Kingsley Idehen's Blog Data Space

Virtuoso Linked Data Deployment 3-Step

Fri, 29 Oct 2010 22:54:32 GMT

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:

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

The problems typically take the following form:

Functionality confusion about the complementary Name and Address functionality of a single URI abstraction
Terminology confusion due to conflation and over-loading of terms such as Resource, URL, Representation, Document, etc.
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:

Faceted Browser Engine UI
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 --

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.
Follow the links presented in the descriptor page.
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.
Use the navigator controls to page up and down the data associated with the "in scope" resource descriptor.

Sample Descriptor Page (what you see post completion of the steps in this post)
What is Linked Data, really?
Painless Linked Data Generation via URIBurner
How To Load RDF Data Into Virtuoso (various methods)
Virtuoso Bulk Loader Script for RDF
Bulk Loader Script for CSV
Wizard based generation of RDF based Linked Data from ODBC accessible Relational Databases

Virtuoso Linked Data Deployment In 3 Simple Steps

Fri, 29 Oct 2010 22:54:32 GMT

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:

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

The problems typically take the following form:

Functionality confusion about the complementary Name and Address functionality of a single URI abstraction
Terminology confusion due to conflation and over-loading of terms such as Resource, URL, Representation, Document, etc.
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:

Faceted Browser Engine UI
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 --

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.
Follow the links presented in the descriptor page.
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.
Use the navigator controls to page up and down the data associated with the "in scope" resource descriptor.

Sample Descriptor Page (what you see post completion of the steps in this post)
What is Linked Data, really?
Painless Linked Data Generation via URIBurner
How To Load RDF Data Into Virtuoso (various methods)
Virtuoso Bulk Loader Script for RDF
Bulk Loader Script for CSV
Wizard based generation of RDF based Linked Data from ODBC accessible Relational Databases

Re-introducing the Virtuoso Virtual Database Engine

Wed, 17 Feb 2010 21:38:01 GMT

In recent times a lot of the commentary and focus re. Virtuoso has centered on the RDF Quad Store and Linked Data. What sometimes gets overlooked is the sophisticated Virtual Database Engine that provides the foundation for all of Virtuoso's data integration capabilities.

In this post I provide a brief re-introduction to this essential aspect of Virtuoso.

What is it?

This component of Virtuoso is known as the Virtual Database Engine (VDBMS). It provides transparent high-performance and secure access to disparate data sources that are external to Virtuoso. It enables federated access and integration of data hosted by any ODBC- or JDBC-accessible RDBMS, RDF Store, XML database, or Document (Free Text)-oriented Content Management System. In addition, it facilitates integration with Web Services (SOAP-based SOA RPCs or REST-fully accessible Web Resources).

Why is it important?

In the most basic sense, you shouldn't need to upgrade your existing database engine version simply because your current DBMS and Data Access Driver combo isn't compatible with ODBC-compliant desktop tools such as Microsoft Access, Crystal Reports, BusinessObjects, Impromptu, or other of ODBC, JDBC, ADO.NET, or OLE DB-compliant applications. Simply place Virtuoso in front of your so-called "legacy database," and let it deliver the compliance levels sought by these tools

In addition, it's important to note that today's enterprise, through application evolution, company mergers, or acquisitions, is often faced with disparately-structured data residing in any number of line-of-business-oriented data silos. Compounding the problem is the exponential growth of user-generated data via new social media-oriented collaboration tools and platforms. For companies to cost-effectively harness the opportunities accorded by the increasing intersection between line-of-business applications and social media, virtualization of data silos must be achieved, and this virtualization must be delivered in a manner that doesn't prohibitively compromise performance or completely undermine security at either the enterprise or personal level. Again, this is what you get by simply installing Virtuoso.

How do I use it?

The VDBMS may be used in a variety of ways, depending on the data access and integration task at hand. Examples include:

Relational Database Federation

You can make a single ODBC, JDBC, ADO.NET, OLE DB, or XMLA connection to multiple ODBC- or JDBC-accessible RDBMS data sources, concurrently, with the ability to perform intelligent distributed joins against externally-hosted database tables. For instance, you can join internal human resources data against internal sales and external stock market data, even when the HR team uses Oracle, the Sales team uses Informix, and the Stock Market figures come from Ingres!

Conceptual Level Data Access using the RDF Model

You can construct RDF Model-based Conceptual Views atop Relational Data Sources. This is about generating HTTP-based Entity-Attribute-Value (E-A-V) graphs using data culled "on the fly" from native or external data sources (Relational Tables/Views, XML-based Web Services, or User Defined Types).

You can also derive RDF Model-based Conceptual Views from Web Resource transformations "on the fly" -- the Virtuoso Sponger (RDFizing middleware component) enables you to generate RDF Model Linked Data via a RESTful Web Service or within the process pipeline of the SPARQL query engine (i.e., you simply use the URL of a Web Resource in the FROM clause of a SPARQL query).

It's important to note that Views take the form of HTTP links that serve as both Data Source Names and Data Source Addresses. This enables you to query and explore relationships across entities (i.e., People, Places, and other Real World Things) via HTTP clients (e.g., Web Browsers) or directly via SPARQL Query Language constructs transmitted over HTTP.

Conceptual Level Data Access using ADO.NET Entity Frameworks

As an alternative to RDF, Virtuoso can expose ADO.NET Entity Frameworks-based Conceptual Views over Relational Data Sources. It achieves this by generating Entity Relationship graphs via its native ADO.NET Provider, exposing all externally attached ODBC- and JDBC-accessible data sources. In addition, the ADO.NET Provider supports direct access to Virtuoso's native RDF database engine, eliminating the need for resource intensive Entity Frameworks model transformations.

Getting The Linked Data Value Pyramid Layers Right (Update #2)

Sun, 31 Jan 2010 22:46:47 GMT

One of the real problems that pervades all routes to Linked Data value prop. incomprehension stems from the layering of its value pyramid; especially when communicating with -initially detached- end-users.

Note to Web Programmers: Linked Data is about Data (Wine) and not about Code (Fish). Thus, it isn't a "programmer only zone", far from it. More than anything else, its inherently inclusive and spreads its participation net widely across: Data Architects, Data Integrators, Power Users, Knowledge Workers, Information Workers, Data Analysts, etc.. Basically, everyone that can "click on a link" is invited to this particular party; remember, it is about "Linked Data" not "Linked Code", after all. :-)

Problematic Value Pyramid Layering

Here is an example of a Linked Data value pyramid that I am stumbling across --with some frequency-- these days (note: 1 being the pyramid apex):

SPARQL Queries
RDF Data Stores
RDF Data Sets
HTTP scheme URIs

Basically, Linked Data deployment (assigning de-referencable HTTP URIs to DBMS records, their attributes, and attribute values [optionally] ) is occurring last. Even worse, this happens in the context of Linked Open Data oriented endeavors, resulting in nothing but confusion or inadvertent perpetuation of the overarching pragmatically challenged "Semantic Web" stereotype.

As you can imagine, hitting SPARQL as your introduction to Linked Data is akin to hitting SQL as your introduction to Relational Database Technology, neither is an elevator-style value prop. relay mechanism.

In the relational realm, killer demos always started with desktop productivity tools (spreadsheets, report-writers, SQL QBE tools etc.) accessing, relational data sources en route to unveiling the "Productivity" and "Agility" value prop. that such binding delivered i.e., the desktop application (clients) and the databases (servers) are distinct, but operating in a mutually beneficial manner to all, courtesy of a data access standards such as ODBC (Open Database Connectivity).

In the Linked Data realm, learning to embrace and extend best practices from the relational dbms realm remains a challenge, a lot of this has to do with hangovers from a misguided perception that RDF databases will somehow completely replace RDBMS engines, rather than compliment them. Thus, you have a counter productive variant of NIH (Not Invented Here) in play, taking us to the dreaded realm of: Break the Pot and You Own It (exemplified by the 11+ year Semantic Web Project comprehension and appreciation odyssey).

From my vantage point, here is how I believe the Linked Data value pyramid should be layered, especially when communicating the essential value prop.:

HTTP URLs -- LINKs to documents (Reports) that users already appreciate, across the public Web and/or Intranets
HTTP URIs -- typically not visually distinguishable from the URLs, so use the Data exposed by de-referencing a URL to show how each Data Item (Entity or Object) is uniquely identified by a Generic HTTP URI, and how clicking on the said URIs leads to more structured metadata bearing documents available in a variety of data representation formats, thereby enabling flexible data presentation (e.g., smarter HTML pages)
SPARQL -- when a user appreciates the data representation and presentation dexterity of a Generic HTTP URI, they will be more inclined to drill down an additional layer to unravel how HTTP URIs mechanically deliver such flexibility
RDF Data Stores -- at this stage the user is now interested data sources behind the Generic HTTP URIs, courtesy of natural desire to tweak the data presented in the report; thus, you now have an engaged user ready to absorb the "How Generic HTTP URIs Pull This Off" message
RDF Data Sets -- while attempting to make or tweak HTTP URIs, users become curious about the actual data loaded into the RDF Data Store, which is where data sets used to create powerful Lookup Data Spaces (e.g., DBpedia) come into play such as those from the LOD constellation as exemplified by DBpedia (extractions from Wikipedia).

Getting The Linked Data Value Pyramid Layers Right (Update #2)

Sun, 31 Jan 2010 22:44:04 GMT

Problematic Value Pyramid Layering

Here is an example of a Linked Data value pyramid that I am stumbling across --with some frequency-- these days (note: 1 being the pyramid apex):

SPARQL Queries
RDF Data Stores
RDF Data Sets
HTTP scheme URIs

From my vantage point, here is how I believe the Linked Data value pyramid should be layered, especially when communicating the essential value prop.:

HTTP URLs -- LINKs to documents (Reports) that users already appreciate, across the public Web and/or Intranets
HTTP URIs -- typically not visually distinguishable from the URLs, so use the Data exposed by de-referencing a URL to show how each Data Item (Entity or Object) is uniquely identified by a Generic HTTP URI, and how clicking on the said URIs leads to more structured metadata bearing documents available in a variety of data representation formats, thereby enabling flexible data presentation (e.g., smarter HTML pages)
SPARQL -- when a user appreciates the data representation and presentation dexterity of a Generic HTTP URI, they will be more inclined to drill down an additional layer to unravel how HTTP URIs mechanically deliver such flexibility
RDF Data Stores -- at this stage the user is now interested data sources behind the Generic HTTP URIs, courtesy of natural desire to tweak the data presented in the report; thus, you now have an engaged user ready to absorb the "How Generic HTTP URIs Pull This Off" message
RDF Data Sets -- while attempting to make or tweak HTTP URIs, users become curious about the actual data loaded into the RDF Data Store, which is where data sets used to create powerful Lookup Data Spaces (e.g., DBpedia) come into play such as those from the LOD constellation as exemplified by DBpedia (extractions from Wikipedia).

5 Very Important Things to Note about HTTP based Linked Data

Sun, 31 Jan 2010 22:31:35 GMT

It isn't World Wide Web Specific (HTTP != World Wide Web)
It isn't Open Data Specific
It isn't about "Free" (Beer or Speech)
It isn't about Markup (so don't expect to grok it via "markup first" approach)
It's about Hyperdata - the use of HTTP and REST to deliver a powerful platform agnostic mechanism for Data Reference, Access, and Integration.

When trying to understand HTTP based Linked Data, especially if you're well versed in DBMS technology use (User, Power User, Architect, Analyst, DBA, or Programmer) think:

Open Database Connectivity (ODBC) without operating system, data model, or wire-protocol specificity or lock-in potential
Java Database Connectivity (JDBC) without programming language specificity
ADO.NET without .NET runtime specificity and .NET bound language specificity
OLE-DB without Windows operating system & programming language specificity
XMLA without XML format specificity - with Tabular and Multidimensional results formats expressible in a variety of data representation formats.
All of the above scoped to the Record rather than Container level, with Generic HTTP scheme URIs associated with each Record, Field, and Field value (optionally)

Remember the need for Data Access & Integration technology is the by product of the following realities:

Human curated data is ultimately dirty, because:
- our thick thumbs, inattention, distractions, and general discomfort with typing, make typos prevalent
- database engines exist for a variety of data models - Graph, Relational, Hierarchical;
- within databases you have different record container/partition names e.g. Table Names;
- within a database record container you have records that are really aspects of the same thing (different keys exist in a plethora of operational / line of business systems that expose aspects of the same entity e.g., customer data that spans Accounts, CRM, ERP application databases);
- different field names (one database has "EMP" while another has "Employee") for the same record
Units of measurement is driven by locale, the UK office wants to see sales in Pounds Sterling while the French office prefers Euros etc.
All of the above is subject to context halos which can be quite granular re. sensitivity e.g. staff travel between locations that alter locales and their roles; basically, profiles matters a lot.

Virtuoso Chronicles from the Field: Nepomuk, KDE, and the quest for a sophisticated RDF DBMS.

Thu, 28 Jan 2010 16:14:04 GMT

For this particular user experience chronicle, I've simply inserted the content of Sebastian Trueg's post titled: What We Did Last Summer (And the Rest of 2009) – A Look Back Onto the Nepomuk Development Year ..., directly into this post, without any additional commentary or modification.

2009 is over. Yeah, sure, trueg, we know that, it has been over for a while now! Ok, ok, I am a bit late, but still I would like to get this one out - if only for my archive. So here goes.

Virtuoso

Let’s start with the major topic of 2009 (and also the beginning of 2010): The new Nepomuk database backend: Virtuoso. Everybody who used Nepomuk had the same problems: you either used the sesame2 backend which depends on Java and steals all of your memory or you were stuck with Redland which had the worst performance and missed some SPARQL features making important parts of Nepomuk like queries unusable. So more than a year ago I had the idea to use the one GPL’ed database server out there that supported RDF in a professional manner: OpenLink’s Virtuoso. It has all the features we need, has a very good performance, and scales up to dimensions we will probably never reach on the desktop (yeah, right, and 64k main memory will be enough forever!). So very early I started coding the necessary Soprano plugin which would talk to a locally running Virtuoso server through ODBC. But since I ran into tons of small problems (as always) and got sidetracked by other tasks I did not finish it right away. OpenLink, however, was very interested in the idea of their server being part of every KDE installation (why wouldn’t they ;)). So they not only introduced a lite-mode which makes Virtuoso suitable for the desktop but also helped in debugging all the problems that I had left. Many test runs, patches, and a Virtuoso 5.0.12 release later I could finally announce the Virtuoso integration as usable.

Then end of last year I dropped the support for sesame2 and redland. Virtuoso is now the only supported database backend. The reason is simple: Virtuoso is way more powerful than the rest - not only in terms of performance - and it is fully implemented in C(++) without any traces of Java. Maybe even more important is the integration of the full text index which makes the previously used CLucene index unnecessary. Thus, we can finally combine full text and graph queries in one SPARQL query. This results in a cleaner API and way faster return of search results since there is no need to combine the results from several queries anymore. A direct result of that is the new Nepomuk Query API which I will discuss later.

So now the only thing I am waiting for is the first bugfix release of Virtuoso 6, i.e. 6.0.1 which will fix the bugs that make 6.0.0 fail with Nepomuk. Should be out any day now. :)

The Nepomuk Query API

Querying data in Nepomuk pre-KDE-4.4 could be done in one of two ways: 1. Use the very limited capabilities of the ResourceManager to list resources with certain properties or of a certain type; or 2. Write your own SPARQL query using ugly QString::arg replacements.

With the introduction of Virtuoso and its awesome power we can now do pretty much everything in one query. This allowed me to finally create a query API for KDE: Nepomuk::Query::Query and friends. I won’t go into much detail here since I did that before.

All in all you should remember one thing: whenever you think about writing your own SPARQL query in a KDE application - have a look at libnepomukquery. It is very likely that you can avoid the hassle of debugging a query by using the query API.

The first nice effect of the new API (apart from me using it all over the place obviously) is the new query interface in Dolphin. Internally it simply combines a bunch of Nepomuk::Query::Term objects into a Nepomuk::Query::AndTerm. All very readable and no ugly query strings.

Dolphin Search Panel in KDE SC 4.4

Shared Desktop Ontologies

An important part of the Nepomuk research project was the creation of a set of ontologies for describing desktop resources and their metadata. After the Xesam project under the umbrella of freedesktop.org had been convinced to use RDF for describing file metadata they developed their own ontology. Thanks to Evgeny (phreedom) Egorochkin and Antonie Mylka both the Xesam ontology and the Nepomuk Information Elements Ontology were already very close in design. Thus, it was relatively easy to merge the two and be left with only one ontology to support. Since then not only KDE but also Strigi and Tracker are using the Nepomuk ontologies.

At the Gran Canaria Desktop Summit I met some of the guys from Tracker and we tried to come up with a plan to create a joint project to maintain the ontologies. This got off to a rough start as nobody really felt responsible. So I simply took the initiative and released the shared-desktop-ontologies version 0.1 in November 2009. The result was a s***-load of hate-mails and bug reports due to me breaking KDE build. But in the end it was worth it. Now the package is established and other projects can start to pick it up to create data compatible to the Nepomuk system and Tracker.

Today the ontologies (and the shared-desktop-ontologies package) are maintained in the Oscaf project at Sourceforge. The situation is far from perfect but it is a good start. If you need specific properties in the ontologies or are thinking about creating one for your own application - come and join us in the bug tracker…

Timeline KIO Slave

It was at the Akonadi meeting that Will Stephenson and myself got into talking about mimicking some Zeitgeist functionality through Nepomuk. Basically it meant gathering some data when opening and when saving files. We quickly came up with a hacky patch for KIO and KFileDialog which covered most cases and allowed us to track when a file was modified and by which application. This little experiment did not leave that state though (it will, however, this year) but another one did: Zeitgeist also provides a fuse filesystem which allows to browse the files by modification dates. Well, whatever fuse can do, KIO can do as well. Introducing the timeline:/ KIO slave which gives a calendar view onto your files.

Tips And Tricks

Well, I thought I would mention the Tips And Tricks section I wrote for the techbase. It might not be a big deal but I think it contains some valuable information in case you are using Nepomuk as a developer.

Google Summer Of Code 2009

This time around I had the privilege to mentor two students in the Google Summer of Code. Alessandro Sivieri and Adam Kidder did outstanding work on Improved Virtual Folders and the Smart File Dialog.

Adam’s work lead me to some heavy improvements in the Nepomuk KIO slaves myself which I only finished this week (more details on that coming up). Alessandro continued his work on faceted file browsing in KDE and created:

Sembrowser

Alessandro is following up on his work to make faceted file browsing a reality in 2010 (and KDE SC 4.5). Since it was too late to get faceted browsing into KDE SC 4.4 he is working on Sembrowser, a stand-alone faceted file browser which will be the grounds for experiments until the code is merged into Dolphin.

Faceted Browsing in KDE with Sembrowser

Nepomuk Workshops

In 2009 I organized the first Nepomuk workshop in Freiburg, Germany. And also the second one. While I reported properly on the first one I still owe a summary for the second one. I will get around to that - sooner or later. ;)

CMake Magic

Soprano gives us a nice command line tool to create a C++ namespace from an ontology file: onto2vocabularyclass. It produces nice convenience namespaces like Soprano::Vocabulary::NAO. Nepomuk adds another tool named nepomuk-rcgen. Both were a bit clumsy to use before. Now we have nice cmake macros which make it very simple to use both.

See the techbase article on how to use the new macros.

Bangarang

Without my knowledge (imagine that!) Andrew Lake created an amazing new media player named Bangarang - a Jamaican word for noise, chaos or disorder. This player is Nepomuk-enabled in the sense that it has a media library which lets you browse your media files based on the Nepomuk data. It remembers the number of times a song or a video has been played and when it was played last. It allows to add detail such as the TV series name, season, episode number, or actors that are in the video - all through Nepomuk (I hope we will soon get tvdb integration).

Edit metadata directly in Bangarang

Dolphin showing TV episode metadata created by Bangarang

And of course searching for it works, too...

And it is pretty, too...

I am especially excited about this since finally applications not written or mentored by me start contributing Nepomuk data.

Gran Canaria Desktop Summit

2009 was also the year of the first Gnome-KDE joint-conference. Let me make a bulletin for completeness and refer to my previous blog post reporting on my experiences on the island.

Well, that was by far not all I did in 2009 but I think I covered most of the important topics. And after all it is ‘just a blog entry’ - there is no need for completeness. Thanks for reading.

BBC Linked Data Meshup In 3 Steps

Fri, 12 Jun 2009 18:09:08 GMT

Situation Analysis:

Dr. Dre is one of the artists in the Linked Data Space we host for the BBC. He is also referenced in music oriented data spaces such as DBpedia, MusicBrainz and Last.FM (to name a few).

Challenge:

How do I obtain a holistic view of the entity "Dr. Dre" across the BBC, MusicBrainz, and Last.FM data spaces? We know the BBC published Linked Data, but what about Last.FM and MusicBrainz? Both of these data spaces only expose XML or JSON data via REST APIs?

Solution:

Simple 3 step Linked Data Meshup courtesy of Virtuoso's in-built RDFizer Middleware "the Sponger" (think ODBC Driver Manager for the Linked Data Web) and its numerous Cartridges (think ODBC Drivers for the Linked Data Web).

Steps:

Go to Last.FM and search using pattern: Dr. Dre (you will end up with this URL: http://www.last.fm/music/Dr.+Dre)
Go to the Virtuoso powered BBC Linked Data Space home page and enter: http://bbc.openlinksw.com/about/html/http://www.last.fm/music/Dr.+Dre
Go to the BBC Linked Data Space home page and type full text pattern (using default tab): Dr. Dre, then view Dr. Dre's metadata via the Statistics Link.

What Happened?

The following took place:

Virtuoso Sponger sent an HTTP GET to Last.FM
Distilled the "Artist" entity "Dr. Dre" from the page, and made a Linked Data graph
Inverse Functional Property and sameAs reasoning handled the Meshup (augmented graph from a conjunctive query processing pipeline)
Links for "Dr. Dre" across BBC (sameAs), Last.FM (seeAlso), via DBpedia URI.

The new enhanced URI for Dr. Dre now provides a rich holistic view of the aforementioned "Artist" entity. This URI is usable anywhere on the Web for Linked Data Conduction :-)

Related (as in NearBy)

Augmenting Last.fm Data with BBC data on the Talis Platform

Time for RDBMS Primacy Downgrade is Nigh! (No Embedded Images Edition - Update 1)

Tue, 27 Jan 2009 19:19:44 GMT

As the world works it way through a "once in a generation" economic crisis, the long overdue downgrade of the RDBMS, from its pivotal position at the apex of the data access and data management pyramid is nigh.

What is the Data Access, and Data Management Value Pyramid?

As depicted below, a top-down view of the data access and data management value chain. The term: apex, simply indicates value primacy, which takes the form of a data access API based entry point into a DBMS realm -- aligned to an underlying data model. Examples of data access APIs include: Native Call Level Interfaces (CLIs), ODBC, JDBC, ADO.NET, OLE-DB, XMLA, and Web Services.

See: AVF Pyramid Diagram.

The degree to which ad-hoc views of data managed by a DBMS can be produced and dispatched to relevant data consumers (e.g. people), without compromising concurrency, data durability, and security, collectively determine the "Agility Value Factor" (AVF) of a given DBMS. Remember, agility as the cornerstone of environmental adaptation is as old as the concept of evolution, and intrinsic to all pursuits of primacy.

In simpler business oriented terms, look at AVF as the degree to which DBMS technology affects the ability to effectively implement "Market Leadership Discipline" along the following pathways: innovation, operation excellence, or customer intimacy.

Why has RDBMS Primacy has Endured?

Historically, at least since the late '80s, the RDBMS genre of DBMS has consistently offered the highest AVF relative to other DBMS genres en route to primacy within the value pyramid. The desire to improve on paper reports and spreadsheets is basically what DBMS technology has fundamentally addressed to date, even though conceptual level interaction with data has never been its forte.

See: RDBMS Primacy Diagram.

For more then 10 years -- at the very least -- limitations of the traditional RDBMS in the realm of conceptual level interaction with data across diverse data sources and schemas (enterprise, Web, and Internet) has been crystal clear to many RDBMS technology practitioners, as indicated by some of the quotes excerpted below:

"Future of Database Research is excellent, but what is the future of data?"
"..it is hard for me to disagree with the conclusions in this report. It captures exactly the right thoughts, and should be a must read for everyone involved in the area of databases and database research in particular."
-- Dr. Anant Jingran, CTO, IBM Information Management Systems, commenting on the 2007 RDBMS technology retreat attended by a number of key DBMS technology pioneers and researchers.

"One size fits all: A concept whose time has come and gone

They are direct descendants of System R and Ingres and were architected more than 25 years ago

They are advocating "one size fits all"; i.e. a single engine that solves all DBMS needs.

-- Prof. Michael Stonebreaker, one of the founding fathers of the RDBMS industry.

Until this point in time, the requisite confluence of "circumstantial pain" and "open standards" based technology required to enable an objective "compare and contrast" of RDBMS engine virtues and viable alternatives hasn't occurred. Thus, the RDBMS has endured it position of primacy albeit on a "one size fits all basis".

Circumstantial Pain

As mentioned earlier, we are in the midst of an economic crisis that is ultimately about a consistent inability to connect dots across a substrate of interlinked data sources that transcend traditional data access boundaries with high doses of schematic heterogeneity. Ironically, in a era of the dot-com, we haven't been able to make meaningful connections between relevant "real-world things" that extend beyond primitive data hosted database tables and content management style document containers; we've struggled to achieve this in the most basic sense, let alone evolve our ability to connect inline with the exponential rate at which the Internet & Web are spawning "universes of discourse" (data spaces) that emanate from user activity (within the enterprise and across the Internet & Web). In a nutshell, we haven't been able to upgrade our interaction with data such that "conceptual models" and resulting "context lenses" (or facets) become concrete; by this I mean: real-world entity interaction making its way into the computer realm as opposed to the impedance we all suffer today when we transition from conceptual model interaction (real-world) to logical model interaction (when dealing with RDBMS based data access and data management).

Here are some simple examples of what I can only best describe as: "critical dots unconnected", resulting from an inability to interact with data conceptually:

Government (Globally) -

Financial regulatory bodies couldn't effectively discern that a Credit Default Swap is an Insurance policy in all but literal name. And in not doing so the cost of an unregulated insurance policy laid the foundation for exacerbating the toxicity of fatally flawed mortgage backed securities. Put simply: a flawed insurance policy was the fallback on a toxic security that financiers found exotic based on superficial packaging.

Enterprises -

Banks still don't understand that capital really does exists in tangible and intangible forms; with the intangible being the variant that is inherently dynamic. For example, a tech companies intellectual capital far exceeds the value of fixture, fittings, and buildings, but you be amazed to find that in most cases this vital asset has not significant value when banks get down to the nitty gritty of debt collateral; instead, a buffer of flawed securitization has occurred atop a borderline static asset class covering the aforementioned buildings, fixtures, and fittings.

In the general enterprise arena, IT executives continued to "rip and replace" existing technology without ever effectively addressing the timeless inability to connect data across disparate data silos generated by internal enterprise applications, let alone the broader need to mesh data from the inside with external data sources. No correlations made between the growth of buzzwords and the compounding nature of data integration challenges. It's 2009 and only a miniscule number of executives dare fantasize about being anywhere within distance of the: relevant information at your fingertips vision.

Looking more holistically at data interaction in general, whether you interact with data in the enterprise space (i.e., at work) or on the Internet or Web, you ultimately are delving into a mishmash of disparate computer systems, applications, service (Web or SOA), and databases (of the RDBMS variety in a majority of cases) associated with a plethora of disparate schemas. Yes, but even today "rip and replace" is still the norm pushed by most vendors; pitting one mono culture against another as exemplified by irrelevances such as: FOSS/LAMP vs Commercial or Web vs. Enterprise, when none of this matters if the data access and integration issues are recognized let alone addressed (see: Applications are Like Fish and Data Like Wine).

Like the current credit-crunch, exponential growth of data originating from disparate application databases and associated schemas, within shrinking processing time frames, has triggered a rethinking of what defines data access and data management value today en route to an inevitable RDBMS downgrade within the value pyramid.

Technology

There have been many attempts to address real-world modeling requirements across the broader DBMS community from Object Databases to Object-Relational Databases, and more recently the emergence of simple Entity-Attribute-Value model DBMS engines. In all cases failure has come down to the existence of one or more of the following deficiencies, across each potential alternative:

Query language standardization - nothing close to SQL standardization
Data Access API standardization - nothing close to ODBC, JDBC, OLE-DB, or ADO.NET
Wire protocol standardization - nothing close to HTTP
Distributed Identity infrastructure - nothing close to the non-repudiatable digital Identity that foaf+ssl accords
Use of Identifiers as network based pointers to data sources - nothing close to RDF based Linked Data
Negotiable data representation - nothing close to Mime and HTTP based Content Negotiation
Scalability especially in the era of Internet & Web scale.

Entity-Attribute-Value with Classes & Relationships (EAV/CR) data models

A common characteristic shared by all post-relational DBMS management systems (from Object Relational to pure Object) is an orientation towards variations of EAV/CR based data models. Unfortunately, all efforts in the EAV/CR realm have typically suffered from at least one of the deficiencies listed above. In addition, the same "one DBMS model fits all" approach that lies at the heart of the RDBMS downgrade also exists in the EAV/CR realm.

What Comes Next?

The RDBMS is not going away (ever), but its era of primacy -- by virtue of its placement at the apex of the data access and data management value pyramid -- is over! I make this bold claim for the following reasons:

The Internet aided "Global Village" has brought "Open World" vs "Closed World" assumption issues to the fore e.g., the current global economic crisis remains centered on the inability to connect dots across "Open World" and "Closed World" data frontiers
Entity-Attribute-Value with Classes & Relationships (EAV/CR) based DBMS models are more effective when dealing with disparate data associated with disparate schemas, across disparate DBMS engines, host operating systems, and networks.

Based on the above, it is crystal clear that a different kind of DBMS -- one with higher AVF relative to the RDBMS -- needs to sit atop today's data access and data management value pyramid. The characteristics of this DBMS must include the following:

Every item of data (Datum/Entity/Object/Resource) has Identity
Identity is achieved via Identifiers that aren't locked at the DBMS, OS, Network, or Application levels
Object Identifiers and Object values are independent (extricably linked by association)
Object values should be de-referencable via Object Identifier
Representation of de-referenced value graph (entity, attributes, and values mesh) must be negotiable (i.e. content negotiation)
Structured query language must provide mechanism for Creation, Deletion, Updates, and Querying of data objects
Performance & Scalability across "Closed World" (enterprise) and "Open World" (Internet & Web) realms.

Quick recap, I am not saying that RDBMS engine technology is dead or obsolete. I am simply stating that the era of RDBMS primacy within the data access and data management value pyramid is over.

The problem domain (conceptual model views over heterogeneous data sources) at the apex of the aforementioned pyramid has simply evolved beyond the natural capabilities of the RDBMS which is rooted in "Closed World" assumptions re., data definition, access, and management. The need to maintain domain based conceptual interaction with data is now palpable at every echelon within our "Global Village" - Internet, Web, Enterprise, Government etc.

It is my personal view that an EAV/CR model based DBMS, with support for the seven items enumerated above, can trigger the long anticipated RDBMS downgrade. Such a DBMS would be inherently multi-model because you would need to the best of RDBMS and EAV/CR model engines in a single product, with in-built support for HTTP and other Internet protocols in order to effectively address data representation and serialization issues.

EAV/CR Oriented Data Access & Management Technology

Examples of contemporary EAV/CR frameworks that provide concrete conceptual layers for data access and data management currently include:

Resource Description Framework (RDF) - an EAV/CR based framework
RDF Linked Data - EAV/CR based framework that mandates de-referencable HTTP based Identifiers
ADO.NET Entity Frameworks - Microsoft .NET based EAV/CR framework
Core Data Services - Mac OS X based EAV/CR framework that evolved from NeXT's Enterprise Object Frameworks (EOF).

The frameworks above provide the basis for a revised AVF pyramid, as depicted below, that reflects today's data access and management realities i.e., an Internet & Web driven global village comprised of interlinked distributed data objects, compatible with "Open World" assumptions.

See: New EAV/CR Primacy Diagram.

The Time for RDBMS Primacy Downgrade is Nigh!

Sun, 25 Jan 2009 00:04:00 GMT

What is the Data Access, and Data Management Value Pyramid?

Why has RDBMS Primacy has Endured?

"Future of Database Research is excellent, but what is the future of data?"
"..it is hard for me to disagree with the conclusions in this report. It captures exactly the right thoughts, and should be a must read for everyone involved in the area of databases and database research in particular."
-- Dr. Anant Jingran, CTO, IBM Information Management Systems, commenting on the 2007 RDBMS technology retreat attended by a number of key DBMS technology pioneers and researchers.

"One size fits all: A concept whose time has come and gone

They are direct descendants of System R and Ingres and were architected more than 25 years ago

They are advocating "one size fits all"; i.e. a single engine that solves all DBMS needs.

-- Prof. Michael Stonebreaker, one of the founding fathers of the RDBMS industry.

Circumstantial Pain

Here are some simple examples of what I can only best describe as: "critical dots unconnected", resulting from an inability to interact with data conceptually:

Government (Globally) -

Enterprises -

Technology

Query language standardization - nothing close to SQL standardization
Data Access API standardization - nothing close to ODBC, JDBC, OLE-DB, or ADO.NET
Wire protocol standardization - nothing close to HTTP
Distributed Identity infrastructure - nothing close to the non-repudiatable digital Identity that foaf+ssl accords
Use of Identifiers as network based pointers to data sources - nothing close to RDF based Linked Data
Negotiable data representation - nothing close to Mime and HTTP based Content Negotiation
Scalability especially in the era of Internet & Web scale.

Entity-Attribute-Value with Classes & Relationships (EAV/CR) data models

What Comes Next?

The Internet aided "Global Village" has brought "Open World" vs "Closed World" assumption issues to the fore e.g., the current global economic crisis remains centered on the inability to connect dots across "Open World" and "Closed World" data frontiers
Entity-Attribute-Value with Classes & Relationships (EAV/CR) based DBMS models are more effective when dealing with disparate data associated with disparate schemas, across disparate DBMS engines, host operating systems, and networks.

Every item of data (Datum/Entity/Object/Resource) has Identity
Identity is achieved via Identifiers that aren't locked at the DBMS, OS, Network, or Application levels
Object Identifiers and Object values are independent (extricably linked by association)
Object values should be de-referencable via Object Identifier
Representation of de-referenced value graph (entity, attributes, and values mesh) must be negotiable (i.e. content negotiation)
Structured query language must provide mechanism for Creation, Deletion, Updates, and Querying of data objects
Performance & Scalability across "Closed World" (enterprise) and "Open World" (Internet & Web) realms.

Quick recap, I am not saying that RDBMS engine technology is dead or obsolete. I am simply stating that the era of RDBMS primacy within the data access and data management value pyramid is over.

EAV/CR Oriented Data Access & Management Technology

Examples of contemporary EAV/CR frameworks that provide concrete conceptual layers for data access and data management currently include:

Resource Description Framework (RDF) - an EAV/CR based framework
RDF Linked Data - EAV/CR based framework that mandates de-referencable HTTP based Identifiers
ADO.NET Entity Frameworks - Microsoft .NET based EAV/CR framework
Core Data Services - Mac OS X based EAV/CR framework that evolved from NeXT's Enterprise Object Frameworks (EOF).

The Semantic Way - Alan Cho's Summary of PwC 2009 tech forecast report on the Semantic Web
Is the RDBMS Doomed - ReadWriteWeb Article
Anti-RDBMS: a list of Distributed Key-Value Stores - by Richard Jones (CTO Last.FM)
How & Why Glue is Using Amazon SimpleDB
Object Database Manifesto (Identity excerpt)
Database Models Overview
Ted Nelson Explaining Irregularity and Idiosyncrasy of Data Structures - ZigZag Demo

New ADO.NET 3.x Provider for Virtuoso Released (Update 2)

Thu, 08 Jan 2009 04:36:47 GMT

I am pleased to announce the immediate availability of the Virtuoso ADO.NET 3.5 data provider for Microsoft's .NET platform.

What is it?

A data access driver/provider that provides conceptual entity oriented access to RDBMS data managed by Virtuoso. Naturally, it also uses Virtuoso's in-built virtual / federated database layer to provide access to ODBC and JDBC accessible RDBMS engines such as: Oracle (7.x to latest), SQL Server (4.2 to latest), Sybase, IBM Informix (5.x to latest), IBM DB2, Ingres (6.x to latest), Progress (7.x to OpenEdge), MySQL, PostgreSQL, Firebird, and others using our ODBC or JDBC bridge drivers.

Benefits?

Technical:

It delivers an Entity-Attribute-Value + Classes & Relationships model over disparate data sources that are materialized as .NET Entity Framework Objects, which are then consumable via ADO.NET Data Object Services, LINQ for Entities, and other ADO.NET data consumers.

The provider is fully integrated into Visual Studio 2008 and delivers the same "ease of use" offered by Microsoft's own SQL Server provider, but across Virtuoso, Oracle, Sybase, DB2, Informix, Ingres, Progress (OpenEdge), MySQL, PostgreSQL, Firebird, and others. The same benefits also apply uniformly to Entity Frameworks compatibility.

Bearing in mind that Virtuoso is a multi-model (hybrid) data manager, this also implies that you can use .NET Entity Frameworks against all data managed by Virtuoso. Remember, Virtuoso's SQL channel is a conduit to Virtuoso's core; thus, RDF (courtesy of SPASQL as already implemented re. Jena/Sesame/Redland providers), XML, and other data forms stored in Virtuoso also become accessible via .NET's Entity Frameworks.

Strategic:

You can choose which entity oriented data access model works best for you: RDF Linked Data & SPARQL or .NET Entity Frameworks & Entity SQL. Either way, Virtuoso delivers a commercial grade, high-performance, secure, and scalable solution.

How do I use it?

Simply follow one of guides below:

Note: When working with external or 3rd party databases, simply use the Virtuoso Conductor to link the external data source into Virtuoso. Once linked, the remote tables will simply be treated as though they are native Virtuoso tables leaving the virtual database engine to handle the rest. This is similar to the role the Microsoft JET engine played in the early days of ODBC, so if you've ever linked an ODBC data source into Microsoft Access, you are ready to do the same using Virtuoso.

Introducing Virtuoso Universal Server (Cloud Edition) for Amazon EC2

Fri, 28 Nov 2008 19:27:12 GMT

What is it?

A pre-installed edition of Virtuoso for Amazon's EC2 Cloud platform.

What does it offer?

From a Web Entrepreneur perspective it offers:

Low cost entry point to a game-changing Web 3.0+ (and beyond) platform that combines SQL, RDF, XML, and Web Services functionality
Flexible variable cost model (courtesy of EC2 DevPay) tightly bound to revenue generated by your services
Delivers federated and/or centralized model flexibility for you SaaS based solutions
Simple entry point for developing and deploying sophisticated database driven applications (SQL or RDF Linked Data Web oriented)
Complete framework for exploiting OpenID, OAuth (including Role enhancements) that simplifies exploitation of these vital Identity and Data Access technologies
Easily implement RDF Linked Data based Mail, Blogging, Wikis, Bookmarks, Calendaring, Discussion Forums, Tagging, Social-Networking as Data Space (data containers) features of your application or service offering
Instant alleviation of challenges (e.g. service costs and agility) associated with Data Portability and Open Data Access across Web 2.0 data silos
LDAP integration for Intranet / Extranet style applications.

From the DBMS engine perspective it provides you with one or more pre-configured instances of Virtuoso that enable immediate exploitation of the following services:

RDF Database (a Quad Store with SPARQL & SPARUL Language & Protocol support)
SQL Database (with ODBC, JDBC, OLE-DB, ADO.NET, and XMLA driver access)
XML Database (XML Schema, XQuery/Xpath, XSLT, Full Text Indexing)
Full Text Indexing.

From a Middleware perspective it provides:

RDF Views (Wrappers / Semantic Covers) over SQL, XML, and other data sources accessible via SOAP or REST style Web Services
Sponger Service for converting non RDF information resources into RDF Linked Data "on the fly" via a large collection of pre-installed RDFizer Cartridges.

From the Web Server Platform perspective it provides an alternative to LAMP stack components such as MySQL and Apace by offering

HTTP Web Server
WebDAV Server
Web Application Server (includes PHP runtime hosting)
SOAP or REST style Web Services Deployment
RDF Linked Data Deployment
SPARQL (SPARQL Query Language) and SPARUL (SPARQL Update Language) endpoints
Virtuoso Hosted PHP packages for MediaWiki, Drupal, Wordpress, and phpBB3 (just install the relevant Virtuoso Distro. Package).

From the general System Administrator's perspective it provides:

Online Backups (Backup Set dispatched to S3 buckets, FTP, or HTTP/WebDAV server locations)
Synchronized Incremental Backups to Backup Set locations
Backup Restore from Backup Set location (without exiting to EC2 shell).

Higher level user oriented offerings include:

OpenLink Data Explorer front-end for exploring the burgeoning Linked Data Web
Ajax based SPARQL Query Builder (iSPARQL) that enables SPARQL Query construction by Example
Ajax based SQL Query Builder (QBE) that enables SQL Query construction by Example.

For Web 2.0 / 3.0 users, developers, and entrepreneurs it offers it includes Distributed Collaboration Tools & Social Media realm functionality courtesy of ODS that includes:

Point of presence on the Linked Data Web that meshes your Identity and your Data via URIs
System generated Social Network Profile & Contact Data via FOAF?
System generated SIOC (Semantically Interconnected Online Community) Data Space (that includes a Social Graph) exposing all your Web data in RDF Linked Data form
System generated OpenID and automatic integration with FOAF
Transparent Data Integration across Facebook, Digg, LinkedIn, FriendFeed, Twitter, and any other Web 2.0 data space equipped with RSS / Atom support and/or REST style Web Services
In-built support for SyncML which enables data synchronization with Mobile Phones.

How Do I Get Going with It?

Virtuoso, PHP Runtime Hosting: phpBB, Wordpress, Drupal, MediaWiki, and Linked Data

Fri, 24 Oct 2008 19:55:00 GMT

Runtime hosting is functionality realm of Virtuoso that is sometimes easily overlooked. In this post I want to provide a simple no-hassles HOWTO guide for installing Virtuoso on Windows (32 or 64 Bit), Mac OS X (Universal or Native 64 Bit), and Linux (32 or 64 Bit). The installation guide also covers the instantiation of phpBB3 as verification of the Virtuoso hosted PHP 3.5 runtime.

What are the benefits of PHP Runtime Hosting?

Like Apache, Virtuoso is a bona-fide Web Application Server for PHP based applications. Unlike Apache, Virtuoso is also the following:

a Hybrid Native DBMS Engine (Relational, RDF-Graph, and Document models) that is accessible via industry standard interfaces (solely)
a Virtual DBMS or Master Data Manager (MDM) that virtualizes heterogeneous data sources (ODBC, JDBC, Web Services, Hypermedia Resources, Non Hypermedia Resources)
an RDF Middleware solution for RDF-zation of non RDF resources across the Web and enterprise Intranets and/or Extranets (in the form of Cartridges for data exposed via REST or SOA oriented SOAP interfaces)
an RDF Linked Data Server (meaning it can deploy RDF Linked Data based on its native and/or virtualized data)

As result of the above, when you deploy a PHP application using Virtuoso, you inherit the following benefits:

Use of PHP-iODBC for in-process communication with Virtuoso
Easy generation of RDF Linked Data Views atop the SQL schemas of PHP applications
Easy deployment of RDF Linked Data from virtualized data sources
Less LAMP monoculture (*there is no such thing as virtuous monoculture*) when dealing with PHP based Web applications.

As indicated in prior posts, producing RDF Linked Data from the existing Web, where a lot of content is deployed by PHP based content managers, should simply come down to RDF Views over the SQL Schemas and deployment / publishing of the RDF Views in RDF Linked data form. In a nutshell, this is what Virtuoso delivers via its PHP runtime hosting and pre packaged VADs (Virtuoso Application Distribution packages), for popular PHP based applications such as: phpBB3, Drupal, WordPress, and MediaWiki.

In addition, to the RDF Linked Data deployment, we've also taken the traditional LAMP installation tedium out of the typical PHP application deployment process. For instance, you don't have to rebuild PHP 3.5 (32 or 64 Bit) on Windows, Mac OS X, or Linux to get going, simply install Virtuoso, and then select a VAD package for the relevant application and you're set. If the application of choice isn't pre packaged by us, simply install as you would when using Apache, which comes dow to situating the PHP files in your Web structure under the Web Application's root directory.

Installation Guide

Download the Virtuoso installer for Windows (32 Bit msi file or 64 Bit msi file), Mac OS X (Universal Binary dmg file), or instantiate the Virtuoso EC2 AMI (*search for pattern: "Virtuoso when using the Firefox extension for EC2 as the AMI ID is currently: ami-7c31d515 and name: virtuoso-test/virtuoso-cloud-beta-9-i386.manifest.xml, for latest cut*)
Run the installer (or download the movies using the links in the related section below)
Go to the Virtuoso Conductor (*which will show up at the end of the installation process* or go to http://localhost:8890/conductor)
Go to the "Admin" tab within the (X)HTML based UI and select the "Packages" sub-menu item (a Tab)
Pick phpBB3 (or any other pre-packaged PHP app) and then click on "Install/Upgrase"
The watch one of my silent movies or read the initial startup guides for Virtuoso hosted phpBB3, Drupal, Wordpress, MediaWiki.

At the current time, I've only provided links to ZIP files containing the Virtuoso installation "silent movies". This approach is a short-term solution to some of my current movie publishing challenges re. YouTube and Vimeo -- where the compressed output hasn't been of acceptable visual quality. Once resolved, I will publish much more "Multimedia Web" friendly movies :-)

Where Are All the RDF-based Semantic Web Applications?

Wed, 01 Oct 2008 23:09:00 GMT

In response to the "Semantic Web Technology" application classification scheme espoused by ReadWriteWeb (RWW), emphasized in the post titled: Where are all the RDF-based Semantic Web Apps?, here is my attempt to clarify and reintroduce what OpenLink Software offers (today) in relation to Semantic Web technology.

From the RWW Top-Down category, which I interpret as: technologies that produce RDF from non RDF data sources. Our product portfolio is comprised of the following; Virtuoso Universal Server, OpenLink Data Spaces, OpenLink Ajax Toolkit, and OpenLink Data Explorer (which includes ubiquity commands).

Virtuoso Universal Server functionality summary:

Generation of RDF Linked Data Views of SQL, XML, and Web Services in general
Deployment of RDF Linked Data
"On the Fly" generation of RDF Linked Data from Document Web information resources (i.e. distillation of entities from their containers e.g. Web pages) via Cartridges / Drivers
SPARQL query language support
SPARQL extensions that bring SPARQL closer to SQL e.g Aggregates, Update, Insert, Delete Named Graph support (i.e. use of logical names to partition RDF data within Virtuoso's multi-model dbms engine)
Inference Engine (currently in use re. DBpedia via Yago and UMBEL)
Host and exposes data from Drupal, Wordpress, MediaWiki, phpBB3 as RDF Linked Data via in-built support for PHP runtime
Available as an EC2 AMI
etc..

OpenLink Data Spaces functionality summary:

Simple mechanism for Linked Data Web enabling yourself by giving you an HTTP based User ID (a de-referencable URI) that is linked to a FOAF based Profile page and OpenID
Binds all your data sources (blogs, wikis, bookmarks, photos, calendar items etc. ) to your URI so can "Find" things by only remembering your URI
Makes your profile page and personal URI the focal point of Linked Data Web presence
Delivers Data Portability (using data access by value or data access by reference) across data silos (e.g. Web 2.0 style social networks)
Allows you make annotations about anything in your own Data Space(s) on the Web without exposure to RDF markup
A Briefcase feature that provides a WebDAV driven RDF Linked Data variant of functionality seen in Mac OS X Spotlight and WinFS with the addition of SPARQL compliance
Automatically generates RDFa in its (X)HTML pages
Blog, Wiki, WebDAV File Server, Shared Bookmarks, Calendar, and other applications that look and feel like Web 2.0 counterparts but emitt RDF Linked Data amongst a plethora of data exchange formats
Available as an EC2 AMI
etc..

OpenLink Ajax Toolkit functionality summary:

Provides binding to SQL, RDF, XML, and Web Services via Ajax Database Connectivity Layer (you only need an ODBC, JDBC, OLE-DB, ADO.NET, XMLA Driver, or Web Service on the backend for dynamic data access from Javascript)
All controls are Ajax Database Connectivity bound (widgets get their data from Ajax Database Connectivity data sources)
Bundled with Virtuoso and ODS installations.
etc.

OpenLink Data Explorer functionality summary

Distills entities associated with information resource style containers (e.g. Web Pages or files) as RDF Linked Data
Exposes the RDF based Linked Data graph associated with information resources (see the Linked Data behind Web pages)
Ubiquity commands for invoking the above
Available as a Hosted Service or Firefox Extension
Bundled with Virtuoso and ODS installations
etc.

Note:

Of course you could have simply looked up OpenLink Software's FOAF based Profile page (*note the Linked Data Explorer tab*), or simply passed the FOAF profile page URL to a Linked Data aware client application such as: OpenLink Data Explorer, Zitgist Data Viewer, Marbles, and Tabulator, and obtained information. Remember, OpenLink Software is an Entity of Type: foaf:Organization, on the burgeoning Linked Data Web :-)

Linked Data Planet Keynote (RDFa based remix edition)
On The Cusp: A Global Review of the Semantic Web Industry.

Crunchbase & Semantic Web Interview (Remix - Update 1)

Wed, 27 Aug 2008 18:16:37 GMT

After reading Bengee's interview with CrunchBase, I decided to knock up a quick interview remix as part of my usual attempt to add to the developing discourse.

CrunchBase: When we released the CrunchBase API, you were one of the first developers to step up and quickly released a CrunchBase Sponger Cartridge. Can you explain what a CrunchBase Sponger Cartridge is?

Me: A Sponger Cartridge is a data access driver for Web Resources that plugs into our Virtuoso Universal Server (DBMS and Linked Data Web Server combo amongst other things). It uses the internal structure of a resource and/or a web service associated with a resource, to materialize an RDF based Linked Data graph that essentially describes the resource via its properties (Attributes & Relationships).

CrunchBase: And what inspired you to create it?

Me: Bengee built a new space with your data, and we've built a space on the fly from your data which still resides in your domain. Either solution extols the virtues of Linked Data i.e. the ability to explore relationships across data items with high degrees of serendipity (also colloquially known as: following-your-nose pattern in Semantic Web circles).

Bengee posted a notice to the Linking Open Data Community's public mailing list announcing his effort. Bearing in mind the fact that we've been using middleware to mesh the realms of Web 2.0 and the Linked Data Web for a while, it was a no-brainer to knock something up based on the conceptual similarities between Wikicompany and CrunchBase. In a sense, a quadrant of orthogonality is what immediately came to mind re. Wikicompany, CrunchBase, Bengee's RDFization efforts, and ours.

Bengee created an RDF based Linked Data warehouse based on the data exposed by your API, which is exposed via the Semantic CrunchBase data space. In our case we've taken the "RDFization on the fly" approach which produces a transient Linked Data View of the CrunchBase data exposed by your APIs. Our approach is in line with our world view: all resources on the Web are data sources, and the Linked Data Web is about incorporating HTTP into the naming scheme of these data sources so that the conventional URL based hyperlinking mechanism can be used to access a structured description of a resource, which is then transmitted using a range negotiable representation formats. In addition, based on the fact that we house and publish a lot of Linked Data on the Web (e.g. DBpedia, PingTheSemanticWeb, and others), we've also automatically meshed Crunchbase data with related data in DBpedia and Wikicompany data.

CrunchBase: Do you know of any apps that are using CrunchBase Cartridge to enhance their functionality?

Me: Yes, the OpenLink Data Explorer which provides CrunchBase site visitors with the option to explore the Linked Data in the CrunchBase data space. It also allows them to "Mesh" (rather than "Mash") CrunchBase data with other Linked Data sources on the Web without writing a single line of code.

CrunchBase: You have been immersed in the Semantic Web movement for a while now. How did you first get interested in the Semantic Web?

Me: We saw the Semantic Web as a vehicle for standardizing conceptual views of heterogeneous data sources via context lenses (URIs). In 1998 as part of our strategy to expand our business beyond the development and deployment of ODBC, JDBC, and OLE-DB data providers, we decided to build a Virtual Database Engine (see: Virtuoso History), and in doing so we sought a standards based mechanism for the conceptual output of the data virtualization effort. As of the time of the seminal unveiling of the Semantic Web in 1998 we were clear about two things, in relation to the effects of the Web and Internet data management infrastructure inflections: 1) Existing DBMS technology had reached it limits 2) Web Servers would ultimately hit their functional limits. These fundamental realities compelled us to develop Virtuoso with an eye to leveraging the Semantic Web as a vehicle from completing its technical roadmap.

CrunchBase: Can you put into layman’s terms exactly what RDF and SPARQL are and why they are important? Do they only matter for developers or will they extend past developers at some point and be used by website visitors as well?

Me: RDF (Resource Description Framework) is a Graph based Data Model that facilitates resource description using the Subject, Predicate, and Object principle. Associated with the core data model, as part of the overall framework, are a number of markup languages for expressing your descriptions (just as you express presentation markup semantics in HTML or document structure semantics in XML) that include: RDFa (simple extension of HTML markup for embedding descriptions of things in a page), N3 (a human friendly markup for describing resources), RDF/XML (a machine friendly markup for describing resources).

SPARQL is the query language associated with the RDF Data Model, just as SQL is a query language associated with the Relational Database Model. Thus, when you have RDF based structured and linked data on the Web, you can query against Web using SPARQL just as you would against an Oracle/SQL Server/DB2/Informix/Ingres/MySQL/etc.. DBMS using SQL. That's it in a nutshell.

CrunchBase: On your website you wrote that “RDF and SPARQL as productivity boosters in everyday web development”. Can you elaborate on why you believe that to be true?

Me: I think the ability to discern a formal description of anything via its discrete properties is of immense value re. productivity, especially when the capability in question results in a graph of Linked Data that isn't confined to a specific host operating system, database engine, application or service, programming language, or development framework. RDF Linked Data is about infrastructure for the true materialization of the "Information at Your Fingertips" vision of yore. Even though it's taken the emergence of RDF Linked Data to make the aforementioned vision tractable, the comprehension of the vision's intrinsic value have been clear for a very long time. Most organizations and/or individuals are quite familiar with the adage: Knowledge is Power, well there isn't any knowledge without accessible Information, and there isn't any accessible Information without accessible Data. The Web has always be grounded in accessibility to data (albeit via compound container documents called Web Pages).

Bottom line, RDF based Linked Data is about Open Data access by reference using URIs (HTTP based Entity IDs / Data Object IDs / Data Source Names), and as I said earlier, the intrinsic value is pretty obvious bearing in mind the costs associated with integrating disparate and heterogeneous data sources -- across intranets, extranets, and the Internet.

CrunchBase: In his definition of Web 3.0, Nova Spivack proposes that the Semantic Web, or Semantic Web technologies, will be force behind much of the innovation that will occur during Web 3.0. Do you agree with Nova Spivack? What role, if any, do you feel the Semantic Web will play in Web 3.0?

Me: I agree with Nova. But I see Web 3.0 as a phase within the Semantic Web innovation continuum. Web 3.0 exists because Web 2.0 exists. Both of these Web versions express usage and technology focus patterns. Web 2.0 is about the use of Open Source technologies to fashion Web Services that are ultimately used to drive proprietary Software as Service (SaaS) style solutions. Web 3.0 is about the use of "Smart Data Access" to fashion a new generation of Linked Data aware Web Services and solutions that exploit the federated nature of the Web to maximum effect; proprietary branding will simply be conveyed via quality of data (cleanliness, context fidelity, and comprehension of privacy) exposed by URIs.

Here are some examples of the CrunchBase Linked Data Space, as projected via our CruncBase Sponger Cartridge: