In retrospect, with SARS, there was chatter on discussion boards that pointed to a problem in Asia that was puzzling health care workers. While there was no name for the problem at the time, the discussion was largely about symptoms and the associated problems. Interestingly, the response to SARS required an unprecedented collaboration between public health resources around the globe — another KM challenge.

A virtual network of epidemiologists brought together public health institutions, ministries of health, and WHO Country Offices to analyze the spread of SARS and to define appropriate public health measures. (Learning from SARS: Preparing for the Next Disease Outbreak — Workshop Summary, 2004, p. 44)

So, lessons from the SARS experience now influence how we respond to global health issues in a flat, interconnected world. Here is the online version of the book referenced above:

And here is a paper on SARS and the KM opportunity for public health — From SARS to systems: developing advanced knowledge management for public health. [Stud Health Technol Inform. 2004;100:149-56.]

Back to swine flu. Can information sources be used to predict an outbreak like swine flu?

Google’s flu trends uses a number of terms, in aggregate, to spot trends in flu enquireies on their site. They even developed a version specific to the Mexico outbreak. The spike on this chart in January and February precedes the recognition by public health authorities.

Similarly, Veratect, a small company in Washington state [@Veratrect on Twitter] claims to have spotted this flu outbreak and notified a number of its corporate clients in advance of the general public health warnings. They were even accused of not reporting this information to Mexico authorities.

The Associated Press reports …

Veratect Inc., a 2-year-old company with fewer than 50 employees, combines computer algorithms with human analysts to monitor online and off-line sources for hints of disease outbreaks and civil unrest worldwide. It tracks thousands of “events” each month — an odd case of respiratory illness, or a run on over-the-counter medicines, for example — then ranks them for severity and posts them on a subscription-only Web portal for clients who want early warnings.

The idea fueling Veratect and similar companies is that blogs, online chat rooms, Twitter feeds and news media and government Web sites are full of data that public health agencies could use to respond faster to problems like outbreaks of swine flu.

Detecting public health outbreaks and even foiling terrorism has become more and more an information problem. Data scattered on the web can be turned into information and ultimately knowledge with the right tools and lenses. Knowledge pattern recognition has become one of the great challenges for today’s organizations and for society.

Addendum (May 26, 2009): Here is another related article from Wired — This article refers to Veratect and also HealthMap.

As I watched this story, I was reminded how even biology today is an information science. The importance of data and information to generating knowledge about this virus is underscored in stories such as this.

Enjoy.

Of particular interest, the article points to real life examples of the semantic web technology already in use by corporations and consumers. Two case studies are presented:

• work being done in the area of drug discovery at organizations such as Cincinnati Children’s Hospital Medical Center, ELi Lily, and Pfizer; and,
• health care applications such as: the initiative at the University of Texas Health Science Center “called SAPPHIRE (for situational awareness and preparedness for public health incidences using reasoning engines)” … which … “integrates a wide range of data from local health care providers, hospitals, environmental protection agencies and scientific literature.”

Consumer services are also emerging built with Semantic Web components. They point to the British firm Garlik that “uses Semantic Web software to compare previously incompatible databases to alert subscribers that they might be the target of an identity thief. Garlik culls disparate personal identity information from across the Web, integrates it using common vocabularies and rules, and presents subscribers with a clear (and sometimes surprising) view of their online identity.”

Another exemplar referenced in this article is The Friend of a Friend (FOAF) project which crosses social networking sites and other web pages to “find common interests amongst friends and acquaintances.” More recently “FOAF enthusiasts are also now developing semantic trust networks–white lists of trusted senders–as a way to fight e-mail spam.”

Other exemplars from this article include:

• Science Commons — “which helps researchers openly post data on the Web. The nonprofit organization provides Semantic Web tools for attaching legally binding copyright and licensing information to those data. This capability allows a scientist, for example, to instruct a software applet to go find information about a particular gene–but only information that comes with a free license.” … and,
• DBpedia – “… an effort to smartly link information within Wikipedia’s seven million articles. This project will allow Web surfers to perform detailed searches of Wikipedia’s content that are impossible today, such as, “Find me all the films nominated for a Best Picture Academy Award before 1990 that ran longer than three hours.” …”
• A demonstration Semantic Web site by Oracle Technology Network “that can analyze blogs, podcasts and discussion groups to find related commentary about specific topics.”

Finally, the authors of this article remind us that most of the Semantic Web will be transparent and we won’t realize how companies are providing improved information and services. They do illustrate the effect of this technology with this illustration:

“… soon enough the Semantic Web will give more direct power to us, too, allowing us to go on eBay and not just say “find me the Toyota Priuses for sale” but “find me only used, red Priuses for sale for less than $14,000 by people who are within 80 miles of my house and make them an offer.” …”

I particularly like this illustration as it points to future potential for serch technologies that can be enabled by Semantic Web technologies and frameworks.

It is through practical applications like those illustrated in these cases and exemplars that the “grand vision” of the Semantic Web will be realized.