Over on my personal blog, I've written a couple of posts that outline two key thoughts on the transformative effects that Semantic Web technologies can have in the enterprise:
There's a key corrollary of these two observations that you need to keep in mind when building, browsing, or buying Semantic Web software. Semantic Web software must be easy to use.
On the surface, this sounds a bit trite. Surely we should demand that all software be easy to use, right? While ease of use is clearly an important goal in software design in general, I'd argue that it's absolutely crucial to successfully realizing the value from Semantic Web software. Here's why:
Software that is hard to use has two main effects. First, it frustrates and annoys the user. Users won't choose to use frustrating software for any more tasks than they absolutely have to. Second, hard to use software limits the audience who can benefit from it. This is particularly true for software that is hard to use because it is complicated. If a software application lacks an intuitive user experience, demands that users be familiar with URIs, RDF, or OWL, or requires knowledge of (or learning) an analytics or data access language like MDX or SQL, then it is immediately limiting its use to IT professionals, a small fraction of a company's employees. If a business manager wants to accomplish something with this hard-to-use software, they've no other option but to schedule time with IT, define their requirements, and wait for the results. And all of this takes significant calendar time; enough time, in fact, that it marginalizes the calendar time benefits promised by the flexibility of Semantic Web technologies.
In short, if Semantic Web software is hard to use, then many of the benefits of using these technologies in the first place are immediately lost.
Conversely, if Semantic Web software is easy to use, on the other hand, then the benefits of Semantic Web technologies' flexibility are brought directly to the end user, the business user. The business manager can bring together new data sets for analysis today, rather than a week for now. An analyst can setup triggers and alerts to monitor for key business indicators today, rather than waiting 3 months. A senior scientist can begin looking for correlations within ad-hoc sets of data today, rather than next year.
We try our best to take this to heart at Cambridge Semantics. We call it reach, and it forms one of our core guiding principles as we develop Anzo. Simply stated, reach means that all capabilities of the software should be usable by as broad a universe of users as possible. This is one of the reasons that we built one of our very first applications around collaborating with Microsoft Excel. But we also bring reach to other areas, from allowing end users to easily connect database data, to driving analytics via simple Excel formulas, to giving users the ability to define their own rules and alerts on the fly, to providing Anzo on the Web as an easy to use, self-service dashboard application for interacting with Semantic Web data.
