Over the years, I've had people ask me how a taxonomy differs from an ontology. The answer (or at least a reasonably simple answer) is that "a taxonomy is a tree shaped ontology".

It is worth digging  bit deeper to understand what that means, however:

Way back in the early 18th century, a Swedish biologist by the name of Carl Linnaeus…

Marketing, at least in the IT sector, has been replaced by memes. Every so often a Gartner slide deck goes viral, and the next thing anyone knows, pithy and mostly meaningless phrases and sayings are driving Fortune 500 strategies. Execs commit to multi-billion-dollar initiatives to make sure that their companies are perceived as being hip or cool (or,…

Tips

1. Don't try to put the cart before the horse: realize that efficient data preparation (and thus interoperable standards) and data quality, especially in the enterprise environment, are a basic requirement for…

A researcher from the IICSE University DE, United States, has come up with trivial examples that put down the 6-Degree Theory, the theory that made Kevin Bacon appear in association with Academia online, Bacon.

Amongst those,…

1. Hybrid approach: Semantic AI is the combination of methods derived from symbolic AI and statistical AI. Virtuously playing the AI piano means that for a given use case various stakeholders, not only data scientists, but also process owners or subject matter experts, choose from available methods and tools, and collaboratively develop workflows that are most likely a good fit to tackle the underlying problem. For example, one can combine entity extraction based on…

Will Artificial Intelligence make subject matter experts obsolete?

Imagine you want to build an application that helps to identify wine and cheese pairings. Who will perform best? Applications solely based on machine learning, those ones which are based on experts' knowledge only, or a combination of both?

Most of the machine learning algorithms were…

Things, not Strings

Entity-centric views on enterprise information and all kinds of data sources provide means to get a more meaningful picture about all sorts of business objects. This method of information processing is as relevant to customers, citizens, or patients as it is to knowledge workers like lawyers, doctors, or researchers. People actually do not search for documents, but rather for facts and other chunks of information to bundle them up to provide answers to…

 Guest blog by Greg Roberts at Packt Publishing

(to see this graph in its fully interactive form see http://gregroberts.github.io/)

I love Python, and to celebrate…

NASA is using big data to make complex knowledge more readily available. Learn how graph visualization can help turn large corpus of documents into concrete insights.

A database of lessons learned

Even in a mature and knowledge-driven organization like NASA, finding an answer to a common business issue can be frustrating. Past surveys at NASA have shown that most people have trouble finding the…

How many times a day do we ourselves, or hear someone else, utter the phrase “Google it”? It’s hard to imagine that a phrase so ubiquitous and universally understood has been around for less than two decades. The word “Google” has become synonymous with online search, and when we think about why this, it’s because Google yields the most relevant, comprehensive results, quickly. Essentially, it has changed the way we find and interact with content and information.

We’ve seen the…

Organizations are struggling with a fundamental challenge – there’s far more data than they can handle.  Sure, there’s a shared vision to analyze structured and unstructured data in support of better decision making but is this a reality for most companies?  The big data tidal wave is transforming the database management industry, employee skill sets, and business strategy as organizations race to unlock meaningful connections between disparate sources of…

As a long-term member of the Linked Data community, which has evolved from W3C's Semantic Web, the latest developments around Data Science have become more and more attractive to me due to its complementary perspectives on similar challenges. Both disciplines work on questions like these:

• How to extract meaningful information from large amounts of data?
• How to connect pieces of information to other pieces in…

On 19^th…

Here’s a brilliant presentation from Mike Bowers, Principal Engineer at the Church of Jesus Christ of Latter Day Saints.  It accomplishes two major objectives; Mike reviews the strengths and weaknesses of the five major classes of databases today (relational, dimensional, object, graph and document).  He then dissects the major NoSQL databases on the market including MarkLogic, Mongo, Riak, Cloudant/Couch DB and Cassandra.  How do they stack up? Are they enterprise ready?  If developer…