07 Sep Quest for the Knowledge Enterprise
As an Intelligence Professional, my mission was to seek out information that others were trying to conceal. Do you ever feel like that is too often your task when trying to find the answers to life’s persistent questions, or even something you need to buy? In an enterprise, those answers may be hidden in someone’s brain, in a document (unstructured data) or in a database (structured data). Worse, pieces of the answer may be spread out in multiple places and formats. Many, including Shannon and Kolmogorov have proposed frameworks to evaluate information complexity and its impact. Until we can build intelligent automated helpers for your search, the problem will continue, and grow…
The definition of Knowledge Enterprise is in flux. I think it is generally agreed that most workers in the information economy are knowledge workers. The key enablers are smarter information systems and processes. Is the Knowledge Enterprise the one that delivers the most knowledge to users (Google lead the pack for the 2010 MAKE award)? Or is it the one that best empowers its own with the knowledge they need to perform their knowledge tasks?
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A key benefit to understanding context and enabling devices and systems to deliver actionable information is that organizations and businesses of all sizes will be able to spend less time juggling content and more time using it. Smarter systems will juggle it for you and deliver what you really need more quickly. This becomes more important as the complexity and quantity of information grows (see Francis Heylighen of Belgium) leading to loss of control. Heaven knows that’s happening everywhere, especially with the rise of social media and its burgeoning universe of content. Too many more needles – Too many more haystacks!
Mike had an idea. http://mike2.openmethodology.org/ describes a framework and methodology for Enterprise Information Management that includes many of the components needed to move from information systems to knowledge systems. But even Mike remains squarely inside the boundary of traditional information processes and lacks the clear pathway to knowledge processing (as opposed to smarter information processing).
How would you evaluate the Knowledge Profile of your organization? Organizations like Teleos make a business of evaluating Enterprise Knowledge capabilities. The social revolution, with its expanding raft of ways to measure your social outreach effectiveness, may seem more important to many companies today. And for the marketing folks, putting reliable metrics around social content and interaction is very important. For IS folks, the importance of maturity of knowledge processing capabilities will increase rapidly as all the organization’s knowledge workers feel growing need to aggregate content from more sources of structured and unstructured knowledge.
My belief is that the information floodgates are already open, and the companies that compete most effectively will be the ones that learn to ride the big wave of social content. Few organizations will be able to do so without smart planning. The key will be to build new processes to push all new content through knowledge engines to sort, categorize and exploit the buried gems of knowledge as it flows in. AI and expert systems gave us a taste of what computers can do. Big data and content convergence are opening new vistas daily, supporting new models for knowledge representation and optimization. I intend to show how systems with ontologies capable of processing and understanding human language in context, in conjunction with big data approaches will deliver more actionable knowledge to more people.
|Click below to look in each Understanding Context section|
|4||Perception and Cognition||5||Fuzzy Logic||6||Language and Dialog||7||Cybernetic Models|
|8||Apps and Processes||9||The End of Code||Glossary||Bibliography|