The motivation behind this post is a response to the Read/WriteWeb post titled: Semantic Web: Difficulties with the Classic Approach.

First off, I am going to focus on the Semantic Data Web aspect of the overall Semantic Web vision (a continuum) as this is what we have now. I am also writing this post as a deliberate contribution to the discourse swirling around the real topic: Semantic Web Value Proposition.

Situation Analysis

We are in the early stages of the long anticipated Knowledge Economy. That being the case, it would be safe to assume that information access, processing, and dissemination are of utmost importance to individuals and organizations alike. You don't produce knowledge in a vacum! Likewise, you can produce Information in a vacum, you need Data.

The Semantic Data Web's value to Individuals


Increasingly, Blogs, Wikis, Shared Bookmarks, Photo Galleries, Discussion Forums, Shared Calendars and the like, have become invaluable tools for individual and organizational participation in Web enabled global discourse (where a lot of knowledge is discovered). These tools, are typically associated with Web 2.0, implying Read-Write access via Web Services, centralized application hosting, and data lock-in (silos).

The reality expressed above is a recipe for "Information Overload" and complete annihilation of ones effective pursuit and exploitation of knowledge due "Time Scarcity" (note: disconnecting is not an option). Information abundance is inversely related to available processing time (for humans in particular). In my case for instance, I was actively subscribed to over 500+ RSS feeds in 2003. As of today, I've simply stopped counting, and that's just my Weblog Data Space. Then add to that, all of the Discussions I track across Blogs, wikis, message boards, mailing lists, traditional usnet discussion forumns, and the like, and I think you get the picture.

Beyond information overload, Web 2.0 data is "Semi-Structured" by way of it's dominant data containers ((X)HTML, RSS, Atom documents and data streams etc.) lacking semantics that formally expose individual data items as distinct entities, endowed with unambiguous naming / identification, descriptive attributes (a type of property/predicate), and relationships (a type of property/predicate).


Devise a standard for Structured Data Semantics that is compatible with the Web Information BUS.

Produce structured data (entities, entity types, entity relationships) from Web 1.0 and Web 2.0 resources that already exists on the Web such that individual entities, their attributes, and relationships are accessible and discernible to software agents (machines).

Once the entities are individually exposed, the next requirement is a mechanism for selective access to these entities i.e. a query language.

Semantic Data Web Technologies that facilitate the solution described above include:

Structured Data Standards:
    RDF - Data Model for structured data
    RDF/XML - A serialization format for RDF based structured data
    N3 / Turtle - more human friendly serialization formats for RDF based structured data
Entity Exposure & Generation:
    GRDDL - enables association between XHTML pages and XSLT stylesheets that facilitates loosely coupled "on the fly" extraction of RDF from non RDF documents
    RDFa - enables document publishers or viewers (i.e those repurposing or annotating) to embed structured data into existing XHTML documents
    eRDF - another option for embedding structured RDF data within (X)HTML documents
    RDF Middleware - typically incorporating GRDDL, RDFa, eRDF, and custom extraction and mapping as part of a structured data production pipeline
. Entity Naming & Identification:

Use of URIs or IRIs for uniquely identifying physical (HTML Documents, Image Files, Multimedia Files etc..) and abstract (People, Places, Music, and other abstract things).

Entity Access & Querying:

    SPARQL Query Language - the SQL analog of the Semantic Data Web that enables query constructs that target named entities, entity attributes, and entity relationships

The Semantic Data Web's value to Organizations


Organizations are rife with a plethora of business systems that are built atop a myriad of database engines, sourced from a variety of DBMS vendors. A typical organization would have a different database engine, from a specific DBMS vendor, underlying critical business applications such as: Human Resource Management (HR), Customer Relationship Management (CRM), Accounting, Supply Chain Management etc. In a nutshell, you have DBMS Engines, and DBMS Schema heterogeneity permeating the IT infrastructure of organizations on a global scale, making Data & Information Integration the biggest headache across all IT driven organizations.


Alleviation of the pain (costs) associated with Data & Information Integration.

Semantic Data Web offerings:

A dexterous data model (RDF) that enables the construction of conceptual views of disparate data sources across an organization based on existing web architecture components such as HTTP and URIs.

Existing middleware solutions that facilitate the exposure of SQL DBMS data as RDF based Structured Data include:

BTW - There is an upcoming W3C Workshop covering the integration of SQL and RDF data.


The Semantic Data Web is here, it's value delivery vehicle is the URI. The URI is a conduit to Interlinked Structured Data (RDF based Linked Data) derived from existing data sources on the World Wide Web alongside data continuously injected into the Web by organizations world wide. Ironically, the Semantic Data Web only platform that crystallizes the: Information at Your Fingertips vision, without development environment, operating system, application, or database lock-in. You simply click on a Linked Data URI and the serendipitous exploration and discovery of data commences.

The unobtrusive emergence of the Semantic Data Web is a reflection of the soundness of the underlying Semantic Web vision.

If you are excited about Mash-ups then your are a Semantic Web enthusiast and benefactor in the making, because you only "Mash" (brute force data extraction and interlinking) because you can't "Mesh" (natural data extraction and interlinking). Likewise, if you are a social-networking, open social-graph, or portable social-network enthusiast, then you are also a Semantic Data Web benefactor and enthusiasts, because your "values" (yes, the values associated with the properties that define you e.g your interests etc) are the fundamental basis for portable, open, social-networking, which is what the Semantic Data Web hands to you on a platter without compromise (i.e. data lock-in or loss of data ownership).

Some practical examples of Semantic Data Web prowess:
    DBpedia (*note: I deliberately use DBpedia URIs in my posts where I would otherwise have used a Wikipedia article URI*)