Myths About Semantic Technology (Part I)


The most exciting integration story this year, in my humble opinion, is how semantic technology can be applied to silos.


Until now, articles on this topic have been as rare as giant pandas. But recently, I've found a slew of articles focusing on how semantic technology can and is being used to tackle enterprise information problems.


In fact, the spring edition of the PricewaterhouseCoopers Technology report is devoted to the semantic Web and semantic technology. It's available for free download, but if you don't want to read all 58 pages, ReadWriteWeb - which is quickly becoming one of my favorite sites - wrote a nice summary on how semantic technology can be applied to business data.


Likewise, the recent issue of the Data Strategy Journal is devoted to semantic technology.


These pieces provide more insight into how semantics can be applied to enterprise information, but they also help clear up a lot of popular misconceptions about semantic technology. As I read, I kept a list of the common semantic technology myths. I came up with six total. In each case, the reality behind the myth shows how significant semantic technology could become in the way that companies and organizations manage data and integration.


Because of the length, I've decided to split the list in two, sharing three today.


Myth: Semantic technology is only for the Web.
Reality: This may be the most common misconception about semantic technology, but it's just not so. As PriceWaterhouseCoopers explains in "Spinning a Data Web," semantic technology can be applied to internal systems as well:

The issues that the World Wide Web has with data semantics and data silos are simply web-scale versions of what enterprises have been struggling with for years. The term 'Semantic Web' says more about how the technology works than what it is. The goal is a data Web, a Web where not only documents, but also individual data elements are linked. .... And don't let the term 'web' fool you into thinking this approach applies only to Web-based information; the underlying technology also applies to internal information and non-Web-based external information. In fact, it can bridge data from anywhere-including your data-including your data warehouse and your business partners.

In fact, PriceWaterhouseCoopers says the semantic Web could be used to solve large-scale data integration.


Myth: The semantic Web will be separate from the one we use now.
Reality: It's not and wasn't intended to be, according to Paul Miller, who sets readers straight on this myth in "A Place in the Enterprise":

Despite some false starts, it has become increasingly clear that (Sir Tim) Berners-Lee and his peers never intended the creation of a new and separate Web created and reasoned upon by software. Rather, they anticipated the gradual enrichment of today's documents through the addition of structure; structure that whilst largely invisible to the human reader will enable additional value to be easily extracted.

Myth: Semantic Web technology is really only for accessing structured data.
Reality: I've noticed most articles on the semantic Web focus on how it will give us online access to information currently hiding in databases. While that's true, it's only part of the story. First, semantic technology could make integration simpler, as a recent Data Strategy Journal article on semantic technology and master data management explains.


Second, it can also be used for unstructured data. In fact, Thomson Reuters is already using a semantic system to provide more insight into unstructured text submitted to its service, as Miller points out in another Data Strategy Journal article, "Bringing Semantic Technologies to Enterprise Data."


On Monday, I'll share the myths that are of specific concern to businesses interested in semantic technology.