In preparation for attending the second annual Conference on Semantic Web in Healthcare and Life Science (CSHALS 09) next week, I have been reviewing my notes from last year's conference. As I twittered yesterday, my favorite line last year was from conference chair Eric Neumann (herewith properly attributed, unconstrained by the 140 character twitter limit): “What do we mean by semantics?”
The semantic web is all about providing meaning that computers can read (or “understand”, to the level that they can infer new knowledge from old). Using one of the foundational standards, RDF, each semantic web statement is called a “triple” since it is constructed of subject-verb-object triple. Examples would be “Venturecyclist is-a blog” and “Venturecylist is-authored-by Richard-Dale” and “Richard-Dale is-a Venture-Capitalist.” From this, the right kind automated inference engine could calculate “Venturecyclist is-authored-by a-venture-capitalist.” As you can see, writing even simple knowledge in this form is verbose (lots of triples for even simple statements of knowledge). When there are enough triples (millions, or even billions), then automated inferencing does actually produce interesting and novel information, as reported in Scientific American, for example.
Eric Neumann also provided a wonderful definition of the goal of the semantic web community, semantic interoperability: automated interoperating systems where a consumer of semantic web content understands all the needed context and meaning of the content, whatever the use of the content, even though the publisher knows nothing of the use case of the recipient.
My own extension to this is that the publisher should self-certify which ontologies and authorities they are using in publishing the content, and there should be an annotation system available (like link-backs), which allows for anyone to add their own semantic annotations. Self-annotation might include provenance of a triple (where it came from, source, current level of confidence in its truth etc).
In the healthcare arena, semantic web technologies allow for combining clinical data about a patient (Patient blood-sugar-level-is X) with standards of care (Blood-sugar-level-threshold is Y) and (Insulin treats blood-sugar-above-threshold). As life science researchers in the lab discover new knowledge about genes, proteins, pathways and treatments, then this can be matched with clinical data about patients in semantically interoperating systems. This allows for further clinical data about populations to inform further research and also, as implied above, for prescribing evidence based treatments.
This may all seem a little esoteric; it is, and it is still a series of commercially untested technologies (see yesterday's post on betting the bank). However, consider how easy it is to contribute photos and more to Google Earch. KML files are used by Google Earth (and other apps) to provide geographic meaning to anything from photos to facts. KML may not, strictly, be expressed in triples, but it provides an interesting example where real meaning (in this case, of geography) is available in machine-readable form, usable by any application that wants it. Imagine Google Body or Google DNA or Google Heart, where all the lab and medical knowledge can be combined in a model of our body or our DNA or our heart, the same way anyone can contribute new material for Google Earth using KML. As a triple, my conclusion would be:
--> (That-idea has value).
Bet the Bank
With IT spending running as high as 25% of revenue, and a risk-taking culture, Wall Street firms are old favorites as customer prospects for venture capital backed startups.
It is tough to sell information technology products to Wall Street firms right now (if you can find any left). Balance sheets are shrinking, employee counts are shrinking, budgets are shrinking and risk taking has pretty much disappeared. However, smart vendors and smart buyers know that these times of retrenchment can be great times for the right kind of IT investment. In general that means something that pays for itself in a few months even in periods of severe contraction, something that is proven in the field, and provides new capabilities for when the economy starts to pick up, leaving competitors in the dust. This doesn't just go for Wall Street, but for many (or even any) large enterprises.
When thinking about new technology, large enterprises tend to think about whether the new technology has been field-proven to scale and perform, and trade that off against the risks of the new technology failing. Obviously a new, unproven technology will be more readily adopted if it doesn't cause too much harm if it fails a few times. If it is a "bet the bank" situation, then you can bet that only proven technology will be considered.
Here is a chart that illustrates the point, using Sigma Partners portfolio company examples, of course. EqualLogic (sold to Dell last year) provides very stable, low risk, more efficient disk storage systems. Initiate's software for bringing together data about customers from multiple systems is also very well proven, but is used in very high-profile applications (eg call centers) and if it fails then the call center operations may cease. As yet unproven software (at least in commercial applications) such as Acquia's editions of the open source Drupal system can be adopted for intranets and other low-risk areas of a corporation. No-one ever buys "bet the bank" technology which has not been field tested and proven to scale.
How does this compare to my life as a venture cyclist, and most people's buying habits? Answer: it's pretty similar. I am happy to buy a new, fangled "unproven" pair of biking gloves, but I would like my helmet to have a good pedigree!
It is tough to sell information technology products to Wall Street firms right now (if you can find any left). Balance sheets are shrinking, employee counts are shrinking, budgets are shrinking and risk taking has pretty much disappeared. However, smart vendors and smart buyers know that these times of retrenchment can be great times for the right kind of IT investment. In general that means something that pays for itself in a few months even in periods of severe contraction, something that is proven in the field, and provides new capabilities for when the economy starts to pick up, leaving competitors in the dust. This doesn't just go for Wall Street, but for many (or even any) large enterprises.
When thinking about new technology, large enterprises tend to think about whether the new technology has been field-proven to scale and perform, and trade that off against the risks of the new technology failing. Obviously a new, unproven technology will be more readily adopted if it doesn't cause too much harm if it fails a few times. If it is a "bet the bank" situation, then you can bet that only proven technology will be considered.
Here is a chart that illustrates the point, using Sigma Partners portfolio company examples, of course. EqualLogic (sold to Dell last year) provides very stable, low risk, more efficient disk storage systems. Initiate's software for bringing together data about customers from multiple systems is also very well proven, but is used in very high-profile applications (eg call centers) and if it fails then the call center operations may cease. As yet unproven software (at least in commercial applications) such as Acquia's editions of the open source Drupal system can be adopted for intranets and other low-risk areas of a corporation. No-one ever buys "bet the bank" technology which has not been field tested and proven to scale.
How does this compare to my life as a venture cyclist, and most people's buying habits? Answer: it's pretty similar. I am happy to buy a new, fangled "unproven" pair of biking gloves, but I would like my helmet to have a good pedigree!
All Atwitter
If you have not thought much about Twitter, it is time to start thinking. If you think Twitter is just for meaningless chatter, or twenty-something time-wasters, then think again.
Did you hear that the first report, and photo, of the "Miracle on the Hudson" was on Twitter (an example of "crowd powered media")? Did you know CNN (and other news sources) publish important breaking news on twitter, and they really do reserve it for important stories?
What is Twitter anyway?
Twitter is a micro-blogging service for sending out updates of up to 140 characters (exercise to reader: why 140 characters?). Yes, it started as a way to tell your friends that you were awake, brushing teeth, drinking coffee, reading paper ... . But, like the telephone, email, blogs - all equally attractive time-wasters for socialites - new and important utility is emerging.
You can "follow" other people's tweets; I follow CNN, Jeff Pulver, and others; I don't follow the GOP, John Cleese, the UK Prime Minister, Darth Vader (brilliant), or, ... well you get the picture.
You can look at what's hot right now, or how the twittersphere treated a topic recently. You can track specific keywords on twitter (using either twitter search or, even better, TweetGrid or TweetDeck), to see what people are saying about you, your town, your employer, your competitor, your favorite charity. Did you know that someone unauthorized might be misrepresenting you, your company or your favorite charity (check out this Exxon-Mobil story)?
Some folks conjecture that all this may even be a threat to Google's predominance - and from that viewpoint, twitter really is a superior human powered search engine. However, I think there is both more and less to twitter than that. Twitter is less in that it is not about search, and it has a weak position to become a search leader (too easy to spam). Twitter is more in that it is as powerful as email has been, certainly more powerful than blogs, to change how we find and publish information and how we interact with our friends and the world around us.
Get going on Twitter.
Get an account. Go slow. Follow some folks. Don't believe me ... look at what David Pogue (NYT) has to say, and, in a similar vein, see 8 Useful Tips To Become Successful With Twitter.
Did you hear that the first report, and photo, of the "Miracle on the Hudson" was on Twitter (an example of "crowd powered media")? Did you know CNN (and other news sources) publish important breaking news on twitter, and they really do reserve it for important stories?
What is Twitter anyway?
Twitter is a micro-blogging service for sending out updates of up to 140 characters (exercise to reader: why 140 characters?). Yes, it started as a way to tell your friends that you were awake, brushing teeth, drinking coffee, reading paper ... . But, like the telephone, email, blogs - all equally attractive time-wasters for socialites - new and important utility is emerging.
You can "follow" other people's tweets; I follow CNN, Jeff Pulver, and others; I don't follow the GOP, John Cleese, the UK Prime Minister, Darth Vader (brilliant), or, ... well you get the picture.
You can look at what's hot right now, or how the twittersphere treated a topic recently. You can track specific keywords on twitter (using either twitter search or, even better, TweetGrid or TweetDeck), to see what people are saying about you, your town, your employer, your competitor, your favorite charity. Did you know that someone unauthorized might be misrepresenting you, your company or your favorite charity (check out this Exxon-Mobil story)?
Some folks conjecture that all this may even be a threat to Google's predominance - and from that viewpoint, twitter really is a superior human powered search engine. However, I think there is both more and less to twitter than that. Twitter is less in that it is not about search, and it has a weak position to become a search leader (too easy to spam). Twitter is more in that it is as powerful as email has been, certainly more powerful than blogs, to change how we find and publish information and how we interact with our friends and the world around us.
Get going on Twitter.
Get an account. Go slow. Follow some folks. Don't believe me ... look at what David Pogue (NYT) has to say, and, in a similar vein, see 8 Useful Tips To Become Successful With Twitter.
Top 10 Lies; Top 10 Truths
Some great reading for your weekend.
Guy Kawasaki has a couple of posts from 3 years ago which still ring true:
And some truths from elsewhere:
Guy Kawasaki has a couple of posts from 3 years ago which still ring true:
And some truths from elsewhere:
- Top Ten Truths About the Digital Ecosystem from Geoffrey Moore
- 10 Harsh Truths About Corporate Websites from Smashing Magazine
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