Today the Pew Center released a survey regarding the future of the Semantic Web. More than half of those responded didn’t think that the vision associated with the Semantic Web would be realized – that’s a startling conclusion, really. It’s even more remarkable given the fact that those who responded negatively didn’t think it would even happen by 2020.
In our last post on Intelligent Healthcare, we talked a bit about Electronic Healthcare Record systems. EHR/EMR technology is an important piece of the larger set of clinical systems as it represents a patient centric organizational framework. However; EHRs are only part of a larger picture. One area that is particularly promising for the application of Semantic technology to healthcare is process management. When we discuss process management in this context, we’re not talking about traditional process management software solutions. Healthcare process management is in a sense a formalization of (medical) practice approaches that for the most part aren’t automated and in many cases likely never can be fully automated.
Threat Management is still a relatively new concept; there is no industry standard definition for it. In fact, the few people who are talking about it right now tend to view it from at least two very different perspectives – one a product focused approach to unifying perimeter security tools and two, a practice-focused management paradigm. As it evolves, Threat Management will eventually encompass both of those perspectives and will likely become perhaps the single most important element within any given Cyber Security solution.
Much if not all of the discussion over the past two years in regards to Healthcare Modernization has revolved around the deployment of Electronic Health Records (EHR) systems. Monies were budgeted to EHR adoption in last year’s Stimulus package and more monies will be allocated towards EHR adoption as a result of the recent Healthcare Reform package. So what does this all mean in regards to Intelligent Healthcare and the application of Semantic technology? First we’ll need to take a closer look at EHRs.
In part 1 of the Cyber Security and Semantics series we discussed some of the highlights of how or where semantics may help transform the practice of Cyber Security. To under the full implications of why Semantics and Semantic Technology is so crucial for Cyber Security we need to examine more of the problem space associated with.
Some of you here already know it – many others are still asking it though – “What is the Big Deal with Semantic Technology, we don’t get it.” Fair Enough. If we had to pick one thing that crystallizes the importance of what we’re doing and link it a problem that just about everyone in IT faces today chances are we could change industry perceptions and make some real progress.
In part 1, we established that the primary focus for most Healthcare related IT initiatives is data interoperability. This is a requirement that lends itself to being solved using Semantic Technology. However, the industry is now involved in dozens of XML-based formal standards definition efforts. The standards-based approach (without mediation or mitgation by semantic technology) has lead to more expense and complexity…
Perhaps the best way to understand whether Semantic Technology has the potential to become an IT industry vertical is by measuring the demand for Semantic Technology Skills in the current job market. There is no way to predict at this point whether Semantic Technology will become associated with specific technologies (like Master Data Management) or will grow to become an integral part of all systems engineering…
Science has always been dependent on Semantics; Semantics provide the structure for knowledge organization as well as providing the foundation for reasoning processes. Semantic Technology is poised to facilitate the next generation of Scientific Methodology and knowledge exploitation.
Asessing and exploiting "market potential" is complicated. Every new technology must pass through this process in order to achieve adoption. Semantic technology faces an even more difficult challenge given the pervasive nature of its potential. However, we can help accelerate this process by providing real world problem solving examples of how this potential can be harnessed (both technically and from the business perspective).