Directions in Open Science

Mike TraversSRI Bioinformatics Research

Group

For AIC Lunch and Learn, 30 Jan 2012

About this talk

• Partly a trip report from Open Science Summit 2011

• Partly an attempt to define open science and explore its impact

• Partly an excuse to talk about some of my own vaguely related work

• And partly some semi-crazy speculation about future projects in this space

The Open Science Summit unites researchers, life science industry professionals, students, patients and other stakeholders to discuss the future of collaborative science and innovation.

…in-depth sessions on new models for drug discovery and clinical trials, personal genomics, the patent system, the future of scientific publications, and more.

What is Open Science?

• Many different things, but boils down to:• Removing barriers to scientific

communication and collaboration:– Social– Technical– Legal– Economic– Bureaucratic

• To accelerate scientific progress• Utilizing modern technology

Driven by technological change

• The Internet has radically reduced communication costs

• So old institutions of scientific communication are now obstacles– Closed academic publishers, notably:

• Internet will transform scientific media just like it has newspapers, TV, social life….

• The difference is: science is more important than sharing cat pictures

For-profit academic publishing is a racket

A very lucrative one

Starting to be rumbles of complaint (boycotts) from academics

Open

• Most visible and successful branchof open science

• Articles are free to read, payto publish

• Funders are starting to requiresome form of public access

Gold: OA journal, Green: OA self-archivingOpen Access to the Scientific Journal Literature: Situation 2009, PLoS ONE, Bo-Christer Björk et al

Research Works Act• H.R.3699 – “A bill to ensure the

continued publication and integrity of the peer-reviewed research works by the private sector.”No Federal agency may adopt, implement, maintain, continue, or

otherwise engage in any policy, program, or other activity that--(1) causes, permits, or authorizes network dissemination of any private-sector research work without the prior consent of the publisher of such work; or(2) requires that any actual or prospective author, or the employer of such an actual or prospective author, assent to network dissemination of a private-sector research work.

Myth 1: American consumers have a right to free access to articles their tax dollars fund.

FactAmerican taxpayers do not fund peer reviewed research articles; they fund some of the research that is used in those articles…

Beyond Open Access• Not going to say a whole lot about OA, because:• It’s easy to understand• It’s pretty clearly going to win in the long term• By itself, not a very radical change to how science

is done:– Knowledge is still in paper-sized chunks– Papers are peer-reviewed prior to publication;– Once something is published, it’s static

• All these parameters are being challenged in some way by other efforts

• George Whitesides (Harvard chemist): “The concept of the scientific paper is eroding before our very eyes”

Variations on publishing

• “Peer review is broken”– Too slow– Too biased– Too rigid– May be “the worst system except for all the others”

• Pre-peer-review publication– Eg arXiv.org

• Micropublication– Crowdsourcing, blogs, wikis….

• Open-notebook science– No gap at all between bench and publication

• Database-linked publications• Dynamic Review Papers

Biggest sequencing operation in the world

Generating 6 terabytes/day of genomic data

Open-Source Genomic Analysis of Shiga-Toxin–Producing E. coli O104:H4 Rohde et al 2011 (NEJM)Toxic E. coli outbreak in Germany May 2011:We released these data into the public domain… which elicited a burst of crowd-sourced, curiosity-driven analyses carried out by bioinformaticians on four continents. Twenty-four hours after the release of the genome, it had been assembled; … Five days after the release of the sequence data, we had designed and released strain-specific diagnostic primer sequences, and within a week, two dozen reports had been filed on an open-source wiki …dedicated to analysis of the strain

Sequenced the rice genomehttps://github.com/ehec-outbreak-crowdsourced

GigaScience is a new integrated database and journal co-published in collaboration between BGI Shenzhen and BioMed Central, to meet the needs of a new generation of biological and biomedical research as it enters the era of "big-data."

Dynamic Review Papers

Conventional paper

Paired withDynamically-updated,wiki-based paper/database/model

Driving apps

Who comes to Open Science Summits?

Activist Organizations

Participatory Medicine& Disease Foundations

Startups

Social paper and citation management

Scientific servicesmarketplace

Web-based moleculelibrary management

Citizen Science

Somewhat less garage-y

• Independent research institute, started from data released by Merck

• Repository of experimental data (Sage Commons)

• Network of cooperating institutions

• Starting to build a computational platform (Synapse)

Synthetic Biology

And some individual researchers

• Peter Murray-Rust Chemist, Cambridge, promoter of Chemical Markup Language and semantic web“Closed science makes people die!”

• Victoria StoddenStatistician, Columbia, reproducibility of computational science(cf ClimateGate)

Some open science success stories

• Galaxy Zoo• FoldIt• Nutrient Network (NutNet)• Prazinquantel synthesis

Galaxy Zoo

• Citizen science (loosely)• Image classification task• Mechanical Turk-like approach (but

unpaid)• About 200K participants• Discovered a whole new class of

galaxies (“green pea”) and a quasar mirror

• 22 published papers in 3 years

Social sharing of algorithms (“recipes”)

Descent with modification

Matthew Todd, chemist at U of Syndney

Schistosmiasis

Looking for synthesis for known drug Prazinquantel (PZQ) in enantiopure form

Open-notebook science (LabTrove)

Nutrient Network (NutNet)

What paper has the most authors?

• NutNet paper:40 authors, 41 institutions

• This one from SLAC and elsewhere:407 authors, but only 35 institutions

Three variations on the scientific process

• Automated Science• Distributed Science• Web-scale Intelligent Science

• Open Science as the lubrication / accelerant that makes these feasible

Afferent: Automation for Drug Discovery

• Combinatorial Chemistry• Planning software to drive lab robots

Distributed Science

• Some science (eg evaluation of drug candidates) is highly parallelizable,

• Hence distributable• CollabRx was initially supposed to

support “virtual pharma companies” that would tie disparate academic research efforts into focused teams

Web-scale Intelligent Science

• Imagine all of science as a giant distributed computational process

• Individual scientists are agents – working on a small part of the problem– Sharing their results– Getting feedback and funding dependent on

success

• Centralized data integration and decision tools used to help determine next useful experiment

Steps towards distributed intelligence

• Adaptive clinical trials– Rather than a classical trial with two arms run to

completion– Change the distribution of test cases based on

ongoing results

• Now imagine this strategy applied more globally across all treatments for a disease

• Credit for this slightly mad vision goes mainly to Marty Tenenbaum:– AI Meets Web 2.0 (2006)– Shrager, Tenenbaum, Travers, Cancer Commons:

Biomedicine in the Internet Age (2011)

What does all that have to do with Open Science?

• Open Science is lowering barriers to collaboration

• So it’s a necessary but not sufficient step towards this new kind of science

• CollabRx may just have been too early:– the groundwork hasn’t been laid yet, – we are still working on basics – (eg standards for representation)

• Reducing friction (or transaction costs) can be incredibly important

“Changing the cost of innovation fundamentally changes the nature of innovation” – Joichi Ito

TCP, HTTP etc are the containerization of data.

So what’s the analog for scientific knowledge?

Standardized Legal and Institutional Mechanisms

A mix of technical, institutional, and legal standardization:

-Standard licenses (parameterizable)

-RDF representation for licenses.

-Web Tools to generate these

-Sites that collect and “market” available materials.

BioBike, a platform for open science

• Conceived of as a vehicle for getting biologists to do their own knowledge-based biocomputing.

• Lisp + Frame system + Bioinformatics Tools– Through-the-web programmability– Community sharing of code and data– Visual Programming Language

• Open Source •

Jeff Elhai, Arnaud Taton, J. P. Massar, John K. Myers, Michael Travers, Johnny Casey, Mark Slupesky, Jeff Shrager. BioBIKE: A Web-based, programmable, integrated biological knowledge base. Nucleic Acids Research, 2009

BioBike and Open Science

• BioBike wasn’t for Open Science per se• But it did explore some ideas in web-based

biocomputation• The next-generation BioBike platform:– Data: Big data, Open data, semantic web

integrated– Programming: Able to deal with large scale and

distributed workflows with human elements– Collaboration: Integrating different communities

in a “trading zone”KnowOS: The (Re)Birth of the Knowledge Operating System. Mike Travers, JP Massar, and Jeff Shrager, International Lisp Conference 2005

What is a platform?• The economic meaning of “platform” is interesting• Something that:

– Supports two-sided network effects– Stands in the middle and extracts a toll

• Examples:– Credit cards

(merchants ↔ consumers)– Operating systems

(application developers ↔ users)

• Science has more complicated networks and relations– Data providers– Data consumers– Service providers– Analysts (statisticians, eg)– Patients

• A science platform is not going to make anyone rich like Facebook, but it would be nice to have a powerful and standard way for all these groups to collaborate.

Open Data is outstripping analysis capacity

• Or in other words: – data is cheap,– attention, knowledge, & expertise are

expensive

• A platform for collaborative computational interpretation of biological data

• To better leverage the expensive resources

identifies advancing new computational infrastructure as a priority for driving innovation in science and engineering.

Scientific discovery and innovation are advancing along fundamentally new pathways opened by the development of increasingly sophisticated software.

the overarching goal of transforming innovations in research and education into sustained software resources that are an integral part of the cyberinfrastructure

Anti-open arguments

• Peer-review is an essential filter; without it too much nonsense gets out

• Electronic availability of articles actually leads to narrowing of science (Evans, 2008)

• Privacy, HIPAA, etc.• Need to retain IP for economic motivation• The problem isn’t availability of data; it’s

making sense of what we do have• See PRISM for more

Opener Science

• Science is already pretty open!

• institutions of opennessplayed a role in the foundation of science, including the first scientific journals

Historical Origins of Open Science

• Before the invention of science, knowledge of the natural world was closely guarded, passed down from master to apprentice.

• The development of institutions of openness was a key factor in the scientific revolution (Paul David, Stanford economist)

• …and the printing press was a key factor in that.

So…

• The printing press is almost 600 years old• The scientific journal is almost 350 years old• There’s been some advancement in

communication technology since then…• Science will eventually change:– Either a modest acceleration of the scientific

process, – Or as significant and discontinuous as the first

scientific revolution

• Which one? An open question.

Further Reading

End