OpenLink Community Blog

I had the opportunity the other day to converse about the semantic technology business proposition in terms of business development. My interlocutor was a business development consultant who had little prior knowledge of this technology but a background in business development inside a large diversified enterprise.

I will here recap some of the points discussed, since these can be of broader interest.

The field is young. We can take the relational database industry as a historical precedent. From the inception of the relational database around 1970, it took 15 years for the relational model to become mainstream. "Mainstream" here does not mean dominant in installed base, but does mean something that one tends to include as a component in new systems. The figure of 15 years might repeat with RDF, from around 1990 for the first beginnings to 2015 for routine inclusion in new systems, where applicable.

This does not necessarily mean that the RDF graph data model (or more properly, EAV+CR; Entity-Attribute-Value + Classes and Relationships) will take the place of the RDBMS as the preferred data backbone. This could mean that RDF model serialization formats will be supported as data exchange mechanisms, and that systems will integrate data extracted by semantic technology from unstructured sources. Some degree of EAV storage is likely to be common, but on-line transactional data is guaranteed to stay pure relational, as EAV is suboptimal for OLTP. Analytics will see EAV alongside relational especially in applications where in-house data is being combined with large numbers of outside structured sources or with other open sources such as information extracted from the web.

EAV offerings will become integrated by major DBMS vendors, as is already the case with Oracle. Specialized vendors will exist alongside these, just as is the case with relational databases.

Can there be a positive reinforcement cycle (e.g., building cars creates a need for road construction, and better roads drive demand for more cars)? Or is this an up-front infrastructure investment that governments make for some future payoff or because of science-funding policies?

The Document Web did not start as a government infrastructure initiative. The infrastructure was already built, albeit first originating with the US defense establishment. The Internet became ubiquitous through the adoption of the Web. The general public's adoption of the Web was bootstrapped by all major business and media adopting the Web. They did not adopt the web because they particularly liked it, as it was essentially a threat to the position of media and to the market dominance of big players who could afford massive advertising in this same media. Adopting the web became necessary because of the prohibitive opportunity cost of not adopting it.

A similar process may take place with open data. For example, in E-commerce, vendors do not necessarily welcome easy-and-automatic machine-based comparison of their offerings against those of their competitors. Publishing data will however be necessary in order to be listed at all. Also, in social networks, we have the identity portability movement which strives to open the big social network silos. Data exchange via RDF serializations, as already supported in many places, is the natural enabling technology for this.

Will the web of structured data parallel the development of web 2.0?

Web 2.0 was about the blogosphere, exposure of web site service APIs, creation of affiliate programs, and so forth. If the Document Web was like a universal printing press, where anybody could publish at will, Web 2.0 was a newspaper, bringing the democratization of journalism, creating the blogger, the citizen journalist. The Data Web will create the Citizen Analyst, the Mini Media Mogul (e.g., social-network-driven coops comprised of citizen journalists, analysts, and other content providers such as video and audio producers and publishers). As the blogosphere became an alternative news source to the big media, the web of data may create an ecosystem of alternative data products. Analytics is no longer a government or big business only proposition.

Is there a specifically semantic market or business model, or will semantic technology be exploited under established business models and merged as a component technology into existing offerings?

We have seen a migration from capital expenses to operating expenses in the IT sector in general, as exemplified by cloud computing's Platform as a Service (PaaS) and Software as a Service (SaaS). It is reasonable to anticipate that this trend will continue to Data as a Service (DaaS). Microsoft Odata and Dallas are early examples of this and go towards legitimizing the data as service concept. DaaS is not related to semantic technology per se, but since this will involve integration of data, RDF serializations will be attractive, especially given the takeoff of linked data in general. The data models in Odata are also much like RDF, as both stem from EAV+CR, which makes for easy translation and a degree of inherent interoperability.

The integration of semantic technology into existing web properties and business applications will manifest to the end user as increased serendipity. The systems will be able to provide more relevant and better contextualized data for the user's situation. This applies equally to the consumer and business user cases.

Identity virtualization in the forms of WebID and Webfinger — making first-class de-referenceable identifiers of mailto: and acct: schemes — is emerging as a new way to open social network and Web 2.0 data silos.

On the software production side, especially as concerns data integration, the increased schema- and inference-flexibility of EAV will lead to a quicker time to answer in many situations. The more complex the task or the more diverse the data, the higher the potential payoff. Data in cyberspace is mirroring the complexity and diversity of the real world, where heterogeneity and disparity are simply facts of life, and such flexibility is becoming an inescapable necessity.

I had the opportunity the other day to converse about the semantic technology business proposition in terms of business development. My interlocutor was a business development consultant who had little prior knowledge of this technology but a background in business development inside a large diversified enterprise.

I will here recap some of the points discussed, since these can be of broader interest.

The field is young. We can take the relational database industry as a historical precedent. From the inception of the relational database around 1970, it took 15 years for the relational model to become mainstream. "Mainstream" here does not mean dominant in installed base, but does mean something that one tends to include as a component in new systems. The figure of 15 years might repeat with RDF, from around 1990 for the first beginnings to 2015 for routine inclusion in new systems, where applicable.

This does not necessarily mean that the RDF graph data model (or more properly, EAV+CR; Entity-Attribute-Value + Classes and Relationships) will take the place of the RDBMS as the preferred data backbone. This could mean that RDF model serialization formats will be supported as data exchange mechanisms, and that systems will integrate data extracted by semantic technology from unstructured sources. Some degree of EAV storage is likely to be common, but on-line transactional data is guaranteed to stay pure relational, as EAV is suboptimal for OLTP. Analytics will see EAV alongside relational especially in applications where in-house data is being combined with large numbers of outside structured sources or with other open sources such as information extracted from the web.

EAV offerings will become integrated by major DBMS vendors, as is already the case with Oracle. Specialized vendors will exist alongside these, just as is the case with relational databases.

Can there be a positive reinforcement cycle (e.g., building cars creates a need for road construction, and better roads drive demand for more cars)? Or is this an up-front infrastructure investment that governments make for some future payoff or because of science-funding policies?

The Document Web did not start as a government infrastructure initiative. The infrastructure was already built, albeit first originating with the US defense establishment. The Internet became ubiquitous through the adoption of the Web. The general public's adoption of the Web was bootstrapped by all major business and media adopting the Web. They did not adopt the web because they particularly liked it, as it was essentially a threat to the position of media and to the market dominance of big players who could afford massive advertising in this same media. Adopting the web became necessary because of the prohibitive opportunity cost of not adopting it.

A similar process may take place with open data. For example, in E-commerce, vendors do not necessarily welcome easy-and-automatic machine-based comparison of their offerings against those of their competitors. Publishing data will however be necessary in order to be listed at all. Also, in social networks, we have the identity portability movement which strives to open the big social network silos. Data exchange via RDF serializations, as already supported in many places, is the natural enabling technology for this.

Will the web of structured data parallel the development of web 2.0?

Web 2.0 was about the blogosphere, exposure of web site service APIs, creation of affiliate programs, and so forth. If the Document Web was like a universal printing press, where anybody could publish at will, Web 2.0 was a newspaper, bringing the democratization of journalism, creating the blogger, the citizen journalist. The Data Web will create the Citizen Analyst, the Mini Media Mogul (e.g., social-network-driven coops comprised of citizen journalists, analysts, and other content providers such as video and audio producers and publishers). As the blogosphere became an alternative news source to the big media, the web of data may create an ecosystem of alternative data products. Analytics is no longer a government or big business only proposition.

Is there a specifically semantic market or business model, or will semantic technology be exploited under established business models and merged as a component technology into existing offerings?

We have seen a migration from capital expenses to operating expenses in the IT sector in general, as exemplified by cloud computing's Platform as a Service (PaaS) and Software as a Service (SaaS). It is reasonable to anticipate that this trend will continue to Data as a Service (DaaS). Microsoft Odata and Dallas are early examples of this and go towards legitimizing the data as service concept. DaaS is not related to semantic technology per se, but since this will involve integration of data, RDF serializations will be attractive, especially given the takeoff of linked data in general. The data models in Odata are also much like RDF, as both stem from EAV+CR, which makes for easy translation and a degree of inherent interoperability.

The integration of semantic technology into existing web properties and business applications will manifest to the end user as increased serendipity. The systems will be able to provide more relevant and better contextualized data for the user's situation. This applies equally to the consumer and business user cases.

Identity virtualization in the forms of WebID and Webfinger — making first-class de-referenceable identifiers of mailto: and acct: schemes — is emerging as a new way to open social network and Web 2.0 data silos.

On the software production side, especially as concerns data integration, the increased schema- and inference-flexibility of EAV will lead to a quicker time to answer in many situations. The more complex the task or the more diverse the data, the higher the potential payoff. Data in cyberspace is mirroring the complexity and diversity of the real world, where heterogeneity and disparity are simply facts of life, and such flexibility is becoming an inescapable necessity.

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

• Referent, Identifier, and Descriptor/Sense (The Data Perception Trinity) illustration
• Referent, Identifier, and Descriptor/Sense Trinity (as exploited in FOAF+SSL based Secure WebIDs) illustration
• Demystifying Linked Data via EAV Model based Structured Descriptions
• What do people have against URIs and URLs?
• The URI, URL, and Linked Data Meme's Generic HTTP URI
• Simple Explanation of RDF and Linked Data Dynamics
• Linked Data and Identity
• FOAF+SSL FAQ
• LOD Community Thread (showing evolution of this manifesto based on feedback from members such as Richard Cyganiak).
• Googlebase Data API Docs
• Google Data Protocol (GData)
• Microsoft's OData Protocol
• Magic of De-referencable Names and actual Data via Binky Video
• Social Objects Presentation (aka. Social Linked Data Objects) - by Jyri Engeström
• What's a Reference?

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

• Referent, Identifier, and Descriptor/Sense (The Data Perception Trinity) illustration
• Referent, Identifier, and Descriptor/Sense Trinity (as exploited in FOAF+SSL based Secure WebIDs) illustration
• Demystifying Linked Data via EAV Model based Structured Descriptions
• What do people have against URIs and URLs?
• The URI, URL, and Linked Data Meme's Generic HTTP URI
• Simple Explanation of RDF and Linked Data Dynamics
• Linked Data and Identity
• FOAF+SSL FAQ
• LOD Community Thread (showing evolution of this manifesto based on feedback from members such as Richard Cyganiak).
• Googlebase Data API Docs
• Google Data Protocol (GData)
• Microsoft's OData Protocol
• Magic of De-referencable Names and actual Data via Binky Video
• Social Objects Presentation (aka. Social Linked Data Objects) - by Jyri Engeström
• What's a Reference?

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

• Referent, Identifier, and Descriptor/Sense (The Data Perception Trinity) illustration
• Referent, Identifier, and Descriptor/Sense Trinity (as exploited in FOAF+SSL based Secure WebIDs) illustration
• Demystifying Linked Data via EAV Model based Structured Descriptions
• What do people have against URIs and URLs?
• The URI, URL, and Linked Data Meme's Generic HTTP URI
• Simple Explanation of RDF and Linked Data Dynamics
• Linked Data and Identity
• FOAF+SSL FAQ
• LOD Community Thread (showing evolution of this manifesto based on feedback from members such as Richard Cyganiak).
• Googlebase Data API Docs
• Google Data Protocol (GData)
• Microsoft's OData Protocol
• Magic of De-referencable Names and actual Data via Binky Video
• Social Objects Presentation (aka. Social Linked Data Objects) - by Jyri Engeström
• What's a Reference?

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).

Situation Analysis

Since the beginning of the modern IT era, each period of innovation has inadvertently introduced its fair share of Data Silos. The driving force behind this anomaly remains an overemphasis on the role of applications when selecting problem solutions. Unfortunately, most solution selecting decision makers remain oblivious to the fact that most applications are architecturally monolithic; i.e., they fail to separate the following five layers that are critical to all solutions:

1. Data Unit (Datum or Data Object) Identity,
2. Data Storage/Persistence,
3. Data Access,
4. Data Representation, and
5. Data Presentation/Visualization.

The rise of the Internet, and its exponentially-growing user-friendly enclave known as the World Wide Web, is bringing the intrinsic costs of the monolithic application architecture anomaly to bear -- in manners unanticipated by many. For example, the emergence of network-oriented solutions across the realms of Enterprise 2.0-based Collaboration and Web 2.0-based Software-as-a-Service (SaaS), combined with the overarching influence of Social Media, are producing more heterogeneously-structured and disparately-located data sources than people can effectively process.

As is often the case, a variety of problem and product monikers have emerged for the data access and integration challenges outlined above. Contemporary examples include Enterprise Information Integration, Master Data Management, and Data Virtualization. Labeling aside, the fundamental issues of the unresolved Data Integration challenge boil down to the following:

• Data Model Heterogeneity
• Data Quality (Cleanliness)
• Semantic Variance across Contexts (e.g., weights and measures).

Effectively solving today's data integration challenges requires a move away from monolithic application architecture to loosely-coupled, network-centric application architectures. Basically, we need a ubiquitous network-centric application protocol that lends itself to loosely-coupled across-the-wire orchestration of data interactions. In short, this will be what revitalizes the art of application development and deployment.

The World Wide Web is built around a network application protocol called HTTP. This protocol intrinsically separates the five layers listed earlier, thereby enabling:

• Use of Generic HTTP URIs as Data Object (Entity) Identifiers;
• Identifier Co-reference, such that multiple Data Object Identifiers may reference the same Data Object;
• Use of the Entity-Attribute-Value Model to describe Data Objects using real world modeling friendly conceptual graphs;
• Use of HTTP URLs to Identify Locations of Resources that bear (host) Data Object Descriptions (Representations);
• Data Access mechanism for retrieving Data Object Representations from persistent or transient storage locations.

What is Virtuoso?

A uniquely designed to address today's escalating Data Access and Integration challenges without compromising performance, security, or platform independence. At its core lies an unrivaled commitment to industry standards combined with unique technology innovation that transcends erstwhile distinct realms such as:

• Data Management (Relational, RDF Graph, or Document),
• Data Access Middleware,
• Web Application & Services Deployment,
• Linked Data Deployment, and
• Messaging.

When Virtuoso is installed and running, HTTP-based Data Objects are automatically created as a by-product of its powerful data virtualization, transcending data sources and data representation formats. The benefits of such power extend across profiles such as:

• Information & Knowledge Workers,
• Systems Integrators & Architects,
• Distributed Collaboration & Social Media,
• Cloud Computing, and
• Application Development.

Product Benefits Summary

• Enterprise Agility — Virtuoso lets you mix-&-match best-of-class combinations of Operating Systems, Programming Environments, Database Engines and Data-Access Middleware when building or tweaking your IS infrastructure, without the typical impedance of vendor-lock-in.
• Data Model Dexterity — By supporting multiple protocols and data models in a single product, Virtuoso protects you against costly vulnerabilities such as: perennial acquisition and accumulation of expensive data model specific DBMS products that still operate on the fundamental principle of: proprietary technology lock-in, at a time when heterogeneity continues to intrinsically define the information technology landscape.
• Cost-effectiveness — By providing a single point of access (and single-sign-on, SSO) to a plethora of Web 2.0-style social networks, Web Services, and Content Management Systems, and by using Data Object Identifiers as units of Data Virtualization that become the focal points of all data access, Virtuoso lowers the cost to exploit emerging frontiers such as socially-enhanced enterprise collaboration.
• Speed of Exploitation — Virtuoso provides the ability to rapidly assemble 360-degree conceptual views of data, across internal line-of-business application (CRM, ERP, ECM, HR, etc.) data and/or external data sources, whether these are unstructured, semi-structured, or fully structured.

Bottom line, Virtuoso delivers unrivaled flexibility and scalability, without compromising performance or security.

Related

• HTTP URI Abstraction and Linked Data
• Be The Master of Your Own Search Index
• Who's Data Is It?
• MDM & Linked Data
• What is Linked Data Oriented RDF-zation?
• Semantic Web: Travails to Harmony Illustrated