 Okay, so a quick overview of what we're going to be looking at today. So we're going to look at what is reshare, you know, what it is, how it works, where we find it, etc. We're going to also talk a little bit. So the first part of today's workshop is just a short presentation. We're going to have a look through a few topics such as the data sharing checklist, what is reshare, the deposit process, a little bit on documentation and how to prepare that for archiving, a little bit on access, as in access restrictions that we can apply in our data, and then we're going to move on to the demo. So we're going to log in into reshare and I'm going to create a data collection. I am also an administrator for reshare. So you know, the data that comes in, me and my team would look at it, review it, you know, contact you or contact the depositor with further questions, etc., until the collection is ready to be published in our catalogue. And then after the demo, we're going to have a look at your questions that Gail said. Please, there's a Q&A option on your screen. So please add any questions you may have there and we're going to have a look at them at the end. Okay, so let's start with what is reshare. So reshare is the UK data services self-deposit repository. So it's an online data repository where researchers or depositors can start the process themselves so they can log in into the system, create a record for their data and submit it for review. That is the website there copied and of course you will have access to these slides, so you should have all this information. So reshare allows depositors, as I said, to create the data collection themselves and also to upload the documentation and data files themselves. So there's no sending via any means. You upload the files directly into the system and then reshare sort of brings it to us in the review area for us to check. So once completed by depositors, the collection, so the data comes into a review area where of course we check it for disclosure risk, for copyright breaches, validity of file formats, level of documentation. Pretty much just everything that needs to be there to allow future reuse. So there's also a place on the, and I'm going to show you this later when we do the demo on the website where we give you a full list of these review procedures, so exactly what we look at so that you know in advance and you can prepare it accordingly. But just to say that all numerical data files are checked and we check at least the 10% random sample of sexual data. And this of course is sometimes a lot higher than 10% depending on the data, but yeah, that's just the general guidelines. And then of course the published data collection are accessed from our data catalog and the link is there and I'll also show you this later when we do the demo. So a little bit about the deposit process. So as we can see, we have two separate sections really. So we have the depositor area or the researcher area. So that is where you would log in into the system. You would create the metadata record for that collection. So you pretty much have to fill in some information about the data. That is where you can also upload the files. So this is data and documentation. You can also set access and license conditions. Of course this is something that sometimes is done together with the depositor. So don't worry too much if you don't necessarily know what options to choose. So we are able to advise on that once the collection comes into review. So we would look at it and if there's any uncertainty around what access level would be appropriate for that data, we can advise you and of course after looking at the data. And of course the license would also match that access level. So don't worry too much if you're not sure about what access level or what license to choose because we can have a conversation about that after the review process. And of course after you fill in all the information and you've uploaded the data and the documentation files and everything, you can submit the collection. Once you do, it comes into the review area. So that is where we take a data service, we're able to review it and we would get back to you or to the depositor with feedback, if there are any edits necessary or if there's any, for example, fields that were left empty or that need filling in or that if there's any more information needed or documentation is not sufficient. So we get back to you or to the depositor with feedback and we are able to send the collection back to your review area, sorry, to your work area. So from review, we send it back to the depositor where you can edit it again. I should have said that once you submit, you're not able to edit the collection anymore. So once it comes into review, we are the ones who can edit it. So only one person or one team can edit it at the time. So yeah, if there's any edits that still need to happen, we can send it back to the depositor area and you can make changes and resubmit it for you. And then hopefully once that is ready, we can go ahead and publish it. And of course that can repeat as many times as necessary. So this sort of going back and forth between these two areas can happen as many times as necessary. Or of course we've had situations where collections were perfect the first time around. So we were just able to publish. Okay, moving on to a data sharing checklist. So this is just a few aspects to keep in mind that would make your deposit process a little easier and smoother in terms of those questions that we come back to depositors about. It's important that for data that we receive, that we ingest that consent was sought to cover data sharing. So sometimes there might be different processing grounds chosen to process that data by the research team. But that might not cover data sharing. So sharing that data in an archive to be used in the future by another research team by other researchers for different purposes. So there would be different processing conditions. So this would need to cover, so this informed consent would need to cover data sharing and long-term preservation and curation. This is why at the point of deposit, one of the documentation, so in that documentation category that I mentioned earlier, we would ask for a blank copy of the consent in the form and an information sheet if there was one. So the reason why we ask for that, and of course it's a blank copy, I'll say that again, the reason why we ask for that is just to check the language that was used around data sharing to make sure that there was no language used in the consent form on the information sheet that would preclude data sharing. So sharing the data, publishing it in a repository or in an archive for future reuse. Okay, the next part of course before sharing data is making sure that we protect identities and this is by means of anonymization. So of course not, and not collecting personal data. So here's the principle of data minimization. So only collect data and especially personal data that is necessary. So make sure to minimize that as much as possible. But of course before sharing the data we would need to anonymize it or to pseudonymize it, of course there are different levels here, as I'm sure you have encountered this before. There is just one anonymized state. Data is a full spectrum and data is available under many different anonymization levels if we can call them that. And yeah, so that is important to consider before sharing the data. And that is also where we, depending on the level of anonymization and the risk of disclosure still present in the data, that is where we would implement access restrictions. Of course the more anonymized data is, we could publish that under open access for example, but if we have data that is perhaps de-identified or pseudonymized to a level where there is still a risk of disclosure in the data, then we probably only publish that under safeguarded or permission only, right? There is, we're not going to go too much into anonymization today. There is however a separate workshop that we run on this. I think that will be on the 1st of June, if I remember correctly, or I think it is sometime in June. There is a slide at the end. I run that together with my colleague Maureen and we cover both quantitative and quantitative data. So this is something that you are interested in, please join that, because we are not going to go into much detail about it today. But yeah, so we would regulate access where needed on all or parts of the data. This is why, you know, in reshare we can apply access restrictions at file level, so it's not applied at collection level, sorry, I'm just making some sense. So each individual file will have its own access level. So if you have for example a mixed methods project and you're uploading different types of data, it might be that for example the survey data can be under open access and you also have interviews of focus groups and those can be, you know, more restricted, it can be the safeguard or permission only depending on, you know, the risk of disclosure there. So yeah, but we're going to have a look at that when we look at reshare in more detail. A couple more things to remember here is to of course store personal sensitive data to securely and separately, by separately here of course there would be different measures needed depending on what we're trying to protect, you know, if we have, if we're storing data that is if you're storing personal data, then of course we have to be more careful using encryption. And there's another webinar, another workshop that we run on that called data management basics. So if you are interested more in this, then you can also sign up for that or you can find more information on our website. Yeah, and to utilize encryption and consider the storage location, again in terms of backup, you know, we don't want to just have one copy of the data. So yeah, if you need to know more about sort of that data security strategy, please have a look on our website or join the data management basics webinar. Okay. Right, moving on to documentation. So when we come to the point of deposit, you know, we log in into reshare or I'm not sure if, well, it might be that perhaps in the future you know, you'll choose to share your data somewhere else. But once you, you know, you try to deposit your data somewhere, it won't be just the data files that you'll have to upload, right, it will also be some context around that data and some documentation files. So in terms of documentation, planning ahead saves a lot of time and will help you keep things organized. What we usually ask depositors is to think about what information a stranger to the project would need in order to understand, replicate or reuse that data. So replicate the findings of course or reuse the data. So you know, if someone were to access your data in five years from now, someone with no prior knowledge of the project, what information they would need in order to use that data correctly. And of course, planning to archive the data will be useful to know in advance. So because different archives or repositories might have different guidance around formats, metadata standards, so this can vary a lot. So it's ideal if you can to check this in advance, you know, ideally as early as possible in your project so that you know, you know, perhaps what formats you should be storing your data in. Yeah, so that can be something that can give you a lot of trouble if you leave it until the end of the project and you realize that you have to, you know, convert data and so on. So in terms of actual documentation, so project level documentation. So what we refer to as project level documentation. So this includes information about the study. So what were, you know, for example, what were the main research questions? What were we interested in that, in that project? The type of data of course that was collected to answer these questions. And then we have data level documentation. So this includes information at the level of the individual data file. So for an interview transcript, you know, this could be, for example, the header at the beginning of the interview, you know, telling us who is the interviewer, you know, the date of the interview. When I said who is the interviewer, I didn't mean the name, I meant, you know, some demographic information and of course the information that we are allowed to share. Not, I didn't mean the name or personal information. And for, you know, for quantitative data. So that can be the level of a particular variable in a data set. So, you know, making sure that we have clear variable labels, value labels, et cetera. So just making sure that everything is clear for someone to be able to understand it. Okay, in more detail, what to include as documentation. So this is, so data collection methodology and processes. So this is information about sampling, sample size, field or protocol. So of course, what applies, right? Interviewer interactions, depending on what type of data we're collecting. Codebook, a user guide for quantitative data, information sheet and consent form. As I mentioned earlier, we need to make sure that, you know, language use was not what does not work with data sharing, excuse me. Questionnaires, show cards, topic guides, et cetera, for transcripts, header with context information. So this can be dates, let's just say dates in place of interviewer, interview details in line with consent form, as we said, et cetera. A data list, so this is an overview. So for qualitative data, this is an overview of key information about each data file. We refer to it as a map to the collection. We also have a template for this that you can just download and adapt to your project. And we have an example in a later slide. And my dog has chosen to play with this speaker. I hope she'll stop. Okay, so and then links to reports and publications. So preferably the OIs were possible. So if there's any publications related to the data you are sharing, then ideally we would also include that the OIs so that people can have that and then can go visit it if needed. If there's any related data or data that the data you're deposited can be linked to, we should know that both for disclosure purposes and also to know that there is related data out there for whoever's trying to access this. So really any links, if there is a website perhaps for the project, you'll be able to add it and we're going to have a look later as where you can add this on the project. Okay, I mentioned the data list and this is a type of documentation file that is uploaded along with qualitative data. So here we have an example. We have 20 different interview transcripts and we have information about each of them. We have the Farmer Code, Age, Farm Scheme, et cetera. So this type of file is very useful because whoever lands on your data collection page can just go to this file and see a summary of all the files that are uploaded in that collection. It also allows them to perhaps if they're interested in a sub-sample of the data that you have in that collection to just search for whatever they're interested in. Perhaps in this case they're only interested in, I don't know, dairy farms, right? So they would know to go to the transcript that says farm type dairy, right? And we have the text file there, text file name, so they know exactly which file to go and open. They don't have to go through each individual file, open it, look at it, et cetera, right? And it also, it helps them, it might be that this is not something that is useful for them. So they would just open it and look at this and decide, OK, I don't think I can use this, right? So it saves a lot of time and it also, it's a very useful piece of information about that collection. And as I said, we have a template for this that you can just download and, of course, change the column names and make it your own. OK, a little bit about organizing data. So, of course, planning in advance, this is with a view to share the data, of course, at the end of the project. So this is, it's important to have the data and the documentation files are planning to share very well organized, using a logical structure and ensure that, you know, if you have, if it's quite a larger team in the project, working on that project, that everyone is using the same sort of scheme, the same guidelines, the same file naming conventions, et cetera. So as examples, use a hierarchical structure of files, group them in folders. As I said, at the point of deposit, you will be able to upload data depending on data type. So we will have to have it grouped anyway into different folders, into audio, for example, or transcripts, or annotated transcripts, or survey data. Whatever it is, it should be clear and it should be grouped accordingly, according to file, to data type and file type. OK, moving on to access, as I mentioned, you will be able to select this and reshare for each file that you upload or folder. This is selected in line with, of course, what the participants have agreed to in line with the anonymization level that has been applied to the data. So, but we have three, at the UK Data Archive, we have three different options. We have open, safeguarded, and controlled. So for open, this is available to anyone without registration under an open license. Then we have safeguarded. So this is available after registration. So anyone who wants to access that data will have to register and agree to our end user license. And under this safeguarded level, there can be special arrangements, such as deposit or permission. So anyone wanting to access that data would have to ask for permission from the data depositor. Or we can have an embargo for a fixed time period while publications are underway. That's also an option. Initially, it's for up to 12 months from the date of deposit, but that can be changed. So if at the end of the 12 months, the depositor tells us, well, my publication is still not out, we can extend that if needed. And then there's controls. So this is only available for remote or safe from access for users that have undergone some training, and the project has been approved. So this is similar to the, I think, ONSSRS, or it's basically a trusted research environment for those of you that are familiar with that. And yeah, so. And we run the training for that ourselves as well. There's an assessment at the end of it. So this is because the data on this access level is quite, the risk of disclosure is higher than the data that would be under open or safeguarded. OK, so some final slides here. I think we are changing at the end of the presentation, and we can move on to the demo. So some best practice guidance. We have on our website if you want to read more on any topics in data management. There's also the says that data management expert guide. We have a book as well that we published on managing and sharing research data. And of course, we have our training and events. I mentioned quite a, I mentioned a couple other workshops in this presentation. So if you want to sign up for any of them, do go to our events page. There's some tools and templates. So as I mentioned, I mentioned the data list template on the slide at the bottom there. We also have templates for model consent forms and survey consent statement. We have a transcription template, a transcription instruction. So the links are here for you. And of course, you can also find them on the website. Some further resources as well on anonymization, guide to social science preparation and archiving, the DMP online. So if you're putting together your data management plan, that it's a very good resource. Of course, stay connected. If you have any questions, do use the contact link. That it's the first link on this page. And then our team will assign that to someone who can help you. And of course, you can contact us on Twitter. And we have a YouTube page as well, which of course you can find past recordings and useful videos as well. Upcoming events, so these are a few of the workshops coming up. So we have introduction to copyright. We have the Safe Researcher training. So that is the training that someone who wants to access that controlled category data would have to go through. We have getting started with secondary analysis. We have data documentation, consent issues and data sharing. And I mentioned the anonymization webinar that we're running on the 15th of June. That is the correct date on how to anonymize qualitative and quantitative. So I'll see you there if you sign up for that one. And of course, I include the advance page so you can register if you'd like for any future events. And now we've reached the demo. So if you're preparing to deposit data, you can start creating a data collection in real time with me if you'd like. The steps really, so that is the ReShare website. So it's ReShare.ukdataservice.ac.uk. You will need to register first if you haven't. So perhaps, and that will take, if you haven't registered yet, that will take a little bit longer. So you won't be able to create it in real time with me. But if you are already registered with UKDS, then you just have to log in. And then I created a data collection, but we'll do it together from there. So I'm going to stop sharing now so I can get everything set up for the demo. Hopefully you can see my screen. So first things first, so this is the UKDataservice website. And this is where you can search our data catalog. So any data collections we have about over 9,000 at the moment. You can find them here. You can search by keyword. You can search by, you know, if you know the data collection number like I did, or by survey. Or yeah, you can search by many, many factors. So I'm just going to find the data collection to use as an example here and go. So here we have it, architectures of this place, humanitarian strategies for sheltering refugees. So we have in-depth expert interviews. OK, so I'm going to use this just to show you how. So this is a data collection that has been deposited via reshare. And it has been already published, of course. And so this is how it looks like. We have details. We have title, study number. We have the access level. So this data are open. We have the persistent identifier. So this is the DOI for this data collection. So in the citation of this data collection, you know, if you're able to, sorry, not if you're able to, if you're using this collection and want to cite it, you should include this so that, you know, it takes anyone who's reading that citation to this page and to this data. We have the data creator. We have sponsors and contributors. We have the sponsor. So this was funded by the Economic and Social Research Council. We have the grant number. We have topics. We have keywords. We have an abstract. We have coverage and methodology. So data fieldwork, countries, observation unit, kinds of data, method of data collection. We have citation and copyright. So the citation for this, we have it here. And as I mentioned, the DOI that we saw above, right? Copyright edition history, okay. And then to access this, if I click on access data, it will take me to download from ReShare repository. So I'm just going to select this and this is how it looks in ReShare. So ReShare is a separate website to the UK data service. And this is pretty much the information we've already looked at, right? Coverage and methodology. We have access and administration. And we have the available files. So we have data. We have documentation. So we discussed documentation. We have the consent form here. We have a zip folder with supporting documentation. We have a README file. We have the number of downloads. So this is how many times the data has been downloaded and how many times this page has been viewed. There is some more metrics there. Okay, we can also see how many times it's been treated. And then we have related resources. So during the presentation, I mentioned that, we can add a website for this. We can add, this is a documentary trailer here that was added, okay? So the reason I'm showing you this is because now that we're going to create a record in ReShare, we're going to have to add exactly these fields that you see here. So it's useful to see them first, how they're meant to look like once they're published so that we know and make our lives easier when we're actually having to fill them in, okay? So now, moving to the ReShare homepage. So this is ReShare.ac but you can add to service.ac.uk. This was in the presentation as well. So you will have to register if you haven't yet. I am, of course, registered. So I'm just going to log in, okay? Okay, so this is how it looks like once you have already logged in. This is my homepage once I log in. We can see here on the left that we have quite a few options. You will only have my data. The reason why I have additional ones is because I have admin rights. But if we go under my data, this is actually what you, this is where we are at the moment. And you can see here all the collections I published in the past. Of course, there's quite a few there. But if you're planning to deposit more than one collection, then obviously you will find them all in here. And if you don't, you know, if you start your deposit in time, you can save it, you can come back to it. And to edit, you just need to select this yellow pencil here. Before you start to deposit, there's some guidelines here. Just in terms of how to zip bundle your files, you know, check your recommended file formats if you haven't yet. File naming, you know, creating a readme file, essential documentation, right? So we have a readme file, we have clear variable and value labels as we've seen in the presentation. We have a questionnaire, a data dictionary for survey data, a data list for interviewees, blank copies of consent form information sheet, right? So this is just some additional information if this is the first time you land on this page. And then if we're ready, we can go ahead and create a new data collection, okay? So as we can see at the top, we have six different sections. We have terms and conditions, ground details, people, data collection, upload and deposit. So we will have to go through all these sections. However, if we, as I said, we start perhaps earlier on in the project or we're not ready yet to deposit the data or different reasons, we can always save it for later and we would, you know, in three months from now, we can come back and find it under my data, okay? So yeah, that is an option. And then once we are done with one section, we select next, we move on to the next section and the data is saved, the information that we added is saved once we click next, okay? We see there's some asterisks. So throughout these sections, the sections that are mandatory, so you would absolutely have to fill in that section or we would come back, ask you for it and that feedback that we come back with. So yeah, notice them. So in this terms and conditions section, we have, we pretty much just need to accept the terms and conditions, right? You can read them here, it will be, yeah. So there's for you to read. And once you're happy with that, this is pretty much just a summary or yeah, to some of the most important points in that. So just confirming that you are the owner of the copyright. So pretty much if you collected normal data and during your project, then that will be true. Or if you use secondary data, you know, you would have to declare that in the grand detail section. So once you have read the terms and conditions, you need to agree before we can move forward. So I'll do that. Okay, the next section is grand details. And here we have to provide a grant reference, project title, project description. Okay, so if your project is funded by UKRI, so if you have a UKRI grant number, you can insert it in here. So this is why I'm using this collection, which we already looked at as an example. So I'm going to use that grant number. And once you do that with, of course, your own grant number, this should pull that from Gateway to Research. It should harvest that information from Gateway to Research and it's particularly slow. Oh no. Oh, there we go. It found it and then it disappeared again. There we go. This is exactly the project that we looked at. This is the, yeah, so if we select it, these fields are populated automatically, so you don't have to save you some work. Okay, so ground holders, everything is added, project dates. Okay, so if you're happy, of course you can edit this if you'd like. You can edit, for example, the project description if there's anything that was initially added under grant information and perhaps that changed during the project, of course you can edit it and change it. Okay, and then we can move on to next. So that was an easy section because it's all harvested. As you can see here, it also harvested the name of the PI and it will do that automatically with the, right, so it's the same name here. And yeah, it can be changed. I doubt the PI would change, but anyway. Okay, so adding affiliation, you can also add an ORC number or CID, or you don't know how that is pronounced. If you have one, write owners. So if, as I said, if you're the posting data that you collected during this project, then that would be your name on the right owners. If you're using secondary data, then of course that would be different. But if you have any questions or you're not sure what to add here to let us know when we're happy to advise, another thing to point out, you'll see that there are question marks for each section. So if you're not sure what should go under that section, select the question mark. Then we have contact information. So this is, as you can see, it also has an asterisk, well actually they all have an asterisk here, set for contributors. Sometimes this is left blank, but it's important to fill it in. And especially it's important to provide an email for this because that is my address. It's to provide an email for this because anyone who might have, of course questions about the data, they need to have someone to contact. And of course for each we can add more rows, right? We can change the order using these arrows on the side and we can also add contributors. So if there's anyone perhaps, I don't know, a research assistant of someone you would like to also include or give credit to. You're welcome to do that here. And of course we have as many rows as we want. Another thing to mention is that whoever we include under data creators, those would be the people that are mentioned in the citation, right? So if we look at the citation of the data collection, so the citation is here at the top, yeah. Those would be the people that are added here under data creators. So that is just something to keep in mind. And the order, right? So that's why we can order, right? Okay, so here we have this section pretty much filled in. Of course I'm not going to fill this in because it's going to take time, but I'm just going to move on to the next section. But you'll notice that as soon as you move and you haven't filled in one of the mandatory fields, you'll get a warning at the top. So please to make sure that you, that you do that. Okay, so data collection title, we're just going to do example webinar, just for this collection. But of course the title would be this, right? So this is the title of the data collection. Then we have an abstract and the abstract is this. So this is the data description abstract. This is the grant information. So this big text here is actually the text that was imported under grant information here. And it's different from the abstract for the data description. So this is actually under the data collection section. We just have information about the data that is deposited that will be present in this collection. Underground details, this is information that was available under, so if we go to UKRI, sorry, oh actually. Yeah, if we go to UKRI Gateway to Research, this is where all the information is. And we add this grant number. Yeah, so this is where it's, that information is harvested from and this is that abstract, okay? But this is information that of course is added at the beginning of the project. So it might, it's different from information that we want to add that is actually about the data collection that has been deposited. It might be that when we plan the grant at the beginning of the project, we plan to, I don't know, for example, only collect survey data, right? That might change throughout the project. We decide, okay, we also want to do interview data. So it won't be the same. Okay, so once we have the abstract here, then we have keywords. And I'm just going to do one example. So as you start typing, so this is a controlled vocabulary. So you'll notice that some of the fields here are machine-readable metadata. So you will select or you will add in keywords and others are just open texts like this. On the topic classification, I can't remember what in the collection. Okay, so on the topics, we have social welfare policy and systems and we have history. So I'm just going to add history, okay? So that added history there. Of course, we can add as many as applicable, okay? We have temporal coverage and this is already something that has been harvested in from Gateway to Research and we can leave it or we can change it if it has changed. We also have temporal coverage. If for example, it's historical data. So it will be different from collection period. Geographical coverage. So this is, we can either just add country or we can add a more London, for example. We can add a spatial unit if that is applicable as well. And then methodology. This is also a very important field just because we need to describe. Oh, wow. I have a, there we go, there we go. Okay, methodology we have here. So it's important to fill in this because it will give us information about how the data was collected, what type of data we're talking about. So right, we have unstructured in-depth quality interview, qualitative interviews, okay? So I'm just gonna add that in. Observation unit in this case is individual kind of data. It's text, right? Data sourcing, processing and preparation. So this is anything about the source of the data collection. If we have derived data, et cetera, any quality assessment or anything that would need to be, would be important for someone to know about the data processing aspect. And then we have type of data. In this case is qualitative and mixed methods. We have the resource language. So we also have data in other languages, not just in English. So we can add here if it applies. Related resources, so this is where we can add, as I mentioned, we can add a website, we can add publications, we can add different sources. So the DOI or the URL would go in here, the name, and then we can choose the type of resource. So it can be either a data collection or it can be a publication or software or website, right? We can just choose the type. And of course we can add as many as we want. We do advise you that after the collection is published, if at the point where the collection is published, you don't have your publication out, that's fine. But we strongly encourage you to, once the publication is available to contact us so that we can add it to the data collection. It just makes everything more complete and it provides more information, just has everything in one place and people can find both the data and the publication that came out of it. And then we have notes and access. So this is any information that would be useful for us. This is not going to be published, it's only available once the collection is, see there's no notes and access here. Well, there is, but it's not the same field. Actually that comes from somewhere that that's something actually we add in. But this information is actually something that you can use to say, for example, I don't know, I had 15 interviews, but I didn't have consensus share from 20, so I'm only uploading 30, or I would like an embargo for X amount of time if it's less than 12 months, six months, otherwise we're just applied the 12 months default. So anything really that, or if you're not unsure about the license, or if you're not sure about what access level to apply, or about anything about an organization, yeah, so anything would just go in here. And then you wouldn't have this, this is just for really purposes. So once we are happy with all the information that we added here, we can go ahead and select next from the bottom. I'm just going to use the sections at the top because you won't, if you haven't filled in all the mandatory fields, you won't be able to use the next bottom at the, the next bottom, the next, yeah, at the bottom of the page, but you can skip through sections this way. Don't do it, please, because you will have to provide that information. Okay, so here we are actually uploading our files, so I'm just going to choose some random files for this, and I'm just going to use a word file for this purpose. So it can be an individual file or it can be a bundle, so it can be a folder, but if it is a folder, it needs to be zipped up, okay? And once we upload it, we have an expandable section here to select access and license. So we see here that we can select the access level, it can either be open or registered or closed access. So this is under embargo or if there should be, if user should require permission from the depositor to access the data, okay? So for this, I'm just going to say registered. I'm going to pretend this is a data file, right? So I'm just going to leave data here, but depending on what file you're uploading, right? So it can be a data and documentation bundle, it can be a documentation file, it can be additional metadata, it can be a data file or a readme file for this. So I'm just going to select data because it's data. I'm just going to pretend it's a file transcript, sorry, no, interview transcript, okay. Embargo date, of course, if this is something that you would like to have applied, you can select it there and then the license, right? So we have a few options here, I'm sorry. We have a few options here. We have creative comments and a few variations of that. So that would apply for open access. And then we have our UK data service and user license. So this would apply for registered data. So for safeguarded data and for closed access, right? And then the creative comments would apply to open data. So I selected registered users, safeguarded data. So I'm going to select the UK data service and user license, okay? As I said, if you're not sure about what license to choose, don't worry. We can now, we definitely checked out before everything is published. So there's, there should be any concerns there. And if we just select save, we can find it there. And of course we can add as many files as we want. You know, we can add the, and that's necessary, right? So we looked at documentation and what we should be uploading. So do make sure that you, that you provide all the documentation and all the, and of course all the data. And then once we're done, we can move on to deposit. So we are just going to select next. So once this, of course this is the last section. So it's going to remind us about all the fields that we still haven't filled in. And you need to confirm, you know, that you agreed to the conditions that the data files have been anonymized, that they don't contain any disclosive or personal information. So having said that, you know, we have collections where, you know, the interviewees were happy to have their identities disclosed. And that is perfectly fine. Of course, if there is a consent form for it, and so that would be an exception, of course. But for everything else, you know, we shouldn't, you shouldn't upload data that hasn't been identified, that contains personal information, unless again, you have permission to do that. Okay. And of course that sufficient documentation is uploaded to make this data collection usable for future research. Okay. And everything else. And once we're happy, we can deposit the collection. Now, as we saw that will then push it into review. We won't be able to edit it anymore. We would still see it under my data, but you won't be able to edit it. And then, so it comes into review, we check it, and then we contact you. And, you know, we either say everything is fine. This is where, you know, your collection hasn't published. This is where you can find it. This is a citation, the OI, et cetera. Or if not, you know, we would send you an email with, you know, can you please fill in this field? Yeah, it's a job. Make sure you upload this file. So I'm not going to deposit it, of course, because this is a mock, I'm just going to save it for later. And I will be able to find it here under my data. If I go all the way at the bottom. Yeah, it's there, yeah. So this is all the information that we just added. So the title, the abstract that we imported, the abstract that we added. We added the topic history, we added the refugees. Yeah, so keyword, refugee, project dates. Yeah, so all the information that we just added is there. That's the file that we just uploaded as well. And if we select, if we open that field, we can see that the options that we chose, right? So this is, this should be under safeguarded access. It is a data file, it is an interview transcript. We added that information in. We selected and use a license. We also have the file size, okay? Yeah, so this is it. So of course, you can have it in your work area as long as you need. You can start a collection earlier, have it in your work area. Perhaps it's a larger project and you're waiting for your colleagues to send you any files or et cetera or so. Yeah, that is the record created, that's the demo. As you can see, we have the ReShare homepage, right? And there's also a video here on how to deposit your data. There's some exemplary data collections here. If you'd like to have a look, we also have a section on Legals. So this is information on the deposit terms and conditions. This is terms and conditions for safeguarded data, for open data. Yeah, so there's quite a lot of information here. At the top, we also have the review procedures, as I mentioned earlier during the presentation. So this is exactly what checks we're doing during the review process. So we have generic project-level checks, we have file-level checks, and then for a quantitative data, for qualitative data, documentation, file checks, right? So we're looking at sufficient documentation is available, essential documentation, topic list, so that's the data list, questionnaire, okay. So yeah, you can find all this here. There's also an FAQ, there's help section, with some more information. There's a metrics section as well. So once your collection is published, you can use this section to see how your collection has been used. So how many data downloads, how many file downloads, you can sort here, of course, by your, you can select your data collection and have a look at that. How many data downloads, right? Data type downloads, the most downloaded data, okay. So that is, I think, everything that I wanted to share.