 Okay, so good afternoon everyone, just sharing my screen with you and we can start this second module. We will discuss many things today. Okay, so you should see my screen now. So, I'm sorry, this is not the correct. I took the wrong one. Okay, so, okay. So, we will discuss today about open access and fair principles. So, before we start, I just launched the Mentimeter for you. You can go there and then you can you can go to menti.com and then enter the code or you can directly go to the link. I guess maybe Ali can share the link with you in the chat. And while you take your time to vote for this Mentimeter, it is a simple question. Then we can go on and start the lesson and we will discuss today on a particular aspect of open science. We have seen in the first module that open science is an umbrella term. It comprises different actions that you can embrace and embed in your workflow. So, today we're going to the deep details of how you can open access your publication, your research data, and also your other results. For example, the software. I just recalled the definition that we have seen in the first module. So, open access means free and unrestricted online access to research outputs, both text and data, but also other research results. So, one thing that I would like to stress here is that when we say free, we are referring to the end users. So, of course, everything that you will do and all the tools and infrastructure you will use to make your results open access will have a cost. But this is not on the shoulder of the end users that wants to access your results. We have learned in the first module again that open access doesn't mean paying for publishing and we will see now what this means. In practice, you have to follow some simple steps that I am describing now. These steps rely on the fact that we already have good infrastructures that allow us to deposit and share our results. And as you may recall, these are open access repositories. We have seen the slides before and just highlighted that in many cases, your institution does have already a repository or you can go and check if you're specific thematic or disciplinary community maintains an open repository. And we will in this part of the course discuss about how to use literature repositories and also catch all repositories because they can also contain text. So, when I speak about literature, I mean text, basically documents. So, you have to think about the articles you write but also reports. It is important to share, for example, project deliverables and other kind of documents that you may think could be useful for others. So, how to perform open access to scientific literature. It is quite easy. You have two ways you can do that. You can either choose a gold open access journal. We have seen that in these journals, your article will be available in open access to everyone from the very first moment of publication. We have seen that not all these kind of journals apply APC to the authors. We will discuss this in details in a while. So, it's not always true that you have to pay for publishing in this kind of journals. But indeed, they will make your content available to everyone to read immediately. Then, the second way that you have to perform open access to literature is what we call the Green Road. So, when you publish a paper in a journal, you can always share with the world in open access a version of your paper. Wherever this paper has been published, you can use this version and deposit it in an open archive, so in our repository. And still, you can do this in compliance with the copyright regulations. So, what happens is that the editors may require an embargo period, which is the period that lasts between the deposit and the openness of your paper. So, basically, if you publish a paper today, you can deposit immediately your paper in our repository, and then you can apply an embargo period, which means that according to the policy of the publisher, suppose this publisher puts an embargo period of 12 months, you can set the repository to open the attachment, so the paper, in 12 months from now, from the date of the publishing. Once you are using a repository to share your article, but this actually holds for all kind of material that you can deposit, you should guarantee the reuse. And for papers, what you can do is that you can set an open license for people to reuse your paper. Usually you can use, for example, creative commons, we will see them in a moment. And so you could ask people to openly reuse your material and possibly cite you, for example, but we will see details in a moment. What are the versions of a paper that you can deposit in our repository? Well, they depend on the policy of your editor. And these are three versions. So we have the preprint, which is your final draft that you submitted to the journal. This is your original manuscript and does not contain the comments of the peer review process. So it is the first version you sent to the editor for submission. Be aware that for some journals, the preprint you sent must be original. So if you already deposit this in a preprint server, for example, some journals will not accept your paper for publication. But it is often the case that this is the only version that you can share with others. So preprint are very useful because their copyrights usually remain within the author. So what happens is that after you published your paper, at least you can deposit the preprint in our repository. One thing and one comment that I have here is that is actually very often the case that preprint are not so different from the published version. What happens often is that if the preprint contains major error or is not in a good shape, it's usually rejected by the reviewers. And it's not so often that we see major revision to be applied to the preprint. So usually the preprint gives a very good idea of the contents of the final version that is published. So they are good for scientists that can read them in advance with respect to the published version, which is often, as you have seen, closed behind a paywall. So the second version that you can usually deposit is what it is called the postprint or accepted manuscript. This is the final version, including the reviewer comments, and it is identical to the published one except for the editorial layout. So for the number of columns, the shape, the dimension of the figures, or the name, volume and date for the journal that you published your paper in. So the final version can be the editorial PDF or published version. So this is the exact version that you published, you see published in the journal website with layout and graphic that are typical to the journal. Usually this version is available for deposit in your repository for open access journals and is, as said, identical in the contents to the postprint. So these are the three versions that you can choose to deposit in your repository. And how do you know which one? Well, each journal has a specific policy on deposit and embargo periods. And you can check it through a very easy tool to use, which is Sherpa Romeo database. I am leaving you the link. So this database basically tells you what you can do with each of these versions for the different journals. So it is very useful. You will learn very easily that if you usually publish in the same journals, then it's a matter of starting and getting to know the rules. And then you will be able to do this very quickly. One other resource that I would like to mention here is that there is what is called a directory of open access journals that can help you in finding an open access journal in your field. This directory is a curated directory. Journals in here have to apply to enter the directory and there is a very good check by the editorial board of the DOIJ. They also apply some kind of seal to the best open access journals that follow specific rules. So this is a good resource that you can use also to distinguish between scientific publications and what you may know are called the predatory journals. Now this directory is curated and it is periodically checked. So you are almost pretty sure that predatory journals do not fit into this directory. You can also use another good tool to distinguish between a good and not good publisher or journal which is this think check submit. And you can use it to understand whether your venue for publication is a good one or not, independently on the fact that this is an open access or not open access journal. Okay, so I have some tips for you for some journals that are quite familiar in your community. So this is a screenshot from the Sherpa Romeo directory. So as you can see here you will find some general conditions for the journals. It's going to tell you whether you can deposit your pre-print or post-print and under which condition. In this case you see you can either deposit the pre-print and post-print and not publish the version. Okay, so you can read also the statements and check because there is a link the policy of the specific journal. Okay, so it says that you can use your institutional repository or a funder agency repository and so on. And so you are, you can use that as your repository. One thing that I would like to highlight here is that ResearchGate, academia.edu, Mandley or SciHub, as you may imagine, are not considered as some sites where you can deposit a copy of your your manuscript. This you may have to know because many researchers today for example are sharing original published articles in ResearchGate and academia.edu. But this does not comply with the rules of the journals and they violate actually copyrights. It is a news of some years ago that I think it was Pringer issued, asked to be to ResearchGate to remove 1.5 million or something articles that were uploaded to this platform. So this is not legal, you have to know and you should instead use your institutional or funder repository. So this is another example that you have and here as well you see that you can either deposit your pre-print or post-print version in a repository and you also have the link again to the policy of the publisher. And what you can see here is that you can publish the post-print, so they call it here the author's accepted manuscript. After and you can deposit and then make available your version after 12 months. So there is an embargo period to apply. Okay so having said that and how you can apply the rules for open access to your publication, I would like to discuss with you about the plan S. You probably already heard about this. It has been quite a revolution in the field so it's interesting to discuss the details. So plan S is an initiative that was launched in late 2018 and it was an initiative, it is an initiative that is supported by a coalition of funders. So we will see them in a moment. But the main goal of plan S is that starting from next year scientific publications that result from research which is funded by public grants and by those funders of course must be published in compliant open access journals or platform. By saying open access journals of platform the plan S makes a list of requirements. Basically you cannot publish in hybrid journals so we have seen these hybrid journals are those asking both for submission to read and APC to open access a single paper. They require no embargo period. This is very important because in this case what you can do is either publishing in fully gold open access journals or journals that provide you the deposit in compliance with the copyrights or better the contrary a copyrights agreement which is compliant with the fact that you can deposit your postprint into an open repository. So as we said the coalition S is a group of funders, organizations and initiatives that have endorsed the plan. As you can see the European Commission is one of the member of this coalition. We have also other many other members. What are the consequences? Well I said that this plan was launched in late 2018 and what happened is that the plan S led to the fact that institutions and countries tried to change the way the contracts for the services of the publisher were drafted. So they went for what we call today transformative agreements. Basically large institutions or countries are contracting different publishing models to allow their researchers to publish in open access all their works instead of paying to give access and read the article that others write. So these kind of contracts are called publishing read. So basically the amount of money that the institutions and the country are giving to the publisher serve to both read the contents of the journal and to publish everything that comes from this country or that institution in the journal itself. One of the main characteristics of plan S and transformative agreement is that the content must be published and publicly available. So transparency is one of the main characteristics of transformative agreements. What happened was that many many countries and many institutions or coalitions of institutions joined these transformative agreements and what happened is that many deals were actually signed with also big publisher UC Springer Nature or also Elsevier and many others. There is a complete list by country and by institution that is available in the ISAC initiative website. So you can go and check whether your country or institution already signed some some transformative agreement. One important thing is that these agreements are called transformative because their main goal is to go from the current business models for scientific publishing to a full open access business model. So these agreements need to contain a statement from the publisher that they will transform the business model of that specific journal into a fully gold open access journal. Okay so plan S also makes makes available a good journal checker tool. So basically in case you do not know whether your combination of journal that you choose to publish in the compliance to the rules of your funder and of your institution whether it is or not compliant with the plan S you can simply check by using this tool. Okay so I will stop here the the discussion about the this literature open access. So before I go to the to the part that regards the fair fairness and fair principle I'm going to see you I see you have some questions. So okay someone is asking where we can find the slides from the last session sent a link but I didn't find the slides. I will put the slides in Zenodo apologies I didn't have time to do that yet but the idea is that you will find in Zenodo. I know I'm hardy here so maybe I'm hardy you can also explain where people can find the link. Yes precisely I think the way we will proceed is yeah using Zenodo to share openly the the slides and we will of course then also link to to these presentations on the Tricera website. There will be a dedicated section for the one dedicated for open science and we'll probably dedicate the page for the webinar. So all the links will be shared with you as soon as possible. Okay great so there is another question from Julia I think the version that you send as a second revision paper after our revise and resubmit result but before the final reviewers comments is this also a pre-print in other words sometimes you send several versions of to the journal before it is accepted that the pre-print can be the last version you sent before accepted with final reviewer comments the answer is no. So the pre-print is only your original manuscript the the one that you sent in the first submission process okay so this is your original manuscript that has nothing that includes no comments from from the reviewers okay whereas while you the version that you send the subsequent versions if you have more than one discussion with the reviewers are let's say we can call them a preliminary version but what it counts is that you have a distinction between the pre-print that does not contain the reviewers comments and then you have the post-print which is identical in the contents to the final published version okay so of course the only difference can be some minor changes in the in the layout of the version and the editorial of course editing okay so i hope i answered your question okay i don't know if there are any other questions from for this i see there is a discussion in the chat no no no okay no others okay okay so um before i go uh in this um i i start the uh the fairness uh what i would like to share with you is the results of the mentimeter so the mentimeter was asking you whether your data is findable accessible interoperable and reusable so uh uh this is what you answered so you basically think that your data is highly findable uh and accessible okay you think also that your data is reusable and in a certain way is also interoperable okay that is good to uh this is good to know i just leave you a few moments i see some someone is is voting still uh and then we will close this uh this voting and uh we will then go and and and go on with our lesson okay so i'm closing the voting now just to freeze this image and then let's discuss now about uh the fair principles okay first of all we will need some definitions a couple of them not many things uh digital object so in the context of this presentation uh i refer to any research results in its digital form that can be uploaded and eventually open shared uh in our repository so a digital object can be an article a data set a piece of software an image video a presentation uh or a conference poster and whatever you can consider our research results so um the other thing uh that you have to keep in mind during this lesson is that when you deposit something in our repository you are creating a new record of the repository this new record is composed of two parts the first one is the payload so it is the physical digital object how to say the file that you are uploading these can be one or more files and uh uh can contain different can be files in different formats uh the payload can include the the for example a data set in uh in a spreadsheet uh and for example any accompanying material like uh a readme file or whatever you think uh may be included in a single record then on the other side you have the metadata uh the metadata is a set of data that describes your digital object so the payload that you are depositing okay so in this slides you see a screenshot from Zenodo and you can see that we have in the central parts in the violet case the the file so if you click on the file you can download it and then you have in blue the parts that represent the metadata of this of this object so you have the date of submission you have the the access right this is an open access so you have the type of resource so this is a lesson uh you have the title you have the author so you have the description uh and then you can have also technical information like the doi for example keywords um uh you can see from here which projects which grant um were used to produce this uh this record and so on you also have the versioning of course so the record consists both in the payload so the files and the metadata okay so having said that we can start and go into the details of uh the fare principles uh so uh first of all um the fare principles indicate a list of principles of course that can help you uh in making your data ready for open science they are principles and not standards so uh the thing is um there is no single way to apply the fare principle to all science it really depends on um the discipline and on the specific way you apply a workflow to your work okay so it both depend on the context and on how you work these principles were designed to enable an optimal use of research data and methods so uh when I say use I mean reuse also by others um the fare principles were designed in two years time by a group of different experts um so there was a very big discussion about the fare principle and what they did they listed a set of 15 principles now these principles are very technical so um I'm not going to go into the details of what the single principles say but I will leave you the link you will find in my presentation to go and check uh I will give you today more a flavor of what is the meaning of this fare principle and how you can apply them to your workflow so first of all what does fare mean um well fare is an acronym it means a findable accessible interoperable and reusable now let me start from the last one reusable because this is the goal of the application of the fare principle reusable means that your data can be reused by others in your research so uh this is the goal that you have to keep in mind when you try to apply the fare principle to your results always keep in mind that everything that you do is because someone may reuse your results findable means that uh your data or your result is uh findable by others so other can find your data and they can even cite it uh accessible means that your data is accessible to others uh we have seen that this doesn't mean that your data must be open but it means that you have to clearly state who will have access when and how to your results interoperable uh means that uh your data uh can be integrated with other data and or they can be easily used and read by machines okay so um it means making your data interoperable with others and also with automatic workflow or application or computers or whatever okay so um um next is uh these slides that allows me to to tell you that there is a life cycle for your data start for from the planning uh collection or creation of data processing and analyze uh publish and share preserve and reuse this life cycle is uh strongly that the fare principle are strongly interconnected with this data life cycle but it is not possible to connect a single principle to a single step of this life cycle so everything that you do during the life cycle of your data uh can um interfere with the application of the fare principles again i would like to stress that applying the fare principles doesn't mean that you have to openly share research data so fare data doesn't mean open data what is the difference okay so open data are data that can be freely used shared enriched by anyone anywhere and for any purpose um fare data instead are data that follow a series of good practices that allow data access still respecting any ethical legal and contract contractual restriction so why am i telling you that because your research data could in principle contain personal information so uh you will fall under the privacy and GDPR restrictions for sharing your data could fall under the copyright so in the case of a database with creative structure for example or could fall under the su-generous rights uh so which um are database that are obtained thanks to a substantial investment can be protected by patent or industrial secrets so some data cannot be shared openly okay so and data sharing needs to respect the specific low and framework where your data were created data needs to be protected against uh uh known authorized access this is very important so for example think of clinical data or personal uh information so the question is how can you adhere to the fear principle if your data cannot be opened well you can still uh by managing correctly your data and create and share a description of your data uh by doing these other researchers may ask for permission to us access your data for reuse purposes and they can give a specific aim and following the rules that are defined by the law so in this case you can apply what is called restrict access to the record payload so to the files but not to the metadata so still you can share the metadata but close the access to a specific payload files so let's go into the details of um of uh good practices that you can apply uh to make your data fair what will happen to your data when when you will apply the fear principle well first of all you will learn today that um applying the fear principle will make you think and plan in a good way your data life cycle so basically you will produce high quality data you will maximize the impact of your research because people will get to know that you have a good quality results you will improve the recognition within and also behind your research community as I said in in the beginning the application of the fear principle strongly depends on the specific context and discipline and on the way a single researcher works okay so here no one size fits all but why should you apply the fear principle uh and why do you need them uh the ultimate goal uh we we we saw it a few minutes ago is that you are doing all this to make your data or your digital object your result reusable and also safe this is quite important because you will provide um uh you you will make your data reusable to others but you will also make your data safe uh and so you will not lose your data um this is the main goal uh that as I said you will have to keep in mind when you try to apply the fear principle to your results so the the main question is are my result reusable by someone that was not involved in its collection or creation this is a very important question that you have to keep in mind that you you will have to answer when you for example uh are choosing some tools or are um uh choosing a strategy to apply the fear principle so how can you make your data fair um we have some basics for verification these are the elements that you will have to work with first of all is the documentation these uh will make your data understandable by others by giving the context where the data were created uh metadata uh will make your data easy to find uh because they describe your data so people will use your metadata to understand what is inside the payload data formats are key because uh they make your data simple uh they make your data simple to combine to other data and they also make data machine readable um access to data means a strategy to say who when and how can have access to your data persistent identifiers are another key element um they link um are persistent link to data that follow that allows other to find the inside so give credit to to your data and then licenses of course that are used to tell others what uh they can do with your data so let's go through this list of of elements one by one uh documentation it specifies the context that led to the creation or collection of your data and they make the data understandable to others uh in the beginning of your project activity and this is the planning phase uh you will have to clearly define uh a strategy to structure and document your data this is very important because uh you may want to use a specific methods tools software um you will have to uh detail the metadata that you want to use uh you will have to detail the processes so who worked with the data what they did with the data and what are the relation to other data or other results for example publications um these elements needed to be uh detailed and thinking of them from the very beginning will uh easy your work okay because many times for example in the documentation in the description of the data if you do not think about what you're doing at what you will do with the data it will be um it will be difficult to uh to go back into the the past and change for example your method or the tools you use to generate the data so this is a very important thing that you have to plan from the very beginning metadata uh what are metadata we have learned that they are data describing data they are very important for accessing the data um understand the data and process them so here is a parallel to a photo and the metadata for for a picture so in here you see that we have some standard information like the format for example uh jpeg uh the dates uh where we took this picture um the name of the file uh but then we also have uh for example the information about the camera that was used to take this picture uh and also the settings of the specific settings of the camera when we took the pictures so all of this information is contained into the metadata uh why it is important uh for example to use specific standards because you will spend less time in creating and interpreting the data uh if you use the standards of your discipline and also uh you can spend more time to actually make and and perform science um metadata can help in making your data findable uh interoperable and reusable there is a very large list of types uh of different types of metadata standard we have specific standards for uh discipline uh so for example the data documentation initiative gives us some ideas about the standards in the social science and humanities uh but we also have general uh metadata schema that we can use to uh describe basically everything uh the doubling core um is one of these so it's quite generic uh we'll tell you about the title the authors the subject and so on um it is always good to use uh the standards of your discipline if uh it is widely used by the community uh whereas uh general standards can be used uh in case you do not have a specific standard for the metadata in uh your discipline accessibility uh now the question here is uh how can I make can I make my data accessible to others we have seen that not all the data uh can be accessible uh who will be granted access and how so these are the questions that you have to think about when you uh when you will plan the accessibility to your data um so uh now we go and discuss a little bit of the the um the fare principle in in large so findable the first step uh in reusing someone else's data is to find them of course so it will be crucial that your data adhere to this principle metadata and data should be easy to find for both humans and machines um and machine readable metadata are essential for automatic discovery of data set and also services uh so this is an an essential part of the verification process some definition again that will help us in understand how we can make our data findable persistent identifiers uh persistent identifier is a long lasting reference to a document a file a web page or any other object uh when I say long lasting in principle will mean forever of course this is not possible but we have to um we have to make sure that these links will will last for a very long time um this is usually a term that we use in the context of the digital objects that are accessible of the internet and typically for this reason um the identifier are not only persistent but also actionable what it means it means that you can plug it into a web browser and be taken directly to the identified source so some examples in the open science context are the orchid ID uh this is an alphanumeric code that uniquely identify a scientific or other academic authors or contributors if you do not have the one yet you should because this will allow you to be findables also over the years so in five ten years time uh you may have uh you may work for a different institutions and it could be um difficult for others to find you so uh in case you have an orchid ID it will be very easy to understand for example where you currently work uh a DOI is another kind of uh of persistent identifier and it is used to identify an object and it's it's a standardized um it's a standardized identifier so um it's it is still a persistent identifier but it's standard it's also standard a DOI um aims to be resolvable so um uh this is also a very important characteristic um what they do is that they bind the DOI to the metadata and about the the object for example a url so they they will always tell you where to find the object an example is this of course for example publisher um release a DOI for the single article so so if you tag the DOI of your article and and you put it into the your web browser you will be linked directly uh to the publisher page where you can find the article uh persistent identifiers are very useful uh because they make your data findable and accessible uh if you will uh read the 15 um fair principle as they are defined you will find that that persistent identifier are a key element in this 15 principle how can you assign a DOI persistent identifier to your object you do not have to care because uh persistent identifier will are often assigned by institutions and by repositories so uh you or repository will probably assign a persistent identifier to your digital object uh for example Zenodo assigns DOI to the digital objects that do not already have one we said that persistent identifier will make your data accessible uh what does uh it means it means that once the user finds uh the data um he or she will have to understand how they can be accessed and uh these can also include the unauthentication or authorization process uh but how can you give access to your um your results again uh you uh can use a repository we have seen we have many types of repository we can distinguish them by the uh who by who is creating uh and and using the repository so uh we can uh see that we can either have thematic or disciplinary repositories uh like archive for example or institutional or national repositories for example France has a national repository which is called HAL and typically uh only people that come from a specific institution or nation or um are from a specific uh discipline can use these kind of repositories um on the other hand we can distinguish the repository on the contents they host so either we have literature repositories which are reserved to text or data repository uh one thing that I would like to stress here is that the kind of content reflects into the metadata that these repository host so for example for literature repositories we will use a specific kind of metadata to describe the different text that can be deposited there data repositories are uh very important and they are often disciplinary or thematic because they have specific metadata that fully describe the type of data uh they can preserve then uh we can have catch hold repositories that can allow you to deposit uh different kinds of of products for example presentation posters software uh data literature whatever this kind of repository do not have um very um specific metadata but they rely on general um general metadata schema like the doubling core that we have seen Zenodo is one of the most used uh catch hold repositories there is an important difference that you have to keep in mind so you can use the repository to deposit so to upload an object uh on the platform um and this platform will implement a long-term preservation of your content so by depositing you will not lose your information then the other step that you can take is to give access so once you have deposited the object you as an author can choose the type of access that can be granted we can think of an open access so everyone can access without restriction a restricted access and it is the author that will set up a strategy to to say who when and how they will they can ask for permission to be granted access closed access means that no one can even ask you to be granted access and then you have the embargoed one which is the one that we have seen you basically first deposit and then you open the payload just after a period of time uh giving access also means to assign a license to reuse the contents and usually we can use the creative commands that we will see in a while these are the access rights in Zenodo uh other repository have more than four access rights uh for example sometimes if they are institutional they will have an access which is provided only to those that that work for these institutions uh and so on but these are the main ones that you can find so we have the open access which means that everyone anytime from everywhere can access the contents and use and for any purpose and then you can see here that when you apply the open access button then you will have to specify a license for reuse there is what it is called the embargoed access we have talked about this a few minutes ago so here you will be able to define the embargo date which will be the date when your payload will be opened so everything will be granted open access rights and then here again you have to specify the license in the very first moment of deposit because the embargo will finish and then the record will open automatically so you will have to define the license immediately for what concerns the restricted access this is how Zenodo implements it so you will have to fill in this module for conditions you will be free to to apply whatever conditions you want to your to your record so decide who and how and when they can they can ask for a big granted access regarding Zenodo it happens that you if a user wants to to access your record they can they can click on a button and they can send you a message through the platform so the the people asking will not be given your email address but they will send you a message through the platform and you will receive a notification in your email and they will have to provide a specific request so they will have to provide the the proof that they follow under the conditions that you listed then you could decide to grant access and what happens is that you will send them a private link that they can use only once to download the resources and to access it okay then the last type of access is of course the closed access here as you can see you do not have to specify any licenses because these information that it is stored in closed access is not meant for be reused by others this is a warning because when you attach your data to the article that you published by for example sending an excel file to the publisher this does not mean that you are depositing the data so journals do not guarantee a long-term preservation of the attachments and the creation of the data you are simply sending it like you could do via email okay so this doesn't mean to apply the fair principle and to deposit your data in a secure space how can you grant open access to research data you have to consider where your data will be stored so where you you you will deposit you should find a trusted repository of course it is better to use disciplinary repository if they are available if not Zenodo is a very good solution because it is already for example connected with open air and with funders so it is good to use Zenodo also for this reason disciplinary repository how to find them you can use the re3data and of course when you are depositing you should provide full metadata according to your discipline standards so when you compile the the metadata form be sure that you include all the necessary information do not limit to the mandatory fields but also include other information that can be useful to others then after you deposit you can open your data we have seen sometimes you can't but in this case we are discussing how to open access the data that can be opened you can apply an embargo period also thinking of your specific project and you should choose the most open license possible so we are talking about the cc0 or the ccbi documentation of course please attach all useful documentation about how the data was was collected and and deposit the data set okay interoperability usually when you are working on others data you are often requested to integrate with other data maybe with data you have collected or also with others in addition we have seen that the data need to interpret with applications or workflows for analysis for example storage and processing so using community standards and best practices is key to achieve interoperability some repositories also give you some extra tools that you can use to allow for a larger interoperability for example in Zenodo you are able to link other digital objects so you can provide the identifier not necessarily a DOA but you can also provide a handle or another kind of ID for your resource then you can describe what kind of resource you are linking for example if you are depositing in Zenodo a data set it may be useful to link it to a paper that describes this data set or that was conceived thanks to the data set so you can say which kind of resource you are linking and you can also identify the the relation between the object that that you are depositing and the one that you are citing. Reusability as we have seen this is the ultimate goal of fair so optimize the reuse of data to achieve this metadata and data should be well described so that they can be replicated and or combined in different settings in order to be reusable you should specify a license so you should tell others how they can reuse your data and you should specify the provenance so where is your data coming from we have seen that not all the data can be shared because they can be either automatically protected by the law or regulated by contract or sometimes they can be subject to community norms or academic best practices so just to give you some considerations for data protection okay so copyright is a property right in certain types of original literary artistic and scientific works copyright does not protect idea instead you can use confidentiality to protect for example confidential information so these may be for example written in a contract or the information may be marked as confidential in this case you are not allowed to share it the use of confidential information might give rise of course as you may understand to claim for compensation if confidentiality is breached so please be sure that the data is not confidential if you want to share it data subject rights arise in information that identifies individuals and are recognized by data protection laws in the EU so the GDPR privacy some patents are registered patents are registered rights in novel inventions of products or processes and one thing that I would like to stress here is that when dealing with research if you want to patent something you should not publish it before this is because in order to deposit a patent you will need to prove that the invention that you are patenting was not published before so if you write an article and then you want to patent something this is not the way you should do it you should first register the patent and then you could in principle write an article about the same the same invention now for some journals this is not allowed so you should submit in principle novel papers so a patent which is already registered could be intended as an already available publication so it is often the case that if you patent something a publisher could say we will not accept this for publication okay so bear in mind that if you want to patent something the first thing you should do is to patent and then you can maybe search for the possibility to publish it also keep in mind that the patenting is a very long process so for some inventions it will take of course a long time and this may and after this time the invention may become obsolete and probably the fact that you want to publish it will be not any more convenient okay so the the last thing is that some research data may not benefit from any legal protection as we have seen for specific information confidential information or individual information but in in some cases some moral and ethical considerations may apply so this is what you have to know to understand how you can you can protect your data one thing that you have to keep in mind is that data is legally speaking not yours this is because data it is not considered intellectual work so no copyright can apply what can happen is that some some protection may act on the way you present and you collected your data because copyright protection covers expression and not idea procedures operating methods or mathematical concepts as such but the protection is instead on the databases and not the data so the data are protected only and especially when they are collected and organized in a specific way we will see what the law consider a database which is not what we usually think when we hear the word database and then there is another thing to consider because in Europe and only in Europe we have what is called a sui generis database rights so these covers not only the reproduction and dissemination of the database but also the extractions and reuse of substantial part in the database so some consideration about data and low protection raw data are not protected by copyright in fact there is no legal definition of data instead the law gives us a definition of a database which is defined as a collection of independent works data or other materials arranged in a systematic or methodical way this is uh something that you can protect by copyright you cannot protect the raw data itself so the copyright protects again not the the raw data contained but the structure the selection or the arrangement of the database contains so the part that is is defined as an intellectual work so the way you you are using two structures select or arrange the data within a database we we see we saw that in Europe we also have a what we call sui generis database rights these protects the substantial effort in obtaining data and not creating the data so usually in this case the right owner is often the institution and not the author so not the researcher but the institution you work for so in this case this is a schema that that summarizes what I'm trying to describe here so on the raw data you have the no protection by law so no copyrights for non-creative database if in case that there was a substantial effort for obtaining the data you can apply the sui generis rights for database that are creative you could both apply the copyright on the structure of of the database and you can also apply the sui generis rights in case there was a substantial effort for obtaining the data this doesn't mean that you are not the author of the data it just means that you will not own any rights on the data so are you the author of the data you collected yes in case you can prove it and how can you prove it you can prove it by deposits with a clear data doi so if you use a repository so you will be the author of the specific data set if the question is do you own any rights on the raw data you collected the answer is no because data is fact and no one can own rights on a fact creative commons so we have seen during this lesson today that you should tell people what they can do with your resources okay the resources that you make available now not all of us are legal experts so we are not in principle all capable of writing proper licenses but there is this framework which is called creative commons and public domain that creates a sort of legal certainty for everyone who wants to work to use works that are licensed with this framework okay so it is very easy to use and to understand there are some simple rules that you have to follow to understand the meaning of the licenses and to use them so first of all creative commons give a worldwide license to anyone to copy and publish the content this is allowed for all the combinations in case you want to require an attribution so in case you want people to cite and to say to state that they used these resources that was provided by you you can apply the by license so CC by means that people that are using your resource will have to cite you in case you do not want to allow a commercial use of your resource then you can apply the NC so non-commercial license now here I want to make a point because as you have learned that during the first module scientific publishing it is indeed a commercial use because it is they are commercial platforms so in case you apply a non-commercial license to for example your data set others will not be able to use your data set to to write a scientific paper so please use this non-commercial license properly then you can tell people whether they can modify or adapt your work in another shape so in this case if you do not want people to modify or adapt your work what you can say is that you can apply the non-derivative license and then what you can also do is that you can tell people how they will be able to share the derivative works in this case you can use the share alike license that makes it mandatory for people to license any modification or adaption of your original work in the same way that you shared okay so there is a summary here of all the kind of licenses that you can find I leave it for reference again please do not consider attaching the the file with your data to your publication as application of the FAIR principle okay so please do not do that there is a very nice resource that I want to cite here it is a fact sheet by creative commons and open science so they briefly describe what is open science and why you should use the creative commons they basically tell you that in order to adhere to the open science principle you should always use three kind of licenses the most used one is the public domain that means indeed that the work that you are sharing is not covered by the copyright but it is in the public domain so everyone can use it CC0 means that it was covered by copyright but you basically are giving away your rights and you can licensees without any restriction they also are telling you some important step for example that do not think that by not including the by license so CC by to your work this means that others will not cite you because as you may know it is bad science and not to cite the source of your information so if someone finds your data which is licensed in CC0 they still will have to say that they found that this information that they are using for example in their article provided by someone and this someone of course is you the author of the data set so what creative commons actually tells you is that you should apply the CC0 or the public domain to your data and then ask for credit and provide a clear citation that researchers that are using your data can simply copy and paste to give you credit for your work okay this is a summary of what we have seen today you have seen that uh uh findable sorry fair means findable accessible interoperable and reusable we have discussed about persistent identifiers metadata standards provenance and so on so this is a summary that you can use to understand if you put all the elements in in your workflow in order to apply the fair principle again once your data is fair you can decide to go open how do you do that we have seen that you can use a repository you have to choose which kind of data can be opened by keeping in mind the principle as open as possible as closed as necessary so just closed what cannot be open and in practice it is very simple because you already have your data in a repository because you had to follow the fair principle so simply apply an open access right to your data one thing is that is making your data fair will it make it reliable well the answer is no because it depends on you so fair gives you some principle and best practice that you can use to manage your data and to share it but it will help you in make your data have a higher quality because you will have to think clearly and plan clearly your data lifecycle but still the content of your data is made by you so it's you that makes the data reliable now before we go and and discuss a little bit more in the detail to the current open science practices in your domain so in the ecd domain I would like to go back to the to the Mentimeter so let me just close my presentation the link is always the same so I just reopen okay Ali did you already uh I opened it again because okay people didn't have the time to vote okay okay no problem because now we have the same question again so uh after you have seen and you heard about a fair can you give another answer and tell us do you think now that you know what fair is do you think that your data is findable accessible interoperable and reusable so it will be nice to see what you thought before following the lesson if it is the same or if it is difference okay do we have any questions from the oh no questions no questions okay okay we just give a moment but I already see some difference if the people voting now are the same as we had before then we see that the previous was a bit more I think there was okay so just closing the vote just to see yes people thought that their data were more findable and accessible and also reusable than now so this is already something so um I don't know if uh you want uh anyone wants to comment that or we can go um why why do you think now that your data is less findable in uh accessible and reusable than before if you want to write in the chat or raise your hands uh it is pretty much a matter of planning and designing and then you you can start using some specific tools that we will also provide that during this course of course the repository is very important so choosing the right repository is key to apply the fair principle there is also a quite uh um okay there is a comment I often put my data in websites that are linked to the website of my institution but this is not a repository yes so one thing that I have to tell you is that putting data into a website is good for for example to allow people to find it but it is not sustainable the thing is that for example if you have a website for your project what will happen to this website when the project is over okay think in a five or ten years time who will maintain this website and then this website is basically not visible uh to all the other infrastructures that uh instead uh go and find the information uh in uh in the repositories okay so what you can do you can uh yeah exactly now I'm reading the comments a fun experience with the with the some older you project websites yes because what happens is that if you do not maintain if you do not have a plan for sustainability what happens is that the information that will be stored in this website will get lost okay um whereas repositories are often maintained by very big and old institutions like university for example okay then or or by uh by stable communities okay uh fear does not guarantee long-term preservation well this is this is uh what do you mean Hamat you mean that the cronium doesn't include the preservation well I mean I think this is this is a quite of a long debate as far as I understand but maybe you can you can clarify this more um you know providing your data on a on a fair enabling data repository does not necessarily uh let's say in a in a in a guaranteed way uh guarantee long-term preservation of the data I mean over over which time frame your data is is preserved is not necessarily uh clear from a fair enabling data repository but okay correct me if I'm wrong it's I think it's a long debate and and it goes through different discussions over data repository certifications but yeah okay so in this case I have to say that the accessible part includes that your data should be accessible for a long time now we can discuss about what the long time means because there is no um how to say there is no um identification on how long your long-term preservation means so uh we say usually 10 years time um but for example the the uh the guidelines for fairness from the European Commission does do not specify how long you should preserve your data but it's long term um certification of the repository is a very um is a discussion that that is taking place uh now so the thing is uh we already defined the fair principle but then we have to ensure that uh people will uh be able to understand whether a platform that they will use or a service that they will use to make their data fair is actually fair enabler so um there is uh uh there are some some frameworks for certification for it's for example um the core trust seal is a certification but this does not certify your your repository is fair enabler um there are discussion in the community right now to understand how they can say that our repository is is a fair enabler okay for example if you think of the core trust seal uh which is issued by by dance in in the Netherlands uh they certified up to now I think a hundred repositories uh whereas for example open air collects information from 17 000 repositories so you can see that this is a very very short and small um uh part of the repositories out there um so in this moment this is the the how to say that the the conversation is on how we can guarantee and and say that something is fair and it's not uh I have to say that currently we are thinking of designing um a framework where there is no in and out so there will be no um how to say stronger certification in the sense that either you have the the seal or not but the the the idea is to provide a framework where you can have different uh kind of fairness okay uh depending on how you design your your platform or your repository okay so I don't know if ellie wants to add anything about this no that's a very big discussion yes just know that uh to to enable services and repositories to be fair is not something it's something that is uh requires costs uh so it's it's not a cost-less um procedure uh not all countries uh have uh uh you know policies in place that can probably fund through those through the through their funding systems can fund um the acquisition of this kind of certifications and also it's not the certification it's that you have to uh you have to buy the services that will uh let you certify then your your service so it's it's too complex and it's something that it's it will take a long time but the uptake will take a long time but it's it's it's going towards that direction though however I think that we shouldn't you know um we should be more um inclusive uh today than you know exclude the posters from from that yes amada is uh did we answer your yeah no no I fully agree I mean I I think it's it's uh it's a difficult question that requires time and thought and research and there's you know quite some research on this it's uh and I agree I mean one should be think also inclusive and flexible and uh and anyway I mean it's an ongoing transformation so not everything will happen directly in overnight but um it's just I think it's important to keep those issues in mind because they are they are relevant and timely questions for for research and thought yes there is uh there is this discussion now and and we we should be for the moment we should be as open as possible you know because not all the repositories out there can as Ali was was saying there is also a problem of cost so not all of them can afford the the cost that is asked to be certified and and also um the numbers are so little now that's uh it will be impossible for everyone to to access this kind of platforms okay so uh let's go back so thank you I just um close there is a question yeah oh sorry I didn't see it no no worries so it's uh from Alexis uh domain specific repositories are often maintained by smoke communities which may not stand for 10 years let's say would you advise maximum would you advise also preserving copies of submitted datasets on generic repositories like cenota okay yes thank you for these questions because this um this is very useful to specify that it is um possible to deposit in different venues so if you think this repository which is maintained by a small community is useful for you because this is your reference community but you are not sure about the sustainability plan of this repository then you should definitely deposit also in Zenoto also one other thing that I would like to stress is that Zenoto will give you a DOI for your record so probably I can I can tell that if it is a small community they are not able in this specific repository that you are mentioning they are not able to provide you with a DOI okay but DOIs are very important because with the DOI stands the sustainability okay because the DOI is a framework that is standardized and the institutions that are granted the fact that they can provide the DOIs have to have to make sure that they can provide the link between the persistent identifier and the resource so these are usually very large institutions or like Zenoto is is maintained by the CERN so I believe CERN will be there in 10 years time so it is something that can also provide you with sustainability and with the with the preservation of your information so that was very good question yes you can you can preserve the copies in many many places the thing that you have to keep in mind is that for example if you put your dataset in Zenoto and then you get a DOI then you should not ask for a different DOI from another repository in case they provide okay because it is the same resource and must have the same DOI okay okay so is Zenoto the recommended service from for now well I can say that Zenoto is very useful but first you should look for a specific repository in your community because in this way you will be sure that for example the metadata standards that they use is specific for your for your contents we have for example in Europe there is there has been several years 10 years projects to to build the research infrastructures for specific domains okay so in case for example your data are very specific and you have a research infrastructure that provides specific repositories for your data you should deposit in this kind of repositories okay Zenoto is recommended for what we call the long tail of science so all these scientists that do not have structured research infrastructure that they can refer to for example domain specific repositories or services but it is very useful also because of the DOI I think so they will give you a DOI for your resource so in case you do not have a specific repository for your domain please use Zenoto when I say a specific repository I mean also a repository that is widely used within your community so probably if there is you already know because you're using it already for your research okay it must be something that is recognized by your community as a repository where a trusted repository okay and this is part of the discussion we were having with Amads about what it means to have a trusted repository and certified repository it is often the case that you cannot really certify what the community think is something that they use often okay so okay so let's go back to the presentation and we have a few slides more about the current open science practices sorry Amad there's an interesting question maybe to clarify about github oh sorry it's relevant probably to say yeah we are discussing about it now choosing do not have country restriction considerations I do not understand fully the question the questions that Mehmet asked as I remember open science repository choosing do not have country restrictions considerations I think Ahmed was referring to the one before that do you have any opinions regarding github okay so we can maybe we can take this after the presentation because we're going to discuss about github in a moment okay so just keep using the question and answer button if you have to any questions about that and we can resume yeah yeah perhaps I can reply to Mehmet yeah yeah yeah thanks yes there are no country restrictions in choosing your repository but it would be good I mean if you want to keep them in your institution and your institution has one and there are no thematic repositories out there it would be a good practice to keep them there that's my answer yet it's also often the case that if your institution has a repository often they also have a policy and and rules to follow about the repository so often you are required to deposit in your institutional repositories so it can be that you have to but then you can also deposit everywhere else okay so let's discuss about how to embrace open science in your domain so we have discussed about the file sharing there are a lot of services out there and then you also have software management tools we have github but also others but still even if you are how to say I can advise you to use these kind of software management tools because they are very very useful to deploy software for example github there is something that is missing so everything that you have seen in the previous slide so services for data sharing we are talking about the dropbox google drive github for a software management they do not publish your products in the academic sense because publishing means that there is a venue where you publish that is recognized by the academic community for example scientific journals okay I want to tell you something about this in a moment publishing your products also means that your products can be preserved and we have seen preserved means that they will be there for a long time uh making your you these kind of services that we have seen in the previous slides do not make your product citable and findable okay so they do not for example assign a PID to your product and they they do not carry attribution and scientific credit so people again will will not be able to cite your product in the academic way and they do not enable reproducibility because reproducibility is complex and storing your information your resources somewhere does not really allow reproducibility okay you need all the rest of the fair principle to be applied to your product for example you should make your product interoperable you should link it to other resources and so on this is a very very nice switch a few years ago someone wrote you can download your our code from the url url supplied good luck downloading the only postdoc who can get it run okay though so um this is true uh sharing does not mean that you are um that you are compliant with the fair principle there is a lot of more okay so what can you do um well um you can make your data and your software fair uh we have seen that there are some some some specific technical specification that can help us in making our data fair our software can make can be made fair as well so use our kid to identify the the authors or the contributors because these will make them findable uh try to develop in a structured or a collaboratively and open way and this is where github helps you but then this is not it uh because as we saw github uh will not um publish your software in the academic way but you need more and what you need is that you need to deposit and preserve in a trustworthy repository and get a doi so a piz that can identify your resource and this can be done through zonodo you have to choose a clear license because this way people will know what they can do with your data and your software deposit and update uh if needed i read me file uh with your code or in your data because this will tell people uh document to your people how this code or this data were uh um created or collected um the context of the code and the data and this way people can really reuse your data and understand your code better um use versioning this is very important especially for software um and link to other research objects okay link to data to software to articles to whatever you need to make your resource um understandable uh okay so let's see what zonodo is uh zonodo is a catchall repository as i said it is maintained by cern and it was developed thanks to a collaboration between cern and open air so it can be trust because these are long long-term initiatives and institutions zonodo allows you to get a doi for free this doi can be used for citation and it can for this reason enable a credit mechanism so your um your resource will be easy to find and to site so you can see here um that zonodo provides a doi you can see here that there's a link to github and i'm going to tell you in a moment how this can be done zonodo just let me go back a little bit if you see in the right hand in the right hand side of of the zonodo screenshot you will find a phrase which says site as so this is very important because this way zonodo provides a simple method to site resources you can simply copy and paste this uh can be seen as something very simple but believe me when you have to site something that is not an article people will get confused and they will not know how to site it but this way everything that is included in zonodo will have a citation that can be copied and paste and people will cite you more and more easily uh so as we said uh citable products are findable reusable and therefore enable degrees of errorness by this we mean uh that can be that they can uh the resources can be reproducible um you can replicate uh for example an experiment and so on so not only you can reuse but you can reproduce replicate and so on so there are a number of initiatives around software uh this uh is a software heritage it is international initiative to preserve software these people also uh are are are going to through uh paper software and they are go and they are digitalizing software and they are providing a place where you can enable you can preserve your software in the years this is a very good initiative that I wanted to uh to mention then there is another resource that you can use which is which are the software and data papers now these are specific kind of scientific literature so uh but the the main aim of a software or a data paper is to describe a software or a data set okay so you do not uh in in software and data paper you do not tell people what you did uh thanks to your software or or what conclusion you reached thanks to your data but instead you describe fully the software and the data uh because they are software because they are scientific papers you will get a DOI attached to the article so you can cite directly the article describing the software or the article describing the paper however um the software and the data itself should be cited on the same basis as another research product if they are available uh so if a software data paper exists and it contains results uh that are important to the work then the software and data paper should also be cited in addition to the software and data not always it is a case that you have the software paper and also the software shared okay so in this case please cite the software paper uh if instead the software or the data set is provided separately as a specific resource you should you should cite that instead there are a number of data paper journals for example nature has scientific data which is uh data paper journal um data in brief which is issued by Elsevier data mdpi patterns bio data intensive science so these are some kind of uh data journals that you can think of publishing in uh software paper journals are also uh very common uh we have a list here probably you already know some of them uh but then we should go uh and make another step so what are the best effort that that you can make towards reproducibility uh so first of all you should think of uh archiving your article preprints in public repository we have seen that it is almost all the time the case that you can archive a preprint as an open access version of your paper so archive the preprint then please publish the post prints of a published article so if the journal is closed and not open access please provide the postprint in public repository of course in respect to copyrights but please um consider doing this because this way your article will be open to anyone uh maybe after an embargo period uh but uh if you think of the article that you that you read in your research it is often the case that for example you read an article that was issued last year okay so often the the embargo period is about 12 months uh can be up to 24 or 36 for specific discipline but it is not your case so how many times you you happen to use uh and read an article that was published more than 12 months before well in this case if you have deposited your postprint in in in a repository then your article will be available after 12 months time or six or whatever it is the embargo period of your journal then publish your data and software in an open repository as open as possible as closed as necessary um and this will give people the information they need that are described in the article try to also publish data and software papers to describe your products and keep your products uh semantically interlinked that means to give all the necessary information to link the product so you have seen Zenodo is a very good solution because it allows you to give uh to put links in your in your um between your your resources um then you can also share on the web i mean there is no uh you can of course tweet about your research uh you can put your things in your website it's perfectly fine but please before doing that be sure that everything is in place in a trusted uh place and can be uh preserved now this is um what i wanted to tell you with my slides and what i want to do now is that i will open the comments and the question in Mentimeter for you and in the meanwhile let's please let me um uh let me just find a useful resource which is the link between github and open era i want to share with you and show you i don't know if we have any questions uh in the chat okay so please feel free also to use a Mentimeter to uh to comment um i would ask yes sorry i would ask uh what is the the biggest challenge that you you see when applying for principles like now that you you know about for principles what is for you the the biggest challenge thank you while you think about what's right in in the Mentimeter or if you have any question i want to share with you this okay so this is uh um it is a guide from github uh there is um how to say an initiative uh joined by github and Zenodo um the thing is you can use github to deploy your software okay design and develop your software and then github allows you to link everything to the Zenodo uh to deposit a copy of the status of your uh your software in Zenodo and then be assigned a DOI now this is very important because as you uh as you learned uh this will allow you to publish your software in the academic sense uh so you will need to simply choose what resources to to deposit in Zenodo via github so once you're done with your software and you're happy with it uh you can choose what they called in in in github a repository and then this repository can be shared through the Zenodo then you log in and you link authorize the exchange of information uh you can archive uh the repository that you choose checking the repository settings and you can also create a new releases this way your software will be attached a DOI and will be present in Zenodo but then if you go on and you develop some extra uh extra versions of your software this will be linked in Zenodo as well so if you have a new release you can link everything in in in Zenodo okay so you will have a DOI and your resource will be published now the example that I had my slide was was a piece of software coming from github that was developed by uh by the the open air team so as you see it is um it is possible and very simple to to transfer everything in Zenodo and to get a DOI for your code okay so I'm putting in the chat sorry I put everyone I put in the chat the link for this resource that you can go and check I hope this can be useful now we go back to the minting meter okay I see someone is typing okay okay uh I see data journal from mdpi in your slide I think it was in some sort of black list of agendas but sometimes and then be removed but still have someone supported the concerns about it can we say mdpi journals are not predatory okay this about predatory journals is is very very it's a very large conversation okay uh first of all there is no uh they wear some attempts for having black lists in the in the past but it's very very difficult to to uh even describe what a predatory journal is and now there are some guidelines that you can use I I showed you in my slides before that you can use for example the DOIJ directory to understand if a journal is is trustable you can use the think check submit button to to understand if you're the chosen journal is is trustable uh there were some attempts to to have a list of of characteristics for a predatory publisher and guess what it was demonstrated that Elsevier had all the characteristics of of a predatory publisher so it is a very very thin uh how to say boundaries that we are working at uh it is often the case that some publisher are considered predatory predatory for for a while and then they do not uh for for the future so it is very very difficult to say um I've heard someone else saying that mdpi journals can be considered predatory but this was often because they insist a lot and send you a lot of emails but instead that they uh I had this conversation I'm telling you that uh because I had this conversation today with with that person with the Ilaria uh Ellie that you know and uh from DOIJ but also Ellie is from from DOIJ so she can confirm mdpi is not considered a predatory publisher but sometimes they do have some some uh how to say some uh they they insist a lot for example for the emails and so so so yeah sometimes they they can be a bit uh too much but instead that they are a good publisher so Ellie I don't know if you want to add something we had a similar conversation this morning with the with a person uh that was asking us if one of the journals the issue which is called the minerals is is a predatory journal but it looked to us that this editorial board was pressing for a response and asking many times to become a reviewer or something so this is not really the only thing for predatory journals Ellie no no I don't have something to okay yeah nobody yeah I talk too much so I don't know if you if I answered your your question um I can also maybe I'm sorry yeah I was going to link this uh this uh uh Bjorn Brands uh pay uh blog about uh al severe as a predatory journal but go on I'm just going to find no I wanted to just add it's one of the questions that I receive very often when uh people after a training they or a session similar to ours uh after they go and search for a journal in the serparumio often sometimes they don't find something and this is because they are trying to find information about conferences conference proceedings so there are two things that apply for conference proceedings either you have to look at who is the main publisher and check these policies of that publisher and either some some records are already included in serparumio but it's very rare that you will find records only for conferences I know that there are some publishers that try to to do that and are very are very good in providing timely information about this and the third is that you have to look at if you don't find a information neither in serparumio or in the publisher page but then you have to look at the copyright agreement that they have sent to you and we see that most of the times they have some uh some information there some text that reads as you can you know after submitting you can deposit in an open access post or something like that okay so we have uh I see there is something in the chat um film was my question thank you very much and to be honest my reviews are not as hard as in the journals in my area it seems for me quite easy to publish there and I think that it will be against me at some point if I publish much there because it looks that you publish there because you can pay it or that is what other researchers say yes this is often the case that people think that they they merge the fact that a journal is open access and requires apc and then these makes people think that since authors pay then the peer reviewers or the editor will be much more likely happy to accept manuscript but think also that nature is asking thousands of euros for publishing so and and you probably will not think that since you're paying for publishing in nature then nature is is a predatory journal or the quality of the papers are are not so high because you are paying for publishing okay so do not confuse the fact that the business model of a journal with the quality of the journal itself and this is very important in computer science there is Horatia is telling us that in computer science the core ranking is quite reliable for conferences okay so there is a rank for conferences okay thank you Horatio may I profit maybe for this time to add a few words since we are also talking in the context of Chisteria and that I can jump back to to the different points you've said that you've covered today so just remind and to somehow link back to what I've said at the beginning of the session yesterday so starting from next year so the call that would open December this month of course we we would require we have already required before open access for all publications funded by Chisteria but now we eliminate any embargo so we really go along the lines of the of the plan s and and fully implement open access without embargoes and and for data as well we require data to be shared on on fair enabling data repositories now of course this will apply for the next call in in a in a strict sense but obviously everyone who is already funded by Chisteria is is encouraged to follow those good practices because those are really the good open scientific practices and in fact many many Chisteria researchers already follow such practices voila okay great so your word these are the rules that are coming these are the opportunities actually yes I mean this is this is true it is a very good it's a great opportunity and the thing is that we we need to start changing our mentality and I mean science and and the scientific progress is is something that we do for the society so we should try as much as possible to to easy this process and to allow others to start and reuse our our results so yes there was a there was something that I wanted to tell you before when I was talking about the fact that one thing is to make a your result available for example on a website or on github and one other thing is publishing it in the academic sense so I had yesterday a very nice conversation with the un-american researchers in sociology and this person called us because we are managing a community in Zenodo about COVID-19 and apparently I probably probably all of you know about the young report which was this report written by this scientist that was meant to prove that the COVID the SARS-CoV-2 virus was created in a laboratory so this report is actually one of the records of Zenodo so because these scientists deposited the report in Zenodo so she called us to understand why we we were hosting this report and we had a very long conversation but the final remark is that this way this report was published in the academic sense so it has it is in our repository it is marked as a preprint it has a doi so now the thing is other scientists can start a conversation and can start discussing about this record and apparently they can also cite it in order to say okay I do not agree with this young report for these these and these reasons now if this report was instead published on a blog it could be out of the scientific discussion because researchers actually discuss in their papers about others papers and about others resources that are recognized as scientific product it is not often the case that for example never happens that you are discussing in your paper about let's say a software that was published on on a blog but instead if the same software was published in a software paper you probably could discuss about it so it is quite interesting to see that there is a still how to say there are some some structured there is a structured way that the where the discussion takes place for science and this is quite quite interesting to think about so this is why you should publish it in order because then everyone will will understand that this is a part of a scientific product okay I don't know if you have any other questions or remarks doubts something that is not clear okay so I guess so we can we can probably close the module here next time Ellie will tell you more about the search data management and data management plan right Ellie yes yes it's about data management plans and Argos how to use the the opener tool for creating data management plans and about how you can use all the well not all but the a majority of some of the tools that were mentioned during Emma's sessions yes not yesterday it was on Wednesday and today so uh yes this is what we'll be viewing together next yes there is a question github is linked to Microsoft correct is there any hidden important things to keep in mind about this well I don't know how to answer this question I don't think there is any hidden things behind this I don't know yes Ellie Amazon also is a majority of the storage that the university is using yes on also Google so yes I mean these are these are inevitable this is inevitable yes I mean we're using zoom platform to to have this this record I mean it's not always I mean these are services so it's not always bad to use private services it is the fact is we have to be how to say we have to be sure that we understand the terms of use of what we're using so this is the good yeah and I would say that the collaborations are done via agreements so agreements also included you know data transfer and data protocols and so on so it's good to have those in place so this allows us to use in an academic way use the services in an academic way yes which is different from the free services that you can get for example google services that I that I showed you I think I believe in the first module that terms of use was about the the free service that you can use with your google account your personal google email and and google drive but they have different kinds of terms and conditions for example for the service that they provide to academic institutions so you should be aware of what are the terms of services of this commercial service I agree and yes I agree that's it yeah okay so Jean disagree I disagree GAFA hosted platforms could or should be avoided if academia provided equivalent solution yes this should be but but it's not always the case that they can provide equivalent solutions so this is what I was also included in my previous module if you have a better option use it I mean if your institutions provides you with a storage service or with with sharing services that you can use for for sharing information with your colleagues that is perfectly fine but then if you do not have your institution supporting you in this then you should find another way in our Chisera project we strictly avoid google drive zoom and so on yes this is completely fine I mean I use a variety of different solutions in different projects but this often depends on what are the partners involved and if there is actually a partner that can provide a different solution so yes there is also Microsoft's one drive if or academic reasons like it's tied to the affiliation of the institution that you are using yes again data agreements and those things apply okay so yes I think I think we can we can close the sessions if we have no further remarks so I want to thank you for being here today and I will put all material in Zenodo and then Hamada will you take care of of sharing all the links with the participants um yeah well we have to to to discuss this I think together to find the best way to to reaching out and then share the the links okay the fastest possible we can we could discuss this after the after the session okay definitely let's yeah find the quickest and easiest solution okay great okay many thanks to everyone and I'll see you next week thank you thank you