The Semantic Enterprise

The Semantic Enterprise

Summary: The video above by Manu Sporny of Digital Bazaar provides a clear and simple overview of the semantic web for 'newbies', explaining the limitations of the internet in its current incarnation and the potential of next generation intelligent agent machines to help us find information.While the greater semantic web shows great promise, it is going to be an immensely complex process linking up all content on the entire internet as it continues to grow - effectively tagging everything online.


The video above by Manu Sporny of Digital Bazaar provides a clear and simple overview of the semantic web for 'newbies', explaining the limitations of the internet in its current incarnation and the potential of next generation intelligent agent machines to help us find information.

While the greater semantic web shows great promise, it is going to be an immensely complex process linking up all content on the entire internet as it continues to grow - effectively tagging everything online. The task is arguably much more viable within the manageable boundaries of a specific business environment.

Information context is immensely important and powerful within the enterprise. We are all familiar with the huge document graveyards multiple Sharepoint shared drives and wikis can become - we spend time laboriously finding the location of information and then arriving at the single destination where it lives, over and over again.

While we have some very effective current generation enterprise 2.0 social network style software solutions for collaboration, there is an ongoing huge issue of scaling: an online environment for a team of say 40 can break down when it expands to 400, choking on its own success in a sea of information, for example. This is not the fault of the software but rather of the content being created and uploaded, which lacks the metadata which enables machines to filter and 'read' and process it.

Connectivity with parallel projects in similar environments can be even more challenging and labor intensive to keep current and relevant.

Intriguingly, the next generation of enterprise business software may prove to be more sophisticated than the current consumer web 2.0 experience.

The ability to provide contextually grouped rich content to employees within a well defined internal semantic web is much easier to achieve than the much bigger challenge of the consumer semantic web, and can tie in with IT security protocols whether on premise and behind firewalls, in the cloud or a combination.

By providing contextual connections in all company content, a new employee or partner will be able to get up to speed much faster, with connections being provided as they explore content in different applications, all unified by metadata.

Enterprise search, currently a huge challenge, particularly across multiple applications and their associated databases, will be transformed into a powerful context engine. The productivity and efficiency gains of this approach will be substantial, but more importantly the 'knowledge is power' factor provided by these rich referrals will create smarter minds more quickly. This also has major implications for training and learning management systems.

Thompson Reuters, who as a news organization have a vested interest in the world being as tagged as possible, are making great strides with their 'Open Calais' api, based on Clear Forest which they acquired in 2007. More on this later this month.

i mentioned the rich context example of the Freebase breakfast cereal 'base' in this post recently -, another example is this 'base' for jazz musician John Coltrane, with various contextual possibilities and sub categories and groups.

These two 'base' examples provide a glimpse into a future enterprise organized around semantic logic and conventions. Pitching in to help build a much more interlinked next generation internet, and piping structured intelligent information like these examples into your website with data portability will be the consumer web of the future.

The enterprise version will be tagging and linking up all that content currently sitting in silos to make it more accessible and useful - building a centered, interconnected rich information tree of knowledge which has room to grow.

Topics: Emerging Tech, Browser


Oliver Marks leads the Global Digital Enterprise Team at HP, having previously provided seasoned independent consulting guidance to companies on effective planning of business strategy, tactics, technology decisions, roll out and enduring use models that make best use of modern collaborative and social networking tools to achieve their business goals.

These are Oliver's views and not those of his employer HP.

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  • You cannot find what you did not store...

    I agree with Oliver about the challenges and the opportunities in this space.
    I would like to add, from my experience at SAP, that you cannot find what you did not store in the system. Sounds simple, but it is not.
    As the enterprise's information 'fabic' become more complex, due to additional structured and unstructured data that been stored, more and more content/data/info is getting lost due to 'un-documented' mediums, used for collaboration and communication. For example, IM, Skype, video and other 'work-around' methods, used by creative employees...
    The Semantic Enterprise would have to be flexible and be able to handle additional 'sources' of information.

    In my daily activities at [b]Veodia[/b], I see how much integration of these new mediums (such as video) to the existing IT system is critical for the Enterprise knowledge.

    As the Enterprise is usually one (or more...) steps behind the Web, it would be interesting to see if we would be able to learn from the Semantic Web challanges.
    Etay Gafni
    • Semantic Enterprise and Employee Competitiveness

      The flaw in Etay Gafni?s comment (above) is clinging to the closed network "structure" concept while considering an approach to semantically aggregating and integrating existing and emerging classes of source content. Such clinging triggers a death-spiral of information overload induced decision paralysis and loss of competitiveness. Enterprise competiveness is at risk when not contextually aware of minute-to-minute feeds of global events and data and there ?contextual inference? on enterprise tactics and strategy.

      Each existing and emerging classes of source content has been uniquely expressed in some digital format and each continues to evolve. The grass roots innovators are not linked to any standards, but push what ever seems to be working to achieve their unique desired result. No vendor library of syntactic format-recognition code can ever scale in this creatively exploding semantic digital-object format environment. Each grass roots innovator has its own unique interpretive knowledge-base; they alone use, (Ontology) to bridge their chasm between the rich message contained and their achievement of a useful digital representation of their (semantic) message.

      However - Ontologies stay-put, they are uniquely local and should not integrate or aggregate.

      Being in command of actionable, globally interpreted, contextually relevant information is the next generation of competitive success. Ontology is the contextual-meaning-aware, interpretive community of practice?s tool enabling this next generation.

      Ontology enables ?n dimensional tagging? to populate ?n dimensional graphical representations of the meaning intended to be disclosed by the author or creator of each informational object?s content.

      The nature of a user attaining a personal competitive advantage is: being "semantically aware" of all timely-available contextual information important to that individual user - such an abstract view is "structure-less;" never within the network schema itself ? but a powerful, graph-based, semantically and context aware index engine.

      Practitioners within the field of Ontology can be found along a spectrum of constructs, from fuzzy-matching to ridged modeling. Structure is the core of the model-driven "semantic interoperability" community (think EDI "ridged" electronic data interchange). Jarg? work takes the "Fuzzy approach:" as the active thesaurus enriching the meaning of what "all human senses perceive" within a unique community of practice.

      Through our lens, Ontologies stay-put, they do not integrate or aggregate. Ontology in Jarg's fuzzy world is always a dynamic local knowledge-base, often with other structures within, such as DB schemas, non-textual object content and media content's metadata. It's a false-hood, in my view, to approach aggregating and integrating existing ontologies. Their sole purpose is the continually enrich the graphical representation (abstraction) of the meaningful teaching within all that community?s knowledge objects.

      Ontology is truly the localized interpretive, "current understanding tool" used to parse-out (and graph) the detailed (fragments of) contextual meaning within the data, knowledge, objects and media held dear by that community of practice. Ontology is groomed and nourished at the grass roots, encompassing the active thesaurus of "all the human senses" perceived by each community member and is invalid beyond that community. Their meaningful graph fragments co-exist within the powerful semantic distributed index with all other communities of practice fragments. That is the magic, enabling the next generation of search and intelligent agents to serve the need for competitive advantage of each economic and social individual and organization.

      So, I hope that you have an image of Ontology - as a localized reference of meaning; an interpretive reference-base and not the actual data, knowledge, objects and media itself. Think of the interpretive brain (as ontology) of each county ambassador during a United Nations general assembly debate. Each understands an abstract (graph) of the contextual meaning of only their country's assets and multi-facetted objectives; and, must interpret those (graph fragments), when responding to any (graph fragments) of another ambassador's question.

      Being "semantically aware" of all timely-available contextual information important to you means that you can not expect to command network bandwidth to directly query each individual global data source or listen in on all channels of live media feeds. The nature of your being "semantically aware" of all available contextually relevant information, important to you, requires a "structure-less," abstracted, contextually aware view over all accessible information sources.

      The solution is a graph-fragment index, which is your ambassador; the index's graph engine understands your needs and can effectively go to all the other ambassadors in the distributed index to discover exactly what is available within all (graphed) information sources, to fulfill your detailed requests. Then re-order all according to most contextually relevant for you.

      Enterprise competiveness is at risk when not contextually aware of minute-to-minute feeds of global events and data; and, there ?contextual inference? on enterprise tactics and strategy; as well as an individual?s professional career prospects.

      It's being in command of a "context aware fragment cloud (Jarg's index) - where your persistent, index-resident queries (agents ? routing search), are dynamically serving-up your personal information needs in real-time. The competitive advantage is only realized when you become "always contextually situation-aware."

      Ontology is local, Jarg's context aware fragment index engine is global; together they enable situation-aware, competitive advantage. "The Semantic Enterprise Advantage"

  • RE: The Semantic Enterprise

    Jenny Zaino did a nice job on our Kyield as well as
    semantic enterprise systems more generally fyi--