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Simple Virtuoso Installation & Utilization Guide for SPARQL Users (Update 5)

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.
# PermaLink Comments [2]
01/16/2011 02:06 GMT-0500 Modified: 01/19/2011 10:43 GMT-0500
Simple Virtuoso Installation & Utilization Guide for SPARQL Users (Update 5)

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.
# PermaLink Comments [2]
01/16/2011 02:06 GMT-0500 Modified: 01/19/2011 10:43 GMT-0500
Virtuoso Linked Data Deployment In 3 Simple Steps

Injecting Linked Data into the Web has been a major pain point for those who seek personal, service, or organization-specific variants of DBpedia. Basically, the sequence goes something like this:

  1. You encounter DBpedia or the LOD Cloud Pictorial.
  2. You look around (typically following your nose from link to link).
  3. You attempt to publish your own stuff.
  4. You get stuck.

The problems typically take the following form:

  1. Functionality confusion about the complementary Name and Address functionality of a single URI abstraction
  2. Terminology confusion due to conflation and over-loading of terms such as Resource, URL, Representation, Document, etc.
  3. Inability to find robust tools with which to generate Linked Data from existing data sources such as relational databases, CSV files, XML, Web Services, etc.

To start addressing these problems, here is a simple guide for generating and publishing Linked Data using Virtuoso.

Step 1 - RDF Data Generation

Existing RDF data can be added to the Virtuoso RDF Quad Store via a variety of built-in data loader utilities.

Many options allow you to easily and quickly generate RDF data from other data sources:

  • Install the Sponger Bookmarklet for the URIBurner service. Bind this to your own SPARQL-compliant backend RDF database (in this scenario, your local Virtuoso instance), and then Sponge some HTTP-accessible resources.
  • Convert relational DBMS data to RDF using the Virtuoso RDF Views Wizard.
  • Starting with CSV files, you can
    • Place them at an HTTP-accessible location, and use the Virtuoso Sponger to convert them to RDF or;
    • Use the CVS import feature to import their content into Virtuoso's relational data engine; then use the built-in RDF Views Wizard as with other RDBMS data.
  • Starting from XML files, you can
    • Use Virtuoso's inbuilt XSLT-Processor for manual XML to RDF/XML transformation or;
    • Leverage the Sponger Cartridge for GRDDL, if there is a transformation service associated with your XML data source, or;
    • Let the Sponger analyze the XML data source and make a best-effort transformation to RDF.

Step 2 - Linked Data Deployment

Install the Faceted Browser VAD package (fct_dav.vad) which delivers the following:

  1. Faceted Browser Engine UI
  2. Dynamic Hypermedia Resource Generator
    • delivers descriptor resources for every entity (data object) in the Native or Virtual Quad Stores
    • supports a broad array of output formats, including HTML+RDFa, RDF/XML, N3/Turtle, NTriples, RDF-JSON, OData+Atom, and OData+JSON.

Step 3 - Linked Data Consumption & Exploitation

Three simple steps allow you, your enterprise, and your customers to consume and exploit your newly deployed Linked Data --

  1. Load a page like this in your browser: http://<cname>[:<port>]/describe/?uri=<entity-uri>
    • <cname>[:<port>] gets replaced by the host and port of your Virtuoso instance
    • <entity-uri> gets replaced by the URI you want to see described -- for instance, the URI of one of the resources you let the Sponger handle.
  2. Follow the links presented in the descriptor page.
  3. If you ever see a blank page with a hyperlink subject name in the About: section at the top of the page, simply add the parameter "&sp=1" to the URL in the browser's Address box, and hit [ENTER]. This will result in an "on the fly" resource retrieval, transformation, and descriptor page generation.
  4. Use the navigator controls to page up and down the data associated with the "in scope" resource descriptor.

Related

# PermaLink Comments [0]
10/29/2010 18:54 GMT-0500 Modified: 11/02/2010 11:55 GMT-0500
Data 3.0 (a Manifesto for Platform Agnostic Structured Data) Update 5

After a long period of trying to demystify and unravel the wonders of standards compliant structured data access, combined with protocols (e.g., HTTP) that separate:

  1. Identity,
  2. Access,
  3. Storage,
  4. Representation, and
  5. Presentation.

I ended up with what I can best describe as the Data 3.0 Manifesto. A manifesto for standards complaint access to structured data object (or entity) descriptors.

Some Related Work

Alex James (Program Manager Entity Frameworks at Microsoft), put together something quite similar to this via his Base4 blog (around the Web 2.0 bootstrap time), sadly -- quoting Alex -- that post has gone where discontinued blogs and their host platforms go (deep deep irony here).

It's also important to note that this manifesto is also a variant of the TimBL's Linked Data Design Issues meme re. Linked Data, but totally decoupled from RDF (data representation formats aspect) and SPARQL which -- in my world view -- remain implementation details.

Data 3.0 manifesto

  • An "Entity" is the "Referent" of an "Identifier."
  • An "Identifier" SHOULD provide a global, unambiguous, and unchanging (though it MAY be opaque!) "Name" for its "Referent".
  • A "Referent" MAY have many "Identifiers" (Names), but each "Identifier" MUST have only one "Referent".
  • Structured Entity Descriptions SHOULD be based on the Entity-Attribute-Value (EAV) Data Model, and SHOULD therefore take the form of one or more 3-tuples (triples), each comprised of:
    • an "Identifier" that names an "Entity" (i.e., Entity Name),
    • an "Identifier" that names an "Attribute" (i.e., Attribute Name), and
    • an "Attribute Value", which may be an "Identifier" or a "Literal".
  • Structured Descriptions SHOULD be CARRIED by "Descriptor Documents" (i.e., purpose specific documents where Entity Identifiers, Attribute Identifiers, and Attribute Values are clearly discernible by the document's intended consumers, e.g., humans or machines).
  • Structured Descriptor Documents can contain (carry) several Structured Entity Descriptions
  • Stuctured Descriptor Documents SHOULD be network accessible via network addresses (e.g., HTTP URLs when dealing with HTTP-based Networks).
  • An Identifier SHOULD resolve (de-reference) to a Structured Representation of the Referent's Structured Description.

Related

# PermaLink Comments [6]
04/16/2010 17:09 GMT-0500 Modified: 05/25/2010 17:10 GMT-0500
Data 3.0 (a Manifesto for Platform Agnostic Structured Data) Update 5

After a long period of trying to demystify and unravel the wonders of standards compliant structured data access, combined with protocols (e.g., HTTP) that separate:

  1. Identity,
  2. Access,
  3. Storage,
  4. Representation, and
  5. Presentation.

I ended up with what I can best describe as the Data 3.0 Manifesto. A manifesto for standards complaint access to structured data object (or entity) descriptors.

Some Related Work

Alex James (Program Manager Entity Frameworks at Microsoft), put together something quite similar to this via his Base4 blog (around the Web 2.0 bootstrap time), sadly -- quoting Alex -- that post has gone where discontinued blogs and their host platforms go (deep deep irony here).

It's also important to note that this manifesto is also a variant of the TimBL's Linked Data Design Issues meme re. Linked Data, but totally decoupled from RDF (data representation formats aspect) and SPARQL which -- in my world view -- remain implementation details.

Data 3.0 manifesto

  • An "Entity" is the "Referent" of an "Identifier."
  • An "Identifier" SHOULD provide a global, unambiguous, and unchanging (though it MAY be opaque!) "Name" for its "Referent".
  • A "Referent" MAY have many "Identifiers" (Names), but each "Identifier" MUST have only one "Referent".
  • Structured Entity Descriptions SHOULD be based on the Entity-Attribute-Value (EAV) Data Model, and SHOULD therefore take the form of one or more 3-tuples (triples), each comprised of:
    • an "Identifier" that names an "Entity" (i.e., Entity Name),
    • an "Identifier" that names an "Attribute" (i.e., Attribute Name), and
    • an "Attribute Value", which may be an "Identifier" or a "Literal".
  • Structured Descriptions SHOULD be CARRIED by "Descriptor Documents" (i.e., purpose specific documents where Entity Identifiers, Attribute Identifiers, and Attribute Values are clearly discernible by the document's intended consumers, e.g., humans or machines).
  • Structured Descriptor Documents can contain (carry) several Structured Entity Descriptions
  • Stuctured Descriptor Documents SHOULD be network accessible via network addresses (e.g., HTTP URLs when dealing with HTTP-based Networks).
  • An Identifier SHOULD resolve (de-reference) to a Structured Representation of the Referent's Structured Description.

Related

# PermaLink Comments [6]
04/16/2010 17:09 GMT-0500 Modified: 05/25/2010 17:10 GMT-0500
Revisiting HTTP based Linked Data (Update 1 - Demo Video Links Added)

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

# PermaLink Comments [0]
03/04/2010 10:16 GMT-0500 Modified: 03/08/2010 09:59 GMT-0500
Revisiting HTTP based Linked Data (Update 1 - Demo Video Links Added)

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

# PermaLink Comments [0]
03/04/2010 10:16 GMT-0500 Modified: 03/08/2010 09:59 GMT-0500
Revisiting HTTP based Linked Data (Update 1 - Demo Video Links Added)

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

# PermaLink Comments [0]
03/04/2010 10:16 GMT-0500 Modified: 03/08/2010 09:59 GMT-0500
Revisiting HTTP based Linked Data (Update 1 - Demo Video Links Added)

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

# PermaLink Comments [0]
03/04/2010 10:16 GMT-0500 Modified: 03/08/2010 09:59 GMT-0500
Linked Data & Socially Enhanced Collaboration (Enterprise or Individual) -- Update 1

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:

# PermaLink Comments [0]
03/02/2010 15:47 GMT-0500 Modified: 03/03/2010 19:50 GMT-0500
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