Kingsley Uyi Idehen's Weblog

Note: An updated version of a previously unpublished blog post:

Continuing from our recent Podcast conversation, Jon Udell sheds further insight into the essence of our conversation via a “Strategic Developer” column article titled: Accessing the web of databases.

Below, I present an initial dump of a DataSpace FAQ below that hopefully sheds light on the DataSpace vision espoused during my podcast conversation with Jon.

What is a DataSpace?

A moniker for Web-accessible atomic containers that manage and expose Data, Information, Services, Processes, and Knowledge.

What would you typically find in a Data Space? Examples include:

• Raw Data - SQL, HTML, XML (raw), XHTML, RDF etc.
  
  
• Information (Data In Context) - XHTML (various microformats), Blog Posts (in RSS, Atom, RSS-RDF formats), Subscription Lists (OPML, OCS, etc), Social Networks (FOAF, XFN etc.), and many other forms of applied XML.

• Web Services (Application/Service Logic) - REST or SOAP based invocation of application logic for context sensitive and controlled data access and manipulation.

• Persisted Knowledge - Information in actionable context that is also available in transient or persistent forms expressed using a Graph Data Model. A modern knowledgebase would more than likely have RDF as its Data Language, RDFS as its Schema Language, and OWL as its Domain  Definition (Ontology) Language. Actual Domain, Schema, and Instance Data would be serialized using formats such as RDF-XML, N3, Turtle etc).

How do Data Spaces and Databases differ?
Data Spaces are fundamentally problem-domain-specific database applications. They offer functionality that you would instinctively expect of a database (e.g. AICD data management) with the additonal benefit of being data model and query language agnostic. Data Spaces are for the most part DBMS Engine and Data Access Middleware hybrids in the sense that ownership and control of data is inherently loosely-coupled.

How do Data Spaces and Content Management Systems differ?
Data Spaces are inherently more flexible, they support multiple data models and data representation formats. Content management systems do not possess the same degree of data model and data representation dexterity.

How do Data Spaces and Knowledgebases differ?
A Data Space cannot dictate the perception of its content. For instance, what I may consider as knowledge relative to my Data Space may not be the case to a remote client that interacts with it from a distance, Thus, defining my Data Space as Knowledgebase, purely, introduces constraints that reduce its broader effectiveness to third party clients (applications, services, users etc..). A Knowledgebase is based on a Graph Data Model resulting in significant impedance for clients that are built around alternative models. To reiterate, Data Spaces support multiple data models.

What Architectural Components make up a Data Space?

• ORDBMS Engine - for Data Modeling agility (via complex purpose specific data types and data access methods), Data Atomicity, Data Concurrency, Transaction Isolation, and Durability (aka ACID).
  
  
• Virtual Database Engine - for creating a single view of, and access point to, heterogeneous SQL, XML, Free Text, and other data. This is all about Virtualization at the Data Access Level.

• Web Services Platform - enabling controlled access and manipulation (via application, service, or protocol logic) of Virtualized or Disparate Data. This layer handles the decoupling of functionality from monolithic wholes for function specific invocation via Web Services using either the SOAP or REST approach.

Where can I see a DataSpace along the lines described, in action?

Just look at my blog, and take the journey as follows:

• Front Door (Web 1.0)
• Lounge (Web 2.0) via GData or OpenSearch
• Floor Plan via FOAF or SIOC RDF Data Sets (Graphs)
• Rest of the house (beyond Web 2.0) sending  SPARQL Queries to a SPARQL Endpoint.
  

What about other Data Spaces?

There are several and I will attempt to categorize along the lines of query method available:
Type 1 (Free Text Search over HTTP):
Google, MSN, Yahoo!, Amazon, eBay, and most Web 2.0 plays .

Type 2 (Free Text Search and XQuery/XPath over HTTP)
A few blogs and Wikis (Jon Udell's and a few others)

•    SIOC enabled sites (aka points of semantic web presence)
  
•    PingTheSemantic
  

• My Blog Data Space (as stated earlier in this post)
  
• My General Data Space - (ditto; note that this is currently experimental)
  

What About Data Space aware tools?

•    OpenLink Ajax Toolkit - provides Javascript Control level binding to Query Services such as XMLA for SQL, GData for Free Text, OpenSearch for Free Text, SPARQL for RDF, in addition to service specific Web Services (Web 2.0 hosted solutions that expose service specific APIs)
•    Semantic Radar - a Firefox Extension
•    PingTheSemantic - the Semantic Webs equivalent of Web 2.0's weblogs.com
•    PiggyBank - a Firefox Extension

Note: An updated version of a previously unpublished blog post:

Continuing from our recent Podcast conversation, Jon Udell sheds further insight into the essence of our conversation via a “Strategic Developer” column article titled: Accessing the web of databases.

Below, I present an initial dump of a DataSpace FAQ below that hopefully sheds light on the DataSpace vision espoused during my podcast conversation with Jon.

What is a DataSpace?

A moniker for Web-accessible atomic containers that manage and expose Data, Information, Services, Processes, and Knowledge.

What would you typically find in a Data Space? Examples include:

• Raw Data - SQL, HTML, XML (raw), XHTML, RDF etc.
  
  
• Information (Data In Context) - XHTML (various microformats), Blog Posts (in RSS, Atom, RSS-RDF formats), Subscription Lists (OPML, OCS, etc), Social Networks (FOAF, XFN etc.), and many other forms of applied XML.

• Web Services (Application/Service Logic) - REST or SOAP based invocation of application logic for context sensitive and controlled data access and manipulation.

• Persisted Knowledge - Information in actionable context that is also available in transient or persistent forms expressed using a Graph Data Model. A modern knowledgebase would more than likely have RDF as its Data Language, RDFS as its Schema Language, and OWL as its Domain  Definition (Ontology) Language. Actual Domain, Schema, and Instance Data would be serialized using formats such as RDF-XML, N3, Turtle etc).

How do Data Spaces and Databases differ?
Data Spaces are fundamentally problem-domain-specific database applications. They offer functionality that you would instinctively expect of a database (e.g. AICD data management) with the additonal benefit of being data model and query language agnostic. Data Spaces are for the most part DBMS Engine and Data Access Middleware hybrids in the sense that ownership and control of data is inherently loosely-coupled.

How do Data Spaces and Content Management Systems differ?
Data Spaces are inherently more flexible, they support multiple data models and data representation formats. Content management systems do not possess the same degree of data model and data representation dexterity.

How do Data Spaces and Knowledgebases differ?
A Data Space cannot dictate the perception of its content. For instance, what I may consider as knowledge relative to my Data Space may not be the case to a remote client that interacts with it from a distance, Thus, defining my Data Space as Knowledgebase, purely, introduces constraints that reduce its broader effectiveness to third party clients (applications, services, users etc..). A Knowledgebase is based on a Graph Data Model resulting in significant impedance for clients that are built around alternative models. To reiterate, Data Spaces support multiple data models.

What Architectural Components make up a Data Space?

• ORDBMS Engine - for Data Modeling agility (via complex purpose specific data types and data access methods), Data Atomicity, Data Concurrency, Transaction Isolation, and Durability (aka ACID).
  
  
• Virtual Database Engine - for creating a single view of, and access point to, heterogeneous SQL, XML, Free Text, and other data. This is all about Virtualization at the Data Access Level.

• Web Services Platform - enabling controlled access and manipulation (via application, service, or protocol logic) of Virtualized or Disparate Data. This layer handles the decoupling of functionality from monolithic wholes for function specific invocation via Web Services using either the SOAP or REST approach.

Where can I see a DataSpace along the lines described, in action?

Just look at my blog, and take the journey as follows:

• Front Door (Web 1.0)
• Lounge (Web 2.0) via GData or OpenSearch
• Floor Plan via FOAF or SIOC RDF Data Sets (Graphs)
• Rest of the house (beyond Web 2.0) sending  SPARQL Queries to a SPARQL Endpoint.
  

What about other Data Spaces?

There are several and I will attempt to categorize along the lines of query method available:
Type 1 (Free Text Search over HTTP):
Google, MSN, Yahoo!, Amazon, eBay, and most Web 2.0 plays .

Type 2 (Free Text Search and XQuery/XPath over HTTP)
A few blogs and Wikis (Jon Udell's and a few others)

•    SIOC enabled sites (aka points of semantic web presence)
  
•    PingTheSemantic
  

• My Blog Data Space (as stated earlier in this post)
  
• My General Data Space - (ditto; note that this is currently experimental)
  

What About Data Space aware tools?

•    OpenLink Ajax Toolkit - provides Javascript Control level binding to Query Services such as XMLA for SQL, GData for Free Text, OpenSearch for Free Text, SPARQL for RDF, in addition to service specific Web Services (Web 2.0 hosted solutions that expose service specific APIs)
•    Semantic Radar - a Firefox Extension
•    PingTheSemantic - the Semantic Webs equivalent of Web 2.0's weblogs.com
•    PiggyBank - a Firefox Extension

Note: An updated version of a previously unpublished blog post:

Continuing from our recent Podcast conversation, Jon Udell sheds further insight into the essence of our conversation via a “Strategic Developer” column article titled: Accessing the web of databases.

Below, I present an initial dump of a DataSpace FAQ below that hopefully sheds light on the DataSpace vision espoused during my podcast conversation with Jon.

What is a DataSpace?

A moniker for Web-accessible atomic containers that manage and expose Data, Information, Services, Processes, and Knowledge.

What would you typically find in a Data Space? Examples include:

• Raw Data - SQL, HTML, XML (raw), XHTML, RDF etc.
  
  
• Information (Data In Context) - XHTML (various microformats), Blog Posts (in RSS, Atom, RSS-RDF formats), Subscription Lists (OPML, OCS, etc), Social Networks (FOAF, XFN etc.), and many other forms of applied XML.

• Web Services (Application/Service Logic) - REST or SOAP based invocation of application logic for context sensitive and controlled data access and manipulation.

• Persisted Knowledge - Information in actionable context that is also available in transient or persistent forms expressed using a Graph Data Model. A modern knowledgebase would more than likely have RDF as its Data Language, RDFS as its Schema Language, and OWL as its Domain  Definition (Ontology) Language. Actual Domain, Schema, and Instance Data would be serialized using formats such as RDF-XML, N3, Turtle etc).

How do Data Spaces and Databases differ?
Data Spaces are fundamentally problem-domain-specific database applications. They offer functionality that you would instinctively expect of a database (e.g. AICD data management) with the additonal benefit of being data model and query language agnostic. Data Spaces are for the most part DBMS Engine and Data Access Middleware hybrids in the sense that ownership and control of data is inherently loosely-coupled.

How do Data Spaces and Content Management Systems differ?
Data Spaces are inherently more flexible, they support multiple data models and data representation formats. Content management systems do not possess the same degree of data model and data representation dexterity.

How do Data Spaces and Knowledgebases differ?
A Data Space cannot dictate the perception of its content. For instance, what I may consider as knowledge relative to my Data Space may not be the case to a remote client that interacts with it from a distance, Thus, defining my Data Space as Knowledgebase, purely, introduces constraints that reduce its broader effectiveness to third party clients (applications, services, users etc..). A Knowledgebase is based on a Graph Data Model resulting in significant impedance for clients that are built around alternative models. To reiterate, Data Spaces support multiple data models.

What Architectural Components make up a Data Space?

• ORDBMS Engine - for Data Modeling agility (via complex purpose specific data types and data access methods), Data Atomicity, Data Concurrency, Transaction Isolation, and Durability (aka ACID).
  
  
• Virtual Database Engine - for creating a single view of, and access point to, heterogeneous SQL, XML, Free Text, and other data. This is all about Virtualization at the Data Access Level.

• Web Services Platform - enabling controlled access and manipulation (via application, service, or protocol logic) of Virtualized or Disparate Data. This layer handles the decoupling of functionality from monolithic wholes for function specific invocation via Web Services using either the SOAP or REST approach.

Where can I see a DataSpace along the lines described, in action?

Just look at my blog, and take the journey as follows:

• Front Door (Web 1.0)
• Lounge (Web 2.0) via GData or OpenSearch
• Floor Plan via FOAF or SIOC RDF Data Sets (Graphs)
• Rest of the house (beyond Web 2.0) sending  SPARQL Queries to a SPARQL Endpoint.
  

What about other Data Spaces?

There are several and I will attempt to categorize along the lines of query method available:
Type 1 (Free Text Search over HTTP):
Google, MSN, Yahoo!, Amazon, eBay, and most Web 2.0 plays .

Type 2 (Free Text Search and XQuery/XPath over HTTP)
A few blogs and Wikis (Jon Udell's and a few others)

•    SIOC enabled sites (aka points of semantic web presence)
  
•    PingTheSemantic
  

• My Blog Data Space (as stated earlier in this post)
  
• My General Data Space - (ditto; note that this is currently experimental)
  

What About Data Space aware tools?

•    OpenLink Ajax Toolkit - provides Javascript Control level binding to Query Services such as XMLA for SQL, GData for Free Text, OpenSearch for Free Text, SPARQL for RDF, in addition to service specific Web Services (Web 2.0 hosted solutions that expose service specific APIs)
•    Semantic Radar - a Firefox Extension
•    PingTheSemantic - the Semantic Webs equivalent of Web 2.0's weblogs.com
•    PiggyBank - a Firefox Extension

Finally! The real implications of "Data Ownership", "Data Access", "Data Storage", and Web 2.0 are gradually taking shape.

I don't want to repeat myself about Web 2.0 (definitions, Semantic Web nexus etc.. just search this Blog data space for past commentary. Neither, do I want to repeat my warnings about the timeless tendency to ignore the implications of "Application or Service Logic", "Data Access", and "Data Storage" separation ambivalence (Virtuoso's purpose and architecture embodies my vision re. this matter).

Note the reference to Gdrive in the article. Well, we have also built an Open Source and Standards based (Atom 1.0, OpenSearch, GData, SPARQL, RDF, WebDAV, SQL, etc..) equivalent of what is speculated re. GDrive called the OpenLink Briefcase (the item described as a "Virtual Spotlight" during my recent podcast interview with Jon Udell) which is one of several distributed collaborative applications that make up our"OpenLink Data Spaces (ODS)" product offering.

Anyway, enjoy the post below from Publishing 2.0:

Data Storage Is the Key to the Web App Revolution: "

The future of Web 2.0 and the web app revolution will hinge on one critical issue — where the data is stored. The advantages of hosted, instantly upgraded, never-have-to-install applications on the web are obvious and many — anyone who has ever struggled with software installation and upgrading knows this intuitively.

But there is a downside that is less obvious to the average person and that is starting to get increasing attention — most web apps, like Gmail and Flickr, require storing your data on somebody else’s servers. This is convenient and saves a lot local disk space, but it puts the security of your data beyond your control and, worse, it puts the ownership of your data potentially beyond your control.

Marshall Kirkpatrick Mike Arrington shined a spotlight on this issue with respect to photo storage — it turns out the while Flickr will let you share your photos with the world, it won’t let you share those photos with competing web photo apps like upstart Zooomr:

Tate from Zooomr says that the exports are a cost of doing business, that Web 2.0 is where ‘the roach motel stops’ and that Zooomr will always make it easy for their customers to take their data elsewhere. That’s easy to say when you’re the underdog, but the issue does lead to some questions about data portability and web services. Day one of the post-Gates era seems like a good time to consider such questions.

There’s also a NYT article on the web app revolution that raises data storage as one of the key barriers to adoption:

And you must be comfortable with the idea that your addresses, your correspondence and your documents don’t reside on your hard drive in your computer in your home. They are stored at sites controlled by a giant company.

And this is just the consumer side of the issue. Inside the enterprise, the issue becomes more acute — most companies are not going to want their critical data stored outside the corporate firewall — this is the biggest barrier to Google competing with Microsoft for control of business applications. And this is a potential advantage of Microsoft’s stated strategy of making its Live web apps an extension of existing client and server software — the data can still be stored where it has always been stored.

It strikes me that there is a huge opportunity here to create a single point of secure online storage that can be accessed from any web app. The open architecture principles of Web 2.0 (APIs, etc.) would seem to make this approach obvious.

Gdrive perhaps?

UPDATE

I corresponded with Nick Carr on this issue, and he makes some good points about data security:

Companies have long allowed payroll data (pretty sensitive stuff) to sit on service providers’ servers, and lots of them are doing the same with customer data (also extremely sensitive) through, eg, Salesforce.com. On the consumer side, given individuals’ cluelessness about security and even backups, it’s probably considerably safer for most people to stick their data on an outside company’s servers than to keep it on their own hard drives.

On the corporate side, the outsourcing of data storage depends to some degree on the future of data security legislation. On the consumer side, granted that most people would do better outsourcing the securing of their data, but perceived control, even at the expense of actual security, is also a powerful force.

Nick also comments, ‘I’m a big advocate of web apps, but that NYT piece today could have been written by Google’s PR department.’ Indeed.

Regarding my mis-attribution of the TechCrunch post to Mike Arrington instead of Marshall Kirkpatrick, it’s interesting how easy it was to make that mistake — that’s what happens when the brand becomes synonymous with a person.

Finally! The real implications of "Data Ownership", "Data Access", "Data Storage", and Web 2.0 are gradually taking shape.

I don't want to repeat myself about Web 2.0 (definitions, Semantic Web nexus etc.. just search this Blog data space for past commentary. Neither, do I want to repeat my warnings about the timeless tendency to ignore the implications of "Application or Service Logic", "Data Access", and "Data Storage" separation ambivalence (Virtuoso's purpose and architecture embodies my vision re. this matter).

Note the reference to Gdrive in the article. Well, we have also built an Open Source and Standards based (Atom 1.0, OpenSearch, GData, SPARQL, RDF, WebDAV, SQL, etc..) equivalent of what is speculated re. GDrive called the OpenLink Briefcase (the item described as a "Virtual Spotlight" during my recent podcast interview with Jon Udell) which is one of several distributed collaborative applications that make up our"OpenLink Data Spaces (ODS)" product offering.

Anyway, enjoy the post below from Publishing 2.0:

Data Storage Is the Key to the Web App Revolution: "

The future of Web 2.0 and the web app revolution will hinge on one critical issue — where the data is stored. The advantages of hosted, instantly upgraded, never-have-to-install applications on the web are obvious and many — anyone who has ever struggled with software installation and upgrading knows this intuitively.

But there is a downside that is less obvious to the average person and that is starting to get increasing attention — most web apps, like Gmail and Flickr, require storing your data on somebody else’s servers. This is convenient and saves a lot local disk space, but it puts the security of your data beyond your control and, worse, it puts the ownership of your data potentially beyond your control.

Marshall Kirkpatrick Mike Arrington shined a spotlight on this issue with respect to photo storage — it turns out the while Flickr will let you share your photos with the world, it won’t let you share those photos with competing web photo apps like upstart Zooomr:

Tate from Zooomr says that the exports are a cost of doing business, that Web 2.0 is where ‘the roach motel stops’ and that Zooomr will always make it easy for their customers to take their data elsewhere. That’s easy to say when you’re the underdog, but the issue does lead to some questions about data portability and web services. Day one of the post-Gates era seems like a good time to consider such questions.

There’s also a NYT article on the web app revolution that raises data storage as one of the key barriers to adoption:

And you must be comfortable with the idea that your addresses, your correspondence and your documents don’t reside on your hard drive in your computer in your home. They are stored at sites controlled by a giant company.

And this is just the consumer side of the issue. Inside the enterprise, the issue becomes more acute — most companies are not going to want their critical data stored outside the corporate firewall — this is the biggest barrier to Google competing with Microsoft for control of business applications. And this is a potential advantage of Microsoft’s stated strategy of making its Live web apps an extension of existing client and server software — the data can still be stored where it has always been stored.

It strikes me that there is a huge opportunity here to create a single point of secure online storage that can be accessed from any web app. The open architecture principles of Web 2.0 (APIs, etc.) would seem to make this approach obvious.

Gdrive perhaps?

UPDATE

I corresponded with Nick Carr on this issue, and he makes some good points about data security:

Companies have long allowed payroll data (pretty sensitive stuff) to sit on service providers’ servers, and lots of them are doing the same with customer data (also extremely sensitive) through, eg, Salesforce.com. On the consumer side, given individuals’ cluelessness about security and even backups, it’s probably considerably safer for most people to stick their data on an outside company’s servers than to keep it on their own hard drives.

On the corporate side, the outsourcing of data storage depends to some degree on the future of data security legislation. On the consumer side, granted that most people would do better outsourcing the securing of their data, but perceived control, even at the expense of actual security, is also a powerful force.

Nick also comments, ‘I’m a big advocate of web apps, but that NYT piece today could have been written by Google’s PR department.’ Indeed.

Regarding my mis-attribution of the TechCrunch post to Mike Arrington instead of Marshall Kirkpatrick, it’s interesting how easy it was to make that mistake — that’s what happens when the brand becomes synonymous with a person.

Finally! The real implications of "Data Ownership", "Data Access", "Data Storage", and Web 2.0 are gradually taking shape.

I don't want to repeat myself about Web 2.0 (definitions, Semantic Web nexus etc.. just search this Blog data space for past commentary. Neither, do I want to repeat my warnings about the timeless tendency to ignore the implications of "Application or Service Logic", "Data Access", and "Data Storage" separation ambivalence (Virtuoso's purpose and architecture embodies my vision re. this matter).

Note the reference to Gdrive in the article. Well, we have also built an Open Source and Standards based (Atom 1.0, OpenSearch, GData, SPARQL, RDF, WebDAV, SQL, etc..) equivalent of what is speculated re. GDrive called the OpenLink Briefcase (the item described as a "Virtual Spotlight" during my recent podcast interview with Jon Udell) which is one of several distributed collaborative applications that make up our"OpenLink Data Spaces (ODS)" product offering.

Anyway, enjoy the post below from Publishing 2.0:

Data Storage Is the Key to the Web App Revolution: "

The future of Web 2.0 and the web app revolution will hinge on one critical issue — where the data is stored. The advantages of hosted, instantly upgraded, never-have-to-install applications on the web are obvious and many — anyone who has ever struggled with software installation and upgrading knows this intuitively.

But there is a downside that is less obvious to the average person and that is starting to get increasing attention — most web apps, like Gmail and Flickr, require storing your data on somebody else’s servers. This is convenient and saves a lot local disk space, but it puts the security of your data beyond your control and, worse, it puts the ownership of your data potentially beyond your control.

Marshall Kirkpatrick Mike Arrington shined a spotlight on this issue with respect to photo storage — it turns out the while Flickr will let you share your photos with the world, it won’t let you share those photos with competing web photo apps like upstart Zooomr:

Tate from Zooomr says that the exports are a cost of doing business, that Web 2.0 is where ‘the roach motel stops’ and that Zooomr will always make it easy for their customers to take their data elsewhere. That’s easy to say when you’re the underdog, but the issue does lead to some questions about data portability and web services. Day one of the post-Gates era seems like a good time to consider such questions.

There’s also a NYT article on the web app revolution that raises data storage as one of the key barriers to adoption:

And you must be comfortable with the idea that your addresses, your correspondence and your documents don’t reside on your hard drive in your computer in your home. They are stored at sites controlled by a giant company.

And this is just the consumer side of the issue. Inside the enterprise, the issue becomes more acute — most companies are not going to want their critical data stored outside the corporate firewall — this is the biggest barrier to Google competing with Microsoft for control of business applications. And this is a potential advantage of Microsoft’s stated strategy of making its Live web apps an extension of existing client and server software — the data can still be stored where it has always been stored.

It strikes me that there is a huge opportunity here to create a single point of secure online storage that can be accessed from any web app. The open architecture principles of Web 2.0 (APIs, etc.) would seem to make this approach obvious.

Gdrive perhaps?

UPDATE

I corresponded with Nick Carr on this issue, and he makes some good points about data security:

Companies have long allowed payroll data (pretty sensitive stuff) to sit on service providers’ servers, and lots of them are doing the same with customer data (also extremely sensitive) through, eg, Salesforce.com. On the consumer side, given individuals’ cluelessness about security and even backups, it’s probably considerably safer for most people to stick their data on an outside company’s servers than to keep it on their own hard drives.

On the corporate side, the outsourcing of data storage depends to some degree on the future of data security legislation. On the consumer side, granted that most people would do better outsourcing the securing of their data, but perceived control, even at the expense of actual security, is also a powerful force.

Nick also comments, ‘I’m a big advocate of web apps, but that NYT piece today could have been written by Google’s PR department.’ Indeed.

Regarding my mis-attribution of the TechCrunch post to Mike Arrington instead of Marshall Kirkpatrick, it’s interesting how easy it was to make that mistake — that’s what happens when the brand becomes synonymous with a person.

"We all know that structured data is boring and useless; while unstructured data is sexy and chock full of value. Well, only up to a point, Lord Copper. Genuinely unstructured data can be a real nuisance - imagine extracting the return address from an unstructured letter, without letterhead and any of the formatting usually applied to letters. A letter may be thought of as unstructured data, but most business letters are, in fact, highly-structured." ....

"The labels "structured data" and "unstructured data" are often used ambiguously by different interest groups; and often used lazily to cover multiple distinct aspects of the issue. In reality, there are at least three orthogonal aspects to structure:

* The structure of the data itself.

* The structure of the container that hosts the data.

* The structure of the access method used to access the data.

These three dimensions are largely independent and one does not need to imply another. For example, it is absolutely feasible and reasonable to store unstructured data in a structured database container and access it by unstructured search mechanisms."

Data understanding and appreciation is dwindling at a time when the reverse should be happening. We are supposed to be in the throws of the "Information Age", but for some reason this appears to have no correlation with data and "data access" in the minds of many -- as reflected in the broad contradictory positions taken re. unstructured data vs structured data, structured is boring and useless while unstructured is useful and sexy....

The difference between "Structured Containers" and "Structured Data" are clearly misunderstood by most (an unfortunate fact).

For instance all DBMS products are "Structured Containers" aligned to one or more data models (typically one). These products have been limited by proprietary data access APIs and underlying data model specificity when used in the "Open-world" model that is at the core of the World Wide Web. This confusion also carries over to the misconception that Web 2.0 and the Semantic/Data Web are mutually exclusive.

But things are changing fast, and the concept of multi-model DBMS products is beginning to crystalize. On our part, we have finally released the long promised "OpenLink Data Spaces" application layer that has been developed using our Virtuoso Universal Server. We have structured unified storage containment exposed to the data web cloud via endpoints for querying or accessing data using a variety of mechanisms that include; GData, OpenSearch, SPARQL, XQuery/XPath, SQL etc..

To be continued....

"We all know that structured data is boring and useless; while unstructured data is sexy and chock full of value. Well, only up to a point, Lord Copper. Genuinely unstructured data can be a real nuisance - imagine extracting the return address from an unstructured letter, without letterhead and any of the formatting usually applied to letters. A letter may be thought of as unstructured data, but most business letters are, in fact, highly-structured." ....

"The labels "structured data" and "unstructured data" are often used ambiguously by different interest groups; and often used lazily to cover multiple distinct aspects of the issue. In reality, there are at least three orthogonal aspects to structure:

* The structure of the data itself.

* The structure of the container that hosts the data.

* The structure of the access method used to access the data.

These three dimensions are largely independent and one does not need to imply another. For example, it is absolutely feasible and reasonable to store unstructured data in a structured database container and access it by unstructured search mechanisms."

Data understanding and appreciation is dwindling at a time when the reverse should be happening. We are supposed to be in the throws of the "Information Age", but for some reason this appears to have no correlation with data and "data access" in the minds of many -- as reflected in the broad contradictory positions taken re. unstructured data vs structured data, structured is boring and useless while unstructured is useful and sexy....

The difference between "Structured Containers" and "Structured Data" are clearly misunderstood by most (an unfortunate fact).

For instance all DBMS products are "Structured Containers" aligned to one or more data models (typically one). These products have been limited by proprietary data access APIs and underlying data model specificity when used in the "Open-world" model that is at the core of the World Wide Web. This confusion also carries over to the misconception that Web 2.0 and the Semantic/Data Web are mutually exclusive.

But things are changing fast, and the concept of multi-model DBMS products is beginning to crystalize. On our part, we have finally released the long promised "OpenLink Data Spaces" application layer that has been developed using our Virtuoso Universal Server. We have structured unified storage containment exposed to the data web cloud via endpoints for querying or accessing data using a variety of mechanisms that include; GData, OpenSearch, SPARQL, XQuery/XPath, SQL etc..

To be continued....

"We all know that structured data is boring and useless; while unstructured data is sexy and chock full of value. Well, only up to a point, Lord Copper. Genuinely unstructured data can be a real nuisance - imagine extracting the return address from an unstructured letter, without letterhead and any of the formatting usually applied to letters. A letter may be thought of as unstructured data, but most business letters are, in fact, highly-structured." ....

"The labels "structured data" and "unstructured data" are often used ambiguously by different interest groups; and often used lazily to cover multiple distinct aspects of the issue. In reality, there are at least three orthogonal aspects to structure:

* The structure of the data itself.

* The structure of the container that hosts the data.

* The structure of the access method used to access the data.

These three dimensions are largely independent and one does not need to imply another. For example, it is absolutely feasible and reasonable to store unstructured data in a structured database container and access it by unstructured search mechanisms."

Data understanding and appreciation is dwindling at a time when the reverse should be happening. We are supposed to be in the throws of the "Information Age", but for some reason this appears to have no correlation with data and "data access" in the minds of many -- as reflected in the broad contradictory positions taken re. unstructured data vs structured data, structured is boring and useless while unstructured is useful and sexy....

The difference between "Structured Containers" and "Structured Data" are clearly misunderstood by most (an unfortunate fact).

For instance all DBMS products are "Structured Containers" aligned to one or more data models (typically one). These products have been limited by proprietary data access APIs and underlying data model specificity when used in the "Open-world" model that is at the core of the World Wide Web. This confusion also carries over to the misconception that Web 2.0 and the Semantic/Data Web are mutually exclusive.

But things are changing fast, and the concept of multi-model DBMS products is beginning to crystalize. On our part, we have finally released the long promised "OpenLink Data Spaces" application layer that has been developed using our Virtuoso Universal Server. We have structured unified storage containment exposed to the data web cloud via endpoints for querying or accessing data using a variety of mechanisms that include; GData, OpenSearch, SPARQL, XQuery/XPath, SQL etc..

To be continued....

Last week I put out a series of screencast style demos that sought to demonstrate the core elements of our soon to be released Javascript Toolkit called OAT (OpenLink Ajax Toolkit) and its Ajax Database Connectivity layer.

The screencasts covered the following functionality realms:

1. SQL Query By Example (basic)
2. SQL Query By Example (advanced - pivot table construction)
3. Web Form Design (basic database driven map based mashup)
4. Web Form Design (advanced database driven map based mashup)

To bring additional clarity to the screencasts demos and OAT in general, I have saved a number of documents that are the by products of activities in the screenvcasts:

1. Live XML Document produced using SQL Query By Example (basic) (you can use drag and drop columns across the grid to reorder and sort presentation)
2. Live XML Document produced using QBE and Pivot Functionality (you can drag and drop the aggregate columns and rows to create your own views etc..)
3. Basic database driven map based mashup (works with FireFox, Webkit, Camino; click on pins to see national flag)
4. Advanced database driven map based mashup (works with FireFox, Webkit, Camino; records, 36, 87, and 257 will unveil pivots via lookup pin)

Notes:

• “Advanced”, as used above, simply means that I am embedding images (employee photos and national flags) and a database driven pivot into the map pins that serve as details lookups in classic SQL master/details type scenarios.
• The “Ajax Call In Progress..” dialog is there to show live interaction with a remote database (in this case Virtuoso but this could be any ODBC, JDBC, OLEDB, ADO.NET, or XMLA accessible data source)
• The data access magic source (if you want to call it that) is XMLA - a standard that has been in place for years but completely misunderstood and as a result under utilized

You can see a full collection of saved documents at the following locations:

• My Mashups demo directory (Google and Yahoo! demo variants but note these do not work with Safari or IE at the current time. IE7 issues will be resolved in the next day or so)
• My Pivots demo directory (other Pivots will be added as I build and save them)
• My Saved Queries (a collection of saved QBE generated queries)