Tag: #ticket2OsUC3M

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Embracing Open Science: What I learned so far

Image by storyset on Freepik

When I first started the Ticket to Open Science course at UC3M, I had already been exposed to the Open Science concept and was familiar with some of its tools. After all, I’m working on a research project funded by the European Union that has to comply with several Open Science standards. I was familiar with the FAIR principles and the importance of a data management plan and platforms like Zenodo. Yet, this course offered so much more. It made me realize how much I still had to learn and introduced me to many platforms and tools essential for conducting and sharing research effectively.

The course emphasized the importance of transparency, accessibility, and collaboration not only when disseminating research but also throughout the research process (as a new researcher, I confess that I had been focusing more on the finish line rather than the entire research process). It highlighted that each researcher is responsible for embracing these changes. It also made me realize the substantial effort involved in adhering to open science principles throughout the research process. This is not to say that progress hasn’t been made. Indeed, there are many tools and platforms available to facilitate or at least assist researchers in their Open Science journey. From platforms that help create data management plans based on standard templates, such as Argos or the Spanish version from Consorcio Madroño, to open data platforms like the Open Science Framework (OSF) and collaborative tools like GitHub or Overleaf, there is a wealth of support available in the Open Science universe (you just need to know where to look).

Reflecting on the concept of Open Science, it’s challenging to understand why any researcher would oppose it. The idea of promoting open, transparent, and inclusive research that enhances the reproducibility and reliability of researchers’ work, fosters greater collaboration across disciplines, and contributes to a more inclusive and equitable scientific community seems aligned with why most people become researchers in the first place. Yet, Open Science is still met with suspicion by many academics. Some are concerned about intellectual property and potential misuse when sharing data or methodologies, while others are more focused on individual achievements and publishing in high-impact journals. On top of that, it is undeniable that Open Science practices are resource-intensive, requiring time, funding, and technical skills that many researchers still lack.

The main issue, however, seems to be the lack of incentives. The current academic system rarely acknowledges or rewards efforts to share data or engage in Open Science practices. Researchers who invest time and effort in making their work open often do so without formal recognition or career advancement benefits. While some steps have been taken to address this, we still have a long way to go. As a PhD student, I believe young researchers are under more pressure to adopt Open Science practices while their work is still mostly evaluated based on their paper outputs.

I know there are no easy answers here, but I can see that building an Open Science network, like the one Eva Mendes is attempting with this course, can provide support, resources, and collaborative opportunities that make adopting open practices more feasible for researchers. It also helps promote awareness, educating other researchers on the value of Open Science and the available tools, hopefully shifting the academic culture towards Open Science. From my part, what I can do is lead by example, incorporate Open Science practices in my research, and hopefully inspire others to follow suit. After all, I believe in Open Science principles, but I can’t deny that it would be nice to be rewarded for it too.

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Open Science: the Collective Advancement of Science

Since I began to take an interest in science, I always liked the idea of sharing the advances that could be achieved through effort and research. At first, it was just an idea, but when I discovered that it had a name and it was Open Science, it became much clearer to me that I wanted to be a part of it. When I saw that the Universidad Carlos III de Madrid was addressing this field and allowed me to increase my knowledge in this area, I saw it as an opportunity to start understanding how to properly use the tools. That’s where everything covered in this fantastic course “Ticket to Open Science” comes in. Open Science is a great revolution in democratizing and socializing science, allowing everyone to participate in the advances being made, not limiting their understanding or their ability to use it to just a handful of people. Access to open science has personally allowed me to access knowledge in certain fields or topics that, at first, I might not have thought would interest me. One of the ideas I particularly like about open science is the lack of competition. Working in research centers can lead us to focus solely on producing redundant results or those with little novelty just to force a publication. Open Science tries to avoid that. The aim is to democratize this knowledge, promoting progress over publication, which in my opinion makes science advance much faster in certain directions of knowledge. In this course, this idea has been made clear, seeking the balance that every researcher must have. Do we seek to publish? Of course, publications give you visibility within your field of specialization, but do we want to promote progress? Absolutely. And that’s where the Open Access tools seen throughout the course come into play. The existence of these tools promotes these advances as they allow for a more global sharing of all the achieved progress. In my personal opinion, it is this duality between a scientific publication and an openness of data, code, or obtained metrics that fosters a double scientific advancement, both in the technical direction and in the direction of opening up to society.

What we have seen during the course?

During the Ticket to Open Science course, we covered a large number of topics related to open science and how to use it in research. The first sessions introduced us to Open Science in a global way, giving us a general overview of what we were going to discuss. We were also given tools to use open science and tips on how to apply it within our research field. We learned about the principles of FAIR data and how to create our own DMP plans, which allowed us to establish what type of data we would handle and how we would manage it during our research. We were also introduced to the internal tools available at UC3M, such as UNiOs and the library support. This was very important as it made us aware that UC3M encourages us to work in open science by providing us with its own tools for it.

The following sessions focused more on the legislative and ethical aspects of open access, emphasizing the need to always maintain ethics in our publications and the open access information we generate. In the last sessions, we were introduced to Citizen Science and public engagement, which was one of the most illustrative parts of the course, highlighting the idea of opening science to everyone so that people from anywhere in the world can participate in the advances. The final session was specifically centered on open science techniques for the engineering field, where we could clarify much more specific doubts about our research and the data we generate in our area of study.

In addition to the lectures, the course included a series of Open Cafes, where experts from different parts of the world, both nationally and internationally, presented us with more concrete cases from all the previously explained fields. These sessions were highly illustrative as they allowed us to see how the open science community is global, and how from different parts of the world there is a focus on developing these tools.

And now what?

Once the course is finished, all that remains is to put everything we’ve learned into practice. But how can I do this? Firstly, all the developments I have been working on during my PhD have been uploaded to an open access platform like GitHub. All the uploaded code is associated with a paper, which we always try to ensure is open access. This allows all the advances made to be viewed both in paper format (which references GitHub) and directly on GitHub (which references the paper). In addition to this, I have started using the tools provided by UC3M and the library, which allows us to upload all the work done to the university’s public repositories so that the university community and anyone else can access these works.

As a final reflection, I would like to add that the existence of these courses promotes the progress of science. These courses can open the minds of different audiences, from university students to professors, encouraging science to raise its voice and demonstrate that together we can achieve much more solid and lasting advances.

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Open Science: the revolution in the socialization of science

A few years ago, when I began to study and research Open Science, most authors relied on the concept that it was an umbrella that recognized the value of open science as accessible, collaborative, and reproducible. This idea shown in the following image continues to have prominence when it comes to explaining Open Science. I share this perspective of Open Science and at this point after everything that has been addressed in the Ticket course to Open Science I consider that Open Science is a true revolution in the socialization of science.

Representation of Open Science by Eva Méndez

From experience I have also been able to verify the benefits of Open Science. I come from Cuba where access to information is restricted by factors inherent to the United States blockade of the island and the Cuban government’s own decisions and this bias interferes with the quality and transparency of science, so in one of the issues of the course, when we were asked if Open Science also involved differences between geographical regions, I took a position in saying that there are indeed differences. Hence, it is one of my motivations to delve into this topic. It is not about competing in “impact factors”, it is about advancing a little more every day in raising awareness and in the daily practices of the academy; democratizing knowledge will depend on the sustainability of Open Science. Although, I am concerned that Data Management Plans, for example, are not common practice and that literacy on these topics is often reduced to theoretical approaches or at least prioritized.

What unites us

We agree that access to information is a universal human right, and the Open Science model constitutes an opportunity to fulfill and guarantee that right in the long term. Currently, there is a greater institutional will to promote processes covered by Open Science. Government structures have been legislated that reinforce work for the common good of access to information and open knowledge. We are aware that everyone must do their part by developing data management plans, participating in groups promoting Open Science, using open tools and software, sharing the results and data of our research, collaborating on projects. research. In this sense, this course brings us closer to tools that I was unaware of and from now on I intend to continue using. The use of data and information repositories, Virtual Learning Environments, the willingness to publish in Open Access journals and advisory services are examples of good practice. On this last point, I am grateful for the meeting that a group had with Raúl Aguilera Ortega, from the UC3M library service, and he told us about policies when publishing in open access journals, as well as databases and repositories, which can be opportunities. in our development as researchers.

Reclaim the common

The progress of science rests on the generation of scientific knowledge as a social-collective process. Strategies from now on must focus on teaching offers, audiences, tools and methods with data intensive science and open science. It is never enough to raise your voice and investigate Open Science; courses like this must be diversified as spaces for debate and with the participation of various specialists who share their knowledge and experiences.

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Thinking about Open Science

The course presented to the participants a conceptual and practical journey to know, deepen, and rethink the new scientific paradigm called Open Science (OS). The classes and Open Coffee modules were designed as complementary instances where the encounter between the theoretical aspects and the concrete tools and initiatives was fostered. This methodology allowed bringing theoretical issues into daily practice and showing different examples of good OS practices.
The reasons why we need Open Science were clearly established: visibility and transparency. Scientific knowledge must flow freely, be available, findable, searchable, and usable. The research must be transparent in the processes, data, and results, but also in the evaluation to which it is subjected. In order to give meaning to these words, it is necessary to rethink the scientific system thoroughly, what scientists are expected to do, how they are evaluated, and what is rewarded. Transforming a competitive and closed system into a collaborative and open one implies a profound cultural change, which this course greatly contributes to.
The program presented a broad set of applications, infrastructures, and information systems among other initiatives that institutions have been promoting to trigger a change in scientific culture. These initiatives, oriented to different aspects of OS, both at European and international level, provide theoretical and conceptual support to open science and promote good research practices. For example, we learned about OpenAire, EOSC, Unesco declarations, FAIR principles, Horizont Europe policies, Sherpa Romeo and Juliet, among many others.
Ticket to OS gave me the opportunity to refresh and update my knowledge on topics that I have been working on, such as Open Access, while allowing me to delve into topics I was barely familiarized with, such as citizen science and Open Data.
Furthermore, the course allowed me to rethink my thesis in OS code, particularly on the topics related to open data and FAIR data. I wondered about the possibility of carrying out a Data Management Plan. The DMP should consider not only the data but also the procedures and instructions to be executed with the data. Ideally, in a OS level, having Open Data based on the FAIR principles would be the most suitable for any thesis. I would be delighted for my data to be findable, accessible, interoperable, and reusable; FAIR would provide transparency, reproducibility, and reliability to the research. However, in my thesis I am going to work with data that comes from a subscription source: Web of Science. I wonder if the data can be shared and understand that it may not be possible. I will need to investigate further to see if there is a way that this data can be shared. I think this is an issue that needs to be addressed because those of us who work with bibliometric studies tend to use data source from commercial providers that hinder their sharing. As for how I intend to become an open scientist, I will start by working with open source systems such as R, publish the result of my research openly, deposit my work in the repository of my universities (UC3M and University of the Republic), use the permanent identifiers, and continue to look for ways to use data that can be shared.
My opinion about OS is that it is a new scientific paradigm, because it undermines the very structure on which the scientific system is built: competition for access to information and data, blind peer review, large oligopolies editorials, the scientific evaluation system according to the number of peers and their impact, among other aspects. In contrast, OS proposes a collaborative, transparent science, available to everyone, including the non-academic community. A science for the citizen, which addresses complex problems that arise from societies with an interdisciplinary approach; a science where the results are within reach with no other obstacle than access to a device with internet where the data is also shared. Open Science proposes open review systems. It also proposes an evaluation in which scientific quality is not only measured from the impact factor but with alternative metrics, where open publication, open data, and the transparency of research are well valued for the promotion of individuals, groups, and institutions. Otherwise, it would be inconsistent to promote certain changes and continue to reward outdated practices.

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Open Science feelings. I’m in.

When I started this course about Open Science, even after seeing the agenda, I remember thinking “well, for my professional development, all this content sounds familiar to me, I have read about this at some point …. ” I knew the difference between Open Science and Open Access to publications, I could talk about Plan S, I knew the FAIR principles, the importance of data management plans, I had even participated in an exporadic way in some citizen science project related to health, terms like metadata, repositories, green/gold open access, interoperability or reuse, are present in my vocabulary almost weekly, but always to support other researchers. 

However, although I was aware of the strengths and weaknesses of these subjects, I did not dimension how complex this universe is.

Once I finished the course, I felt like I had the puzzle pieces and they fit, making the whole picture start to be visible to me. I have realised how important Open Science is in the whole research process. 

Open Science is changing the way people understand the research process. It’s not limited to  Open Access, to publications or data, it includes open peer review, citizen science and others. Open Science is a new paradigm to generating and sharing knowledge, and beyond that, to support an equity society with no one left behind even in those low resourced environments. 

Another relevant aspect I found is the importance of the Research Data Management Plan. As a researcher I will prepare a Data Management Plan to establish what kind of data I am going to collect or generate and analyse, if I’ll need to get some special permissions to reuse them, where I am  going to save and preserve those datas, or how open they are thought to be.

Establishing a strategy  of our research considering Open Science should be one of the priorities in our research process in order to build an open network that reinforces collaborations, open knowledge transfer, open innovation and implementation of our research. This strategy will also improve the visibility and dissemination of the research.

Science should be easily accessible, and published in a fast way in order to prevent  duplicate projects and get better results by exposing research achievements although it sometimes implies a mentality or cultural change to be retracted or criticised, making visible mistakes, not enough (or gaps) evidence to get conclusions or  things like that.  Anyway, all of this generates knowledge.

Some tools and apps have been used for me during last years as mendeley, zotero, zenodo, open metrics tools, social media tools, creative commons licences, sherpa romeo, although I have discovered new tools and apps as RIO, Authorea, Lens, Core, or Pubpeer, as well as amazing initiatives as open science MOOC, Research Data Alliance or EOSC that I am sure they can help me along my researcher life.

Nevertheless, we also found weakness in this movement. Despite the huge effort from European Commision and some governments, there are still difficulties with many policy makers, governments or institution managers who don’t support this new paradigm and hold to the old structure.

Publishers play a critical role in this Open Science Movement. On one hand, most of them are adapting their policies to publishing, providing Open Access options with the same quality standards, including Open Peer Review, and asking for open data to validate research. Here, one of the problems is the expensive price of some APC for instance. Other issues we have to deal with are predatory journals which found an extraordinary way to earn money publishing low quality articles or cheating authors with unreal Impact Factors.

Policy makers also play an essential role in funding, developing rules and strategies and providing needed structures to incorporate Open Science to every single statement of our society from citizens to institutions, etc.

And last but not least, institutions who support and assess research should implement a complete change in the rewarding system. 

As PhD student I think that actions like to design a strategy for publication and dissemination,  to use social media, to use and update unique and persistent identifiers (ORCID, research ID..) to use open licencies, to share my research outcomes in an open way (publishing preprints, making my data FAIR, using open repositories….), or add some tools or apps studied along these Open Science Sessions, are essentials to become an Open Scientist.

As an Information Specialist I am sure all the knowledge I got will be absolutely useful in my daily routine supporting my colleagues. 

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Open Science, Open Excellence

Open Science: a very broad topic that some fear while others love.

It took me 2 years of PhD program to understand why the research industry is flawed. I am not willing to perform a socioeconomic approach, but, as far as I understand, the monetization of knowledge even though has been useful in terms of copyright when generating value to companies/countries, I think that it must be redirected and somehow democratized if we, as a society, want to improve. In general, by game theory we can state that humans GROW if they SHARE, and in this case the sharing must be performed in terms of knowledge and resources.

My expectations of the course were very high. Before then, I barely knew about the concept. My humble approach was: “Open Science is the legal implementation of Sci-hub”. Nothing could be more untrue, Open Science is MUCH more, not only “the Robin Hood of knowledge”. In this course, I learnt about the specifications of Open Science and how the world is implementing all the official infrastructure, all the paths a researcher can take to become an Open Scientist. Open Science is a new paradigm (as the first session of the course was called), with new methods and different points of view when contributing with others. Quality vs. Quantity. The advertisement in social media in a competitive-productive way. In essence, meritocracy in strict sense.

One of my favorite sessions was the 5th one, Citizen Science and Public Engagement, because it woke up my childish spirit. When I was a child, I loved to experiment with machinery, watch animals, understand curious physical phenomena. I loved to try how different inputs resulted into different outputs, to understand the mechanism of things in simple day-to-day situations. This passion did not die but became a bit numb.

If citizen science become a thing, society will improve for sure, not only in terms of proficiency but also psychologically. Most kids do not like science because it is explained in third-person, it is boring and the reward is invested in the long-term future under the premise “you will get a good job and be financially independent”. On the other hand, most adults do not feel fulfilled because they could not pursue their dream, but, what if they could not pursue their dream because they did not know what the dream was about? Most people do not know what is their talent, what if one of the best potential-ornithologist is someone who liked birds but ended up working in something else because he/she could not learn about the migration of swallows? What if the private publishing was one of the reasons of not being able to develop a passion?

If citizen science is a project that can be materialized, I am sure the world will be happier, people will be able to study or do hobbies without restriction. And without restriction, endless contributions may appear.

In connection with that, I believe that citizen science performed a qualitative leap, specially during last year, since Covid pandemic struck. Then, a lot of Open Science was performed, I do not know if it was under this “specific” name, but at least it was conceptually performed. Knowledge was way more shared, researchers were taken more seriously, new free of charge research-kind applications were created, etc. And with reference to this last example, I would like to connect the ending of my blog with the question: How are your plans to become an “Open Scientists” during your PhD and beyond?

(Banner: I do not perform any kind of monetary-reward advertisement, I just think that the following application is an example of Open Science that must be shared and used in the research field)

A few months ago, a friend of mine asked me: “Hey! are you more an Obsidian or a Roam Research person?” For those who do not know them, they are applications that connect concepts, notes and knowledge, and gather them in a very useful way creating the so-called “Vault of Wisdom” (others call it “Second Brain”). The difference between them is that Obsidian is free-of-charge and it has the capability to publish the notes online. It was created during the lockdown (approximately) when a group of programmers wanted an Open Source knowledge manager app.

Then, my plans to become an Open Scientist begin with this application (Obsidian), in which I plan to publish everything I know, particularly everything involved in my PhD discoveries, including all the Open Science Café information that I obtained from this course.

However, even though this approach is extracurricular and non-oficial, academically I would like to participate in the Open Science world, for example, by publishing in the IEEE Access journal, which is an Open Access Journal of the IEEE society.

Also, I would like to incorporate in my day-to-day research life several applications like Github for uploading the code, Overleaf for writing purposes, as well as being more participative in several communities like Twitter or Stack Overflow, among others. In any case, I will save as a cheat sheet, one of my favorite slides of the course (from the first session):

Thanks to this summary of platforms, I will be able to integrate one application at a time so I will GROW by SHARING my knowledge at each stage of the research.

In the end, I think that the course was very useful, I liked the structure of each session and I would recommend it to anyone, even though those who are not researchers. Also, I would like to thank the speakers of the course and the Open Science Café sessions who where very helpful by providing their knowledge and resources, which have been very interesting.