Yeah, so I was just saying that I am Ukrainian. I left as a child and unfortunately cannot carry a very specialized discussion like about physics and Ukrainian. So if that's OK, I will carry on in English so I can stay in this channel in that case.

I guess so. OK, well, I'm I'm really, truly honored to to be here. This is the first slide that I've been using since February, since the full scale invasion of Ukraine.

And it's just a frozen moment in time that I will not change until the ultimate victory of Ukraine. So again, it shows an institute of physics and technology and give that in Harkiv that received some

damage and also displays an article that I learned a great deal from also from Harkiv from another institute. Of course, when I look at this, I think about my own beautiful laboratory in the United States at the University of Pittsburgh and can't help by think about how much we can take for granted the peace and prosperity.

So different from many other speakers, I am representing just myself and my perhaps my university. I am a physicist. I do research in physics.

And my talk here is because I have gone through and still in the middle of a large ordeal kind of an investigation, which you can use as a as an example, as a case study for the need for open science and the methods of open science.

And perhaps for the Ukrainian community, you can well get informed from this by how when you build and rebuild Ukrainian science, you know what should be the best practices going forward? My research is in quantum physics, quantum computing, perhaps, and the machines you see here are low temperature cryogenic equipment.

Let me tell you what kind of science we are after because it will be relevant. So it goes back to the foundations of quantum theory of almost one hundred and ninety years ago.

This brilliant Italian theoretician, Eder Meirana, came up with an amazing hypothetical quantum particle, which is its own antiparticle. And there's been various efforts to identify this object.

Yes. Yeah, so it's it's a fascinating field of study. And about 10 years ago, I was part of the team at the time in the Netherlands where we spotted some evidence of some signatures of this effect.

So if you read on the bottom here and Vincent Mauric is my partner in these investigations, we published this article for which we became extremely famous around the world. You can see all this publicity that this work and the follow ups of this work have received. We used this kind of a nanowire nanoscale, a very small device to measure the low temperatures and find some evidence for this.

And if you look at the Web of Science and type in Meirana, you can see kind of an explosive development right around this time. So this is just sort of a background signal and then this huge growth.

And this is our experiment right here. It's a very interesting and long discussion that I cannot have here in full. But a couple of years later, there was another experiment that made us think that maybe we actually did not.

Maybe we did not make this discovery. There was an alternative explanation for everything that we observed. So that was a very interesting development. And so there was a scientific discussion going on. However, another couple of years later, this huge company, Microsoft, essentially bought my original group in the Netherlands,

hired them and declared that they will build a commercial product, a quantum computer based on our on our work. And that, I guess, created a lot of pressure. So while the scientific debate shifted to, well, maybe this discovery has not been made.

These other people kept publishing works where they made claims that, yes, it is getting better and better and better. So, well, me and Vincent, the two friends from PhD Times, asked for data. We asked them to share with us more data than what they published. And, well, long story short, this is a result.

So far, the investigation is still ongoing. But you can see these two retractions. One is one expression of concern, which is a very big step by an editor. And, you know, not the journals.

These are the top, the cream of the crop of the publishing. OK, somebody needs to be muted over there. Yeah, it's a very nervous topic.

Right. Well, let me explain to you in one slide what actually happened, what we found. So look at this data. The orange, the orange trace is what was in the nature paper.

And when we asked for additional data, the full data is this orange plus blue. And the paper had an explicit statement that the signal does not cross this red dashed line. It just does not. And that's very important for the claim that they made in the paper.

However, right at the boundary where they cut off the data, when they hit the data right at that boundary, the signal goes up and reaches quite a high level of a one point five time the level that they claimed it never exceeded in their work. Right. So by. Demanding additional data by receiving additional data,

we could directly disprove the claim made in this nature paper, and that led to a retraction of this paper. So this is a you can say this is a success, but I want to share with you how difficult how difficult it was.

I have prepared three challenges that I want to share. So first challenges. It is extremely time consuming. The journals, the institutions, the authors, there aren't any procedures for verifying for challenging this work.

Essentially, there's no quality control at the journals. Once it's published, it's extremely hard to, you know, to question it, to revise it. And so here you can see on the slide the timeline for just this one paper, which was the first paper that got retracted. And you can see how many how long how long it took. And by the way, the substantive scientific part is just a couple of months up here.

When we asked for data, we actually got a little bit of data and we found the errors. And so at that point, you would expect you would hope, well, the process, the system takes it from there.

And unfortunately, even in the most progressive countries such as the Netherlands, the United States, the UK, these procedures are simply not there. So going forward, this needs to be obviously improved. Second problem is, of course.

Well, oftentimes when there is one paper, there's more there's more problems. And so we asked for data from a whole bunch of papers, a whole list that you can see here on the left. And you can see when we asked for data, these are the dates and basically the status is unchanged compared to this table.

We received a little bit here and there and we made some criticisms. We suggested some retractions. But in some cases, we were simply denied any data and in some cases we were promised, but effectively denied. So it was not shared. And this is, of course, in contrast with what people will tell you if you ask them, well, how long would it take you to prepare data if people ask for it?

So, you know, a couple of weeks, a month. This is what people say. Of course, this is from my Twitter and my audience is perhaps biased more towards open science, towards those kinds of principles. And they're more willing to share data. But this was a second challenge.

And a third challenge is, well, as a practicing scientist with a big laboratory, I could carry out my own reproduction studies. And I do. These are all the papers from my group where we did perform reproduction studies.

But it's extremely expensive, not to mention time. Each takes months, if not years. But basically, ballpark for our kind of research, each paper is $100,000. So what you're looking at this screen is a half a million dollars and the bill is actually growing.

And this is just to reproduce and verify other people's work. And all of these papers came with negative, their own negative reproduction studies. We were unable to verify the conclusions in the papers published in journals such as Nature and Science and so on.

So this is my lived experience as a scientist in my field, which is very hot and very hyped and famous, but also very interesting. And what did I learn? What did I learn from this experience? This is what I learned. This is a graphic representation of what I learned.

The first thing I learned is kind of the emperor has no clothes. Right. We have Holy Carol. The emperor has no clothes. You know, at Science and Nature, there's no quality control. The quality of peer review is not exceptional. It has the same problems as in any other journal.

The quality of editorial work is low. There is no this very difficult to revise what's been published. And so basically you are you are praying to this God that is a fake idol. Right. You know, basically they have the impact factor. But once you know the game and I have a number of Nature and Science papers myself.

You know. Once you're in, you're in. And basically, you know, after that. So but the good news is and in this conference, we also heard there is everything you need.

All the tools have been developed to do it in a in a better way. And so we all already heard about Zenodo and archive in this conference. And site post is just in the kind of an overlay journal, also from the Netherlands, from the same place, from the Netherlands, made by physicists again. And this is what we basically use now. So I just wanted to promote this a little bit because, look, this is a submission page.

It's just a link from archive that you give them. And this is where the data is for this paper. And these are the reports. Reports are open. You can read them, which is amazing. Right.

So the quality control, the open data is all here. Some of the reports are even signed by our colleagues. I'm very grateful to them, but they can also remain anonymous. And I'm also proud to report that our university has become a sponsor of this journal. And there is still work to do to improve this process.

But this is definitely a lot better. So to to wrap up, you know, this is like preaching to the choir. But, you know, why do we call this science? This is torture. This is a terrible process with all the secret peer review and impact factors and not sharing of the data.

We should simply call this science. Right. And this is not open science. This is just simply science. This is what I think. And finally, because I'm one of the only few speakers from the United States, I wanted to make a little comment not on behalf of the United States, but from the United States.

As I experience it now, United States is kind of slower than Europe in embracing open science. And this has to do with how the government is organized, I think, in the United States. But it's definitely moving in the same direction. And I think once the political decisions are made, United States can move very fast.

And I want to make this statement even more general. You know, this conference is about open science, but it's also about science. And I am very passionate and looking for ways to support and collaborate with Ukrainian scientists now in Ukraine,

because there's been already quite a bit of support for fellowships and scholarships for people who had to flee Ukraine temporarily. But going forward and thinking about the future and here in the United States, we have the same problem here. So, for instance, we may have the money, but we lack the mechanism to transfer the money to Ukraine.

There are certain mechanisms like CRDF and STCU, which work with sort of the larger programs. But we're building something at perhaps one university scale, collaborating with universities in Ukraine. And this work is ongoing. And I hope to have good news soon.

Thank you so much for attention.