dragging scientific communication into the information age

Brian M. Bot | Senior Scientist | Sage Bionetworks

clearScience

Deception at Duke

“I will help you. Trust me.”- Anil Potti to Juliet Jacobs (pictured above)

open

open source

open data

open access

access2research

accessible

clear

research scandals represent merely the extreme of a continuum in the culture of academic research

the status quo tolerates poor communication of findings

6%

21%

8%

11%

54%cannotreproduce

can reproduce in principle

can reproduce w/discrepancies

can reproduce from processed data w/discrepancies

can reproduce partially

Ioannidis A. et al. Repeatability of published microarray gene expression analyses. Nature Genetics 41, 149-155 (2009) | doi:10.1038/ng.295

208,294,724datapoints

124 pagessupplemental material

?? lines unobtainable source code

?? version or architecture ofstatistical analysis program (R)

enumerable R packagesand package dependencies

key R package “ClaNC”no longer available

442 citations

often what is in principle reproducible, is not practically reproducible

unidentified publication‣ from journal with 5 year impact factor of 28‣ article freely available for download‣ data freely available for download

how are we to move science forward

if we cannot understand what was done previously?

Nature 483, 509 (29 March 2012) | doi:10.1038/483509a

let’s go back to basics

4. test hypothesis experimentally

5. analyze experimental data

7. publish results

6. draw conclusions based on data

scientific method

1. define a question

2. gather information and resources (background research)

3. form a hypothesis

8. retest (frequently done by other scientists)

4. test hypothesis experimentally

5. analyze experimental data

7. publish results

6. draw conclusions based on data

⤶

7. publish results

finitein

∞...

submit to journal

analyze on local machine

write a documentsent to reviewers as pdf

printed on paper

static html representation

experimentally generate data @ the bench orfrom a clinical cohort

accepted & digitally typeset

static pdf representation

store on local server

are being artificially uncoupled from

scientific claims

science itself

is hardscience

is hardcommunication

(especially for scientists)

getting harder in an era of

‘BIG DATA’

RESTful APIs

clearSciencere-imagining scientific communication

allow consumption of content at a variety of levels of complexity

and abstraction

leverage (open)

allow users to reassemble an entireanalysis environment

clearScience

RESTful APIs

clearScience

‣ hardware‣ software‣ data‣ code

analysis environment

scientific communicationneeds to evolve

along with scienceneeds to evolve

make it easy to do

good science

clearScience

make it easy to do

AcknowledgementsSage Bionetworks

David Burdick - Rockstar Engineer

Stephen Friend - President and CEO

Erich S. Huang - Director of Cancer Research

Mike Kellen - Director of Technology

External Partners

Myles Axton - Nature Genetics

Phil Bourne - PLoS Computational Biology

Josh Greenberg - Alfred P. Sloan Foundation

Kelly LaMarco - Science Translational Medicine

Ian Mulvaney - eLife Sciences

Eric Schadt - Open Network Biology