The whole thing started by Antony Williams announcing CC support for data on ChemSpider. That was followed by a chain of events and a ton of confusion. Let me add my voice to this debate, since Open Data is near and dear to my heart

I classify scientific data into the following categories

• Raw data: This is the kind of data deposited in Tranche, or RCSB, or GenBank. Sequence data, structural data, raw proteomics data. There are associated metadata that are required for quality and reproducibility.
• Processed data: These are the results of doing something with the raw data, e.g. molecular simulation results from a PDB structure and form a continuum

I can’t but agree with John Wilbanks. Here is the part that all of us should read again and again

The public domain is not an “unlicensed commons”. The public domain does not equal the BSD. It is not a licensing option.

It is the natural legal state of data.

It is a damn shame that we no longer think of the public domain as an option that is attractive. It’s a sign of the victory of the content holders that the free licensing movements work against that something without a license – something that is truly free, not just just free “as in” – is somehow thought to be worse. We’ve bought into their games if we allow the public domain to be defined as the BSD. The idea of the public domain has been subjected to continuous erosion thanks to both the big content companies and our own movements, to the point where we think freedom only comes in a contract.

The public domain is not contractually constructed. It just is. It cannot be made more free, only less free. And if we start a culture of licensing and enclosing the public domain (stuff that is actually already free, like the human genome) in the name of “freedom” we’re playing a dangerous game.

The public domain is the natural place for raw scientific data. That’s where it belongs and always has been. We, myself included, have been guilty of making things more complicated than they need to be. There is a data commons already. Our goal should be to make sure people respect it, and make data available in ways that we can take advantage of it.

Our discussion on content licensing should be limited to processed data, i.e. what we do with data in the public domain. There, we need to allow people to make choices, but keep the raw data unfettered. Those who want to associate copy left licenses with raw data are being dogmatic. Scientific data doesn’t have to be viral or anything like that, it’s there for the greater scientific good, and there’s only one logical mechanism for it. In fact, I would argue that putting copy left on it (a sequenced genome doesn’t belong to anyone) is as wrong as full on copy protection. You may have some embargo on making it publicly available, especially with things like structures where you might want to do something with it before anyone, but in the end the data belong in the public domain

I would like to thank John for putting this down so emphatically and clearly. A lot of us have been saying the same thing for a while, but this is the most clear distillation that I’ve read yet.

That does not mean we don’t have to have a discussion around how we make content (not raw data, but follow on content) available and the implications. Antony was confused for good reason.

Further reading

More from John
Cameron Neylon
Egon Willighaghen
More from Egon
Bill Hooker
Web as platform: Bret Taylor on Open Data
Open Science and licensing
Protocol for implementing open access data
bbgm post on protocol for open data

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So in an era with more scale available, clouds to tap into, accelerators, and new data and distribution models, are we going to see a shift? I still feel that the underlying scientific research has to come from academia. They have the resources, time and incentive to do so, but I think industrial think tanks and expertise can contribute back by working with academia on advanced problems of relevance, e.g. in the area of computing. Will we tap into some of the new domain specific development being done today as a scientific community? It can’t be done by one side or the other. But rather we need to identify approaches as a community and understand what works best, without trying to duplicate efforts. Of course, we need people who understand these new methods and paradigms to implement them.

There will always be a tension between academic research efforts and commercial need. In the life sciences it is especially tough for industry specific apps to be developed from an economic point of view, which is why I believe it will have to be a joint effort.

Your thoughts?

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Technorati Tags: High Performance Computing, Parallel Programming

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• NASA workshop on massively parallel supercomputers
• Aviary - I am out of accounts, but this is sweet
• NY Times - Pursuing the next level of AI
• McKinsey surveys the new software landscape
• Yahoo Design Pattern library
• hackystat - “A framework for collection, analysis, visualization, interpretation, annotation, and dissemination of software development process and product data”
• From the NY Times’ brilliant OSS blog - dbslayer (github repository)
• Erlang vs. MPI

Multimedia & Presentations

• Andrew’s presentation from XTech
• Is it time to throw away your servers
• Abstractions for handling large datasets

Blogspotting

• Greg Linden - This one is from the archives and for all of you interested in computer science, personalized search etc

Self Assembly

Once again, life is very hectic, so not much to report. Follow me on Friendfeed, twitter or check out the Tumblelog, where I am have been putting up some cool stuff lately

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Foldit combines gaming with protein structure prediction. It’s an interesting approach to spreading scientific problems. Folding@home built upon the success of Seti@home and the geek cred of running on gaming consoles and has built quite a following. Will Foldit, which presents a simple, fun interface to get people interested in protein structure (and the existence of Folding@home makes this somewhat familiar to geeks everywhere) be an example of how we can leverage crowdsourcing? Andrew makes some interesting points (which I agree with) on weighting crowdsourcing, although that’s always a hard thing to do, but I’d like to see karma, etc come into play here.

It’s good to see protein structure getting some attention and continuing to be creative. It’s always been my favorite scientific subject. The field lends itself to “pretty pictures”, so getting non-experts involved is a possibility.

The site and server have had connectivity issues since I’ve been trying, so perhaps they need help with web resources, cause lots seem to be interested.

Here is a list of people supporting the project: UW Animation Research Labs, UW Baker Lab, DARPA, Microsoft, and Adobe. Nice list.

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Technorati Tags: David Baker, Foldit, Protein Folding, Protein Structure Prediction, Gaming, Crowdsourcing

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You don’t get to see job descriptions like this too often in the life sciences. Have to love the What you get section.

What does the job description tell us. It’s a web-based consumer focused company with a focus on healthcare and with an informatics backend. Comes out of Stanford and has a Nobel prize winner advising it, which sounds very much like Andy Fire (based on the Stanford angle).

Let’s start the speculation.

Guess where I found this position; by tracking ‘bioinformatics’ on Twitter

Technorati Tags: Andy Fire, Healthcare, Stealth Startup, Stanford, Xooglers

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Good afternoon,

The Berkman Center for Internet & Society is pleased to announce that the faculty of Harvard Law School has unanimously approved a motion for open access: articles will be made freely available in an online repository. With the success of this motion, Harvard Law becomes the first law school to make an institutional commitment to open access to its faculty’s scholarly publications.

In February, Harvard University’s Faculty of Arts and Sciences unanimously passed an open access motion spearheaded by computer science professor and Berkman faculty co-director Stuart Shieber. Professor Shieber’s work and leadership, along with that of Harvard library director Robert Darnton, paved the way for Berkman faculty director William Fisher and executive director John Palfrey to bring an open access proposal to Harvard Law School.

The Berkman community is tremendously proud and excited about the success of these important initiatives.

The full release from Harvard Law School can be found online at http://www.law.harvard.edu/news/2008/05/07_openaccess.php.
Contact: Harvard Law School Office of Communications

The Berkman Center’s announcement, including a link to the full text of the open access motion, can be found online at http://cyber.law.harvard.edu/node/4273.

Image via WikipediaTechnorati Tags: Berkman Center, Open Access

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Many months ago, I started talking about the monetization of biological data, a theme that’s been present throughout the history of bbgm. In general, I have maintained that for the most part, the value lies not in the raw data, but in what we can do with the data. It looks like there is an interesting discussion brewing on the web around some of these ideas. Here are three a couple of posts, I think in chronological order

Peter Murray-Rust. The comment from Rich Apodaca is a must read. There is a follow up post from Antony Williams as well.

I will just re-iterate a generalizations, because I am only peripherally familiar with the specifics. On the web, data should be available as an addressable resource. The fact that data is available as RDF is great (and I wish more data was available as such). However, my personal preference is that data, especially open data, needs to be accompanied by APIs that allow the data to be accessed in a number of formats (not a dump per se). I think over time the acceptable formats will be established. The key aspect here are the business models. Is the business in providing a service on top of the data? For example for more than X number of API calls, there could be a fee associated.

These business models are going to be the key. Just like Open Source has found business models as have some web services, the models that allow people to build upon Open Data are the key

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Technorati Tags: Open Data, Web Services, CrystalEyes, ChemSpider

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Please email me if you continue seeing problems … mndoci AT mndoci — DOT — com

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Angiotensin-converting enzyme 2 (ACE2) is a key renin-angiotensin system enzyme involved in balancing the adverse effects of angiotensin II on the cardiovascular system, and its overexpression by gene transfer is beneficial in cardiovascular disease. Therefore, our objectives were 2-fold: to identify compounds that enhance ACE2 activity using a novel conformation-based rational drug discovery strategy and to evaluate whether such compounds reverse hypertension-induced pathophysiologies. We used a unique virtual screening approach. In vitro assays revealed 2 compounds (a xanthenone and resorcinolnaphthalein) that enhanced ACE2 activity in a dose-dependent manner. Acute in vivo administration of the xanthenone resulted in a dose-dependent transient and robust decrease in blood pressure (at 10 mg/kg, spontaneously hypertensive rats decreased 71+/-9 mm Hg and Wistar-Kyoto rats decreased 21+/-8 mm Hg; P<0.05). Chronic infusion of the xanthenone (120 microg/day) resulted in a modest decrease in the spontaneously hypertensive rat blood pressure (17 mm Hg; 2-way ANOVA; P<0.05), whereas it had no effect in Wistar-Kyoto rats. Strikingly, the decrease in blood pressure was also associated with improvements in cardiac function and reversal of myocardial, perivascular, and renal fibrosis in the spontaneously hypertensive rats. We conclude that structure-based screening can help identify compounds that activate ACE2, decrease blood pressure, and reverse tissue remodeling. Administration of ACE2 activators may be a valid strategy for antihypertensive therapy.

Here’s the HPCwire story, which really doesn’t tell me much other than really high throughput docking, but they use words like

That in itself is a significant accomplishment because no one has ever specifically identified a compound that enhances the activity of an enzyme using a rational structure-based approach

Anyone have a subscription to Hypertension? I am really curious cause nothing I read screams “unique” to me. Of course, I can just wait till tomorrow and try and get to the paper from work.

Update: Got the paper, and still don’t get the fuss. It’s an elegant virtual screening strategy, but I wouldn’t say it’s revolutionary. I was hoping to see something more advanced, e.g. protein flexibility, better energy functions, etc.

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Technorati Tags: Virtual Screening, Structure-based Drug Design, Hypertension, High Performance Computing

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Aside. It’s interesting that Sun talks about OpenSolaris as the OpenSolaris community
Technorati Tags: Cloud Computing, Amazon Web Services, Sun Microsystems, OpenSolaris, ZFS

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