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"For about five years around the turn of the century most of my days were spent helping clients manage their knowledge. Back in 2000 knowledge management (KM) was really big. Every year I'd head off to Amsterdam for the obligatory industry conference, KM Europe. We even had our own home grown conference, KM UK, with pretty much the same people but with less impressive venues. Then suddenly things went quiet - KM Europe was suddenly cancelled in 2005, KM UK limped along (and is still going today). KM had lost its way. The promises hadn't been fulfilled. Of course KM just didn't disappear overnight - it just degraded gracefully. One client, a very large UK multinational, shed their KM teams and announced that KM was now 'embedded in the business'. KM still goes on but it's likely to be on the margins and not essential for peak organisational performance whereas in 2000 KM really was positioned as a game changer. So what happened? That's a good question and one which this post is my first attempt at exploring why KM failed to deliver on its early promises. And why do this sort of navel gazing now? Because knowledge management appears to be making a comeback but this time it has a shiny new suit and it's called social learning."

Sense-making consists of both asking and telling. It's a continuing series of conversations. We know that conversation is the main way that tacit knowledge gets shared. So we continuously seek out explicit knowledge, in the form of written work or other knowledge artifacts left by others. We then have conversations around these artifacts to make sense of them. Finally, we share new, explicit knowledge artifacts which then grow our bodies of knowledge. Sharing closes the circle, because being a personal knowledge manager is every professional's part of the social learning contract.

"In this video I describe the Three Eras of knowledge management that I have previously written about on this blog, Where Knowledge Management has Been and Where it is Going - Part One, Part Two, and Part Three."

"At Reebok, the cushioning in a best-selling basketball shoe reflects technology borrowed from intravenous fluid bags. Semiconductor firm Qualcomm's revolutionary color display technology is rooted in the microstructures of the Morpho butterfly's wings. And at IDEO, developers designed a leak-proof water bottle using the technology from a shampoo bottle top. These examples show how so-called "peripheral" knowledge - that is, ideas from domains that are seemingly irrelevant to a given task - can influence breakthrough innovation. "The central idea of peripheral knowledge really resonates," says Wharton management professor Martine Haas. After all, who can't think of examples when ideas that seemed to bear almost no relation to a given problem paid off in some unexpected way? By bringing peripheral knowledge to core tasks, it is well known that work groups can recombine ideas in novel and useful ways. But the problem, Haas notes, is primarily one of attention: How do you get workers focused on a particular task to notice - and make use of - seemingly irrelevant information?"

"Virtually everywhere one looks we are in the midst of a transition for how we organize and manage information, indeed even relationships. Social networks and online communities are changing how we live and interact. NoSQL and graph databases - married to their near cousin Big Data - are changing how we organize and store information and data. Semantic technologies, backed by their ontologies and RDF data model, are showing the way for how we can connect and interoperate disparate information in ways only dreamed about a decade ago. And all of this, of course, is being built upon the infrastructure of the Internet and the Web, a global, distributed network of devices and information that is undoubtedly one of the most important technological developments in human history. There is a shared structure across all of these developments - the graph. Graphs are proving to be the new universal paradigm for how we organize and manage information. Graphs have an inherently expandable nature, and one which can also capture any existing structure. So, as we see all of the networks, connections, relationships and links - both physical and informational - grow around us, it is useful to step back a bit and contemplate the universal graph structure at the core of these developments. Understanding that we now live in the Age of the Graph means we can begin studying and using the concept of the graph itself to better analyze and manage our interconnected world. Whether we are trying to understand the physical networks of supply chains and infrastructure or the information relationships within ontologies or knowledge graphs, the various concepts underlying graphs and graph theory, themselves expressed through a rich vocabulary of terms, provide the keys for unlocking still further treasures hidden in the structure of graphs."

Frequently customers ask me why semantic technologies should be used instead of conventional information technologies. In the areas of knowledge representation (KR) and knowledge management (KM), there are compelling reasons and benefits for selecting semantic technologies over conventional approaches. This article attempts to summarize these rationales from a layperson perspective.

Managing Information Overload is without doubt one of the most important skills an individual can develop today.  With the massive increase in information availability, and with it bombarding us every day, we see people and organisations struggling to maintain their performance as they get weighed down.

"There are many explanations for today's uncertain economy. But Nobel economist Joseph Stiglitz of Columbia University has advanced an analysis that's starting to resonate. In a recent article, Stiglitz says that our problem is "rooted in the kinds of jobs we have, the kind we need, and the kind we're losing, and rooted as well in the kind of workers we want, and the kind we don't know what to do with." To advance our economy, Stiglitz believes that wrenching, fundamental change is required - no less dramatic than the shifts experienced by an earlier generation during the Great Depression. While Stiglitz and I work in different worlds, I see evidence in all types of organizations that we need to better prepare, train, and inspire successful self-directed learners to meet today's challenges. As I see it, there are two big questions to consider. First, what are the critical 21st century skills that the workforce of tomorrow needs to develop and master today? Secondly, how can we improve our learning methods to enable the self-directed learner to thrive in this new environment?"

There is a growing demand for the ability to connect to others. It is with each other that we can make sense, and this is social. Organizations, in order to function, need to encourage social exchanges and social learning due to faster rates of business and technological changes. Social experience is adaptive by nature and a social learning mindset enables better feedback on environmental changes back to the organization.

Value Networks and the true nature of collaboration meets this challenge head on with a systemic, human-network approach to managing business operations and ecosystems.