Twitter Weekly Updates for 2009-02-22

  • If it’s just hosting you need, I’ve got way excess capacity in my dreamhost account. I’d be happy to set you up… re: http://ff.im/ZB7T #
  • Twitter Updates for 2009-02-15 http://ff.im/14tNd #
  • Nice summary! re: http://ff.im/14eMe #
  • Wow. I understand wanting to avoid eye-strain and all that, but it is an electronic device after all. How hard… re: http://ff.im/12PKx #
  • The main difference is that a quiche is made from egg custard, whereas a fritatta is usually just egg, without… re: http://ff.im/14kHk #
  • Liked “Genetic Future : The 1000 Genomes Project is holding back genetics!” http://ff.im/14cTx #
  • Will it take the media as long to realize they lost the speed battle as it did record co’s to realize they lost the digital content battle? #
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Twitter Updates for 2009-02-15

Twitter Updates for 2009-02-14

Could this be the Science Social Networking killer app?

There are tons of social tools for scientists online, and the somewhat lukewarm adoption is a subject of occasional discussion on friendfeed. The general consensus is that the online social tools, in general, which have seen explosive growth are the ones that immediately add value to an existing collection. Some good examples of this are Flickr for pictures and Youtube for video. I think there’s an opportunity to similarly add value to scientists’ existing collections of papers, without requiring any work from them in tagging their collections or anything like that. The application I’m talking about is a curated discovery engine.

There are two basic ways to find information on the web – searches via search engines and content found via recommendation engines. Recommendation engines become increasingly important where the volume of information is high, and there are two basic types of these: human-curated and algorithmic. Last.fm is an example of a algorithmic recommendation system, where artists or tracks are recommended to you based on correlations in “people who like the same things as you also like this” data. Pandora.com is an example of the other kind of recommendation system, where human experts have scored artists and tracks according to various components and this data feeds an algorithm which recommends tracks which score similarly. Having used both, I find Pandora to do a much better job with recommendations. The reason it does a better job is that it’s useful immediately. You can give it one song, and it will immediately use what’s known about that song to queue up similar songs, based on the back-end score of the song by experts. Even the most technology-averse person can type a song in the box and get good music played back to them, with no need to install anything.

Since the reason for the variable degree of success of online social tools for scientists is largely attributed to the lack of participation, I think a great way to pull in participation by scientists would be to offer that kind of value up-front. You give it a paper or set of papers, and it tells you the ones you need to read next, or perhaps the ones you’ve missed. My crazy idea was that a recommendation system for the scientific literature, using expert-scored literature to find relevant related papers, could do for papers what Flickr has done for photos. It would also be exactly the kind of thing one could do without necessarily having to hire a stable of employees. Just look at what Euan did with PLoS comments and results.

Science social bookmarking services such as Mendeley, or perhaps search engines such as NextBio, are perfectly positioned to do something like this for papers, and I think it would truly be the killer app in this space.

Thompson Scientific has a closed science search engine.

They sent me a survey and asked me some simple questions, but I don’t think they asked me the right ones, so I’m going to give a free-form review here. I think it’s a great idea, and presents some features not available anywhere else, but it’s missing some important content, and like everything Thompson does, it suffers from some useability issues.
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Great news for the Louisiana research community – Charity Hospital to be converted to University Medical Center

Maybe there’s a chance I could end up back in this wonderful city and have a career, too.

In a monumental announcement made late this afternoon, Department of Health and Hospitals Secretary Alan Levine said he will recommend that the state build a 424-bed, $1.2 billion academic teaching hospital in Downtown New Orleans that will serve as the hub of a rebuilt medical corridor.

Referring to the DHH proposal, the head of Louisiana State University’s health care division, Dr. Fred Cerise, said, “They revised the business plan a bit based on population and some shift in the makeup of the population, but overall (they) agreed that if we’re going to change the model to more of an academic medical center then we’re going to need the capacity to not only fulfill the charitable mission but also have space for our faculty to see their private pay patients there as well.”

The new hospital will be instrumental in the revitalization of not only the health care industry, but also the entire medical district and Downtown New Orleans. It will serve as the main teaching hub for medical students, nurses, post-graduate residents and other allied health students from LSU and Tulane University. The new facility will be instrumental in developing the DDD’s “industries of the mind” initiative. Attracting members of the creative class, such as leading medical researchers, technicians, and practitioners, is critical for shaping Downtown’s economic future.

The HPS consulting firm’s assessment is less sanguine, but overall deems the success of the center “likely”. Just to help paint the picture of things, the projected patient mix is:

13-21% Medicare
33-35% Medicaid
39-52% indigent