One of my favourite online tools for topline CI research is Google Trends. It's a nifty, easy to use little tool that can help set the scene for some data driven analysis. After all, there's nothing worse than 50-100 pages of closely written text and tables and wondering if you can see the wood from the trees.
Take a look at what Google Labs have done with online Flu data and generated some interesting trends based on seasonal patterns:
They even have a short video to explain more abut the project.
Now, granted, there will be more data on big topics that the general public is interested in but I also use Google Trends a lot in my consulting work – a picture tells a thousand words and puts things firmly in context for discussion. For example, after the recent ASCO conference on cancer data, someone wanted to know what the impact of the new data in maintenance therapy in advanced lung cancer had. The answer? Very little really, as this graph clearly shows:
In fact, the negative news (F) around the adjuvant data in colorectal cancer had a small impact, but the 'noise' for colorectal cancer compared to lung cancer is generally much smaller as this graph shows:
This kind of historical data for global search allows you and I to look at trends and patterns – for free. That's probably the coolest thing about it because open science and access to this kind of data is awesome compared to 10 or 20 years ago when you had to have money to buy some vendors report that might not give you what you need anyway. In this age of self directed research, you have an enormous database of information at hand whenever you need it. It is also miles better than old fashioned search on Google, Yahoo! or whatever engine you choose.
Personally, I've also become a big fan of the Wolfram Alpha search tool for computational data – pages and pages of links do not turn me on but a neat page arranged with relevant tabulated or graphical information is much more cool and interesting. While travelling the other day, I needed to know the figure for lung cancer deaths in the US but didn't have my trusty PDF from the American Society of Cancer Facts and Figures handy. So I used Wolfram Alpha on my iPhone and got what I needed in seconds without having to click on Google links – brilliant!
Now, the information computed was just what I needed, but it would have been even more useful with a side by side table of incidence figures, not just mortality. Fortunately, I happen to know that they are about the same in lung cancer because patients live about a year, but that's not the case for all cancers. No doubt the tool will get even more useful with time.
Overall, these tools are really for finding trends and patterns in science data so you could use them for just about anything you might be interested in, such as diabetes, for example. Recently, a PR firm asked me whether people really distinguished between Type 1 and Type 2 diabetes. I had absolutely no idea, but the Google Trends graph was most instructive, especially as it was also clear that then trend for this disease since 2004 was generally in the downwards direction, possibly reflecting a lack of noise about new therapies:
There are plenty of other tricks you can use with Google Trends to slice, dice and parse the data, including excluding search terms, specifying time periods, look at regional differences etc, all on your desktop!