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"The sensational rise of Big Data within the reporting and analytics realm resembles an uncanny likeness to the escalating popularity of bothersome big-haired British boy 'band', One Direction."

While there may not be a semantic application that can go to work on every issue that requires grappling with Big Data, it certainly has a role to play in many of them. Throw out outliers such as using power grid data to optimize power distribution, and "the lion's share of big data problems are semantic problems," says Dachis Group CTO Erik Huddleston.

"The force driving the most radical change in organizations today is knowledge gained and shared through social media, the great amplifier of our time. Businesses can't hide from the expectations of customers and employees (the iPhone 5). Governments can't hide from the expectations of citizens (the Arab Spring). And trainers can't hide from the expectations of learners. A counterpart to information exchange through social media is the ability to collect and analyze enormous amounts of data about customers, partners, markets, and other quantifiables. Big Data, as it is called, allows companies to respond rapidly and with relevance to their constituents, and leaves them few excuses when they don't."

The world today is filled with information. This proliferation makes it quite overwhelming to make good sense of "big data" that is continuously flowing in from a variety of new sources. In the past, the way to get things done was to keep data close, using small teams to sift through it. But now, people are used to having information at their fingertips. They're accustomed to sifting through it and coming up with new solutions, getting insights in unexpected ways.

"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."

Our company is a science-oriented company, and the core belief is that behavior - human or otherwise - can be mathematically expressed. Yes, people make irrational value judgments, but they are driven by common motivation factors, and the math expresses that. I look at the so-called "big data phenomenon" as the instantiation of human experience. Previously, we could not quantitatively measure human experience, because the data wasn't being captured. But Twitter recently announced that they now serve 350 billion tweets a day. What we say and what we do has a physical manifestation now. Once there is a physical manifestation of a phenomenon, then it can be mathematically expressed. And if you can express it, then you can shape business ideas around it, whether that's in government or health care or business.

"Discovery is the most important business capability in the emerging Age of Insight - it's the missing ingredient that makes Big Data a source of value for businesses and people. The Language of Discovery is an essential tool for providing discovery capability, whether at the scale of designing a single discovery application, determining the value proposition of a new product or service, or managing a strategic portfolio of technology and business initiatives. This presentation outlines the Age of Insight, and suggests deep structural and historic precedents visible in the Age of Reason, especially in the central parallels between Natural Philosophy and the emerging discipline of Data Science. We then review the language of discovery, and consider widely visible examples of products and services that demonstrate the language. We review our own usage of the framework as an analytical and generative toolkit for providing discovery capability, and share best practices for employing this perspective across a variety of levels of need."

"Over the past few decades, Moore's Law, processor speed and hardware scalability have been the driving factors enabling IT innovation and improved systems performance. But the von Neumann architecture-which established the basic structure for the way components of a computing system interact-has remained largely unchanged since the 1940s. Furthermore, to derive value, people still have to engage with computing systems in the manner that the machines work, rather than computers adapting to interact with people the way they work."

A big problem with contextualizing information is that machines still cannot think. They are only able to do calculations, so everything we do to contextualize data in a software system must be "reduced" to statistics and mathematics. When a certain problem cannot be solved using mathematics (and there are many of them!) then the user must jump in.

"Today, we are at the dawn of another epochal shift in the evolution of technology. At IBM Research, we call it the era of cognitive systems. This is a big deal. The changes that are coming over the next 10 to 20 years-building on IBM's Watson technology-will transform the way we live, work and learn, just as programmable computing has transformed the human landscape over the past 60+ years. You could even call this the post-computing era."

Slides from my keynote this afternoon in Paris at the Enterprise 2.0 SUMMIT. Overview of where social business is, what the macro trends are, and the story about consumerization, big data, analytics, and much more.

What do Color, Quora, Hunch, Blippy, and StockTwits have in common? They are examples of companies that generate value for their users by leveraging the concept of the Interest Graph. The list also features some of the most promising startups right now, having raised close to $100 million in venture funding. Pure coincidence?

Gamification is the latest buzzword on the street. It ranked a keynote panel session at Enterprise 2.0 in November and it was one of two main topics discussed at the recent Institute for Social, Search and Mobile Marketing (ISSMM) K1 Executive Roundtable.