Semantic intelligence
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The document introduces the concept of semantic intelligence, which represents the ability to process data and information based on semantic patterns and rules to gain insight. It also represents the ability to harness shared knowledge in a more efficient, automated way across organizations. Semantic intelligence is defined as supporting complex data relationships, combining structured and unstructured data, complex visualization, rules and knowledge collaboration. It has the potential to unify analytic approaches and technologies to provide a more specific set of solution expectations.
Semantic intelligence
- 2. The Future Begins… with an idea Web Servers are one thing, Nuclear Reactors are a bit more dangerous – there are systems which absolutely must not FAIL. Innovation represents the deliberate attempt to change current reality. Those who believe that things can be better or can be done better have the motivation to pursue change – Innovation is the roadmap or blueprint for that change. The Future consists of thousands of such blueprints coming together to build a new reality – Innovation Worx is dedicated to providing consistent and actionable Innovation for you both through our consulting and our presentation series.
- 3. It’s All Semantics “ All our work, our whole life is a matter of semantics, because words are the tools with which we work, the material out of which laws are made, out of which the Constitution was written. Everything depends on our understanding of them.” – Felix Frankfurter Semantics is misunderstood and mostly unappreciated, both in the larger generic sense as well as in current IT practice. This is remarkable considering that Semantics represents a cross-cutting capability specifically dedicated to reducing complexity and deriving meaningful information…
- 4. The Premise Words help us to describe complex concepts without quite so much explanation or research…
- 5. Expanding the IT Lexicon The IT arena has produced thousands of new words to the English language since its inception and many more acronyms. When introducing a new term several questions ought to be kept in mind: Is the term really necessary? Can the word help to solve challenges related to the field (caused by the current lack of clarity)? Is the word just for marketing purposes or does it instead convey an important technical / solution connotation?
- 6. Rationale for Introduction Before we define what Semantic Intelligence is; let’s examine some of the reasons why this term is needed: The field of Semantic Technology has expanded rapidly over the past 5 years; however there is still a gap in understanding as to how it can be applied to real world situations. The disciplines known as Business Intelligence and Decision Support are merging rapidly with Semantic technology. There needs to be a term that properly explains both the nature of the solution and its functionality when it comes to aiding cognition.
- 7. Learning from shared experience or knowledge is how civilization evolved. IT needs to embrace a paradigm that doesn’t always require building solutions from scratch everywhere at the same time.
- 8. Business Intelligence Current IT practice refers to analytic capabilities in several ways; including Business Intelligence, Decision Support, Dashboards, Reports etc. Each of those terms tends to be fairly generic – e.g. any number of solution approaches may be used to develop them. What they share in common is value added examination of underlying data sources based upon defined expectations (queries, rulesets etc.) The great shortcoming of the current paradigm is the inability to share insight or knowledge across enterprises, globally. This leads to a tremendous amount of redundant work for all parties.
- 9. Related Term: Semantic Web The industry definition for this Semantic Web is: “ a web of data that facilitates machines to understand the semantics, or meaning, of information on the World Wide Web. It extends the network of hyperlinked human-readable web pages by inserting machine-readable metadata about pages and how they are related to each other, enabling automated agents to access the Web more intelligently and perform tasks on behalf of users.” If you delve a little further you’ll find references to other terms such as Linked Data, Inference, Vocabulary and Vertical Applications as well as about a dozen standards such as RDF and OWL.
- 10. What if much of the discovery we engaged in online followed predetermined search paths or highways?
- 11. What is the Semantic Web, Really ? This question has perplexed many inside and outside of the IT community for the past decade, despite numerous concerted efforts to educate or otherwise increase awareness. So why hasn’t it caught on, what is hindering adoption? Maturity is one factor, but we’ve already had many years to work with the Semantic Web. Here’s our theory; the term Semantic Web doesn’t necessarily clearly explain the “what” effectively. It represents an end state rather than a specific capability. Such a complex set of capabilities requires more specific description and descriptors that are easily identifiable in context with one another.
- 12. Related Term: Semantic Technology This term is a bit more straightforward as it does clearly represent capability (or in this case a set of related capabilities). The one possible area of confusion relates to whether specific Semantic tools or technology must be built upon published Semantic Web standards or whether they support a somewhat wider set of Semantic Integration practices. An example of the confusion occurred this year when IBM’s Watson defeated Jeopardy’s all time champions. While Watson wasn’t built around Semantic Web standards it was built on a foundation of semantic reasoning and integration.
- 13. Watson demonstrated a number of key capabilities associated with Semantic Intelligence including intelligent search, inference and assignment…
- 14. Related Term: Semantic Enterprise The Semantic Enterprise is a variation of the larger end state term ‘Semantic Web.’ It is meant to represent a prototypical organization that has empowered its IT and Business capability through application of a Semantic Architecture & Lifecycle ( which can be considered part of Semantic Integration ) . Thus a Semantic Enterprise exhibits a number of specific capabilities including Semantic Intelligence, Intelligent Search and Content Management and it utilizes Semantic Integration to guide its solutions lifecycle.
- 15. Semantic Intelligence, Defined Semantic Intelligence exists at two levels; first it represents the immediate (local) ability to process data and information-based semantic patterns and rules in order to gain insight or add value. Secondly it represents on a larger (global) perspective the ability to harness shared knowledge in a more efficient, automated fashion. The second part comes later as more organizations make value enhanced information available in global communities. This process has already begun through development and sharing of Ontologies but Ontologies are only the tip of the iceberg.
- 16. Definition, planning and coordination need to occur not just at the individual solution level but also the meta-solution level – if one wants or expects wide adoption for a meta-solution framework.
- 17. Characteristics of Semantic Intelligence It must support the ability to build and exploit complex data relationships (RDMS supports only simple relationships). It must allow for combination of structured and unstructured data / information (this will often occur by using ontologies or other shared foundation tools). It must support complex visualization. It must support complex rulesets and enterprise-wide (and beyond) knowledge collaboration and aggregation. It must also apply to and integrate within a larger unified Semantic solution framework
- 18. Implications of Semantic Intelligence Semantic Intelligence has the potential to unify a variety of analytic approaches, tools or disciplines. It can accomplish this by providing a more specific set of solution expectations. Semantic Intelligence will likely have an important impact on other related technologies such as Content Management & Publishing, Search Management and other applications (such as ERP) that have significant analytic components. Most importantly, Semantic Intelligence is a near term approach towards beginning to realize the larger potential associated with the Semantic Web.
- 19. Conclusion In order to properly exploit a thing – that thing must be well defined and understood. The Semantic Web in fact represents dozens of concepts and technical standards but has yet to fully effectively define how they fit together. Moreover, there has been little or no definition in regards to the methodology for exploiting those capabilities. As part of our Redefining the IT Lexicon we will provide several more presentations to help better define what Semantics in IT represents and how it can be exploited right now…
- 20. Thought Leaders, Enterprise Solutions Providers…
- 21. Semantech Inc. is InnovationWorx Semantech Inc. is a solutions provider founded in 2007. Our company is located in the Dayton, Ohio metro area. Since our inception we have supported clients in a more than half a dozen industries nationwide. Our company represents a unique approach – we’re not offering just IT or Management Consulting. We specialize in facilitating complex organizational Transformations. This is why Innovation Worx was created. Semantech was founded to facilitate change…