I read once an article comparing networking among businesses and NGOs. The article belonged to a business journal, and was written by a person of the business world with the purpose of calling upon businesses to learn from NGOs strengths. Among others, distinct networks, cooperation and partnership, instead of competing. In addition, the author highlighted the advantages for businesses to partner with NGOs instead of opposing to them. At that time, since I had little experience working with NGOs, I agreed with the author’s opinion and I believed this was an interesting point, but I did not give it more thought than that.

Nowadays, after being introduced to Open Science, I can see how this market competition logic could be a real barrier to research and innovation, and that there is an urgent need of change behind this issue. Whilst for businesses, the value of information and knowledge rests on keeping that information to themseelves and not sharing it with others so that they can remain first in the market; NGOs build huge networks and create space to share ideas, projects, knowledge and resources. In addition, for companies to partner with NGOs means to learn how to reinforce ethics in business and to pursue not only economic profit, but social causes and justice.

Here you can check this article out Turning Gadflies into Allies

The way I see it, Open Science aims this exact transition from the business model towards NGOs networking, applied to the immense field of research. In a nutshell, Open Science aims to combat the closeness of research to build up a more accessible and fair space for researchers.

In this regard, although I barely have two years of experience in research, I am aware of the many limitations that researchers have to face throughout the whole research process, because at some point, I faced them myself.

First of all; Methodologies. It is still really hard to me to truly embrace the idea of methodology; to think about how to approach the topic, what is the most innovative and interesting angle. Second; How to write a clear and interesting key research question. This is indeed a very (maybe the most) important part of the research, because it builds the subject of the study. Third; how to collect and analyse relevant data. And finally, finding the adequate literature and having access to it. Researchers that are part of a big research institution have access to important journals and useful articles, and at the same time, they will get more chances to eventually publish in those prestigious journals, for which they hold high pressure. On the other hand, researchers with no funding that belongs to no research institution, will probably face many difficulties to find proper sources. This, undoubtedly, brings up serious unequal opportunities for researchers. The close access of publishers, journals and academia in general critically jeopardises research dynamics, resulting in walls raised against scientific progress.

However, this course on Open Science has been an eye-opener to a new reality full of hope: it is possible a change in the way we do research nowadays. A more accessible, interoperable, shareable and fair way of doing research. Open Science means not only to have public open access to useful publications, but to be opened to share knowledge from the beginning of the research process through the elaboration of Data Management Plans, in which researches share, and periodically update, how they have developed ideas, methodology, how they came up to research questions, how to collect, store and analyse data, how to interpret findings. Open Science also includes, according to UNESCO, Open Source, Open software and hardware, Open evaluation, Crow-funding, Open Lab, Open Educational Resources, Open Innovation, etc.

Many tools and digital spaces are being created to make Open Science real. There are different open access routes (gold, green, bronze, black and diamond), open social networks (research-gate, academia.edu) open repositories (ArXiv, Europe PubMed Central, Cogprints, RePec, Zenodo, universities, etc.), open science publishers (Open Research Europe) and journals.

Furthermore, initiatives at the institutional level are being adopted to contribute to the transition towards Open Science. For example, the Horizon Europe 2020 programme within the European Union, for which the European Research Council is a flagship component, and the Open Research Europe is the open access publishing service. Many associations are also advocating for Open Science and providing training courses to use open access tools. For instance, ECSA (European Citizen Science Association).

Open Science aims to combat the abusive practices within research, such as the need to pay even three times for having access to publications (the public funding through taxes, the new payment models and the price to access libraries and journals). It aims to tackle the need to also pay for publishing, the constant pressure to publish in academia, and the risk of funding cuts. It also aims that authors always keep their copyrights and that publisher companies do not retain them through exclusive rights agreements.

Nevertheless, despite the advantages that Open Science brings to research, it goes without saying that there are still many challenges to address: For instance, debates over certain open access fees and hybrid systems, the need for researchers to getting familiar with a completely new vision of research, which requires a different mindset, and learning how to use new -and not always simple- tools, data management systems, repositories, publishers, etc. This new conception of research will need to go through a transitional period, full of mistakes and setbacks, but that will eventually conduct us to a more advanced, open and fair way of doing research.

Njoud Maaitah

If I want to summarize this course in one sentence I will say that “The monopoly of information is the biggest obstacle to development”. From this course, I have learned the meaning of Open Science which is considered a systematic shift in science and research practices, with implications for the whole research cycle and its stakeholders. In contrast to closed science, I understand that OS is conducted and presented in such a way that others may participate, cooperate, and join the research endeavor, with all types of data, findings, and methods freely available at all stages of the research process.

After finishing this seminar, I think that almost everyone believes that “open science” will be the way of the research future. What do we do when we’re presented with a difficult scientific problem that we can’t solve? Many of us would approach our colleagues and seek their opinion. Our professional network is beneficial. It is also restricted. Perhaps there are people in another institution or firm, in a different country, who can help us, but we don’t know who they are. Isn’t it true that if we could reach those folks, science would advance more quickly? Or, even better, if they were able to locate us?

Regarding my field, Computer Science, sharing software or research materials with others can assist the discipline to avoid duplicating research efforts and boost cross-lab collaboration. It may also help to raise work visibility. From another hand, Open research provides verification through peer review and clear timeframes. There is also an educational component to this: when code and data are public, it is possible to replicate the results given in papers, which aids comprehension. Fundamentally, replication of discoveries is essential to open research and crucial to enhancing dependability, which benefits scientists at all levels. One of the things that I liked, the DMILawTool which was introduced through this course, it simplifies the legal aspect of data management.

Although there are several advantages to open science as mentioned above, it is undeniable that it necessitates some more time and work, particularly at the outset of a project. Fortunately, internet resources and peer and institutional assistance can help to offset some of these expenses. However, there may be another ‘cost’ or danger. Other researchers may find mistakes if they reanalyze our data or utilize our scripts or software. Obviously, many efforts will try to eliminate such risks. At the same time, we must realize that we are just human and that mistakes will occur.

and that what comes to my mind in the first moment, when the wonderful professor Eva was talking about the basic concepts of open science, I asked myself whether making everything open does not carry any risks to the idea, and by that I mean the rights of the owner, because the concept of open science promotes projects to be open to the public, But after reading more I found that there is something called Open Science Framework(OSF), and it became clear to me that there are ways to keep portions of a project private through OSF. A toggle option on the research project overview page lets individuals with administrator-level rights on the project choose whether certain elements of the project (if not all) will be public or private. Private projects, in general, are not searchable. Users can look for public projects on the internet. Certain parts of a public project can be made private, and they will be concealed from view. The OSF also offers project-level metrics, such as unique visits, downloads per project file, and top referrers, to help measure the effect. So Costs or risks associated with good and open science can be mitigated at institutional or research council levels.

I am planning to follow the steps below to be an Open Scientist:

One: I will try to find many researchers who have the same interests as me, and I will add them through ResearchGate, social media like Twitter, and Fb. Also, I will try to register with groups to post my research ideas and questions.

Second: I will share my research idea with tools and explain my research problem with other researchers. I will be interested in their opinions and their questions from the beginning, I will be grateful if someone gives me advice regards increasing the efficiency of my idea.

Third: I will try to convert my previous research works from closed to open. I will upload my source code, data sets, and results code on Github and share it with other researchers.

Forth: overleaf will be my drafting tool for any next research.

Fifth: my data will be shared through Dryed

And finally, When I finished my work, I will try to publish it through an open journal to be open access.

References

https://fredvbrug.github.io/openScience.html

Willinsky, J. (2005). The unacknowledged convergence of open source, open access, and open science.

I believe that my career as a researcher really began in the last year of my degree (3 years ago), working on my bachelor’s degree Thesis. The strong point of this project was to combine and apply knowledge from my field of expertise (electronic engineering) to concepts that were not so directly related and totally unknown to me at that time (such as hydrogels and their complex chemical concepts). At that time, I wanted to know everything that was known to date about these elements that resembled soft sweets and their electrical behaviour.

That’s when my first question as a researcher arose: how can I achieve such knowledge if many of the articles I find on the internet have restricted access? As some of my colleagues have commented in their respective posts, I understood publications as a means of disseminating knowledge in order to be reused and expanded by others. Therefore, I did not understand the reason for such restricted access.

Also, among other questions, I asked myself, is there a search platform(s) that can compile articles published in different journals and make them easily searchable and accessible? I was aware of several article search tools, but I was interested in the idea of a tool in which all publications would be open access.

Today, in my first year as a pre-doctoral candidate, the Ticket to Open Science course has answered many of my questions and, at the same time, has created new concerns for me as a researcher. From all the course sessions, the main idea for me is, above all, some of the practices to promote and participate in the great project that is the Open Science concept: provide open access to research outputs (including either publications or pre-prints, data, algorithms…), ensure reproducibility, open the processes of research output evaluation (open peer-review) and overall involving all relevant knowledge actors, including citizens. Undoubtedly, the session related to this last point of citizen science was one of the most inspiring and interesting, as it also actively encouraged participation among the course participants. For future editions of the course, I would like to highly recommend that, as far as possible and within the tight schedule, more collaborative activities like the one that took place in this session could be organised.

I was also able to learn about many new tools, which I think are very well summarised in the attached image, provided during the course. I am convinced that, as this is my first year as a PhD candidate, as my experience as a researcher progresses, I will find even more usefulness in these tools that will surely push my work to the next level.

Finally, I would like to comment that recently and at the same time as the course was taking place, I have been able to successfully publish my first article (DOI: https://doi.org/10.3390/s21134414) in the journal Sensors from MDPI, which is Gold Open Access. Thanks to this course I have a better understanding of what this concept entails. However, I must say that when we were talking in some of the course sessions about APCs, I honestly did not expect them to be that high (around 2 grand)! I believe that these costs should be lowered as much as possible to definitely boost and give real meaning to the concept of Open Science.

The word ‘open data’ is never new to researchers in the data science/ statistics field. They can rapidly find and reuse various types of high-quality datasets provided by global companies, institutions and universities via open data repositories, thanks to the FAIR (Findable, Accessible, Interoperable, Reuseable) principle. GitHub, which allows users to share their code as Free and Open Source Software (FOSS), facilitates them to publish code openly for peers review. Researchers also prefer to publish the original version of articles on the arXiv so the community identifies them as the author of articles. Is it reasonable to call such workflow using open access repositories throughout a good practice of open science (OS)?

The answer could be yes if OS is merely defined as FAIR data and shared knowledge. Plenty of software, platforms and communities together consist of an ecosystem in which other researchers can contribute and collaborate in every stage of the research cycle, with data, result, protocol, etc. For instance, the RIO helps the researchers sharing the proposal and being open at the very first stage of research; a shared literature repository like Zotero is becoming the common choice to research references for academia. Besides the mentioned GitHub, there are also AsPredicted for pre-registering, Zenodo for sharing data, Protocals.io to share workflow in the analysis step. This ecosystem also ensures the writing process and publishment open the community. The list goes on.

However, the OS movement cares more than open data and share knowledge. The OS is a paradigm that goes beyond the conceptions of FAIR and FOSS. As the UNESCO (United Nations Educational, Scientific and Cultural Organization) states in the Draft recommendations to OS (2021), OS is an inclusive construct aiming to make scientific knowledge openly available, accessible and reusable for everyone, not only the scientific community but the whole society. The purpose is to benefit academia and society by increasing collaboration and share, and to open the process of scientific knowledge creation, evaluation and communication to the societal actors. It builds on the following key pillars: open access to scientific knowledge, open science infrastructures, open science communication, open engagement of societal actors and open dialogue with other knowledge systems. This blog will discuss particular pillars from a personal perspective. 

Open access to scientific knowledge It is no doubt that every researcher, even student is a beneficiary. The researchers obtain inspiration from all open objects, rather than solely the journals and conferences in a traditional community. The students are closer to the state-of-art academic results more than ever. An open scientific community connects every member more closer such that everyone is not studying silently. But the challenges exist. The wildly used open publishment repository Sci-Hub was suspended by Twitter due to “counterfeit content”. Before this incident, it has been banned in several countries after Elsevier filed a series of lawsuits against it. Therefore, some archivists launched a rescue action on Reddit to save this open repository. Will the OS movement finally become to conflicts and compromises among academia, commercial companies and governments? In the initial stage of the open science movement, these mentioned platforms act as the pioneers to support the scientific community in converting more open. If someday the OS paradigm becomes the requirement of all research activities, will these free-using platforms turn to be profitable? Will the enthusiasm to open accessible science eventually creating more monopoly companies/organisations? 

Open science infrastructures You can never overemphasize the importance of infrastructure to research in the STEM field. But building and maintaining advanced science infrastructures is a heavy financial burden to a university or even a country. The shared infrastructures are therefore built, maintained and accessed by members inside of alliances. Personally, it is a fantastic pillar. With more science infrastructures open to the scientific community, researchers performing big-scale computing can save tremendous time and funds wasted on rent/built supercomputers. But when the infrastructure is no more supercomputers, but devices involving national security, such as space station if it is infrastructure, is the rule “as open as possible, as close as necessary” of open data applicable here? Certainly, open means no threat to safety. Providers reserve the right to close the access to infrastructures, but abuse of this right to set a boundary to open science, to maintain the technical advantages, will aggravate the Mathew effect between developed countries and developing countries.

Other than the discussed pillars, transforming scientific culture and aligning incentives is the action that interests me. The universal assessment metric to research is the publishment in the traditional scientific community. Therefore, researchers manually modify results or data supporting the conclusion in some academic fraud cases, aiming to publish their discoveries in top journals. Except for calling for academic integrity, exploring the new incentives is a crucial issue for the scientific community. When every stage of the research process is open to the community and society, the contributions on data collection, analysis can be tracked and evaluated. 

In my case, I have already uploaded the data to Zenodo and the code to Github. I also applied an ORCID and combined it with my Zenodo and GitHub repository. This is my first step in practising research that meets with the OS paradigm. But as the title indicated, OS is more than open data and FOSS. I will open more research outcomes at every stage of my research process such that I could contribute to other researcher’s work and the scientific community evolving to a more open one.

What you have learned during the course

In this course we went through the “Open Science” topic. Briefly, Open Science is a regular change in the methods used in science and research. It’s a practice of science where everyone can collaborate or contribute, sharing any kind of data related to their research freely.

Among all the topics which have been discussed and explained in the course, I would take the Session 4 Disseminating your research: Open and FAIR data as my favourite one.

In this Session, we covered the aspects about the data you use, generate and share as a researcher. One of the key points was how to make your data FAIR (findable, accesible, interoperable and reusable).

Under this assumption, everything you produced in the course of your research could potentially be shared with the community. For this reason, not only you can win the trust of other researchers, but your results could be checked and confirmed, or even new insights could be derived from your studies.

This constant feedback improves the scientific community by acting as a security mechanism during the research and after the publication.

What is your personal opinion about Open Science and what are the drawbacks for practising OS it from your personal field/career.

As a researcher, I am convinced that investing in improving your “Open Science” skills is a fantastic idea, not only because it eases your work, but also because it contributes to improving the scientific community.

Personally, I will try to incorporate all the tools we have been provided during the course.

Indeed, Open Science is a great tool for researchers. Nevertheless, the amount of extra time and resources it needs to be accomplished should not be ignored.

As a researcher, one of your main jobs should be publishing your achievements and your studies. Especially, when you take in account that the funding sources are limited for the researchers.

This is why, in my opinion, you should not only focus in trying to be the most “Open Science” you can, but also focus in your own publications and achievements.

How are your plans to become an “Open Scientists” during your PhD and beyond.

Among all the ideas which have been presented during the course, I would like to highlight some of my favourites.

To begin with, I will start making my code and data in a way it follows the FAIR guidelines. This means, I’m supposed to correctly comment my code, detail the metadata files for everyone could use it in the future or create a Data Management Plan, and such like.

In addition, the use of Open Science tools (such as Tenzing or ORCID) will allow me to improve my researcher skills and outcomes.

In conclusion, I really liked the course and I would recommend it to any researcher. The speakers (including those in the Open Science Cafés) have been fantastic, and the material (videos, slides, links…) is extremely helpful.

I signed up for this course with the idea that I was already a fully compliant Open Science researcher, so the content of the schedule would somehow ‘validate’ my prior ideas and procedures. To be honest, I didn’t expect great revelations. I could use the course just as a reinforcement of my already ‘accurate’ practices and perhaps with fortune I would get to know a few tools with which my life as a researcher would be easier. But the various sessions and speakers of the course have proved me completely wrong. It is well documented that we often evaluate experiences as a function of our initial expectations, and mines were moderate. In fact, I had attended several courses of similar duration and they were sometimes interesting but most of them barely scraped the surface. Truth is I am impressed with the breadth and depth that this course has brought to me on various domains.

First, from an ethic standpoint: I’ve learnt that following real OS guidelines is not a zero-sum game. On the contrary, by following Platinum OS path only one ‘stakeholder’ can be worse off: big (for profit) publishers. All the other relevant players (researchers, universities and society as a whole) are clearly benefited. Obviously, this is more ideological than anything, but it seems to me that it is no longer bearable to have a scenario in which all the detrimental impact comes to the side of the research community. Moreover, following real OS procedures also can bring about motivation: researchers collaborate as to build stronger networks, better resources and accessible knowledge at every step of the process.

Second, a resource perspective. I’m quite impressed with the amount of OS tools, platforms and repositories that are available. And this leads me to think that practicing OS nowadays is even easier and more efficient than ‘traditional publishing’, if I may. As a result, I already created my own ORCID account (https://orcid.org/0000-0003-4119-2232) and checked on Sherpa Romeo whether the Journal to which I submitted my latest piece of research had an Embargo Policy. Given that it doesn’t have it, I’m now discussing with my coauthors to which preprint repository(/ies) we can upload our research outcomes. Personally, I’ve gotten to know the project OSF by the Center For Open Science and I’m keen on making our work available there.

And thirdly, a resource management viewpoint. I already believed that research pre-registration was a essential practice in order to avoid fraud. For instance, by creating ad hoc hypotheses that matched the final results. That wouldn’t be science/knowledge, but a sophisticated sort of storytelling. However, an OS approach such as carefully designing & implementing a Data Management Plan (DMP) and making it available helps with the aforementioned potential pitfall. In fact, I’m now working on making a more complete DMP myself.

Finally, aside from the materials and resources that we have been offered, I wanted to encourage UC3M to keep investing in OS initiatives (as explained by the head librarian in our final session) and make an effort to advert this UC3M Ticket to Open Science course also for undergrad students too. I firmly consider that this course is going to have an impact on my research career. Hopefully it will have it on others too.

All over the years I spent in college I have been involved in innovation and entrepreneurship movements. The main idea where every entrepreneur movement spins around relates to sharing your idea from the very beginning. It is necessary and essential in order to know its limitations, and whether you may success in its development.

It really shocked me when I started my researcher career inside UC3M, during my master’s thesis and my current post as a PhD student. I did not really understand the reasons why researching was so far away from this policy.

Science, in the way I understand it, refers to figuring out solutions in order to make the world a better place. It may sound childish and innocent, but I think this motivation should be the engine pushing every single step in the researching mechanism.

Science, in the way it actually works, refers to publishing more, choosing quantity over quality. When related with scholarships and grants for developing your PhD, only JRC publications are taken into account, and the more you got, the easier is to achieve that precious goal, no matter how many years and effort you have put into your project.

Ticket To Open Science has brought me closer to the reasons why I became a researcher at first, and a PhD student afterwards. My main goal is, and has always been, to bring engineering closer to social and medical issues and try to find out the way to solve them in low-price and feasible terms. I cannot see this happening through conventional research, where I cannot find the way to share my knowledge with those who could take it and turn it into something better; or make me realize where my weaknesses are in order to develop the best possible product for the final user. All through this seminar, I have understood that Open Science is the way to do it.

For those like me who were not familiar with this term, Open Science refers basically to a combination of procedures that make scientific knowledge openly available and reusable for everyone. Everything inside this project should be open, from your raw data and methodology to your results and discussions.

By sharing every step accomplished, a reproduction of your research is achievable. Hence, errors and updates can be made, and your project can be pushed to the next level, creating something bigger than what you could have done in your own, or simply surrounded by those members of your research group. Additionally, your ideas can serve as an inspiration and a guiding principle for future researchers all over the world.

Furthermore, society can be involved through citizen science, encouraging them to express their problems, test possible results, and learn about different studies that may help them in their daily issues. Researchers do benefit from citizen science as well, receiving opinions and even ideas and personal work from those interested.

As a researcher, I have learnt different repositories where to find papers in the Open, which has been really helpful for me. As long as I have been working with medical issues, where data has a high level of security and confidentiality, it has been specially difficult even to find basic information about joints and individual measures and characteristics. Through these repositories (such as “Dimensions”, etc), some information which I found difficult to find was, not only available, but also easier to gather and to organize.

I have also learnt the importance of publishing in the Open, not only the final papers and studies, but also my coding, raw data, methodology, etc. My first step as a PhD student in order to find my way into the Open Science has been to, along with my research team, send and try to publish our last study in an Open Journal (MDPI). Furthermore, I am starting to develop my Data Management Plan and trying to adapt it to Open Access. I may need to dig deeper in this concept as long as I will be working with medical information and confidentiality is of the upmost importance and difficulty.

I have included this slide because I find it really helpful for having a better understanding about what each researcher can do in order to push Open Science Up.

However, all that glitters is not gold, and Open Science has still some limitations and drawbacks. I find the rather high price needed to publish in Open Science one important limitation, as long as publishing will report a lower personal or institutional benefit in terms of status. Thus, institutions will rather publish in the close where (even though you have to pay too) higher benefits are received; such as JRC ranked publications which may serve you in order to receive financing. Furthermore, Open Science is not that widely spread, so people do not tend to search for specific papers in the Open Sources, and citations may decrease. From my point of view citations should not be that important and Open Science will undoubtedly increase citations in the near future but, being realistic, some measures, such us the h-factor, do represent our ranking as researchers and Open Science still needs a little push up. However, this type of drawbacks can be overcome as time goes by, and Open Science is pushed higher and higher.

So, long story short, I may say that, through this seminar, I have found in Open Science the perfect tool to turn my PhD experience into something society can hopefully benefit from while I grow up as an Open Researcher.

Special Training for PhD Students

•What you have learned during the course

The course contributed effectively by presenting concepts and strategies of fundamental relevance to my UC3 PhD Project.

Important concepts such as Open Science, Open Knowledge, Open Research and Open Scholarchip contributed to a broad and global reflection on my research area.

The Course adds a valuable contribution to the researcher.

•What is your personal opinion about Open Science and what are the drawbacks for practicing OS it from your personal field/career.

As a researcher I believe and have invested in Open Science.

Open Science is a movement that proposes structural changes in the way scientific knowledge is produced, organized, shared and reused. It is a new way of doing science, more collaborative, transparent and sustainable.

•How are your plans to become and “Open Scientists” during your PhD and beyond

The course presented several possible paths that the researcher can follow:

– How to become an Open Responsible Scientist

– Open Science Tools and colaborative research

– Planning Your Strategy to Open Science

– Working in a reproducible way

– Diversity, ethics and other researc standards

In conclusion, the course is very well structured from a content point of view, providing to the PhD student at UC3 Madrid a precise overview of Open Science.

The Open Science Café presents practical and applied views on the subject – an excellent and innovative initiative!

The course stimulated me to publish an article on the subject:  eSCIENCE AND SCIENTIFIC COMMUNICATION IN OPEN SCIENCE

The most interesting topic among the ones taught in this Open Science course was the one about citizen science. That’s why I decided to check Scistarter, a website that listed a lot of citizen science projects [1]. When looking for projects related to my field, Engineering, I found two interesting ones:

Potential Penguin [2]

Potential Penguin is a game that facilitates the learning of classical Physics concepts. By modifying the terrain, you have to help the penguin reach the goal with the indicated amount of potential and kinetic energy.

By playing the game, you are contributing to the project in two ways:

• How visualization can help in learning physics concepts
• What improves the performance in our quantum games

Project Sidewalk [3]

Project Sidewalk uses labels placed by users to improve city planning, build accessibility-aware mapping tools, and train machine learning algorithms to automatically find accessibility issues. There are two ways of collaborating with the project: placing labels or verifying labels placed by other users.

What am I doing to improve Open Science

To generally improve the progress of the Open Science initiative, I’ve sent two papers to two different journals as Open Access publications (paying fees up to 2500 euros before taxes …). These papers are part of the research done for the European project Labyrinth , part of the Horizon2020 initiative, which promotes Open Science.

References

1. SciStarter – SciStarter. (2021). Retrieved 2 July 2021, from https://scistarter.org/
2. Games, S. A. H. : C. S. (n.d.). ScienceAtHome: Games: Potential Penguin. ScienceAtHome.org. https://www.scienceathome.org/games/potential-penguin/.
3. Project Sidewalk. (2021). Retrieved 2 July 2021, from https://sidewalk-sea.cs.washington.edu/
4. Labyrinth 2020 – Ensuring drone traffic control and safety. (2021). Retrieved 2 July 2021, from http://labyrinth2020.eu/