 Copyright, database right, and everything else, even what you didn't want to know, all me the task not to keep you too long from enjoying your coffee. So I hope I can do it rather quickly, and I hope that this will work, but apparently not. So I shall reuse them out. You've had the conclusions throughout the four presentations before me. So you basically know what we recommend. We recommend changing the law. We recommend using the Creative Commons version four of the licenses. So this has been made clear beyond doubt. So the task is actually rather easy for me is to wrap up everything and put a bit everything into context. So that's what I'd like to do. Now, the first slide, you know, it's been repeated legal status of the scientific output is not entirely clear. So I won't delve into the detail. It's been clearly indicated. What hasn't been said is that this legal uncertainty has gathered a lot of discussion at the European level. So you may be happy after the gloomy presentations before us saying that, you know, the corporate framework is not fit for its purpose. It's a barrier to proper scientific communication. It prevents scientists from sharing resources, etc. Well, apparently the message has gone through somewhere at the European Commission and they're now setting up. Well, initiatives to first discuss the matter and hopefully in the not too distant future to modify the Copyright Act, or at least the Copyright Directive, hopefully in a way that is useful for scientific research. Now, the first initiative of the European Union in this sense was calling for a stakeholder dialogue that they called licenses for Europe. And this has gathered a lot of controversy and a lot of discussion. Why? Because, well, they have a work in four working groups on four different issues of corporate law in Europe. And one of them was a special working group on text and data mining. And they gathered there about 30 stakeholders to discuss possible possibilities to allow for text and data mining. Now, the problem there was, and that was last year, the problem there was that the standpoint adopted by the European Commission that was catering for the discussion was to only discuss licensing solutions. So the European Commission insisted that it didn't want to envisage any copyright legislation reform. It only wanted to centre on licensing solutions. Well, this actually led to a third of the participants in the stakeholder dialogues to leave the table to withdraw from the discussion, because they said it is not what they wish. They do not wish to be limited in the possibilities offered to them in examining what solutions should be brought forward to be able to text and data mine. And they also wanted to examine the possibility of introducing a new copyright exception and limitation to allow text and data mining. So they left the table somewhere in April. So that was about a third of the participants. And the participants were representing basically users and scientists. So the ones that did remain at the table were basically representatives of publishing industry and universities, but not many. So they are coming up right now with a document. It's, of course, non-binding because it's a stakeholder dialogue. It will be a set of recommendations by a working group that is not fully representative because a third of the people left. But the good news is that I heard that the European Commission is now considering setting text and data mining up on its agenda. And they will be creating a high-level expert group on text and data mining to examine how copyright law could be modified in the mid-term, I guess, because nothing is really quick at the European Commission, to think of solutions to allow text and data mining. Now, this is the initiative of the European Commission. We have, of course, the UK. The whole discussion on text and data mining flared up incredibly also in the UK. So if it was a small matter or a medium matter at the European level, it became a big matter in the UK. I've attended at least two meetings of experts regarding text and data mining. And this is a text from the Intellectual Property Office. It's the specialized government agency dealing with intellectual property at the UK. And they are going ahead with the plan of introducing a limitation in their copyright act to allow, as you see, data analysis for non-commercial research. Now, they are like the brave hearts of the European Union, because knowing the European framework on copyright law, you may know that it is not easy, or at least it's highly contested that a member state may adopt a new copyright limitation that is not provided for in the framework of the copyright directive of 2001. So text and data mining is not an exception that is listed in the current framework of the directive. So they still believe that in the interest of their scientific community in England and the UK, they need to go ahead with this exception. So they're braving, actually, the current setting of the law. And they are planning to go ahead with adopting a new copyright exception. The only comment that I might formulate here is that they want to limit the text and data mining for non-commercial research. Well, it's a choice. Of course, we have to reach a compromise, and it might be the only compromise to be reached. But this would limit potential public-private partnerships, might limit to some extent the possibilities of text and data mining for activities that might not be purely non-commercial. So this is something to consider. So that's the good news that in the midterm, or perhaps the long term, the law hopefully will be modified because I think everybody realizes that text and data mining is the way to go in science, not only for beta sciences, but also social sciences, are discovering new avenues of interpreting texts, of gathering data in all fields of science. And this is really the way to go, and you don't want to be limited by either commercial publishers or other parties who don't grant you access or only under very restrictive license terms. So I think that with proper lobby and proper push in the right direction, eventually we'll get to a satisfactory solution. Now, the open-air guidelines has been mentioned also throughout the presentations. This is also a core message of our study. It is crucial for data collectors and depositors to ensure first that all necessary corporate permissions have been cleared prior to deposits of a data set into a repository and clearing that corporate also, of course, means clearing the database right. So you need to know that you are indeed allowed to put that data set in your collection, or you need to be aware of how far you can use the data set in your own research. So this is what we mean with rights clearance. You need to be aware of the permissions of all the data sets and information that you're using. And, well, this brings together the question of ownership of the materials. So it's a cold picture. This might be as complex, and I'm sorry, that's not a good news, might be as complex as for museums who want to go through mass digitization of their collection, they need to obtain permission or at least to find a way to mass digitize without getting too much of a headache. Well, scientists need to at least have an idea of how far they can go using somebody else's data sets. So, and this is where license terms are very important. This is a slide that I made a few months ago, but February. I'm sure the proportion has not changed much. What this shows in very tiny character is that the recorded full text data reuse policies worldwide, so the pie chart you see tells you that for almost 85% of all the data sets out there put in repositories, the legal status is either unknown, unstated, or undefined. This is the core of my message. The data sets that are out there, we don't know what we can do with it. So this has to change, and this has to change in the rights management systems of libraries, of other institutions who take those data sets into their repository, and they need to make sure that they know what they can do with it. It might be all rights restricted, or it might be opened up under open content licenses, but at least we need to know they have to be properly labeled to tell the scientists and to tell the users what they can and cannot do with the data sets that they find in those repositories. Can you data mine? Can you not data mine? What can you do for more than 85% of all the repositories out there, you don't know. One good news. Yeah, so it's a message of good news and bad news. And you talked about Narcissus, and Narcissus is Dutch, and Narcissus is closely linked to the data archiving and network services. It's also Dutch, and the dance, as you see, is a repository in collaboration with Narcissus, but dance is really for, it's a repository for data sets. So it's closely linked to Narcissus, but it's purely for data sets. And when you look in dance for specific data sets, you come into the easy website, and I'm not sure I know exactly what easy stands for. Excuse me? Easy archiving. So the EASY is not an acronym. Easy archiving, thank you. Well, so this is a shot that I made for a previous presentation on the 20th of August, 2013. And I'll read you what it says, because I do realize that it's too small. But in August, the dance website, which is sponsored by the Royal Academy of Science and the Dutch Research Council, at the time, their licensing policy was as follows. The EASY website and all material therein are property of dance and or other parties and are protected by rights between brackets, database rights, copyrights and neighboring rights. This implies that material may only be reproduced or used with permission from dance and according to conditions determined by dance. Moreover, this website and databases may not be copied in whole or in part without permission by dance. Well, I don't know if it was my doing or everybody else's doing or what doing, but just for the sake of things, yesterday I checked the website of dance. And surprise, surprise, this is wonderful news. When a data file is deposited in EASY, a license is granted, dance enters into the license agreement with the holder of the rights to the data set. This can either be a person or an organization. Okay, what follows is a big change. The license is non-exclusive. This means that the owner of the data is at liberty to deposit and or make available these data in other places as well. Also, copyright is not waived when data are deposited. It continues to rest with the researcher. Also good news for the researcher. The license entitles dance to include the data set in the archive and to make it available under the conditions stipulated by the project leader when it is deposited. These conditions relate to who will have access to deposited data. According to the principles of the open access movement, research data should be made available as freely as possible. In some cases, however, it may be necessary to limit access. For this reason, dance offers the possibility to categorize data under the heading restricted access. In addition, there is the possibility of placing an embargo on data. The good news is, you will see, it's a change from restricted access. You may only copy this under permission of dance. Depending on the rights of the input giver, we need to figure out how to give you access, but we follow principles of open access. Ideally, in the future, dance will be able to move towards, perhaps adopting a Creative Commons version 4 model. But this, I thought, was a very good progression in the thinking of dance in trying to give researchers access under free conditions of the data sets kept by dance. The guidelines, you've heard them, use of proper access licenses. Because if you free your data sets and the databases that contain them, then you also make sure that these data sets will live in the future. And that's very important for curation and for further science, building on previous data sets. You want to have a living tree, a living mechanism where people can use and curate and care for all the data sets out there. So open access would facilitate this. Now, it has also been pointed out to take care of compatibility issues between licenses. So the most free licenses are CC by license. Shara-like might create, and this is what I say here in the last bullet point, that the Shara-like may have an impact on the reuse by commercial or otherwise parties who have proprietary business models. And they might feel that they cannot use the data sets in the way that will cater for their own business models. So it's a question of, you know, what do we want to allow users to do with the data sets that are produced by scientific research? Do we want just only scientific research on a commercial basis to take place? Or do we want to allow the whole wide world to do something worthwhile with the data sets? It's a question that each institution or government will have to decide. As we saw in the UK, they decided to only allow non-commercial research purposes. It's a choice. It may put limitation on other players in the market. But anyway, any move towards open access is certainly to be welcomed. One last point also that I made in the previous slide. The last bullet point, in Horizon 2020, I think we've heard, not today, but a discussion last night, but I think it's coming anyway, that the Horizon 2020 grants will require data management plans. So if you apply for a grant or if you apply for a Horizon 2020 project and you expect to be generating data, you will have to put into evidence that you can manage or that you have a data management plan. This, of course, can take different aspects, can mean different things. But one of the things that it may mean to have a data management plan, in my opinion, from a legal perspective, is that you should include a proper licensing strategy, or at least a proper workflow to be able to know what you take in, whose rights are attached to the information or data that you're using, and how you will yourself license and make your own data sets available to third parties and the public. So this is basically my very quick conclusion that I hope I didn't keep you too long from the coffee. So thank you very much. Thank you to all the panel.