8 ms·

Why the world of scientific research needs to be disrupted

107 points by llambda 15y ago

deleted 15y ago
[deleted]
e_g 15y ago
In my personal experience the main problem with scientific research today is caused by publication counts representing the sole metric for academic success. Research is 'optimized' for publications and segmented according to conference schedules. That in itself I consider detrimental to the research effort. However the major damage in terms of advancing resarch in my opinion is caused by the induced tendency of scholars to closely stick to the main stream paradigms, trends and topics. Naturally it is much 'harder' to do research that does not directly build up on the current state of the art. Such research usually takes much longer and therefore results in a lower publication frequency. Secondly it is carrying a much higher risk of not bringing about positive results. Thirdly I deem the chances for acceptance in peer reviewed conferences and journals to be much lower. Such venues are often biased towards current main stream research trends.In my observation there is also an aversion against research that questions the state of the art. People who have spent years or decades to master every aspect of the state of the art have a strong incentive to shoot down anything potentially disruptive. As such the incentives are misaligned with regard to the aim of science of figuring out new things.
- jpdoctor 15y ago
  > In my personal experience the main problem with scientific research today is caused by publication counts representing the sole metric for academic success. It also leads to bloat in the literature: People learn the "least publishable increment" and go publish that.
  - e_g 15y ago
    Exactly. A study by Tuliving and Madigan (http://alicekim.ca/AnnRev70.pdf http://alicekim.ca/AnnRev70.pdf) outlines this nicely. In the words of David T. Lykken (http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.118.2655&rep=rep1&type=pdf http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.118...): In their 1970 Annual review chapter on Memory and Verbal learning, Tulving and madigan reported that they had independently rated 540 published articles in terms of their "contribution to knowledge". With "remarkable agreement", they found that they had sorted two-thirds of the articles into a category labelled "utterly inconsequential". "The primary function these papers serve is to give something to do to people who count papers instead of reading them. Future research and understanding of verbal learning and memory would not be affected at all if none of the papers in this category seen the light of day" About 25 percent of the articles were classified as: "run-of-the-mill .. these articles also do not add anything really new to knowledge... [such articles] make one wish that at least some writers, faced with the decision of whether to publish or perish, should have seriously considered the latter alternative" Only about 10% of the entire set of published papers received the modest compliment of being classified as "worthwhile". Given that memory and verbal learning was then a popular and relatively 'hard' area of psychological research, attracting some of the brightest students, this is a devastating assessment of the end product. Hence, of the research ideas generated by these psychologists, who are all card-carrying scientists and who liked these ideas well enough to invest weeks or months of their lives working on them, less than 25% of 40% of 10% = 1% actually appear to make some sort of contribution to the discipline. Given that this work was published in the 1970s when the "publish or perish" pressure was less strongly developed I expect today's number to be worse. Concerning Information Retrieval the field of research of my PhD I would certainly attest that this applies.
    - pnathan 15y ago
      I have been trawling through large numbers of papers recently as part of my computer science Master's background research, and some papers are quite frankly unintelligible garble... I can't even understand how they passed peer review. I would say that of the articles I've read, maybe 5% are meaningful contributions that advance the science; maybe 25% contribute something to the current understanding, perhaps 60% are "we did something cool", and 10% are "are these reviewers awake".
    - jpdoctor 15y ago
      Thanks for those links. During my own PhD, I was pretty sure that the "least publishable increment" became negative. The underlying problem is that there is no penalty for publishing non-increments. For some inexplicable reason, citation impact assessments do not divide by the total number of publications. I have no doubt that such a normalization factor would go a long way to fixing the problem.
- dubya 15y ago
  There's been an attempt to measure paper quality using the "impact factor", but as with seemingly every measure, it's led to shenanigans. Some publishers encourage authors to cite papers from their journals, and some editors write survey papers that happen to cite a bunch of articles from their journals. A recent AMS Notices covered this in math, and I sort of expect it's worse in other disciplines.
  - mynegation 15y ago
    To me it looks a lot like a manipulation of search engine. Maybe Google or Microsoft will not disclose their rank inflation counter-tactics, but what they could do is to provide their solution for this specific verticals. As much as I'd like open-source effort for that, I understand that knowing the rules allows easy manipulation.
    - dasmoth 15y ago
      Well, there already is Google Scholar. I don't know precisely how much effort goes into the ranking algorithms used there -- but I do already use it in preference to Pubmed.
pixcavator 15y ago
Start big: "scientific research needs to be disrupted!" (a trendy word) How? At the bottom: "government agencies funding research should require that those submitting papers must provide their research free of charge".
kia 15y ago
Unless scientists and researchers start to put the interests of collaboration and “open science” ahead of their desire to be promoted or win tenure the system will not change This is the main problem because most won't.
- nickpinkston 15y ago
  Yea, the real question is how to show their efforts in an open system so they can get tenure without fear of being "scooped" by being open
  - markkat 15y ago
    Bingo. There is good reason to fear being scooped. It can cost you funding, and thus, your job.
    - nickpinkston 15y ago
      For sure - I wish we could find ways of seeing whose "code" was "forked" and thus whose shoulders everyone is collectively standing one - the some of that is your advances in the field right? The current system uses paper publishing (# / impact factor) as a proxy for this, but it produces a lot of perverse incentives. If we found a way to see whose concepts were being used and when - people would instead throwing out any idea they'd have hoping that it be picked up (even unknowingly) by other researchers so they can get some of the credit. If this could be done, would it fix this status / scooped problem, and is there actually a way to replicate the "fork" structure of something like GitHub? Unfortunately, science is both: 1.) hard to pull in-depth semantic data out of (I'm guessing a lot of nuance) and 2.) not formally coded like programming language.
- markkat 15y ago
  I absolutely would if I could do it and still get funded. I'd love to share everything openly. Just pay my bills as I do it. Currently, science is funded based on individual results. You can't blame folk for wanting to be promoted or to win tenure.
markkat 15y ago
To disrupt scientific research you need to change the way that science is funded. Science is not for-profit, unlike the disrupted industries mentioned here. If you have to show how determining how a flagella works is going to produce revenue, then you are going to stifle science in another way. Good science is slow, deliberate, and motivated by open-ended questions and discovery, not by end points. We need to fund the process of science, and make sure that the knowledge gained is shared publicly. No other disruption is necessary.
- dalke 15y ago
  "Science is not for-profit" Science is also not not-for-profit. Plenty of for-profit businesses do research, and publish in scientific journals. Some research fields (drug development comes first to mind) have a very large industry presence.
iqster 15y ago
A very practical problem with making data available publicly is privacy. This is likely not going to be an issue for data coming out of the LHSC, but comes into play in CS research. I know a bunch of researchers who work with large datasets that have user locations, cell tower communication, social network data, etc. Of course, even researchers work with data that is annonymized. But almost nothing is truly anonymous. You have to assume that researchers working with the data are going to be sensible about how they use it. If not, they will face serious consequences (i.e. lose their jobs and hurt their reputations). A dataset made public typically cannot be controlled in this manner. Researchers must also go through IRBs (independent review boards) at their institution prior to engaging in research that deals with human subjects. If the collected data is going to be made available publicly, it makes the process more arduous. Btw ... there is a decent dataset repository for CS researchers doing mobile computing called Crawdad.
- brainid 15y ago
  "Researchers must also go through IRBs (independent review boards) at their institution prior to engaging in research that deals with human subjects. If the collected data is going to be made available publicly, it makes the process more arduous." That is not really my experience. Getting IRB approval to release human data just means proper de-identification which one should do anyway. For example, generally subjects are given randomly generated IDs with only the PI having the master list.
mironathetin 15y ago
Two comments: 1. Scientists publish in slow peer reviewed journals, because scientific publication has to be peer reviewed. The reviewers are a very small selection of other scientists, who are expert in the field of the publication. As long as the reviewers don't signal white smoke, a publication is no science by definition. This way of work is important to keep quality excellent. We certainly don't need more quickly published junk that stirs the world but is found to be inaccurate later. Can we accelerate the process of peer reviewing? I doubt that. As I have written, the reviewers are other scientists who have to find the time to read and comment new articles. The more time they spend with this, the less time they spend doing research. So the small amount of experts usually is responsible for being slow. You may be quicker by internet publishing, if (IF!) you work on a highly dynamic field where other scientists are hungry for your results. As the author writes, this is the exception. Most scientific results will be useful only a long time after the publication, if they will be useful at all. In this way, science is much faster than application already. 2. The author writes, we could make progress faster. Please: why? It seems to be a sign of the time that we want to accelerate everything. It is most likely that this will only produce more noise. We need to slow down our lives and our thinking to stay accurate and produce real value. I am glad that science results, at least in my field, are still reliably scrutinized by many. This way I know that reading and spending the time to understand the stuff is worth my time.
- beambot 15y ago
  To add to that, 3. Scientists (particularly academics) should focus on a smaller number of solid, flushed-out papers rather than seeking out the minimum publishable unit. The latter seems to be a byproduct of the tenure process (IMO) and just adds noise.
  - eru 15y ago
    How about you focus on publishing diffs to an overview (or so) instead of self-contained articles?
    - kd0amg 15y ago
bdhe 15y ago
Tim Gowers, fields medallist and the person who started the first polymath project just wrote a couple of blog posts (the latter including suggestions from the former) on a new model of math publishing. They are highly detailed and well thought out and also talk about things one might not understand unless one works in academia. https://gowers.wordpress.com/2011/10/31/how-might-we-get-to-a-new-model-of-mathematical-publishing/ https://gowers.wordpress.com/2011/10/31/how-might-we-get-to-... https://gowers.wordpress.com/2011/11/03/a-more-modest-proposal/ https://gowers.wordpress.com/2011/11/03/a-more-modest-propos...
eor 15y ago
I think the major funding agencies are aware of the problem and the potential, and are working on solutions in their own way (for example, the NSF Office of Cyberinfrastructure's DataNet program, http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=503141 http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=503141). But major cultural change in the way scientific research is conducted just isn't going to happen overnight.
jules 15y ago
Another vector for disruption is with statistics. Scientists use statistics to analyze the results of their experiments all the time. Unfortunately, most scientists are not statisticians. They spend a lot of time on statistics that they want to spend doing things they're good at. They make lots of mistakes, for example using the wrong statistical test or deciding what test to use after the experiment, etc. With today's computer speeds there is no reason to do the statistics the way they're doing it. You don't need to make strong and unjustified assumptions about your data because then you can use a simple T-test. Today with simulation you can do pretty much any statistical test you want. You can do Bayesian inference. However, most of these scientists are not capable of programming that themselves in R. What is needed is a simple GUI interface where they can state their assumptions and enter their data. Then the program calculates their posteriors and does any hypothesis test they want. The statistics scientists use today are optimized for pen and paper. The assumptions no longer hold. Who cares if the computation takes 500 milliseconds on a computer instead of 3 milliseconds?
necolas 15y ago
There are already some efforts to speed up peer-review and make more scientific publications available for free to anyone, e.g., http://www.plosone.org/ http://www.plosone.org/ > Unless scientists and researchers start to put the interests of collaboration and “open science” ahead of their desire to be promoted or win tenure the system will not change Something similar could be said about so many industries, including our own.
deleted 15y ago
[deleted]
irollboozers 15y ago
bum ba da bum http://beta.microryza.com/ http://beta.microryza.com/
galactus 15y ago
I wish people would stop using the word "disruptive" all the time...
- tacoe 15y ago
  Why?
grep2 15y ago
Actually, there are quite a few points where modern technologies would allow for a significant streamlining of research processes. Off the top of my head (as I work in the field): 1. data acquisition - you won't believe in how many labs devices with a computer interface (gpib or whatever) are running in standalone mode, costing hours in grad student hours where parameters are changed and values are read by hand - in the best case people duct-tape something together with a labview program. No. Just No. 2. collaborative data sharing - if you want to show your boss a graph, you email him a jpg - where is the site to upload a csv and show a graph to other people/edit together? 3. Writing papers: The state of the art is mailing a LaTeX(!) or Doc(!) file to your colleagues with .v1.edited appended... Reviewing the published material is just the last step. PS: I'm working on a solution for #3 (Etherpad + LaTeX preview + export in the appropriate journal format). Drop me a line if you're interested in details.
- davidblondeau 15y ago
  My company, Collaborative Drug Discovery (https://www.collaborativedrug.com https://www.collaborativedrug.com) has been developing and offering a secure collaborative data sharing environment for drug discovery data (chemistry and SAR data). There are other tools in the space as well though labs and companies are slow to change. The sector is very secretive and closed so it takes time for habits to change. Some factors have been promoting more collaboration and data sharing: * The increasing cost of research * Specialization and the emergence of micro-biotech (5 people biotech startups) * Foundations like the Bill and Melinda Gates Foundation that push for more collaboration amongst recipients of their grants (disclaimer: Collaborative Drug Discovery has received grants from the Gates foundation as well)
mhb 15y ago
Society for Amateur Scientists: http://www.sas.org/ http://www.sas.org/
chalst 15y ago
Note that the nature of research varies quite a bit from discipline to discipline. Physics has a preprint-oriented culture that reduces the conflict between individual interests and the wider ends of research.

107 points by llambda 15y ago

deleted 15y ago

[deleted]

e_g 15y ago

In my personal experience the main problem with scientific research today is caused by publication counts representing the sole metric for academic success. Research is 'optimized' for publications and segmented according to conference schedules. That in itself I consider detrimental to the research effort. However the major damage in terms of advancing resarch in my opinion is caused by the induced tendency of scholars to closely stick to the main stream paradigms, trends and topics. Naturally it is much 'harder' to do research that does not directly build up on the current state of the art. Such research usually takes much longer and therefore results in a lower publication frequency. Secondly it is carrying a much higher risk of not bringing about positive results. Thirdly I deem the chances for acceptance in peer reviewed conferences and journals to be much lower. Such venues are often biased towards current main stream research trends.In my observation there is also an aversion against research that questions the state of the art. People who have spent years or decades to master every aspect of the state of the art have a strong incentive to shoot down anything potentially disruptive. As such the incentives are misaligned with regard to the aim of science of figuring out new things.

jpdoctor 15y ago
> In my personal experience the main problem with scientific research today is caused by publication counts representing the sole metric for academic success. It also leads to bloat in the literature: People learn the "least publishable increment" and go publish that.
- e_g 15y ago
  Exactly. A study by Tuliving and Madigan (http://alicekim.ca/AnnRev70.pdf http://alicekim.ca/AnnRev70.pdf) outlines this nicely. In the words of David T. Lykken (http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.118.2655&rep=rep1&type=pdf http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.118...): In their 1970 Annual review chapter on Memory and Verbal learning, Tulving and madigan reported that they had independently rated 540 published articles in terms of their "contribution to knowledge". With "remarkable agreement", they found that they had sorted two-thirds of the articles into a category labelled "utterly inconsequential". "The primary function these papers serve is to give something to do to people who count papers instead of reading them. Future research and understanding of verbal learning and memory would not be affected at all if none of the papers in this category seen the light of day" About 25 percent of the articles were classified as: "run-of-the-mill .. these articles also do not add anything really new to knowledge... [such articles] make one wish that at least some writers, faced with the decision of whether to publish or perish, should have seriously considered the latter alternative" Only about 10% of the entire set of published papers received the modest compliment of being classified as "worthwhile". Given that memory and verbal learning was then a popular and relatively 'hard' area of psychological research, attracting some of the brightest students, this is a devastating assessment of the end product. Hence, of the research ideas generated by these psychologists, who are all card-carrying scientists and who liked these ideas well enough to invest weeks or months of their lives working on them, less than 25% of 40% of 10% = 1% actually appear to make some sort of contribution to the discipline. Given that this work was published in the 1970s when the "publish or perish" pressure was less strongly developed I expect today's number to be worse. Concerning Information Retrieval the field of research of my PhD I would certainly attest that this applies.
  - pnathan 15y ago
    I have been trawling through large numbers of papers recently as part of my computer science Master's background research, and some papers are quite frankly unintelligible garble... I can't even understand how they passed peer review. I would say that of the articles I've read, maybe 5% are meaningful contributions that advance the science; maybe 25% contribute something to the current understanding, perhaps 60% are "we did something cool", and 10% are "are these reviewers awake".
  - jpdoctor 15y ago
    Thanks for those links. During my own PhD, I was pretty sure that the "least publishable increment" became negative. The underlying problem is that there is no penalty for publishing non-increments. For some inexplicable reason, citation impact assessments do not divide by the total number of publications. I have no doubt that such a normalization factor would go a long way to fixing the problem.
dubya 15y ago
There's been an attempt to measure paper quality using the "impact factor", but as with seemingly every measure, it's led to shenanigans. Some publishers encourage authors to cite papers from their journals, and some editors write survey papers that happen to cite a bunch of articles from their journals. A recent AMS Notices covered this in math, and I sort of expect it's worse in other disciplines.
- mynegation 15y ago
  To me it looks a lot like a manipulation of search engine. Maybe Google or Microsoft will not disclose their rank inflation counter-tactics, but what they could do is to provide their solution for this specific verticals. As much as I'd like open-source effort for that, I understand that knowing the rules allows easy manipulation.
  - dasmoth 15y ago
    Well, there already is Google Scholar. I don't know precisely how much effort goes into the ranking algorithms used there -- but I do already use it in preference to Pubmed.

pixcavator 15y ago

Start big: "scientific research needs to be disrupted!" (a trendy word) How? At the bottom: "government agencies funding research should require that those submitting papers must provide their research free of charge".

kia 15y ago

Unless scientists and researchers start to put the interests of collaboration and “open science” ahead of their desire to be promoted or win tenure the system will not change This is the main problem because most won't.

nickpinkston 15y ago
Yea, the real question is how to show their efforts in an open system so they can get tenure without fear of being "scooped" by being open
- markkat 15y ago
  Bingo. There is good reason to fear being scooped. It can cost you funding, and thus, your job.
  - nickpinkston 15y ago
    For sure - I wish we could find ways of seeing whose "code" was "forked" and thus whose shoulders everyone is collectively standing one - the some of that is your advances in the field right? The current system uses paper publishing (# / impact factor) as a proxy for this, but it produces a lot of perverse incentives. If we found a way to see whose concepts were being used and when - people would instead throwing out any idea they'd have hoping that it be picked up (even unknowingly) by other researchers so they can get some of the credit. If this could be done, would it fix this status / scooped problem, and is there actually a way to replicate the "fork" structure of something like GitHub? Unfortunately, science is both: 1.) hard to pull in-depth semantic data out of (I'm guessing a lot of nuance) and 2.) not formally coded like programming language.
markkat 15y ago
I absolutely would if I could do it and still get funded. I'd love to share everything openly. Just pay my bills as I do it. Currently, science is funded based on individual results. You can't blame folk for wanting to be promoted or to win tenure.

markkat 15y ago

To disrupt scientific research you need to change the way that science is funded. Science is not for-profit, unlike the disrupted industries mentioned here. If you have to show how determining how a flagella works is going to produce revenue, then you are going to stifle science in another way. Good science is slow, deliberate, and motivated by open-ended questions and discovery, not by end points. We need to fund the process of science, and make sure that the knowledge gained is shared publicly. No other disruption is necessary.

dalke 15y ago
"Science is not for-profit" Science is also not not-for-profit. Plenty of for-profit businesses do research, and publish in scientific journals. Some research fields (drug development comes first to mind) have a very large industry presence.

iqster 15y ago

A very practical problem with making data available publicly is privacy. This is likely not going to be an issue for data coming out of the LHSC, but comes into play in CS research. I know a bunch of researchers who work with large datasets that have user locations, cell tower communication, social network data, etc. Of course, even researchers work with data that is annonymized. But almost nothing is truly anonymous. You have to assume that researchers working with the data are going to be sensible about how they use it. If not, they will face serious consequences (i.e. lose their jobs and hurt their reputations). A dataset made public typically cannot be controlled in this manner. Researchers must also go through IRBs (independent review boards) at their institution prior to engaging in research that deals with human subjects. If the collected data is going to be made available publicly, it makes the process more arduous. Btw ... there is a decent dataset repository for CS researchers doing mobile computing called Crawdad.

brainid 15y ago
"Researchers must also go through IRBs (independent review boards) at their institution prior to engaging in research that deals with human subjects. If the collected data is going to be made available publicly, it makes the process more arduous." That is not really my experience. Getting IRB approval to release human data just means proper de-identification which one should do anyway. For example, generally subjects are given randomly generated IDs with only the PI having the master list.

mironathetin 15y ago

Two comments: 1. Scientists publish in slow peer reviewed journals, because scientific publication has to be peer reviewed. The reviewers are a very small selection of other scientists, who are expert in the field of the publication. As long as the reviewers don't signal white smoke, a publication is no science by definition. This way of work is important to keep quality excellent. We certainly don't need more quickly published junk that stirs the world but is found to be inaccurate later. Can we accelerate the process of peer reviewing? I doubt that. As I have written, the reviewers are other scientists who have to find the time to read and comment new articles. The more time they spend with this, the less time they spend doing research. So the small amount of experts usually is responsible for being slow. You may be quicker by internet publishing, if (IF!) you work on a highly dynamic field where other scientists are hungry for your results. As the author writes, this is the exception. Most scientific results will be useful only a long time after the publication, if they will be useful at all. In this way, science is much faster than application already. 2. The author writes, we could make progress faster. Please: why? It seems to be a sign of the time that we want to accelerate everything. It is most likely that this will only produce more noise. We need to slow down our lives and our thinking to stay accurate and produce real value. I am glad that science results, at least in my field, are still reliably scrutinized by many. This way I know that reading and spending the time to understand the stuff is worth my time.

beambot 15y ago
To add to that, 3. Scientists (particularly academics) should focus on a smaller number of solid, flushed-out papers rather than seeking out the minimum publishable unit. The latter seems to be a byproduct of the tenure process (IMO) and just adds noise.
- eru 15y ago
  How about you focus on publishing diffs to an overview (or so) instead of self-contained articles?
  - kd0amg 15y ago

bdhe 15y ago

Tim Gowers, fields medallist and the person who started the first polymath project just wrote a couple of blog posts (the latter including suggestions from the former) on a new model of math publishing. They are highly detailed and well thought out and also talk about things one might not understand unless one works in academia. https://gowers.wordpress.com/2011/10/31/how-might-we-get-to-a-new-model-of-mathematical-publishing/ https://gowers.wordpress.com/2011/10/31/how-might-we-get-to-... https://gowers.wordpress.com/2011/11/03/a-more-modest-proposal/ https://gowers.wordpress.com/2011/11/03/a-more-modest-propos...

eor 15y ago

I think the major funding agencies are aware of the problem and the potential, and are working on solutions in their own way (for example, the NSF Office of Cyberinfrastructure's DataNet program, http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=503141 http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=503141). But major cultural change in the way scientific research is conducted just isn't going to happen overnight.

jules 15y ago

Another vector for disruption is with statistics. Scientists use statistics to analyze the results of their experiments all the time. Unfortunately, most scientists are not statisticians. They spend a lot of time on statistics that they want to spend doing things they're good at. They make lots of mistakes, for example using the wrong statistical test or deciding what test to use after the experiment, etc. With today's computer speeds there is no reason to do the statistics the way they're doing it. You don't need to make strong and unjustified assumptions about your data because then you can use a simple T-test. Today with simulation you can do pretty much any statistical test you want. You can do Bayesian inference. However, most of these scientists are not capable of programming that themselves in R. What is needed is a simple GUI interface where they can state their assumptions and enter their data. Then the program calculates their posteriors and does any hypothesis test they want. The statistics scientists use today are optimized for pen and paper. The assumptions no longer hold. Who cares if the computation takes 500 milliseconds on a computer instead of 3 milliseconds?

necolas 15y ago

There are already some efforts to speed up peer-review and make more scientific publications available for free to anyone, e.g., http://www.plosone.org/ http://www.plosone.org/ > Unless scientists and researchers start to put the interests of collaboration and “open science” ahead of their desire to be promoted or win tenure the system will not change Something similar could be said about so many industries, including our own.

deleted 15y ago

[deleted]

irollboozers 15y ago

bum ba da bum http://beta.microryza.com/ http://beta.microryza.com/

galactus 15y ago

I wish people would stop using the word "disruptive" all the time...

tacoe 15y ago
Why?

grep2 15y ago

Actually, there are quite a few points where modern technologies would allow for a significant streamlining of research processes. Off the top of my head (as I work in the field): 1. data acquisition - you won't believe in how many labs devices with a computer interface (gpib or whatever) are running in standalone mode, costing hours in grad student hours where parameters are changed and values are read by hand - in the best case people duct-tape something together with a labview program. No. Just No. 2. collaborative data sharing - if you want to show your boss a graph, you email him a jpg - where is the site to upload a csv and show a graph to other people/edit together? 3. Writing papers: The state of the art is mailing a LaTeX(!) or Doc(!) file to your colleagues with .v1.edited appended... Reviewing the published material is just the last step. PS: I'm working on a solution for #3 (Etherpad + LaTeX preview + export in the appropriate journal format). Drop me a line if you're interested in details.

davidblondeau 15y ago
My company, Collaborative Drug Discovery (https://www.collaborativedrug.com https://www.collaborativedrug.com) has been developing and offering a secure collaborative data sharing environment for drug discovery data (chemistry and SAR data). There are other tools in the space as well though labs and companies are slow to change. The sector is very secretive and closed so it takes time for habits to change. Some factors have been promoting more collaboration and data sharing: * The increasing cost of research * Specialization and the emergence of micro-biotech (5 people biotech startups) * Foundations like the Bill and Melinda Gates Foundation that push for more collaboration amongst recipients of their grants (disclaimer: Collaborative Drug Discovery has received grants from the Gates foundation as well)

mhb 15y ago

Society for Amateur Scientists: http://www.sas.org/ http://www.sas.org/

chalst 15y ago

Note that the nature of research varies quite a bit from discipline to discipline. Physics has a preprint-oriented culture that reduces the conflict between individual interests and the wider ends of research.