We like to cover the innovation that is moving mainstream, such as adoption of RDF by Drupal and Facebook.

But we also like to seek out stories from the other end of the innovation pipe, to peek into the research labs. These will often be “bleeding edge”, a bit raw and obviously not ready for prime time.

We started by talking to IBM Research. IBM is one of the masters of the tricky art of connecting early stage research with strategic business priorities. So we were confident that their work would not simply be academic.

RDFa: Check. Ontologies: To Do

RDFa is clearly going mainstream, driven by the desire to be found by search engines and social networks. This is “power tagging”, easy enough for mainstream adoption.

However, creating an ontology requires serious intellectual effort. And the vision of a semantic web powered by linked open data requires ontologies. But try building an ROI case to management for ontology development when management’s view of “long term” is two quarters.

So we are keen to find areas where ontologies have been under development for some time and the pioneers are already getting some results. These early results and the base of existing ontologies creates a positive feedback loop.

Where is this positive feedback loop happening today?

The answer today seems to be healthcare.

Healthcare Is Where The Money Is

In April, we reported on where we saw companies hiring ontologists. The answer: healthcare.

Healthcare is where the money is. Healthcare accounts for about 15% of GDP in America. With ageing populations in all developed economies, it is easy to see a good return on medical breakthroughs.

But why does healthcare need ontologies?

Healthcare Has To Have Ontologies

Kavitha Srinivasa, a research manager at IBM, described the need for rich queries in systems related to clinical records or patent databases. Two examples brought this to life:

1. If the search relates to lungs, it helps if the system knows all the parts of lung.

2. If the search relates to side-effects of a particular drug, it helps if the system knows all the ingredients within that drug.

Kavitha mentioned the wealth of existing ontologies from sources such as Pubmed and University of Washington.

The critical mass of ontologies seems to exist in healthcare. There is money in this market. It is relatively easy to build an ROI case for speeding up searches and avoiding bad searches (false negatives and false positives).

This will be an interesting market to track.

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