User:Carl Boettiger/Notebook/Teaching/2010/04/12

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Notes potentially for my EDG talk.

"Keeping Up" -- a talk to EDG?
Science is growing. Fast. Number of papers published. Genomes on Genbank. Software on CRAN. Everyone's felt the pressure. So what do we do? Keeping with tradition, I'll present my own work in developing comparative phylogenetic methods to identify niche differentiation in Labrid fish. I will try and use this context to pose the question -- what do we do about this information explosion?? I'll review some data to frame the rate of this change and highlight three particular challenges: (1) Big Science - Big Collaborations, (2) Evaluating Science: Quality, Reproducibility, Impact, (3) Rising Demand for Broader Impacts. I'll review literature evaluating what is and isn't effective, present a few examples and tools with which some hope to face these challenges and opportunities.

I'm not really qualified to give an opinion on all this, but I'm interested to give it a try. Bring questions and opinions or maybe we'll hear a lot more about multitype OU processes.

Exponential growth of science

 * Publications
 * digital archive sizes 19 million articles in PubMed, search 60 million times/month.
 * Open access growth
 * How many table of contents do you receive? Read?


 * Databases:
 * Genbank
 * Dryad, species2000,
 * VertNet, itis,
 * NBII,
 * GPDD
 * Nature list


 * Software:
 * Felsenstein's 379 and given up?
 * CRAN 2326 packages, R's exp growth, and adoption in NY Times
 * Public repositories: Github, google code, Sourceforge.

Nature commentary


 * Luckily this is paralleled by the exponential growth of your capacity and free time...  whoops.

Collaborating across barriers
Which is harder: research across institutes or across disciplines?
 * Geographic distance:
 * Who has worked with someone at another institution? Multiple institutions?
 * National Evolutionary Synthesis Center. who has attended working groups, catalysis meetings?
 * Collaborating across disciplines
 * Rise of interdisciplinary centers, initiatives, and education


 * Effectiveness and Challenges
 * Science of Science, New NSF funding
 * Who collaborates successfully
 * Successful working groups share knowledge externally
 * What makes these effective / ineffective?  Research on geographic distance and more from Prof. Cummings, NESCent

Really really big collaborations, informal groups?

 * Coordinate simultaneous development of a project with hundreds of collaborators? Regularly happens in software development

Computer Scientists work in huge groups,
 * not often taught how
 * Informal collaborations. Mailing lists, stackoverflow, social networks.

Quality

 * Peer review/nature comments vs Amazon.com model... Cultural barriers.  New solutions.

Reproducibility

 * Reproducibility

Impact

 * Article level metrics. Data contribution.  software contribution.
 * Rising demands for broader impacts. Science in the eye of the public.  Communicating science.


 * Paper vs package. push button reproducibility.  Open science


 * Mailing lists. stack overflow.
 * Social networks


 * Picnic Day, Obama's NAS speech, educational outreach, who should communicate science and how?
 * Open = Impact


 * What is the minimum unit of science? A p-value? An equation?  Definition?  Hypothesis? A page or edit on a wiki? A paper.
 * What moves science forward in comparative phylogenetics. Lots of kinds of contributions: data, methods, software, technical support.
 * Synthetic science and linking big.

Ways Science is changing to face these challenges

 * Generative Science, Synthetic Science, Open Science
 * New thinking -- google mindset vs yahoo. tags.  Everything is miscellaneous.
 * Crowd sourcing
 * Tools waste time / save time

From the eyes of a young college student, this is fantastic. This is the dawn of a golden era of science. From the eyes of an aging graduate student looking ahead on an uncertain career trajectory, this is terrifying.

Solutions

 * filter

Survey

 * Use a social networking site
 * have joined a scientific social networking site
 * subscribe to a help mailing list
 * have asked a question to a mailing list
 * have answered a question on a list
 * collaborated with someone at another institution
 * have collaborated with someone they've never met
 * read articles as pdfs
 * keep pdfs in a database system
 * used an encyclopedia in the past 5 years
 * used wikipedia in the past 48 hours
 * used software for analysis / calculations / figures yesterday
 * how long would it take for you to reproduce that analysis now?
 * how long to reproduce the computational analysis/figures in a paper you've published?
 * how do you find most articles you read? ToC?  recommendation?  citation?