Linked Data Objects include:

• text/html
• text/turtle
• text/n3
• application/json
• application/rdf+xml
• Others

How Do I Create Linked Data oriented Hypermedia Resources?

You markup resources by expressing distinct entity-attribute-value statements (basically these a 3-tuple records) using a variety of notations:

• (X)HTML+RDFa,
• JSON,
• Turtle,
• N3,
• TriX,
• TriG,
• RDF/XML, and
• Others (for instance you can use Atom data format extensions to model EAV graph as per OData initiative from Microsoft).

You can achieve this task using any of the following approaches:

• Notepad
• WYSIWYG Editor
• Transformation of Database Records via Middleware
• Transformation of XML based Web Services output via Middleware
• Transformation of other Hypermedia Resources via Middleware
• Transformation of non Hypermedia Resources via Middleware
• Use a platform that delivers all of the above.

Practical Examples of Linked Data Objects Enable

• Describe Who You Are, What You Offer, and What You Need via your structured profile, then leave your HTTP network to perform the REST (serendipitous discovery of relevant things)
• Identify (via map overlay) all items of interest based on a 2km+ radious of my current location (this could include vendor offerings or services sought by existing or future customers)
• Share the latest and greatest family photos with family members *only* without forcing them to signup for Yet Another Web 2.0 service or Social Network
• No repetitive signup and username and password based login sequences per Web 2.0 or Mobile Application combo
• Going beyond imprecise Keyword Search to the new frontier of Precision Find - Example, Find Data Objects associated with the keywords: Tiger, while enabling the seeker disambiguate across the "Who", "What", "Where", "When" dimensions (with negation capability)
• Determine how two Data Objects are Connected - person to person, person to subject matter etc. (LinkedIn outside the walled garden)
• Use any resource address (e.g blog or bookmark URL) as the conduit into a Data Object mesh that exposes all associated Entities and their social network relationships
• Apply patterns (social dimensions) above to traditional enterprise data sources in combination (optionally) with external data without compromising security etc.

How Do OpenLink Software Products Enable Linked Data Exploitation?

Our data access middleware heritage (which spans 16+ years) has enabled us to assemble a rich portfolio of coherently integrated products that enable cost-effective evaluation and utilization of Linked Data, without writing a single line of code, or exposing you to the hidden, but extensive admin and configuration costs. Post installation, the benefits of Linked Data simply materialize (along the lines described above).

Our main Linked Data oriented products include:

• OpenLink Data Explorer -- visualizes Linked Data or Linked Data transformed "on the fly" from hypermedia and non hypermedia data sources
• URIBurner -- a "deceptively simple" solution that enables the generation of Linked Data "on the fly" from a broad collection of data sources and resource types
• OpenLink Data Spaces -- a platform for enterprises and individuals that enhances distributed collaboration via Linked Data driven virtualization of data across its native and/or 3rd party content manager for: Blogs, Wikis, Shared Bookmarks, Discussion Forums, Social Networks etc
• OpenLink Virtuoso -- a secure and high-performance native hybrid data server (Relational, RDF-Graph, Document models) that includes in-built Linked Data transformation middleware (aka. Sponger).

Related

• Hypertext Transfer Protocol 1.1 RFC
• Open Data Protocol Glossary
• Simple Explanation of RDF and Linked Data Dynamics
• Collection of post from the past about Linked Data
• Are We There Yet Re. Web++? -- includes link to podcast conversation with Jon Udell
• Web of Linked Data Pivoting Demo from TED -- by Microsoft's Gary Flake
• Microsoft Pivot atop Virtuoso Quad Store's Faceted Browser Engine-- My Demonstration of EAV model transcending data representation variations (i.e., RDF's EAV data model data served up in Microsoft CXML data representation format).

Socially enhanced enterprise and invididual collaboration is becoming a focal point for a variety of solutions that offer erswhile distinct content managment features across the realms of Blogging, Wikis, Shared Bookmarks, Discussion Forums etc.. as part of an integrated platform suite. Recently, Socialtext has caught my attention courtesy of its nice features and benefits page . In addition, I've also found the Mike 2.0 portal immensely interesting and valuable, for those with an enterprise collaboration bent.

Anyway, Socialtext and Mike 2.0 (they aren't identical and juxtaposition isn't seeking to imply this) provide nice demonstrations of socially enhanced collaboration for individuals and/or enterprises is all about:

1. Identifying Yourself
2. Identifying Others (key contributors, peers, collaborators)
3. Serendipitous Discovery of key contributors, peers, and collaborators
4. Serendipitous Discovery by key contributors, peers, and collaborators
5. Develop and sustain relationships via socially enhanced professional network hybrid
6. Utilize your new "trusted network" (which you've personally indexed) when seeking help or propagating a meme.

As is typically the case in this emerging realm, the critical issue of discrete "identifiers" (record keys in sense) for data items, data containers, and data creators (individuals and groups) is overlooked albeit unintentionally.

How HTTP based Linked Data Addresses the Identifier Issue

Rather than using platform constrained identifiers such as:

• email address (a "mailto" scheme identifier),
• a dbms user account,
• application specific account, or
• OpenID.

It enables you to leverage the platform independence of HTTP scheme Identifiers (Generic URIs) such that Identifiers for:

1. You,
2. Your Peers,
3. Your Groups, and
4. Your Activity Generated Data,

simply become conduits into a mesh of HTTP -- referencable and accessible -- Linked Data Objects endowed with High SDQ (Serendipitious Discovery Quotient). For example my Personal WebID is all anyone needs to know if they want to explore:

1. My Profile (which includes references to data objects associated with my interests, social-network, calendar, bookmarks etc.)
2. Data generated by my activities across various data spaces (via data objects associated with my online accounts e.g. Del.icio.us, Twitter, Last.FM)
3. Linked Data Meshups via URIBurner (or any other Virtuoso instance) that provide an extend view of my profile

How FOAF+SSL adds Socially aware Security

Even when you reach a point of equilibrium where: your daily activities trigger orchestratestration of CRUD (Create, Read, Update, Delete) operations against Linked Data Objects within your socially enhanced collaboration network, you still have to deal with the thorny issues of security, that includes the following:

1. Single Sign On,
2. Authentication, and
3. Data Access Policies.

FOAF+SSL, an application of HTTP based Linked Data, enables you to enhance your Personal HTTP scheme based Identifer (or WebID) via the following steps (peformed by a FOAF+SSL compliant platform):

1. Imprint WebID within a self-signed x.509 based public key (certificate) associated with your private key (generated by FOAF+SSL platform or manually via OpenSSL)
2. Store public key components (modulous and exponent) into your FOAF based profile document which references your Personal HTTP Identifier as its primary topic
3. Leverage HTTP URL component of WebID for making public key components (modulous and exponent) available for x.509 certificate based authentication challenges posed by systems secured by FOAF+SSL (directly) or OpenID (indirectly via FOAF+SSL to OpenID proxy services).

Contrary to conventional experiences with all things PKI (Public Key Infrastructure) related, FOAF+SSL compliant platforms typically handle the PKI issues as part of the protocol implementation; thereby protecting you from any administrative tedium without compromising security.

Conclusions

Understanding how new technology innovations address long standing problems, or understanding how new solutions inadvertently fail to address old problems, provides time tested mechanisms for product selection and value proposition comprehension that ultimately save scarce resources such as time and money.

If you want to understand real world problem solution #1 with regards to HTTP based Linked Data look no further than the issues of secure, socially aware, and platform independent identifiers for data objects, that build bridges across erstwhile data silos.

If you want to cost-effectively experience what I've outlined in this post, take a look at OpenLink Data Spaces (ODS) which is a distributed collaboration engine (enterprise of individual) built around the Virtuoso database engines. It simply enhances existing collaboration tools via the following capabilities:

Addition of Social Dimensions via HTTP based Data Object Identifiers for all Data Items (if missing)

1. Ability to integrate across a myriad of Data Source Types rather than a select few across RDBM Engines, LDAP, Web Services, and various HTTP accessible Resources (Hypermedia or Non Hypermedia content types)
2. Addition of FOAF+SSL based authentication
3. Addition of FOAF+SSL based Access Control Lists (ACLs) for policy based data access.

Related:

• Get Yourself A WebID in 5 Minutes or Less via OpenLink Data Spaces (an application layer built atop Virtuoso)
• How To Share Resources Securely Using FOAF+SSL
• FOAF+SSL & WebID Demonstration
• OpenLink Data Spaces & Data Portability.

Socially enhanced enterprise and invididual collaboration is becoming a focal point for a variety of solutions that offer erswhile distinct content managment features across the realms of Blogging, Wikis, Shared Bookmarks, Discussion Forums etc.. as part of an integrated platform suite. Recently, Socialtext has caught my attention courtesy of its nice features and benefits page . In addition, I've also found the Mike 2.0 portal immensely interesting and valuable, for those with an enterprise collaboration bent.

Anyway, Socialtext and Mike 2.0 (they aren't identical and juxtaposition isn't seeking to imply this) provide nice demonstrations of socially enhanced collaboration for individuals and/or enterprises is all about:

1. Identifying Yourself
2. Identifying Others (key contributors, peers, collaborators)
3. Serendipitous Discovery of key contributors, peers, and collaborators
4. Serendipitous Discovery by key contributors, peers, and collaborators
5. Develop and sustain relationships via socially enhanced professional network hybrid
6. Utilize your new "trusted network" (which you've personally indexed) when seeking help or propagating a meme.

As is typically the case in this emerging realm, the critical issue of discrete "identifiers" (record keys in sense) for data items, data containers, and data creators (individuals and groups) is overlooked albeit unintentionally.

How HTTP based Linked Data Addresses the Identifier Issue

Rather than using platform constrained identifiers such as:

• email address (a "mailto" scheme identifier),
• a dbms user account,
• application specific account, or
• OpenID.

It enables you to leverage the platform independence of HTTP scheme Identifiers (Generic URIs) such that Identifiers for:

1. You,
2. Your Peers,
3. Your Groups, and
4. Your Activity Generated Data,

simply become conduits into a mesh of HTTP -- referencable and accessible -- Linked Data Objects endowed with High SDQ (Serendipitious Discovery Quotient). For example my Personal WebID is all anyone needs to know if they want to explore:

1. My Profile (which includes references to data objects associated with my interests, social-network, calendar, bookmarks etc.)
2. Data generated by my activities across various data spaces (via data objects associated with my online accounts e.g. Del.icio.us, Twitter, Last.FM)
3. Linked Data Meshups via URIBurner (or any other Virtuoso instance) that provide an extend view of my profile

How FOAF+SSL adds Socially aware Security

Even when you reach a point of equilibrium where: your daily activities trigger orchestratestration of CRUD (Create, Read, Update, Delete) operations against Linked Data Objects within your socially enhanced collaboration network, you still have to deal with the thorny issues of security, that includes the following:

1. Single Sign On,
2. Authentication, and
3. Data Access Policies.

FOAF+SSL, an application of HTTP based Linked Data, enables you to enhance your Personal HTTP scheme based Identifer (or WebID) via the following steps (peformed by a FOAF+SSL compliant platform):

1. Imprint WebID within a self-signed x.509 based public key (certificate) associated with your private key (generated by FOAF+SSL platform or manually via OpenSSL)
2. Store public key components (modulous and exponent) into your FOAF based profile document which references your Personal HTTP Identifier as its primary topic
3. Leverage HTTP URL component of WebID for making public key components (modulous and exponent) available for x.509 certificate based authentication challenges posed by systems secured by FOAF+SSL (directly) or OpenID (indirectly via FOAF+SSL to OpenID proxy services).

Contrary to conventional experiences with all things PKI (Public Key Infrastructure) related, FOAF+SSL compliant platforms typically handle the PKI issues as part of the protocol implementation; thereby protecting you from any administrative tedium without compromising security.

Conclusions

Understanding how new technology innovations address long standing problems, or understanding how new solutions inadvertently fail to address old problems, provides time tested mechanisms for product selection and value proposition comprehension that ultimately save scarce resources such as time and money.

If you want to understand real world problem solution #1 with regards to HTTP based Linked Data look no further than the issues of secure, socially aware, and platform independent identifiers for data objects, that build bridges across erstwhile data silos.

If you want to cost-effectively experience what I've outlined in this post, take a look at OpenLink Data Spaces (ODS) which is a distributed collaboration engine (enterprise of individual) built around the Virtuoso database engines. It simply enhances existing collaboration tools via the following capabilities:

Addition of Social Dimensions via HTTP based Data Object Identifiers for all Data Items (if missing)

1. Ability to integrate across a myriad of Data Source Types rather than a select few across RDBM Engines, LDAP, Web Services, and various HTTP accessible Resources (Hypermedia or Non Hypermedia content types)
2. Addition of FOAF+SSL based authentication
3. Addition of FOAF+SSL based Access Control Lists (ACLs) for policy based data access.

Related:

• Get Yourself A WebID in 5 Minutes or Less via OpenLink Data Spaces (an application layer built atop Virtuoso)
• How To Share Resources Securely Using FOAF+SSL
• FOAF+SSL & WebID Demonstration
• OpenLink Data Spaces & Data Portability.

The recent Wikipedia imbroglio centered around DBpedia is the fundamental driver for this particular blog post. At time of writing this blog post, the DBpedia project definition in Wikipedia remains unsatisfactory due to the following shortcomings:

1. inaccurate and incomplete definition of the Project's What, Why, Who, Where, When, and How
2. inaccurate reflection of project essence, by skewing focus towards data extraction and data set dump production, which is at best a quarter of the project.

Here are some insights on DBpedia, from the perspective of someone intimately involved with the other three-quarters of the project.

What is DBpedia?

A live Web accessible RDF model database (Quad Store) derived from Wikipedia content snapshots, taken periodically. The RDF database underlies a Linked Data Space comprised of: HTML (and most recently HTML+RDFa) based data browser pages and a SPARQL endpoint.

Note: DBpedia 3.4 now exists in snapshot (warehouse) and Live Editions (currently being hot-staged). This post is about the snapshot (warehouse) edition, I'll drop a different post about the DBpedia Live Edition where a new Delta-Engine covers both extraction and database record replacement, in realtime.

When was it Created?

As an idea under the moniker "DBpedia" it was conceptualized in late 2006 by researchers at University of Leipzig (lead by Soren Auer) and Freie University, Berlin (lead by Chris Bizer). The first public instance of DBpedia (as described above) was released in February 2007. The official DBpedia coming out party occurred at WWW2007, Banff, during the inaugural Linked Data gathering, where it showcased the virtues and immense potential of TimBL's Linked Data meme.

Who's Behind It?

OpenLink Software (developers of OpenLink Virtuoso and providers of Web Hosting infrastructure), University of Leipzig, and Freie Univerity, Berlin. In addition, there is a burgeoning community of collaborators and contributors responsible DBpedia based applications, cross-linked data sets, ontologies (OpenCyc, SUMO, UMBEL, and YAGO) and other utilities. Finally, DBpedia wouldn't be possible without the global content contribution and curation efforts of Wikipedians, a point typically overlooked (albeit inadvertently).

How is it Constructed?

The steps are as follows:

1. RDF data set dump preparation via Wikipedia content extraction and transformation to RDF model data, using the N3 data representation format - Java and PHP extraction code produced and maintained by the teams at Leipzig and Berlin
2. Deployment of Linked Data that enables Data browsing and exploration using any HTTP aware user agent (e.g. basic Web Browsers) - handled by OpenLink Virtuoso (handled by Berlin via the Pubby Linked Data Server during the early months of the DBpedia project)
3. SPARQL compliant Quad Store, enabling direct access to database records via SPARQL (Query language, REST or SOAP Web Service, plus a variety of query results serialization formats) - OpenLink Virtuoso since first public release of DBpedia

In a nutshell, there are four distinct and vital components to DBpedia. Thus, DBpedia doesn't exist if all the project offered was a collection of RDF data dumps. Likewise, it doesn't exist without a fully populated SPARQL compliant Quad Store. Last but not least, it doesn't exist if you have a fully loaded SPARQL compliant Quad Store isn't up to the cocktail of challenges (query load and complexity) presented by live Web database accessibility.

Why is it Important?

It remains a live exemplar for any individual or organization seeking to publishing or exploit HTTP based Linked Data on the World Wide Web. Its existence continues to stimulate growth in both density and quality of the burgeoning Web of Linked Data.

How Do I Use it?

In the most basic sense, simply browse the HTML based resource decriptor pages en route to discovering erstwhile undiscovered relationships that exist across named entities and subject matter concepts / headings. Beyond that, simply look at DBpedia as a master lookup table in a Web hosted distributed database setup; enabling you to mesh your local domain specific details with DBpedia records via structured relations (triples or 3-tuples records), comprised of HTTP URIs from both realms e.g., via owl:sameAs relations.

What Can I Use it For?

Expanding on the Master-Details point above, you can use its rich URI corpus to alleviate tedium associated with activities such as:

1. List maintenance - e.g., Countries, States, Companies, Units of Measurement, Subject Headings etc.
2. Tagging - as a compliment to existing practices
3. Analytical Research - you're only a LINK (URI) away from erstwhile difficult to attain research data spread across a broad range of topics
4. Closed Vocabulary Construction - rather than commence the futile quest of building your own closed vocabulary, simply leverage Wikipedia's human curated vocabulary as our common base.

Related

• Pre-loaded and Pre-configured instances of DBpedia 3.4 - via publicly shared Amazon Elastic Block Storage Snapshots
• Virtuoso & DBpedia Tunning Guide
• What's In a Name & The Linked Data Police.