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Reply | Original | Permalink | Share | TweetI don’t think stream data processing will _remain_ a niche for much longer. I think it will grow rapidly to become far more mainstream, partly because a lot of data will come from sensor networks, partly because machines will create much more data, partly because storage space grows so rapidly that all that sensor data can be kept.I think one has to consider how much of the perceived growth of stream processing is due to ~100 million USD in VC being blown on marketing by new comers to this scene. I agree that the market growing but am not convinced it really is growing fast enough to generate an open standard, yet. Niches do not support competition well, at least commercially.
Reply | Original | Permalink | Share | TweetThat's entirely right color_chart. Blog by definition from wiki says : A blog (a contraction of the term “Web log”) is a Web site, usually maintained by an individual with regular entries of commentary, descriptions of events, or other material such as graphics or video. Entries are commonly displayed in reverse-chronological order. So static content isn't considered as a blog site.
Reply | Original | Permalink | Share | TweetWow this post quite explains what i missed out on by not reading your blog for the last one year :D, great summary. Great blog and i must say that EC2 is a great/awesome service.
Keep up the 30 odd posts a month, they are all good
Reply | Original | Permalink | Share | TweetStill dont get the excel part
They should be though more than a simple program like excel
Reply | Original | Permalink | Share | TweetHappy Christmas, Deepak. I've really enjoyed your posts, comments and positivity this year. My best to you.
Maxine.
Reply | Original | Permalink | Share | Tweet[…] Chris Lasher and co invited me to Virginia Tech to give a talk […]
Reply | Original | Permalink | Share | Tweet[…] I changed jobs […]
Reply | Original | Permalink | Share | TweetI was specifically thinking about algorithms in this case. New ways to solve a problem. Right now there is a formal process to do so, and it works and if you are an academic, no one stops you from implementing your own module, since you get the source code, but since everyone maintains their own flavor of the algorithm, its suboptimal.
But yes, there needs to be some discipline. Big projects like CHARMM have that. Others, I am not sure
Reply | Original | Permalink | Share | TweetLicense issues are typically a problem… social aspects too… such as understanding the source code, lack of documentation and unit tests to help with that, etc…
But, I agree…
Reply | Original | Permalink | Share | TweetIt's hard to say. A piece of scientific software has a much smaller niche than a web framework. The incentive to fork for the purposes of spinning off new directions seems much smaller, though forks for the sake of creating patches makes sense, and provides a chance to provide a patch for when the software maintainers are too slow to do it, fail to provide attribution to people providing bugfixes, or fail to acknowledge bugs exist at all. I have experienced each of these scenarios, and I have to say, this would quell those frustrations.
Reply | Original | Permalink | Share | Tweet50-50 chances to compare it to Wikipedia, at least my though
Reply | Original | Permalink | Share | TweetHi, this is Paul, CEO of Plectix here. (I won't be offended if you decide to remove this post - it's up to you )
Thank you and your readers for the comments: we are listening carefully as we move forward as this sort of implementation has not been done before. We think of Cellucidate as a little bit like a campus development, where we have left the open space as turf and we'll lay the hardened paths down when we see where people want to walk most frequently.
Some quick specifics:
Logo - as I recall it was inspired by a day at the beach
Languages: Kappa is absolutely in the public domain, anyone can use it. We “play nice” with SBML - which is a standard for transporting models, as opposed to being a modeling language in its own right.
ToS: Here's the dichotomy: everyone loves the idea that they can take and add to content that someone else has created and made public. However they often want to keep the work they are doing - which uses some of these public elements - private, at least until they are ready to publish it on their own terms. As the “herder” of all this content, we need to have the rights to make public those elements that the creator has decided to release, while giving people the option NOT to publish their work.
We'll work on the clarity, but in the meantime if someone suggests a form of words that is clearer and that we end up using, i'll be happy to show some appreciation - probably in epicurian form.
Thanks again for the comments - we wish you and your readers a great 2009.
Reply | Original | Permalink | Share | Tweet[…] language, or closer to home the CHARMM scripting language are all examples of DSLs. The other day I blogged about Kappa, which is a DSL as well. So what’s so special about them and why do they come up […]
Reply | Original | Permalink | Share | Tweet[…] The service positions itself as a “social, stock microblogging service”, which uses Twitter as a content production platform, and then adds on to it a stock-centric structure. This immediately appealed to me, since it’s an excellent example of the data finds the data, then people find the people. I believe the way it works is around stock symbols, being able to track them via the Twitter API. What especially made me think about this were Pierre’s blog post and tweets about using Twitter for bioinformatics. This fits into some general paradigms as well, those around harnessing information streams. […]
Reply | Original | Permalink | Share | TweetGreg,
Good points. Hopefully they will realize that having an open format is important and that they will evolve their ToS. The last thing you want is a closed platform and it would appear that's not the intent. Will be watching it evolve during the beta period
Reply | Original | Permalink | Share | TweetThere is a great deal of scope for quality commercial services, such as Cellucidate, targeted for biologists. The refinement of the tools, the collaborative aspects etc. are all great, however there are some minuses here. Their graphical language, Kappa, is proprietary, and not a community standard such as CellML or SBML, or more importantly (SBGN: http://sbgn.org/Main_Page). Second, their terms of use are odd, the system allows privacy controls for the models you create, but their terms of use suggests that they can do what they want with your contributions. I suspect this is more an issue of clarity rather than evil intent.
Reply | Original | Permalink | Share | TweetThe product looks interesting, the logo appears inspired by UniProt.
Reply | Original | Permalink | Share | Tweet[…] via WikipediaThe other day, I blogged about better browser performance and capabilities. Today, Alexander Griekspoor tweeted that while he agreed with my arguments on the […]
Reply | Original | Permalink | Share | TweetYes, and part of the reason for this has been lack of “Analyst Friendly” infrastructure on the Web. Remember, the initial Web (Web 1.0) gave us “Authors”, the first stage of evolution (Web 2.0) gave us the “Citizen Journalis” and “Commenttor”, and now the second stage of evolution (Web 3.0 or Linked Data Web) will usher in the “Analyst” .
Without strucutured and interlnked data as part of the mix, the analysts cannot thrive.
The Linking Open Data (LOD) community [1] has been on the vanguard of this effort towards a Web that facilitates “Analysis for All”
Links:
1. http://esw.w3.org/topic/SweoIG/TaskForces/Commu...
2. http://dbpedia.org/About
Reply | Original | Permalink | Share | TweetQuesto post è grande. Mi sono divertito lettura. Grazie!
Reply | Original | Permalink | Share | Tweet[…] for drugs December 15, 2008 — Richard by seanmcgrath Goldman’s pool for drug research: [Via business|bytes|genes|molecules] And while we are on the subject of blog posts by Derek Lowe, […]
Reply | Original | Permalink | Share | Tweet[…] seanmcgrath Goldman’s pool for drug research: [Via business|bytes|genes|molecules] And while we are on the subject of blog posts by Derek Lowe, […]
Reply | Original | Permalink | Share | Tweet[…] articles by Zemanta Keeping the technology in the background Mark Greaves podcast on Semantic Web business opportunities Tim Berners-Lee Says the Time for the […]
Reply | Original | Permalink | Share | TweetGreat post, Deepak! Je ne sais pas pourquoi je n'ai jamais réalisé moi-même, étant donné combien je entendu parler (et avocat) l'importance d'informaticiens et les développeurs de logiciels de savoir assez sur la science, des objectifs et des flux de travaux à faire un outil que les biologistes vont utiliser . L'inverse se produit presque jamais, mais vous avez raison - il le devrait.
Reply | Original | Permalink | Share | TweetI would agree that adding machine-based methods to make searching more successful would be a useful thing (such as meta tags spelling out certain parts of the research — method, research question — maybe even an app that would identify literature-based allegiances culled from the citations?), but like many methods involved in searching, they work best for those who already know what they are doing. I teach young scientists (undergrads), incredibly bright young minds (mostly in health sciences, neurosciences, premed) who've often been working for over a year on projects with PIs who've never even really explained the RQ driving the project. When these students hit the search engines for the first time, it's is remarkably clear that successful searching is not simply a matter of applying intelligence to a data set, or knowing how to use the MESH in PubMed, or even knowing what you are looking for, but a much more complicated set of skills that involve some content knowledge and some kind of linguistic knowledge that I'm still trying to figure out (I call this skill set “ambient literacy” and its my latest obsession). I can rifle through a pubmed search without a quarter of the content knowledge they have and more successfully find relevant articles — or, have several search engines open at once and use them “against” one another — a skill virtually none of my students have. Partly this is based on a linguistics background, partly it's because I feel about searching the way I am supposed to feel about buying shoes, partly it's just experience — but it's incredibly dicey to teach, and sheer exposure is not the answer. I think there is a culture to science expression that is discipline-specific (as you point out) and also a culture to web-based interaction that Facebook does not prepare the beginning scientist for! I wonder if adding greater machine-based functionality can serve the novice user as well as the expert? Beyond the limits that are already part of a pubmed search, perhaps something that can get at the “aboutness” of a publication?
