Mining Twitter Hashtags for Bad Drug Interactions

Over the years, its not been uncommon to get asked what value I see in Twitter. While my typical answer revolves around the value I get from it personally (keeping up, observing trends, sharing items of value, healthy stimulation from the seemly random sharing from others), this article, “New Role for Twitter: Early Warning System for Bad Drug Interactions” from the University of Vermont, provides an example of something pretty compelling from the academic realm.

And the research team also aims to help overcome a long-standing problem in medical research: published studies are too often not linked to new scientific findings, because digital libraries “suffer infrequent tagging,” the scientists write, and updating keywords and metadata associated with studies is a laborious manual task, often delayed or incomplete.

“Mining Twitter hashtags can give us a link between emerging scientific evidence and PubMed,” the massive database run by the U.S. National Library of Medicine, Hamed said. Using their new algorithm, the Vermont team has created a website that will allow an investigator to explore the connections between search terms (say “albuterol”), existing scientific studies indexed in PubMed — and Twitter hashtags associated with the terms and studies.

Correlating the use of hashtags to potential real world events, in this case drug interactions, can create a potential early warning system that can feed other more traditional practices. This brings to mind related things like Google’s monitoring of flue trends, where public health institutions can also benefit–not just paid advertisers.

I suppose a better answer to the value question should include the exciting thought of what innovation is to come.

(Source)

Exabyte Scale of Genomics Data (and cat videos)

DNA, Image Source: http://www.publicdomainpictures.net/view-image.php?image=42718&picture=dna
DNA, Image Source

Its no surprise that genomics represents a terrific big data challenge, but noting that its data has doubled every seven months over the last ten years is remarkable given how the field is poised to really explode in the coming years.

This article points out the comparison with astronomy and social media:

The authors estimate that the genomics information so far, from sequencing different organisms and a number of humans, has produced data on the petabyte scale (a petabyte is a million gigabytes). However, over the last decade, genomic sequencing data doubled about every seven months, and will grow at an even faster rate as personal genome sequencing becomes more widespread. The researchers estimate that by 2025, genomics data will explode to the exabyte scale – billions of gigabytes. This surpasses even YouTube, the current title holder among the domains studied for most data stored.

Frankly, it is refreshing to see such a valuable area of study surpassing a repository of countless cat videos as a leading data management problem in our society.

(Source)

CIO: Why happiness beats money when choosing a tech career

Some of the best career advice I’ve ever gotten was to sit down and really think about what things you’ve done or experienced in your career that really made you happy. Things you enjoyed doing and were proud of. Write them down. Formulate a plan to pursue more things like those.

So often you start a career listening to the “should’s” of parents or aiming at what pays well. You may even be fortunate enough to know what you want to do and get to pursue your passion from the beginning. But invariably, I think most intelligent and self-aware people reach a few different points during a career where they look around and have to consider, “Wow, I’ve arrived, but is this really like what I thought it was going to be like?”.

In this piece at CIO.com, the author provides some great questions to ask early in your career, and when you find yourself at one of the question points later:

Figure out what you like doing and what you hate doing early on
Figure out what size and kind of company you want to work for
Do you want to be a CEO?

After gaining some experience, thinking about what you hate (or conversely love doing), how the size of the company you work for impacts that, and what your life will be like when you reach the job you strive for (the CEO question), can really illuminate your path forward.

(Source)

Knowledge Management is Dead. Long Live Knowledge Management.

Clearly a title like “Whatever Happened to Knowledge Management?” is going to catch my eye. In this WSJ piece, Thomas Davenport sheds some light on the present state of affairs for KM, and touches on some interesting points about SharePoint:

The technology that organizations wanted to employ was Microsoft’s SharePoint. There were several generations of KM technology—remember Lotus Notes, for example?—but over time the dominant system became SharePoint. It’s not a bad technology by any means, but Microsoft didn’t market it very effectively and didn’t market KM at all.

and something quite prevalent in my world (you may have heard of this “big data” thing):

KM never incorporated knowledge derived from data and analytics. I tried to get my knowledge management friends to incorporate analytical insights into their worlds, but most had an antipathy to that topic. It seems that in this world you either like text or you like numbers, and few people like both. I shifted into focusing on analytics and Big Data, but few of the KM crowd joined me.

In my view, one thing is certain: there is tremendous value locked in the heads of employees, hiding in content of all types, and waiting to be found in large data sets.

Enterprise tools of all kinds, from content management to search to analytics, are continuing to evolve. The increasing demands of global competition are driving a more collaborative workforce.

Regardless of wether we continue to label efforts to unlock that value as knowledge management, they will remain important.

Long live knowledge management.

Blog Migration Complete

Road to the Gorge
Road to the Gorge, 2011

Well, it has been just over 3 years since I began the process of migrating out of Tumblr—let’s just say life has been a little busy during that time. Anyhow, the bulk import is finally complete and I can now start grooming the content and, most importantly, begin adding fresh posts.

I must say the tipping point was finally moving to WordPress and leveraging the automated import tools. I’ve enjoyed RapidWeaver and will continue to use it for some specific projects, but settling on an industry standard platform has some advantages.

Anyhow, things might be a little messy for a while. Please excuse the dust.