Download to read offline
Uploaded byMike Travers
Directions in Open Science
The talk discusses the concept and future of open science, emphasizing the importance of removing barriers to scientific communication and collaboration to accelerate progress. It highlights various open science models, such as open access publishing, and critiques traditional peer review processes while showcasing successful open science projects. The document also touches on the role of technology in transforming scientific work and the potential for new collaborative platforms to enhance research outcomes.
More Related Content
Similar to Directions in Open Science
![UiPath Automation Suite Installation (Hands-On) [2/3]](https://cdn.slidesharecdn.com/ss_thumbnails/automationsuitecommunitysession2-251015095633-a6d862f1-thumbnail.jpg?width=600ounds&width=560&fit=bounds)
Directions in Open Science
- 1. Directions in OpenScience Mike Travers SRI Bioinformatics Research Group For AIC Lunch and Learn, 30 Jan 2012
- 2. 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
- 3. The Open ScienceSummit 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.
- 4. What is OpenScience? • 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
- 5. Driven by technologicalchange • 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
- 6. For-profit academic publishing is a racket Avery lucrative one Starting to be rumbles of complaint (boycotts) from academics
- 7. Open • Most visibleand successful branch of open science • Articles are free to read, pay to publish • Funders are starting to require some form of public access
- 8. Gold: OA journal,Green: OA self-archiving Open Access to the Scientific Journal Literature: Situation 2009, PLoS ONE, Bo-Christer Björk et al
- 9. 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.
- 10. Myth 1: Americanconsumers have a right to free access to articles their tax dollars fund. Fact American taxpayers do not fund peer reviewed research articles; they fund some of the research that is used in those articles…
- 11. 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”
- 12. 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
- 13. Biggest sequencing operation inthe 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 https://github.com/ehec-outbreak-crowdsourced
- 14. GigaScience is anew 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."
- 15. Dynamic Review Papers Conventionalpaper Paired with Dynamically- updated, wiki-based paper/database/mo del
- 17.
- 18. Who comes toOpen Science Summits?
- 19.
- 20. Participatory Medicine & DiseaseFoundations
- 21. Startups Social paper andcitation management Scientific services marketplace Web-based molecule library management
- 22.
- 23. Somewhat less garage- •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)
- 24.
- 25. And some individual researchers •Peter Murray-Rust Chemist, Cambridge, promoter of Chemical Markup Language and semantic web “Closed science makes people die!” • Victoria Stodden Statistician, Columbia, reproducibility of computational science (cf ClimateGate)
- 26. Some open sciencesuccess stories • Galaxy Zoo • FoldIt • Nutrient Network (NutNet) • Prazinquantel synthesis
- 28. Galaxy Zoo • Citizenscience (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
- 32. Social sharing ofalgorithms (“recipes”) Descent with modification
- 33. Matthew Todd, chemistat U of Syndney Schistosmiasis Looking for synthesis for known drug Prazinquantel (PZQ) in enantiopure form Open-notebook science (LabTrove)
- 35.
- 37. What paper hasthe most authors? • NutNet paper: 40 authors, 41 institutions • This one from SLAC and elsewhere: 407 authors, but only 35 institutions
- 38. Three variations onthe scientific process • Automated Science • Distributed Science • Web-scale Intelligent Science • Open Science as the lubrication / accelerant that makes these feasible
- 39. Afferent: Automation forDrug Discovery • Combinatorial Chemistry • Planning software to drive lab robots
- 41. Distributed Science • Somescience (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
- 43. 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
- 44. 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)
- 45. What does allthat 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
- 46. “Changing the costof 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?
- 47. Standardized Legal and InstitutionalMechanisms
- 48. A mix oftechnical, institutional, and legal standardization: -Standard licenses (parameterizable) -RDF representation for licenses. -Web Tools to generate these -Sites that collect and “market” available materials.
- 49. BioBike, a platformfor 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
- 52. BioBike and OpenScience • 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
- 53. What is aplatform? • 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.
- 54. Open Data isoutstripping 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
- 55. identifies advancing newcomputational 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
- 56. Anti-open arguments • Peer-reviewis 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
- 57. Opener Science • Scienceis already pretty open! • institutions of openness played a role in the foundation of science, including the first scientific journals
- 58. Historical Origins ofOpen 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.
- 59. So… • The printingpress 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.
- 60.
- 61.