 All right, good morning, everyone. Thank you for attending this webinar and licensing your research. My name is Courtney Sturtburg. I'm the statistical and methodological consultant with the Center for Open Science. And our webinar is going to be delivered this morning by our guest, Brandon Butler, who is a librarian and a lawyer at the University of Virginia. So just a couple of quick logistical things before we get started. For all of you who may want to ask questions during the webinar, there's a cue and a panel that you can use. And if you click on that, it'll pop up. We'll be able to see your questions more when we're answering them. If anything goes wrong during the webinar, our videos cut out, our sound cuts out, something like that, you can also let us know by using the chat function during the webinar. We'll be watching both of those throughout. So I guess I will hand it off to Brandon now to go ahead and get started. Great. Hello, everybody. I will apologize in advance for my voice. It is failing me slowly, but surely. So contracts are magic, or how and why you should license your research. So here's the roadmap. And as you can see, it's a long roadmap. I have a lot to say. So I hope you will bear with me. I tried and tried to cut this thing down, and I just couldn't do it. So as I say, there's a lot to say. I will hopefully have a few minutes at the end for your questions. And I'll also be trying to watch the little questions panel and see if anything comes up during the presentation. But as you've already seen, I'm having a few tech difficulties. So maybe court me if you see anything, jump in and interject. So I'm going to talk about copyright basics, because you might be wondering, why do I even need to do this? Why is copyright an issue for me? I'll give you some policy arguments about why I think that you should license your research. Why I think it's a good thing for you and for your colleagues and for readers out there. And then we'll finally get to, I think, probably something that attracted most of you, which is the basics about licensing, the different choices that you have. And again, I'll do a little bit of advocacy if you don't mind on why I think going as open as possible is the best way to go. So first, who am I? I am the Director of Information Policy at the University of Virginia Library. I am a lawyer. I formally worked at the American University Intellectual Property Law Clinic, where I and my students represented clients in copyright and trademark and patent litigation and other counseling matters. I worked at the Association of Research Libraries in Washington, DC, where I helped develop national policy initiatives on behalf of libraries. And I worked at a law firm called Dalonis LLP, which was recently bought by a bigger law firm called Coolie LLP. I am a copyright lawyer, but I am not your lawyer. This is not a legal advice session. This is some information that you can use as you wish. And also, by the way, all of this is a little bit US-centric. I'm in the US. I know sort of most of you are in the US, but definitely not all of you are in the US. So when I talk about things like fair use, of course, that's a US-specific doctrine. And I will try to highlight a few other things that are unique to the US and other aspects of the law that might be relevant to other parts of the world. So that's where I'm coming from. Copyright basics. If you write research, you probably own copyrights. Copyright attaches like magic to every work of creative authorship from the moment of fixation. As soon as you put in the paper, the things that you write down, assuming they are minimally creative and the bar is very, very low, as long as you are making some choice in the words you're using and the structure of your expression, the thing you're making is probably creative. There are no more requirements that you register or that you place the proper notice on something when you publish it. All that stuff has been gone for decades now. And copyright, as a result, is really attached to almost everything that we produce. That means that in most circumstances, others are going to need your permission to copy, distribute, or adapt your scholarly works. So who owns copyright and scholarship? In most places, in most cases, the persons who literally write the article or create the any other written representation of information or data is the author for copyright purposes. It's the person who puts pen to paper or fingers to keyboard. So lots of people may contribute information or do work on a project. But the legal author for copyright purposes is the person who creates the document. That is the final condensation of all of that information. The author, in most cases, is not the university, at least again in the United States. Although generally, someone who does something as part of their job, the work belongs to their employer. And research, I think, is, frankly, surely part of the jobs of most research academics. Universities that employ academics in the US, at least, routinely by policy, surrender copyrights back to faculty. And they say, in the ordinary case, you own your scholarship. Now, there are exceptions. If you're doing something that is patentable, where there's potentially a profit to be had from technology transfer, if the university has invested substantial resources, and that doesn't mean they let you use the library. That means they bought you a million-dollar lab. They hired you some lab assistants with expertise. Sometimes universities have carve-outs for that so that they can claim and monetize and control profitable, potentially profitable discoveries and inventions. If this is an issue for you, you will know it. Whoever is funding your grant, whoever is administering your department, you will have that conversation. In the ordinary case, though, you the author are the owner of the copyright. Lots of academics collaborate with other academics, so there can be joint authorship. Again, the joint authors of any work are the two or three or more people who contribute protectable expression to the project. Again, not just someone who monitors the lab equipment. It has to be someone who helps to write or formulate the final written expression of the research. And there must be an intent by all authors that they each be co-authors of the final work. And so this intent can fall apart sometimes, and that would cause people not to be legal joint authors. But again, the key takeaway here is, it's probably not lab techs, probably not. Lots of people who are important helpers, but who do not literally write the research. This may seem a little wonky and abstract, but I think this is, in a way, the most important slide of the presentation. Copyright has a particular attitude toward facts and ideas. Copyright law wants facts, ideas, discoveries, knowledge in the abstract to be free. Once I've learned something, I am free to repeat it. I am free to re-express it and use it in my own learning and research. But copyright nevertheless awards a monopoly on any particular specific expression or selection, coordination, and arrangement of the facts and ideas in a particular work. And copyright protects the specific expression or the selection and arrangement for the life of the author plus 70 years in the ordinary case. So that creates a little bit of a conflict, I think, in a way, in the internal policies of copyright, because the standard containers for knowledge and data are copyrighted works. And therefore copyright de facto, even though there's literally a provision in the Copyright Act that says copyright does not apply to ideas, facts, discoveries, systems, and so on, nevertheless copyright, as a matter of fact, ends up governing the circulation of facts and knowledge because it governs the containers that facts and knowledge circulate in, namely scholarship and the published discoveries of scientists like you guys and other researchers. So there's this tension, right? So one reason to license your research is to help alleviate that tension, right? Why license your research? Well, for readers, when you openly, when you license your research with an open license or any kind of license that tells readers, here's what you can do with my research. It lets researchers in countries or at institutions without massive libraries or journal budgets gain access online, right? When you use something like the open science framework to publish versions of your work, your working papers, post prints, pre prints, when you post those things on the web openly and with a clear license, it tells your readers all over the world that they're free to take and use and understand this stuff without fear, without legal fear. Professionals are another major user of open content. Doctors, engineers, scientists in the private sector, lawyers, these are people who actually are, they need access to the latest research and the latest thinking in order to do good work for real people who need them to be informed. And again, these professionals can't always subscribe to the big journal subscriptions. Lay readers, you know, patients, people who, you know, when your loved ones contract a certain disease, you find that you might get really interested in the cutting edge research on that disease. Advocacy organizations working in Washington and around the world, again, want access to that cutting edge research to support their projects and policy makers, you know? People in Congress, people in key agencies, you know, sometimes those agencies can afford those subscriptions, but often not. And if you want your ideas to make an impact, you need to make sure that they're accessible to those people. Even large research libraries can't subscribe to everything. Works available in full text on the open web are just more discoverable. They can be full text searches searched and crawled. Again, that really facilitates discovery in an important way. Your colleagues will appreciate it when you license your research. For all the reasons above, plus many kinds of research involve copying, reusing, adapting, existing research. So reproducibility studies, for example, they need robust access to data. They need permission to reuse the data so that they can derive their own results from that data. Meta analyses, again, collecting, comparing, combining. These are follow-up research. This is follow-up research that is incredibly important and powerful and the best way to ensure that the follow-on researcher has full access to your work is to give them a very clear statement and a license that permits them to do what they need to do. Text and data mining, right? Digital humanities is a big thing here at UVA, but text and data mining is useful for all kinds of research. And again, this text and data mining, I argue when the courts have said, is ordinarily fair use in the US, but open licensing can really help give people more comfort and especially can give people comfort outside of the US where fair use isn't available so that they can do text and data mining using your research. And then finally for teaching, posting and sharing scholarship in relevant courses. If I wanna teach my course using the cutting edge discoveries in the field, it's really great if I know I can put these journal articles into my course site for students to read without having to worry about whether I have the right license. And then finally, perhaps most importantly for you, licensing your research is good for you. When your work is accessible and discoverable to a much broader audience that can really redound to your benefit. You can have a global reach. There's great stories out there about people who put their work up on the web using an open license like CC buy and their work gets translated. And suddenly they become one of the most important researchers in countries they've never heard of, right? Because someone realizes that their research has important implications for a local concern translates that research and it becomes really important. Again, researchers with less access to expensive journal packages around the country can still find you and again, learn about your ideas, cite those ideas and build on those ideas. There are many studies that show that there is an increased impact and increased citations when works are openly licensed. Unexpected readers, unexpected users and even collaborators can come out of the woodwork when you put your stuff out there and let people find it. And finally, and this is something that I think Jeff Spees at the Center for Open Sciences may be one of the most eloquent advocates for, transparency is consistent with scientific values. Over and over again, if you ask researchers, is it important to share your data or is it important that your experiments be reproducible and so on? They will overwhelmingly answer yes. And so open licensing brings your practice into line with your values. So how do you pick a license? Assuming that, you know, licensing is good for you, that it's, if I've convinced you that licensing will help you and that all of your work is implicated by copyright and so it's really important that all of your work be licensed in some way or another. How do you pick the right license for your needs? First, I'll introduce you briefly to the wonderful world of Creative Commons, which is at creativecommons.org. There are actually many open licenses running around out there. Europe has proliferated a few that are especially for data and databases that respond to the situation around databases because there's a special database right in the EU. And so, and I believe also in South Korea. And so there are a lot of different specialized licenses running around out there, but Creative Commons is really by far in a way the leading sort of provider of open licenses. And what Creative Commons has done is really ingenious. They have these licenses that are made for the public for you to use to give a license to the public. And those licenses are written in three languages, right? There are three versions of every license. There's the human readable license language, which really tells you in ordinary words, what does this license mean? There's lawyer readable languages language, which is much more in depth and in detail and technical, but it describes the language in terms that will satisfy a legally trained professional. And then finally, the Creative Commons licenses are machine readable. That is, they are tags that CC by, CC by and C, when these license tags are associated with content, a machine can be trained to read that and treat different objects differently based on the license. So this was, this is a really brilliant innovation that Lawrence Lessay get Harvard, then at Harvard developed or in the 90s as a way to let people make their content available on the internet and affirmatively declare to the public, these are the things you can do with my stuff so that copyright doesn't become a kind of sand in the gears of the internet. So the way that a Creative Commons license works is that it creates a contract, it creates a legal contract between you and anyone who uses your stuff that is posted subject to a license. So when you publish your work online or anywhere with a license notice like the CC by symbol or the letter CC by, then by publishing your work with that kind of a notice, what you're doing is making an offer in contract law language. You're saying, if you'd like to use this stuff, it's available and that offer I should really, I want to really stress for you is irrevocable. That is, once you publish something with a CC by license or any kind of open license like this, you can take it down, you can get rid of the license notice but once the work has been published with that license notice attached to it, anyone is free to take advantage of that version. They can take the CC by at its face and you can't go back to them later and say, no, no, I'm not doing that anymore. It'll be too late at that point. So you do want to consider carefully what you do here because once you make a decision, you're stuck with it for the foreseeable. Now, once you make that offer, a contract is formed anytime someone uses the content in a way that is consistent with the terms. So when I download your paper and I then post it again on my website, what I'm doing is saying, I understand the CC by license and I am agreeing to be bound by it. And courts have enforced these terms. So it's a working system that creates a legal relationship between you and the public. CC zero is a waiver, right? It's ejecting your work into the public domain. I make no claims whatsoever. That means you don't have to give me attribution. You can treat this as if it was written in 1750. And then the rest of the CC products are licenses. CC by is free for all reuses, copying, adapting, et cetera on the condition that there is attribution. And attribution is reasonable given circumstances. But the reuser is supposed to include the CC by license. So they're supposed to say this content is licensed CC by and who was the person who was the originator of the content. So that CC by is the basic license. And then to that, you can add each of these additional terms. NC is for non-commercial reuse. So CC by NC is you can make any use you like so long as it's non-commercial and you give me attribution. CC by ND means no derivatives. In copyright, a derivative work is any new work that's based on a copyrighted work. So a derivative work includes a translation. It includes a sequel. It includes a combination database. So if I take five or 10 databases and combine them into a single database, that new database is a derivative work. So CC by ND would bar people from combining my data with other data. And then finally SA is the share alike term, sometimes known as copy left. That means that anything, you can use this thing, but any derivative work that you create, excuse me, must be licensed under a similar and under the same terms. So it has to be CC licensed with a share alike term. So let me see if I can, there we go. So why should you be fully open? And by fully open, I mean no, none of the non-commercial, no derivatives. Share likes type of conditions. Why should you choose either CC by or CC zero? For data, I think the answer is fairly clear. Data is different. The natural choice for data is CC zero. As I said at the beginning of the talk, the copyright protected aspect of data is thin. So all of the individual data, all of the individual facts in a database or a collection of data are unprotected and the law intends for those things to circulate freely. You didn't create them, they are not expressive. These things should be free to everyone to reuse. The only thing about data that is copyright protected is the selection and arrangement. So the choice of headings, for example, in a spreadsheet, which things you decided to count. That selection and arrangement can be protected, but it's thin. And so what CC zero does, excuse me, in my view what CC zero does is sort of erase that thin layer and let the data free. If instead you ask for attribution, there's a problem known as attribution stacking in databases where as the size of your database grows, if you collect multiple data collections into a single database, it becomes really difficult to properly attribute the underlying data. Say, well, these cells are from this guy and these cells are from that woman and these cells are from this study. It's rather, data is really not the kind of thing that wants to be attributed in that context. So requiring attribution can be a real problem. As I said earlier, no derivatives means you can't combine your data sets, which again is kind of a problem because combining data sets can be a really powerful research methodology. Share alike can be tricky because there are different share alike licenses out there if you use one of the European share alike licenses rather than as Creative Commons share alike license and each of those licenses says you must share any derivatives using this license. They will cancel each other out and you can't create a new derivative work because you can't license the new derivative work with both licenses. You have to pick the one. So the more complex your license is, the harder it is for anyone to use that material down the road. Finally, I wanna make a claim here which is I think that scholarly norms are enough. That is to the extent that you want credit for your work. The scholarly norms about plagiarism, about attribution, those norms are enough I think to keep honest people honest and you can invoke those norms to get the credit that you'd like. I don't think that you would want to sue someone for copyright infringement because they didn't give you the right citation and I can tell you it'd be very expensive and difficult. I think you're much better off relying on shared values. I'll quote Michael Carroll here. Full open access unleashes the full range of human creativity to translate, combine, analyze, adapt and preserve the scientific record. You just don't know what your data can do until you let it free and let people take the maximum advantage of it. If you use limited licensing, you may be inconsistent with other open platforms as well like Wikimedia Commons. The scope of non-commercial can be really tricky. What if somebody needs to fund their hosting costs by putting ads on a page but other than that, it's a free site that lets people get access to research. Do you really want to say that that person can't share your research with the world? And then finally, ND means no translations, no abridgment, no compilations. So again, these things can be real deal breakers for downstream research. I'll say just a word about publishing in journals. Journals are, they recognize that working papers, preprints and so on, that those things are commonly posted. They're often even posted with CC licenses. They understand that in very few journals have a problem with that. And even after, so if you're wondering if you can share the research that you've done that's been posted already, I mean it's been published already, take a look at your contracts and look at these links below, we'll make sure these slides are available to you. Read your contract and you'll find that you can probably share these things in all kinds of interesting ways, but at the same time, you may have given your copyrights away or given an exclusive license to the publisher. So you really can't license things that you don't own anymore. And so for the things that you've already published, you'll really have to look at your contracts and do your research. See what you can do. And finally, you have to really know your funder obligations. Many funders require certain flavors of open access. And so again, before you choose the license, talk with your funders to see what license they prefer. There's lots of great further reading on this. These are just a few resources. And again, these slides will be available to you. Michael Carroll's research and writing on this is really, really good. The Authors Alliance portal is really, really good. And the Digital Curation Center is great about data, although it also has a lot of stuff about European stuff, which might be less helpful for US-based researchers. And with that, maybe I should see. We have literally like one minute. I told you it was gonna be long, but we can see if maybe there are a few questions. So I see one question. What license would be equivalent to the Green Open Access, which many journals do offer? Do I need to license a Green Open Access article? That's a really great question, Eva. And what's interesting is that Green Open Access, which is for folks who haven't encountered that term before, Green Open Access is self-archiving, right? So the publisher publishes a final version, but they allow you to put a version into an institutional repository or a disciplinary repository. And the truth is that I think for many journals, they will not allow you to make a version that you put into a repository. I'm not sure whether they will allow you to license that version or if they'll only allow you to post it there. That is, the version is there, people can download it, but I'm not sure whether those contracts typically allow you to, whether those contracts typically allow you to then place a license that gives other people to make additional uses, right? So the publisher is happy for the article to be available, but they want it available only in certain places. And if you read those contracts carefully, they also require you to provide attribution to the publisher and a link to the original published version. So you really have to look at your contract and see what the contract allows. But on the negotiation side, when you start talking to people about, excuse me, when you start talking to publishers about the terms in your contract, that's something you could bring up. Once a publisher has said they want your article, you have some leverage. And at that point, you can say, well, I would like to make my pre-print or post-print version available with a CC by license. And you can push for that as a term. And some publishers will accept that. And then David Norris asked, should computer software code be regarded as data or like other kinds of writing? It's a great question. What, how should software be regarded is a real hairball. I don't know exactly, that there are many opinions, but I'll tell you how it is regarded in the US. Software code is treated as a literary work. So it's subject to copyright. And it has, but I'll tell you also that software is similar to data in that it has what we call thin copyright protection. Because so much of software is utilitarian, right? It's functional, it has to do something, and copyright is not supposed to protect purely functional aspects of software code. Courts have really shrunk the scope of copyright protection for software code so that only the most, only the expressive or creative aspects of software code writing, and I'll leave that to your imagination. I don't know exactly what that is, but when something is necessitated by the functionality of the software, courts will tend to say that you can use that, you can reuse that without causing a copyright question. Software is often subject to patent as well, and the patent is actually, up until recently, patent has been a more, the more common way of protecting software than copyright. Can I talk a bit about fair use? I could talk all day about fair use. So could I use journal abstracts in the back end to improve my public databases search engine results? Is that fair use? You know, the fun thing about fair use is that anything you do on the back end, that is the ways that you use text to train a computer, for example, it sounds like you're saying, could I train my, the way that Google does, right, to train its search engine to recognize certain things, or to train my search engine to find things so long as it's not actually revealing the entirety of the work. The courts have said loud and clear that that is fair use. And so if you wanna crawl journal abstracts and then create a search engine that says, you know, this is the journal you're looking for, and then links to where the journal lives online, in a legal location, by the way, if you're linking to illegal locations consistently, that's damaging. But if you wanna crawl journal abstracts and make a search engine out of that, then I would say you would be in pretty good shape in terms of fair use. That's a classic example of search engine fair use. All right, great. Thanks for all the questions. Before I end it, I just wanted to show you all, if you are interested in putting licenses on your content, how you might go about doing that. So as Brennan mentioned, oftentimes you're sharing your content in some sort of public repository. So things like science frameworks, Manoto, FigShare, many of these repositories will allow you to put licenses on your content. And I just wanted to really quickly show you how you could do that on the open science framework. So this is an example project I have. There's this license component, or this license section right here, if I click on this, I'm given some options on what licenses I can give it. Unless it automatically come up or some of the ones Brennan talked about, the CC buy for code, somebody asked about. Many people will oftentimes put an MIT license on their code, which is kind of the CC equivalent for code. It's a very open license that plays well with others, but I can choose other things and put a particular one if I want. So I'm gonna put a CC buy license on my project. And then if I want to, if I go into the data component of my project, I can actually put a different license on that. So if I wanted to put a CC zero license on my data to make sure that that was really reusable, I could do that, thinking kind of the other parts of the project under that CC buy license. And so then when I make the project public, it'll be clear to those who wanna reuse that work how they would go about doing that. All right, so I wanted to thank everyone for coming to the webinar today. Thank Brandon so much for presenting all this great information. This will be posted online after the fact. We've been recording it, so post both the recording and then put a link to the slides if you wanna look at those great resources for further readings after the webinar. So thank you all so much for attending. Thanks everyone. Bye.