This community is restricted to bundle the community at /r/open_science, but we still regularly get requests to post here from new people. Somehow Reddit's search algorithm likes this sub more when searching for "open science" although /r/open_science is 10 times bigger and active.

Does anyone have any ideas on how to solve this?

I have been thinking about this for a few years, I think the broken window fallacy does a good job of summing this situation up. If you are not familiar, it goes: window makers are incentivized to go around town breaking windows, so that they generate more business. This is true in the short-term and microeconomic scale, but in the long term damages the macroeconomic system (the town loses money to buy windows, it becomes a cultural norm to have broken windows, etc.) In other terms there is a short-term incentive in the microeconomic scale that comes at a macroeconomic cost.

Closed vs Open Science seems to be a similar debate, there are short-term incentives to keep science closed as it is a revenue stream that supports some number of families and has benefits that are more immediate and measurable than the benefits of open-science, which could take a generation or longer to fully appreciate.

What this debate ultimately comes down to will be that the countries that do resolve this conflict of interest essentially take an investment opportunity in their future with significant macroeconomic ramifications, they build a scalable (and improving) infrastructure to generate skilled labor which ripples out to effect every aspect of society and culture. Ultimately, these are going to be profitable policies for these countries.

This is also more systemic than just the development of a "super-khan-academy" - in some respects these educational systems already loosely exist (khan academy already exists) but it is not enough to strengthen this one link in the chain. The difficult reality of education and the sciences is that it is about humans, their emotions, incentives, and culture. In addition to the availability of information, we need systems in place to encourage the acquisition and application of available information. There should be prestige and opportunity associated with success in an open-educational system, it should reflect positively on the individuals that apply themselves, creating career and lifestyle opportunities. If a ten year old kid spends eight years becoming a programming god or goddess, they should get job offers from prestigious employers, they are the real deal and they would be a profitable hire.

This is somewhat complicated, because the hiring process of these companies is pressured to depend on the simplest metrics in order to increase their ability to sift through potential candidates. The simplest way to judge a person is: past work history, degrees, referrals, citations, none of which are available to someone who leverages open education in order to raise themselves to the level of exceptionally skilled labor. As long as this applications bottleneck exists, there is a cap on the utility of open education - people are forced to start their own enterprises, or else get lucky in connecting to some number of people who have the bandwidth to recognize their skillset, neither of which are reliable enough to incentive the on-a-whim upskilling of a perfectly competent person who needs to make rent this month.

This is a problem worth thinking about and solving. I live in the United States and it is hard to imagine it happening here, but I would like to see other countries set an example. This system would be easier to adopt in developing countries, because they are already looking for alternatives to a traditional university and educational system. I think this should be seriously considered as major aspect of humanitarian efforts.

Thanks for coming to my TED talk.

Just hit submit on a manuscript. Squee! I'm really on the fence about preprints. On the one hand, I love open science. On the other, I respect the peer review process and think preprints might introduce bias. I'd love to hear opinions on both sides in the comments.

View Poll

Hi everyone!

I am new to the Open Science and I'll soon become a PhD student.

Reading about how science has been and is being turned into a business is very annoying and actually scary for me as I am afraid of becoming a part of this.

I would like to learn if and how the Open Science solves/offers solutions to some current issues below that makes the making of science problematic and difficult:

-Writing papers on / studying very minor issues which can be solved relatively easily and turned into a publication and avoiding difficult but very important problems in the world.

-Writing multiple papers on very popular topics as it will bring more citations and it won't be questioned in terms of its relevancy to the literature

-Caring too much and being forced to care too much about the numbers. Numbers of citations, publications, presentations and so on so that your institution's rankings, your own position and your advisor's support for you stays safe and present.

-Producing mainly theoretical research publications knowing that the real life applications are limited or may fail. Avoiding methodology that tests the application of theories that have real impact on people's lives.

-And mainly being forced into doing many of the above to be able to obtain tenure track, to become a researcher with financial security.

(points summarized from: https://www.sott.net/article/266422-An-aspiring-scientists-frustration-with-modern-day-academia-A-Resignation)

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Thanks for reading. (It would be very appreciated if you would share this post with your networks, thanks!)

Hello open science community! We wanted to introduce to you our podcast that aims to shine a spotlight on the painstaking and time-consuming labor of method development -- labor that too often does not get proper credit and attention but is critical for the progress of science. In our daily work with scientists from all over the world, we hear a lot of stories of how minor tweaks in scientific methods can have a major impact on someone’s research. This might have been the result of a published method that was lacking detail, had typos, or did not mention a specific condition. Our podcast aims to highlight the importance of detailed method sharing for rigorous and reproducible science.

In this episode, NIH Distinguished Investigator, Dr. Kenneth Yamada, joins us to discuss what he’s currently working on, his take on the best practices for reproducible research, and his story on how he spent more than a year perfecting a technique to mass produce a useful protein called fibronectin.

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Hey,

recently, my research group and I published a paper on “Lifetime measurement of the Cesium 5D5/2 state”. You can find the paper on arXiv (arxiv.org/abs/1912.10089) as well as on Physical Review A (https://doi.org/10.1103/PhysRevA.101.042510). We published our measured data on Zenodo:

- DOI: 10.5281/zenodo.3701332

Since we did that the first time and we do not have any experience with open data, we wanted to ask what you think about that. Especially, we are very happy about feedback on what we could improve the next time!

Thanks :)

Good morning everyone (yep European timezones).

As everyone here you most probably have encounter the famous SOA (state of art) phase in your research.

While being overwhelming, and a candy to your curiosity. This phase can also become cumbersome and somewhat tirering if you want to perform a deep search on the field your working on. With the exponential rate of published paper every day, and publication preasure (publish or perish) this SOA is becoming even more stressful nowadays if you want to stay up-to-date.

Personally I truly believe in multidisciplinary field research as new techniques from one field could radically change another one. However as explained, performing a coherent SOA of a new field is taking a large amount of time, that we might not have (nor the expertise). Limitating ourself in one specific field of research.

Therefore, do you know any software that could assist this SOA phase. Ex: Something like a "smart" recommendation system which will propose relevant paper based on a set of paper defined as interesting. Or even a magical tool which will map a field (depence map) and display the interaction between every published paper.

Well I know the recommendation system from Mendeley and Academia (as well as the one from researchGate). Despite not being open source (nor providing any API) they're working decently but still lack precision.

Are you aware of other Interesting software or initiative in this direction.

Sincerely

Take care.

Event where Maastricht University will sign the San Francisco Declaration on Research Assessment (DORA): https://library.maastrichtuniversity.nl/um-open-science-event-2019/

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#climateaction and #openscience... one and the same movement!

#grevepourleclimat et #scienceouverte... même combat !

This initiative was kicked off to allow researchers to show their support for #openscience specifically in the context of #climateaction, #marchforscience, etc. The wider public are constantly being asked, in one form or another, to trust science on the global crises we're facing, and yet the edifice of science isn't leading by example by first opening itself to the public at large. This first version of the manifesto is destined to end up in the French media, so please share far and wide with any French-speaking researchers or professors of science you may know anywhere in the world.

https://preview.redd.it/oxba515o0jn31.png?width=681&format=png&auto=webp&s=3f5a9826425d153a33bac6ad55395299119f0b69