A conversation with Gabriele Marinello
A conversation with Gabriele Marinello
Jo: Welcome to another episode of Access 2 Perspectives conversations. Today we have Gabriele Marinello in the room, who is the founder and CEO at Qeios. And Qeios is a company. Well, as much as you're Italian, the company is registered in Ireland, right? Because that's where you did your study. And maybe this is also a good opportunity for me to hand over to you. Welcome again. One. Warm welcome Gabriele. I was going to say that in Italian. All I can remember now is chao.
Okay. I have more on my record track. It's just recording anxiety. It's hiding it. But yes, It’s great to have you on the show. And yeah, let's get started. So starting with maybe how we met. I remember you telling me that story about to share again when we met at the Urban Science Conference in Berlin. And was it in 2018 suddenly before the Pandemic?
Gabriele: 2018 or 19? I cannot remember. But one of those dates, yeah, definitely.
Jo: So. And then we luckily sat next to each other in a session and that's when we started talking. And that led to collaboration between AfricaArxiv and Qeios, where Qeios is one of the venues and recommended and appreciated repositories for preprints, for peer reviews. Peer review reports that can then be published as such and attributed to the reviews and made citable. But you started with Chaos as a database for definition. So how did this come about and not over to you?
Gabriele: Yeah, of course. Thank you so much for the intro. As you said, the platform as it is right now is quite flexible. It is a venue for many, many different scholarly objects, from definitions to preprints, final articles, peer reviews. But in the very early days we started, the platform was kind of different and the approach was different. We wanted to start by solving a problem in science, which is the fact that there are so many different definitions currently used in science. I mean, definitions of the same entities that researchers need to define and use for the research, to compose the research that have sorry, many, many different meanings according to how they are defined around the world. Like one example, for all the definitions of quality of life, for example, they are currently in use more than 1500 different definitions of quality of life. And research teams around the globe are using I mean, the one that was defined for that specific paper or the one that maybe is in use in the region and so on. But the problem is this once you have to compare different studies that are trying to answer some related questions. So, for example, what is the best treatment for breast cancer, for example? Right. You need to compare different studies. And if you have different definitions, you cannot compare the studies. So you cannot come up with one univocal answer like, okay, the treatment provided by the Chinese scientist is the best one. You cannot say that because you cannot compare the definitions that have been used to compose the study. Right. So we wanted to solve this initial problem and we started envisioning a platform for researchers to compose and provide the same division community with all these different definitions well clustered for the first time under the same caps. So imagine for the first time in history, all the definitions of quality of life well clustered together under the cap quality of life, so that researchers could peer review these definitions and rate these definitions and come up with a podium of the top definitions. So the top ingredients that they should use in science, that it's better for them to use in science, so that not only they could use better ingredients, but also much more comparable ingredients so that research around the globe can be compared and maybe we can find more univocal answers. So we wanted to solve that problem. But in solving the problem, we immediately realized that it wasn't that easy to divide that problem from depublication and the composition of research problems. So we envisioned a platform where researchers again could immediately afterwards, we envisioned an evolution of the nation platform where researchers could use these definitions immediately in their research. To compose the research directly on our platform, we provided them with an editor where they could use all these different building blocks to create their articles. And at that time we thought, why not also let researchers publish the output? I mean, the output is there, is ready. Why don't researchers publish on the platform directly the output?
Jo: It’s the same infrastructure you're using, right? It's not a big extra effort for you as the provider.
Gabriele: Exactly. And we thought why not apply the same peer review process that we have designed for the definitions also to articles as well? At the very end of the process, which is a post publication peer review process that we initially envisioned for the definitions, we decided to translate these also to the optical space. So research is now what they can do is to create an article on the platform, to publish the article straight away on the platform and to immediately post the article online to get reviews from invited peers that we invite. We have an AI which is able to locate the most suitable peers for a specific paper. So to have peers to review these papers and you have a final product, which is a scientific paper which has been built with possibly the best definitions around and which has been peer reviewed in the open, not like in the traditional system, traditional journal where the peer reviews goes by inviting at maximum three peers. It is blind. So it's very different. Here you have the peer review process, which is again out there in the open, where researchers not just invited researchers from us, but also other researchers that are knowledgeable about the topic, can definitely join the process and provide their feedback so that it works more like you team up with your peers rather than in the traditional system. You have these peer reviews that are there to provide an editorial decision to some editors, right? Instead, here you team up with peers. Peers help you amend your paper and you can even version your article, your paper with the insights, with the suggestions from peers. This is why you're not in competition with your peers, but you team up with them. They are there to suggest to you all the amendments that maybe you will need to consider to make a better paper. So you create a vision, two vision, three vision, whatever of your paper, and the entire process is out there, available for anyone to read, for anyone to see. So, yes, we have created an entire environment, a research environment, from research composition to research publication, which is, I would say, open. And, you know, it's it's it has been designed to help researchers create better research, not just, I would say, show up the research you see to create better research. So, yes, from the very beginning, again, to where we are right now, it has been quite a long journey. We have added all these little pieces. But the final product, again, is something that is very enjoyable on the part of the research and very useful for research in general, I would say.
Jo: Yeah, I like what I hear. And I think it feels like, and it sounds like it's explicitly how publishing should be practiced in a digital era. Meaning that the researcher knows what they found as a research outcome and results, they share it with the peers and also the non academic stakeholders who are either contributors as well as recipients of the results, contributors to the research. Some agricultural research obviously has farmers and an agricultural workforce as stakeholders policymakers. So each of them are now capable of being mostly for the scholars or the scholars are mostly prone to actually engage with Qeios in the peer review and the publishing. But as anybody else, because it's open in the public, the other stakeholders can witness what's happening, can also add their comments if they so wish, and that is highly informative to the actual research. Again, to either revise their manuscript, as you state, into another version, to continue the research into new directions they might have not come up with on their own unless it's in the open. And also compared to other established or emerging open or semi open publishing processes that are and I think it's good for various stakeholders to test. Whichever workflow works for seems feasible. But I feel like what you're just describing now, what you've built with chaos and your team is, as I said, it's good for the community. And the community has ownership as much as accountability. And there's no time loss because the process is happening in the open and is owned and coordinated by the actual researchers who've done the work and keep being in charge of their own outcomes and not have to wait on editorial teams who are easily overworked with the task of finding reviewers for the work they want to consider publishing in the Journals. And that just builds a whole cascade of delay processes.
Well, that's good. Okay. Do you see that the community that is now engaging with Qeios, is making it easy for them to make best possible use of the products you've designed, like incorporating the definitions, researchers citing their own definitions that they published and made citable also or other people's definitions, specific terms. So are all the components being made use of complementarity? So because I assume it's also easy to be overwhelmed by the possibilities of a new product or new service.
Gabriele: Exactly. You're totally right. And in this sense we can say that precisely because the finishes are a relatively new object in this quality world, we can say that it is also the most difficult to let researchers use just because it's new. You have to kind of instruct them on what it is they should use and so on. So we can say that that is the part that is the least used on the platform, the definition spot. Instead, what they are using the platform mostly for is for their papers. Because they know what a paper is and what they can get out of it. If they can envision what they can get out of it, they use this platform where there is no editorial process, where there is immediate publication and so on. It's much, much easier for them to start with the paper and then learn by using the platform what a definition is and so on. So we can say that for the most part, and mostly when we engage with new scientists, the platform is being used for papers. For the papers and of course, for the peer reviews of these papers. Because again, we have an invitation process in place, AI assisted, where we invite the peer reviewers. We have the peer reviewers on one side and the papers on the other side. And these two objects are the muscles represented on the platform. And then once they kind of understand the other possibilities on the platform, namely the definitions, they start using that one as well. But to answer briefly to your question, yes, definitely there is a different representation of usage of the different object. I would say definitely that the paper is the one that specifically right now, the preprint is the one that is most represented. But there is an escalation in usage for final papers, final publications. So research is that maybe they have suddenly used the platform for the preprints. Okay. They have seen peer reviews coming to the preprints and at that point with a peer review, the preprint, they have just decided to remove the preprint label which is an option that we have on the platform and make their publication a final publication. Okay. I would say that again, the major usage is for preprints and then once the preview sorry, come in, some of them decided to remove the preprint label and use the platform as a final destination for the words.
Jo: Yeah, perfect. Yeah. Okay. So just briefly on the definitions, I love that feature and I think it's highly available not only to come to terms or as a scientific community to use one definition over the other and be clear of what the definition then entails. But I think, as you also told me, as it's often the case with medicine, that you have one term meaning different things in different communities and for very good reasons. Because the evolution of the understanding of a certain topic or then has a term is often so different and so highly specific to a particular research approach that you end up using the same term but in a different context. And that needs a separate definition. And both definitions, even though they use the same term, have equal spending. And then the way how you came up with a way to assign also a DOI and make the definitions with their descriptions citable now makes it for the first time ever possible to be clear in your research articles, descriptions, methods, whatnot which climate change definition you're referring to as we talk about climate change. Or in my case, I think I postulated, I know I postulated a definition that makes sense to me as a trainer and consultant for open science practices. I defined open Science how I think it makes sense to be defined. And there are, I think, ten or so other definitions about open Science and all of them are true in nature. And I can also subscribe. So it's just that I think open Science to me is also something else on top and maybe less of something else somebody else was defining it as. But that's okay. And I think also to have a scientific discourse, it's essential that we understand what we're actually talking about when we use certain terminologies; reviving some definitions because they're outdated and they're only contextualized to a certain era and then they should only be contextualized to that time of age.
Gabriele: Definitely, yeah, exactly. Even if I said at the very beginning that the aim would be to find the top definitions and so on, as you said, definitely in some cases is not even that easy or is not even what is. I mean, the main object there is maybe instead just to have a place where you can discuss about these objects and maybe provide reasons why some definitions can be different and must be different in different locations, in different time periods and so on. Right. At least you have a place with all these definitions gathered together with the possibility for scientists to peer review these definitions for engaging in a discussion with the authors of the definitions, with other peers and so on, to discuss and come up with some conclusions about these objects. So yes, it is something interesting, definitely.
Jo: And the other thing also, as I'm coordinating and working with a team to run a preprint repository, or started as I've grown and learned to not appreciate the term pre print any longer because there's nothing pre. It's a manuscript, it's the outcome of a research study full stop. And there's nothing pre about it because we're not printing stuff anymore. Unless you're using your own printer. Yes, we are printing books. So thankfully I'd like to have an actual book in my hands. But when we refer to research articles, most information was being consumed online and also most information I assume was being consumed by algorithms and thoughts. Not anymore, as much by humans. I also give a scientific writing course and I often start that course, strategic reading course. And when we talk with the PhD students about how many papers have you read this week? And then people start like, oh my God, I should have the thought process goes like, oh my God, I should have read like 10-20 papers and I just didn't get to it. And I know that feeling from ten a decade ago was already overwhelming then. And imagine nowadays, okay, because hardly anyone has the capacity to read, like to fully read and consume a research article. We just don't have the time and the head space anymore. And that's sad because research articles are structured in a way that they're a full story. They tell a story with the beginning context, description, methodology, so they make sense as a whole, but we can only cherry pick and strategically approach it for information that we're looking for to then move on to the next one. And that's just sad. But I had another conversation earlier today about chat GPT. That's a whole other story. So it's going to be interesting. Where we headed again towards, I think, the approach of seeing preprints as what they are, as you research manuscripts and now having the technology, amongst others, also provided by Qeios, with the possibility to version manuscripts and research output. Also data sets to open them up to feedback by peers for discussion and then for them to evolve further. As long as they have budgeted to continue the research on a particular topic and somebody else might pick up on it or a previous or later version of the manuscript. That's just another level of accessibility to the research and the research output and also making each step in that versioning process citable with a specific DOI or versioning DOI, which still refers to original submission. It just makes so much sense. So I tend to walk away from the term preprint and not with AfricaArxiv or in my own courses with access to perspective, and I tend to talk about manuscripts or research articles and they are published when they're in a repository. It's also a way to publish. So the corporate publishers do not own the term publish. I mean also corporate publishers, the big five don't own the term publishing. But anything accessible, made open to the public is a publication. That's a question, if it's really accessible. Meaning is there a payable or not? And there can still be publication papers and that's a revenue stream and that's also not bad per se, but yeah, as long as you open up your products or the products of your work to the public. It's a publication living document of data sets and manuscripts responding to the nature of science and science communication. So now it feels like we're making technology work for research as a community.
Gabriele: Exactly. And not just that, also the fact that we can define it even more, the fact that a preprint can get peer reviews right now make it not just a publication rather than a preprint as you just said, but also a peer reviewed publication. You see? Yes, we are adding layers recently, layers and layers so that we can maybe provide some more dignity to products that have the same level of dignity of others that they don't have the same branding around. So yes, we definitely hope that we can get there as soon as possible.
Jo: Okay, so what's on the roadmap for Qeios this year and moving forward? What are the next steps?
Gabriele: So yeah, great question. We definitely want to be able to play in the big ocean as much as possible. To be able to do that we need to get indexed in some major databases such as PAMET and so on. So we have started our indexing escalation, I would think, I would say sorry. So we have started applying for example, again PomEd indexing and other databases that will come soon. So that at that point we are providing one more reason for researchers to use the platform not just as a first stop for the research, namely as a preprint venue right now, but as a final destination for the research works. Because again we are playing with
the same set of tools and set of capabilities in terms of providing the same level of discoverability and so on. Yes, in terms of what comes next for Qeios, I would say that this year we're going to do everything that is in our possibilities to expand the discoverability capabilities of the platform in terms of indexing. So this is our big goal for the near future. And along with that of course we are keeping refining, reviewing imitation tools, we're keeping refining the platform, all the features that we have on the platform. But yes, if I have to sum up to one or two things, I would say that the indexing is the biggest one and immediately afterwards is keeping improving our peer reviewing capabilities.
Jo: Brilliant, sounds terrific. And I think, well, we know indexing is key. A Google Scholar is also mostly used across Africa as a reference point because it just works. It's not perfect for making sense of what research if you search for particular research, but it's the indexing system that I think most people use, at least from what I know for Africa and Latin America and Southeast Asia just because of the payroll of web science and scopus of but Pamed I think is it open access? Not sure.
Gabriele: It is. In terms of full text they have two databases, PMC and Medline. The PMC database is more devoted to open science and so on. So they try to have the full text of all the papers that are indexed in that specific database. They are definitely doing a lot for open science as well. Yes, there is a lot of literature right now that you can find open access. The full text on PAMED.
Jo: Yeah. And the director of Open Access journals is also a good resource for journals, I think they're also now embracing preprint repositories which is basically a gateway for Qeios to be indexed in.
It just has a little bitter/sweet connotation because of course Dodge has quality standards for who and how they index. I'm not saying this will necessarily be a barrier for Qeios necessarily, but it's been a repetitive barrier for publishers from Africa where they're being discouraged to resubmit or it's just not possible for them to comply with the standards because of the lack of capacity to some degree in that sense. In terms of global inclusiveness, I think there's still quite a bit to learn to make indexing services and databases fully functional to reflect the publishing force from around the world while still complying with quality standards. So I admire the work that the team at Dodge is doing while I also see how it's well, we're all working on getting on improving this. But I think also crossref is cross reference and data sites are the two key poi assigning organizations and scholarship. Not the only ones though, but the ones that work most towards open science practices and discoverability for the community, let's put it that way. Or primarily having the community's interests in mind first. It's just that I've seen organizations like the Lens indexing, anything that's going through cross ref DOI assignment and also from other databases. So for discoverability of Qeios content, for some discoverability services you don't need to bother about indexing in the first place because it's already happening.
Jo: Just a matter of being aware and where to look. And that's again important for the researchers to also know what they should look out for as in features that a service like Qeios provides, how the DOIs are being assigned for which service and then knowing okay, if I use this service, the Qeios, I know that my work will be discoverable in these in these places. I think that's what we want to achieve to empower research and to make the research output discoverable.
There is a consultative effort right now around the globe that is unprecedented, I would say, in that direction. And I think that we are closer than ever to get in there. So fingers crossed. We will see good things in the coming years. I think.
Jo: I think so, too. And a perfect final statement, unless you want to add something else, but I think it sounds great. Services that Qeios is already providing what's in the pipeline, and I'm looking forward to continuing working with you and hope that many of the researchers and research service providers who are listening will also look into it. Unless you're already using it. Give it a try and just make sure you have all the terms that are important to you in your research registered in Qeios to make them citable.
Gabriele: Exactly. Yeah. Likewise, looking forward to keeping working together again just to team up with all the others working to the same aim. There are so many around the globe these days. So let's team up together and create a better future. Yeah.
Jo: Yeah. A meaningful and functional feature. Rich and futuristic, while still very much in the present scholarly publishing infrastructure.
Gabriele: Indeed. Indeed.
Jo: And it's already quite exciting. It's a bit bumpy here and there. It's an exciting journey already.
Gabriele: Yeah, definitely. Very bumpy, but exciting. Yeah.
Jo: Okay. So welcome back. So listeners expect to hear more from Gabriele and us, and we welcome you to one of our coming shows.
Gabriele: Thank you so much. Thank you so much. Thank you again.