I welcome you all for the today's session on Design of Vertical Summit Curves on Roads. Myself, Pashok Kumar, Aston Professor, Department of Civil Engineering, Vulture and Insur Technologies, Sallapur. Learning outcomes of today's class. At the end of the session, students will be able to calculate the length of vertical summit course. We know that when vehicle travelling along one grid, on this section vehicle travelling on one grid is to move on to another grid. So, opposite to that, this grid is another grid. A change of direction of motion in the vertical plane is involved. So, these vertical curves are required to ease of the change in the gradient. So, we need to connect this plus G1 and G2 by a smooth vertical curve. So, this curve will have ease of the change in the gradient. So, the main criteria behind the designing of vertical curve is the side distance. The vehicle coming on this side should be able to see the object on the opposite side. So, here you can see that the vehicle coming on this section should be able to see the opposite vehicle. So, that he can stop the vehicle or slow down his vehicle speed or taking a diversion. So, this will reduce the happening of accidents on the vertical curves. Summit curve forms when ascending gradient meeting another ascending gradient. So, here the deviation angle is n equal to n1 minus n2. We know that deviation angle is algebraic difference of ascending gradient and descending gradient.  Here ascending gradient meeting a level ground. So, in this case n equal to n1, ascending gradient meeting a descending gradient. So, in this case n equal to n1 plus n2 and descending gradient meeting descending gradient. So, there is another formation of vertical summit curve. So, here in this case n equal to n2 minus n1. Now, let us pause this video and try to give the answer for this question. Is there any necessary of transition curves in the vertical summit curve? We know that the transition curve we already designed in the horizontal curve. Now, let us pause the video and give me the answer for this question. Whether is there any requirement of transition curve in vertical summit curve? I hope you are able to give the answer for this question. The correct answer is looking at this diagram you can understand. The vehicle is going in the upward direction and the gradients in the vertical curve. Now, when it is going in the upward direction, the centrifugal force is acting on the upward direction and gravity is in the opposite direction. So, due to this the part of the self-weight of the vehicle is released or relief is given to the self-weight. So, this further the stresses or whatever the pressure on the tire is also released. And also the further the suspension system of the vehicle the stresses also reduced on the suspension system of the vehicle. So, this will have an advantage where the centrifugal force is in upward and gravity is in downward. There is no all the pressure will be nullified over here. So, this will be added advantages. So, in this case there is no requirement of any transition curve because the centrifugal force is already contracted by this arrangement with the gravity. And another one is having a smaller deviation angles in the vertical curve. We do not require we do not feel any discomfort to the passengers. One is the centrifugal force is not there because of that we are not going with the transition curve. Another is having a very smaller deviation angle. So, here the deviation angle is very small. So, in this case the discomfort to the passengers is also lesser. And another one we are designing the vertical curves considering the side distance criteria and length of the curve is larger in this case. So, in that case there is a shocks or vibrations any jerks that will be not there in the summit curve. So, because of all these reasons so transition curve is not required in the summit curve. Here the main criteria behind designing the vertical curve as I told you to provide a side distance. So, we know that the side distance is classified as stopping, intermediate and overtaking side distance. To minimum you try to provide a stopping side distance. The reason the what is the stopping side distance it is the height of the driver is considered as 1.2 meter and object height is 0.15 meter. If the driver can able to see at height of 1.2 meter and object of height of 0.15 meter on the curve the distance available in front of him is we call as a stopping side distance. So, in this case minimum you can provide a stopping side distance. If the land is available we can still go with a flatter gradient flatter gradient. So, in that case the length of the curve will be larger. So, we can go for thinking on providing the intermediate side distance. So, safety will be higher in the intermediate side distance. If still land is available we can go for overtaking side distance. So, overtaking side distance in this case the driver height is taken as 1.2 meter and object height is also taken as 1.2 meter. So, overtaking side distance means very flat curve. So, in this whatever you are looking this the steep gradient still we have a very flat curve. The length of the curve is larger in that section and the driver have enough distance available in front of him to take a proper action on the summit curves. Let us find out what is the ideal shape of the summit curve. Circular summit curve here this gives the constant side distance because we are designing vertical curves considering the side distance criteria. It gives a very constant side distance. Another one is the shape we are following with the parabolic curve. For a smaller angles both the summit curves and parabolic curve simple parabolic curves follow the same path. But we are insisting to go with a parabolic curve. The reason behind this selecting ideal shape of the summit curve is a parabolic. It is easy arithmetic calculations and coordinate calculations are easy and layout in the field is also easy. So, all together for smaller angles theoretically this circular summit curve is okay. But for considering these advantages all these advantages we are selecting a simple parabolic curve as ideal shape for the summit curves. Let us go for finding out the length of summit curve. As I told you we have to consider the stopping side distance criteria. Here length of curve is more than stopping side distance. In this case you can observe this diagram. Here the height is 1.2 meter and the object height over here is considered as 0.15 meter. So this distance is called as a stopping side distance. In this case the length of the curve is more than stopping side distance. And the n is the division angle. The equation for a simple parabolic curve for when length of the curve is more than stopping side distance. So that gives put the h value as 1.2 meter and the small h as 0.15 meter. So that gives you l equal to ns square upon 4.4. Second case when the length of the curve is less than stopping side distance. So that case the equation is again put the h value as 1.2 and the small h as 0.15. The equation reduces to 2s minus 4.4 upon n. Again considering the overtaking side distance here we are expecting the length of the curve to be more. To have the overtaking operation in the summit curve. So that case the equation is given by ns square upon 8h. So in this case we know that the h is 1.2 meter. So put the h value as 1.2 meter the equation reduces to ns square upon 9.6. When the length of the curve is lesser than overtaking side distance. So it is given by 2s minus 8h upon n and again h is 1.2 meter. The equation is 2s minus 9.6 upon n. Now we need to design for whenever we have the state section. So here one of the state section another state section we are connecting these two. Two alignments are connecting. Here if I leave that same as it is without providing any length of curve. It becomes a kinks on this section. So this kink will have a shocks or any discomfort to the passengers discomfort to the vehicle movement. So now we have we require to have minimum length on these sections. So according to the codal provisions depending upon the speed of the vehicle the minimum length is given as 60 meter. So here it is a maximum grade change is a 0.5 percent. So the grade change is you have to take the algebraic difference of plus a1 and minus a2. So if I take these gradients the algebraic sum is 0.5. So taking that value you can observe as a deviation angle is going reduces the length of the curve is increasing. Another table given by the codal provision here we can while we designing the horizontal curves. You can keep this table as readymade table for what side distance you are designing. If you are going with the stopping side distance and 100 kph you can directly calculate the what is the length of the curve that is 73.6 multiplied by the a. So how to calculate the a is nothing but your deviation angle only. So if I take the algebraic difference of this one this so that becomes a put the a value multiplied by the 73.6. So that gives you a length of the curve for stopping side distance. So suppose if you are going for overtaking side distance so I told you the length of the curve will be still higher compared to the stopping side distance. So higher safety is in the overtaking side distance. So this case one example is given if I take 0.6 percent and length of the curve is 73.6 into a that gives you 191.36. So whenever you are designing the vertical alignment keep this table readymade table with you so that you can cross check whether you are designing as per the codal provisions or you are keeping the minimum length as per the codal provisions. These are the references I have used for representing this presentation. Thank you.


Hello everyone. Welcome to this webinar on using qualitative data in your postgraduate research. My name is Maureen Haker. I teach at the University of Suffolk in childhood studies. And I also have made and continue to make teaching resources for the UK data service. As the name would suggest, we're going to look at some of those resources that are supplied by the UK data service and specifically those that deal with qualitative data. This is an introductory webinar, so we assume that you have little prior knowledge of the UK data service and all of the delights that are held within for budding qualitative researchers. First thing I want to do is check that everyone can hear us. So if you could please let us know. There should be a poll that should show up on your screen. Just let us know that you can hear everything okay. It looks like everyone can hear us. We didn't have a complete response from everyone, so I assume that there's nothing gone wrong on our side in terms of the audio. If you do have difficulties at any point during this webinar, just check the usual technical bits. So check your volume. Make sure that your speaker headset is still plugged in. Also, it's possible to dial in on the phone. We'll be providing the PowerPoint at a later point in time through our website, so you can at least listen in and then capture the PowerPoint later. So let's go ahead and get underway. Here's an overview of what we're going to cover today. I want to say just a little bit about the broader picture of the UK data service, so you know where the qualitative and mixed data fit within that larger picture. I'll then do a very light touch showing how to find and access data, and particularly the qualitative data. I'll also cover student resources which are available to you through the UK data service website. And then I'll close with a case study looking at how one PhD student, or at least she was at the time, reused data within her research. Do be aware we've got webinars and lots of materials that go into much further details on the things like finding and accessing data. This is just a quick overview. I found that people want some information on that even when the primary topic is to cover student resources. So what is the UK data service? We're a comprehensive resource funded by the ESRC. The main job is to be a single point of access to a wide range of secondary social science data. The main purpose then is the collection, ingest and processing of data and further dissemination of that data for people to use. In addition to that data infrastructure core, we also have a service layer which provides extensive support, training, and guidance. Who is it for? Well, we like to think it's for anyone who has an interest in data. Traditionally, our main audience and the people who probably both deposit and use our data the most tend to be academic researchers and students. A lot of other groups are well represented, including government analysts, charities, foundations, businesses, research centers, think tanks. All give us and use our data. Given the importance of data, how it's used, how it's disseminated, we're trying to reach out and support a wide range of communities. Last year, New Front Page was released to the website, which some of you may have already seen. This is just the top half of that page to give you a flavor of what's done. The link to the main page is below that, and I'll show you a bit more of this page and where to find things specific to qualitative and mixed data a little bit later. What kind of data do we hold? A little bit of everything. This session is specifically about some of the qualitative data, but just so you know, the majority of the data, at least judging by the number of collections, is quantitative data. We hold over 6,000 collections, of which 5,000 of them are quantitative collections, and we hold a wide variety of that data. So there's survey data, both cross-sectional and longitudinal, aggregate statistics, domestic and international macro data on the census, so aggregate for 71 to 2011, and micro data for those select years listed here. But I'll focus on qualitative data and related resources. Where does it come from? Well, again, that varies depending on the data type. And some of these sources you see here, including agencies and statistical time series, those clearly are the main sources for quantitative data. Most of our qualitative and mixed data comes through individual academics, through their research grants, often funded by the ESRC, but not exclusively. We certainly take in data by other funders, including the Wellcome Trust in Leverholm and others, and also independently funded work. And also, of course, for some of the qualitative, originally paper-based materials, we hold public records and historical sources, including things like the census. So where you want to have a way of finding some key qualitative data through our website, there is a couple paths to it. So on our home page, there's a box which outlines different types of data, and one of those main areas is qualitative and mixed. If you click on that link, you'll be taken to the page on the left here, which is the key data for qualitative and mixed. If you come to the website through a different way and don't arrive at the home page, you can also get to this page through the main menu at the top. You can see here about us, get data, use data, manage data, and so on. So you would just click use data, and then in the left-hand menu, click on key data. And this is just a collection of about 10 qualitative and mixed-method data sets of things that we know are very well used and we know are very high-quality, easily accessible, and a fairly good introduction to the range of data. That's how that be archived. You can also search using Discover, which you can see on the right-hand side here. Discover works a bit like Google. You simply type in a search term, and the catalog will search through the collection abstracts looking for that word. The screen on the right is what it looks like when you conduct a search using the term food. So let's just take a closer look at this. And you can see here I've entered in to Discover, and you know you're in Discover because of the blue dot on the left there. I've entered in food, and I've circled on the left some of the search criteria that I've also ticked off. So I've said that I only want data collections, and specifically qualitative and mixed-method data. Now importantly, you also have to hit the refine button in order for that filter to take effect. It won't happen automatically. So if you find that your search results aren't coming out, maybe the way that you think they should, make sure you're hitting refine. And again, down here you can see where the data type is entered. As you can see, we've got about 58 collections, and somewhere in those catalog entries there will be food as a keyword. This could be in the abstract, in the title, keywords, subjects, anywhere that food might show up. So you can see a couple examples here, managing food chain risks, changing around food experience, impact of reduced contact with food and the social engagement and well-being of older women. There's other types of filters that are not shown here on the left if you want to be more specific about the kind of data that's returned. There is a whole separate webinar and guides available if you need further information on using Discover. Now that you know how to find data, I'll talk just a little bit about accessing data. Data are freely available to anyone who registers with us. Now we do have material that is held under different licenses. So for example, we hold an open data license, which is freely accessible to anyone. We also have safeguarded data, which will require you to register. And we also hold data under more restricted conditions. Any conditions for a dataset will be listed on the catalog record, but basically if you're using the data for a noncommercial purpose, the data are free to use once you register with us. Data is available in multiple formats. For qualitative data, that's usually some sort of text-based word-processing document. So it could be an RTF or a Word document. We also hold some that are PDFs. We've got very few outputs of qualitative software packages like Envivo or Atlas TI. We also hold some images, audio, and some video as well. There's not huge collections of the audio and video, but increasingly those are accepted. So if you're at a UK university, you would use your own username and password to get in. If you're not, so for example, if you're a student at a university outside the UK who's joining us for this webinar, you'll need to make an application and assuming you meet the criteria and agree to the terms and conditions, which I'll say just a little bit about on the next slide, you can then be issued a UK data service specific username and password, which you can then use to access the data. So the end user license. It would probably take me longer to read through this slide than to explain registration than it would to actually just do the registration. The only thing I'm going to point out is that when you go through the registration, you accept the terms and conditions of the end user license. The end user license is a legal document, and it's about as exciting as any legal document, but I just want to stress two points from it. If you sign up to use the data from the UK data service, you are not to disclose the identity of participants, even if you should discover who they are. In most cases, you'll probably not be able to uncover the identities of the participants because data is almost always anonymized. But if you should, you're not permitted to disclose identities. And secondly, you can't share the data. And that means with anyone, whether it's your supervisors, fellow students, someone you're collaborating with, anybody. We have lots of resources available for students and researchers, and they can always register separately and download that data. So in summary, don't disclose identities or share the data. Those are the two things to remember about the end user license. Downloading data. Again, there's a great short video which walks you through the process. You pick your data. You have to write a short description on what you plan to do with the data, but it's a bit like online shopping. You just add data to your order and then fill out the screens as they appear, and then you'll be able to download it. Now that you know how to find and access the data, you now need to know what can you actually do with it. There's many ways that you can reuse qualitative data. And you can quite simply, for example, just give a description of something. So perhaps of a particular social and historical point in time. Why is this useful? Well, because you can see more of the data than just what publications reveal. You might not be able to see all of the data depending on what's available in the archive, but you can certainly see more than what was published by the original investigators. And this is useful because you won't be limited to just what the researchers thought was salient for their research questions and topics. You can explore it further and see what else might be of interest to answer your questions. You could also consider, for example, doing a literature review, but inputting a bit of data or original sources into that. Another way to reuse data is to consider analyzing the methods used and look at lessons that might be gleaned about the most effective ways of, for example, sampling or specific data collection methods, or even just developing topic guides. One thing that's especially valuable is to look at how an interview was laid out before the interview was conducted. That is, what questions did interviewers think they were going to ask? And then look at what was actually talked about in the interviews. There can be many reasons why certain questions are or are not asked in interviews. Some interview schedules are designed to be more flexible, and sometimes tangents just come up and you want to interrogate those further. In any case, it's an important researcher skill to have that intuition to know what to do, and you can't really see that unless you start comparing interview schedules with actual interview transcripts. Another type of reuse is called reanalysis, which looks at the wide range of approaches you can take in the analysis of a data set. It usually means asking some kind of question that's different from what the original researchers were trying to do. So, for example, Clive Seal and Charteris Black did a study that used comparative keyword analysis of illness narratives. The original illness narratives had been looked at exclusively for health research, so they were specifically looking at how to diagnose certain illnesses and the symptoms that accompany these. When Seal and Charteris Black came along to do the comparative keyword analysis, they were much more interested in analyzing the discussions between doctors and patients rather than the actual health issues that came up in the interviews. So, the question can be very different in that kind of way. Or sometimes, the question can be on a similar topic to the original research but have a slightly different focus. So, for example, Joanna Bornat looked at gerontology and found two different data sets that specifically looked at gerontology, but she was interested in racism, which wasn't the focus of the original work, but that data set was rich enough to allow her to explore this theme within the existing data. You can also do a re-study, and this is where you would take the methods and the original study and replicate it as closely as possible. So, Graham Crowe and Dawn Lyon did this with Ray Paul's collection, School Leaver Study. In the late 1970s, Ray Paul collected essays from students who were asked to imagine that they were nearing the end of their life and something made them think back to the time that they left school. They then wrote an imaginary account of their lives from that point forward. Crowe and Lyon replicated the methods in 2009, right down to the very place that he had collected those essays from. And, perhaps unsurprisingly, drew some really interesting comparisons between these two generations. In short, they were able to show just how much aspirations of young people had changed in 40 years, and in particular, how mass media and advances in technology and healthcare shifted expectations. So, this is a particularly useful method for comparative work. Data is also reused for teaching and learning. So, Joe Haynes is one person who does quite a bit of this. It gives students the opportunity to work with real data and also gives them some hands-on experience while working through analysis of data and the issues that arose from methodological choices. We have a number of teaching data sets available if you're interested in just practicing with real data. And this segues me into the next section of this webinar, which looks at some of those student resources. We're developing, and still are developing, teaching resources, which helps students build research skills and knowledge about specific social science topics. If you go to the Use Data tab, again, along the top menu there, and in the left-hand menu, Click Teaching Resources, you'll see this page. There's a variety of resources, including ones that utilize quantitative data and qualitative data. This is also where you can access our teaching data sets that I mentioned just a few minutes ago. And as we're interested in just qualitative resources, I've clicked this tab, and you can see just the first couple of hits that come up when you click under Qualitative Resources. These resources form a variety of purposes, which you can see listed here. Some are resources which looks at specific collections that were highly influential. Others look at particular research methods or a specific methodological issue. And finally, we have some that are thematic guides. So the resources that are built to look at a specific collection, such as the resource you see here. This one's focused on Cohen's Mods and Rockers, which explores one of Cohen's key ideas of moral panic. The resource allows you to explore the method of data collection, as well as the key themes and findings from the original study. If there's related resources, those are included. And of course, there's a bit of data for you to look at. So if you're looking for a resource that helps you understand some key social science idea, then this sort of resource might be useful. In addition to the Mods and Rockers, we also have teaching resources on Peter Townsend's work on institutional care for elderly and Paul Thompson's Pioneers of Qualitative Research, which explores key contributions to qualitative research methods over the past 60 years. Some of the resources also explore particular research methods. So for example, we have a resource on interviewing, which allows you to analyze and consider selected interview excerpts and how they, for example, set up the interview, pose questions in particular ways, build rapport with an interviewee. We've selected excerpts, which we think are very good examples of these skills. For example, you can see here the difference between an unstructured interview on the left and a structured interview on the right. And just, you know, just basically looking at some of these examples can really help you demonstrate how to respond within interviews and how you might compose your own interview. In addition to interviewing, we also have resources on non-interview methods. Which includes ones like this page on visual methods. And we also have some other research methods building skills like sampling. While these are quite practical resources, we also have some that focus on more abstract skills, like linking theory and research methods. So this resource looks at using a psychosocial approach. And it starts off with giving you an overview of what psychoanalysis is. Then it presents two different data collections, which are informed by psychosocial theories. As part of the explorations, we've assembled documents on methodology, examples from the data, and of course some guiding questions to help you examine how the theory has informed the research design, the interview schedule, and the analysis strategies. We've also provided some insights under the tab, Tudor Resource, which will indicate some of those possible answers for you. Finally, the last resource is the thematic guides. These guides, they collate collections and other resources, which can help you examine commonly researched themes. Some of these thematic guides have tips for analyzing data related to that theme, as well as key collections which address the theme. If you know what you want to study, it may be useful to explore the thematic guide for this to see if there's any considerations you should make before your own inquiry. Now that you know how to find and access data, as well as other resources which might help you to refine your research skills, I'll tell you about April Galway, who is a PhD candidate, and reused data as part of her research. She was particularly interested in accounts from single mothers from the post-war period, 1945 to 1990. She found that personal narratives were missing from the existing literature, and thus she sought to collect oral history from single mothers during this time period. However, she ran into a bit of a problem. She was finding recruiting participants who could speak about the decades immediately following World War II, so specifically the 1950s and 1960s, very difficult. So as one can imagine, the high degree of sensitivity around the topic of unmarried or divorced women in this time period made primary data collection particularly challenging. This is when she decided to turn to the archives. Initially, she had to scour several different archives, including the Imperial War Museum and the Museum of London, but she only had limited success. She was then attending a training session at the British Library, and one of the archivists spoke about a specific interview with Anne Hoad, a divorcee whose oral history was held in the Millennium Memory Bank collection. After a bit more discussion with one of the archivists about her project and this collection, she learned that the collection from which Anne Hoad's stories was drawn from was one of more than 6,000 oral history collected over the decades that she was specifically looking at. And this was all part of the wider BBC project. What was even more promising, however, was that many of these narratives fit the criteria of her project. So specifically, they were single mothers during the post-war period. Once she had found the right collection, she was able to search through the British Library's online catalogue for relevant interviews. As part of this process, she became aware of the significance of the labels given to single mothers during this time period. For example, she writes that an unmarried mother and a single mother indicate completely different sorts of identity. And this was a point that she was able to build upon within her research project. Thus, even the process of sorting through and identifying the interviews helped yield an important analysis point for her thesis. The next stage of her project was to listen through all of the interviews that she identified. While she was not conducting her own interviews, at the same time she quickly became attuned to what was good practice and what sorts of things should be avoided. She writes about how she developed a close relationship with the narrator and could start to identify some of the humor that interviewees drew upon as a collective to discuss motherhood. Although she relied upon existing data, she was still able to glean important methodological skills and, again, points for discussion within her PhD project. Finally, she writes about how initially she was met with surprise when she said that she reused data over conducting her own interviews. There is a debate within the literature on secondary analysis that has been around for some time. In short, some argue that secondary analysis misses out on some of the tacit knowledge that's gained from actually conducting interviews firsthand. While you have the interview transcripts, you may not have some of those underlying understandings about how the interview went, where interviews might have held back, and where an interview started to go a bit sideways. More importantly, however, she was able to identify how these interviews were fundamentally rooted within the political climate of the time. Through her analysis, she was able to pull out some of those threads about generational dynamics, gender, and ethnicity, which was a slightly different angle from the primary purpose of collecting these interviews, so that distance from the initial data collection actually helped to add a layer to her analysis of the interview transcripts. It's worth noting that although April Galway solely used the archive data for her project, you can also supplement your research with archive data, as has been done in other cases. You can also mix and match data from a variety of collections to curate your own data set. April Galway writes that she was, again, often met with surprise when she said she reused data, but has sort of discovered over time that one of the key arguments in the debate on reusing data is that data is being actively constructed at all times, and secondary analysis is just another layer to that construction. So she writes that data is an ongoing creative project that goes beyond just the recorded interview. Before I leave you, I want to highlight one more tool that we have for students and for anyone, really, who uses the UK Data Service. And it's a relatively new tool that has specific uses for qualitative researchers. And this is QualiBank, an online resource which allows you to search, browse, and cite qualitative materials. You can get to it by clicking on QualiBank, which is in the left-hand menu when you go to Discover. It's just two down from Discover. And I'll save this for last, because I think there's a few aspects to this tool, which in some ways perhaps responds to some of the challenges and benefits that April Galway found when she was reusing data. So the tool itself works the same way as Discover, where you just type in a keyword, and you can see I've quickly tried to type in typhoid. And again, like Discover, you can see I've got 20 results that have come up. You can further refine some of these search results by using the filters on the right-hand menu, sorry, the left-hand menu. What's different about how QualiBank searches, though, is that it's actually searching through the data itself. So if you're looking for qualitative data that specifically has certain words or concepts in it, you can use QualiBank to search through the data rather than having to download it and then search through all of those transcripts yourself. Right now, QualiBank has about 25 or 30 collections uploaded into its database. However, this is going to be quickly expanding over the coming months. From these search results further down, I chose to look specifically at an interview with Mrs. Omason. And when you click on one of those search results, you can see the interview transcript is laid out and you've got some metadata right at the top of that interview transcript. What's also nice about QualiBank is that it links to external resources and related collection documentation, which you can see circled here at the top. And if you click on those, you'll be brought down to the bottom of the page after the transcript finishes. And you can see that there's a variety of resources related to this particular interview, including an audio extract, a book extract on the awardee and images that are related to the collection and metadata about the participant. So this is a really useful tool to help you contextualize the data that you're looking at. Finally, there's also the capacity to cite. So let's say that you were looking at the interview transcript from Mrs. Omason, and you actually just wanted to highlight something that she said specifically. You would click on the Create Citation button in the left-hand margin. Highlight the bit that you're interested in, and then that button will turn into a Retreat Citation button. When you hit Retreat Citation, you'll get this pop-up, which is a citation with a persistent identifier of that specific quotation. So at the end of this citation, you can see that there's a URL. If you were to click on that URL, it would bring you to the specific paragraph within that transcript. You know, this just helps add a layer of transparency to your research by allowing you to cite from the data. And it also gives you that further context of what you're looking at. And again, you have easy access then to some of those related documents. Qualibank is a fairly new feature to the UK Data Service, so it's something we're still expanding on and we're still working on materials to help you use it effectively. If you have any queries about it, please feel free to get in touch. That's about it for me. If you do have questions, feel free to type these into the chat box and I'll see if I can get you an answer. We've also got tons of advice for new users and FAQs, all of which expand on what I've covered here. Finally, we also have the UK Data Service Student Forum on Facebook. This forum provides peer-to-peer support for students who are looking at reusing data in their research. Joining the UK Data Service Student Forum is pretty easy. You simply click on the link on the Student Resources page, sign in using your Facebook account, and if you don't have a Facebook account, you can create one, and then just ask to join the forum. We strongly encourage students to join the forum and ask questions or queries that they might have with regards to data analysis. Or if you prefer, you can, of course, get in touch with us via email through any of our social media accounts or you can fill out a form on the website. If you do have any questions, immediately just go ahead and type them in and we'll get to as many as we can. Okay, somebody's asked about accessing this webinar later. So if you go to our homepage and look in the top menu, there's going to be an events page, and if you click on that, there will be a link in the left-hand menu for past events, and from there you'll be able to access the recording and the PowerPoint from this presentation. We've also had another question. Does the UK Data Service hold any recent data or is it normally two to three years old? The data comes from a variety of years, so it sort of depends on what you're looking at. We do have older data, if you're interested in historical data, but we also have researchers who, as soon as they're done with their projects, they will deposit the data that they've got as part of the agreement with their funders. So it really just depends on the topic that you're looking at. It's worth having a scroll through, discover just to see what's there. But yeah, it can come from any point in time. It just depends on how long it takes the depositors to actually put their data in with us. Somebody's asked, we must not share the data in any way. Does the website give any uses or examples of how we might safely use the data? The idea with the end-user license behind sharing the data is that you can't share the data set as a whole with somebody else. So let's say you're collaborating on a research project and that person needs access to the data as well. They need to register separately and agree to the terms and conditions. But let's say, for example, you'd like to cite some of the data in a report, whether it's something that you're submitting for your university work or whether it's something that you plan on publishing, that you're able to do. So once in a while there are some restrictions, which will be clearly laid out when you download the data, such as you can only use a maximum of 300 words from the data set within your quotations. But normally, you can just sort of quote freely as you'd like. You just can't share the whole data set with somebody. Somebody has said that what happens if your university account doesn't work for some reason. So, for example, if it's no longer active or you just go to use your university account and for some reason it's not showing up as one of the options. My first advice would be to get in touch with your IT department within your university. So sometimes universities have to adjust the settings to make sure that their institutional login works with our login system. If that doesn't seem to be working, definitely get in touch with us and let us know. We can try and see if there's something going on that we can sort out for you. But if you are at a university already, you do need to use your university login in order to access the data. The UK data service login is typically reserved for those who are not located within a university structure. So they might be, for example, at a research center or something similar like that. Somebody has asked if audio is available within Qualibank or only text. When you're searching through using Qualibank, it will only search the text. It won't search through audio. But there is some audio that is currently available. These are normally excerpts and there is an accompanying interview transcript. I think in all cases there's an accompanying interview transcript with that audio. So it will be linked under those related resources. We are looking at expanding the collection so that there is more audio that's available. Increasingly, we're getting audio perhaps with or without those transcripts. So we're looking at ways of effectively and efficiently making that available. But it's something that will be built upon within the next couple of years. So in the short term, it's mostly just text that you're going to look at within Qualibank. Somebody has asked how you can join the Student Forum in Facebook. So the UK Data Service Student Forum on Facebook is linked in on our Student Resources page. So if you go to the Use Data tab at the top of our website and then click on Student Resources, you should be able to find the UK Data Service Student Forum linked on that page. When you click it, you just sign in using your Facebook account, or perhaps your computer already has that automatically logged in. And then you just ask if you can join that forum. And again, it's a way for you to be able to communicate with others who are reusing data. And we've also got a UK Data Service staffer who moderates those conversations. So if you do have questions that come up, there's scope there for a bit of guidance as well. Again, somebody's asked if you can download the slides. Those will be available through our website. So please feel free to download those at any point. We'll be posting them within the hour. So keep your eye on the website for those. Somebody's asked about data from international sources. So I'm specifically looking at the Middle East. Whether or not we've got data that's available from international sources really just depends on the topic that you're looking at. You'll need to have a search through Discover or Quality Bank and see what comes up. There is scope in the filter on the left-hand side of Discover to be able to sort of search by particular regions. So you'll just have to see if anything from the Middle East comes up. We certainly do have some collections. I'm thinking specifically of one that looks at women refugee stories, and some of those were certainly from the Middle East. But again, that's just one example of one collection that we have, and you'll have to search through based on what you're interested in looking at and see if there's anything else from the Middle East. Somebody's asked about which disciplines our data accommodates, which is a bit of an interesting question, I think, because it depends on the kind of research question you're asking. So we've got most of our data, it caters to the social sciences, but we do have data held that might touch on other disciplines as well. So, for example, I gave the example of how Ciel and Charteris Black looked at health narratives. Again, it depends on how you want to use that data. But typically, the discipline that the data comes from are psychology, sociology, criminology, childhood studies, those sorts of social science disciplines. Somebody had asked if all of the webinars are accessible at a later time. They are, so we've got a YouTube account, and you can have a scroll through and see what other webinars are available. We've got everything from, if you're interested in more of the quantitative data, we've got webinars that focus specifically on those types of data, and we've also got further webinars that go into more detail about finding and accessing the data. Somebody's asked about training sessions available on how to do qualitative data analysis. We're specifically focused on data reuse, and as part of that, obviously, analysis factors into it. So we do have some resources on our website which sort of explore the reanalysis of data. But in terms of specifically doing qualitative data analysis, I would suggest perhaps looking at the NCRM, who host different sorts of training sessions that look specifically at analysis strategies. But it's a little bit outside our remit. You might get some crossover and see some resources for data analysis, but not specifically. Somebody's asked if you can have access to the UK data service if you're not registered at a UK school. You can, you just need to get in touch with us, and we will send you a UK data service login. So yes, in the first instance, get in touch with us. So on our registration page, there's a bit more information about how to get in touch with us, and we can link you up with a login so that you can access the data. Somebody has asked if you can get a certificate for attending this webinar to submit to the university. We don't normally provide certificates of attendance. I'm not quite sure. I don't think that there's been anyone in touch from a university who is looking for a certificate of attendance. I would suggest emailing us at help at ukdataservice.ac.uk, and we can see if we can sort you out with some sort of email to present your university. Somebody has asked if there's a way to find out about future sessions. Yes, we've got an events page, and on those events pages, future webinars, which again will go through different types of data in more detail, and also give you some examples of reuse cases, which might inspire you on developing your own research project. And beyond that, we've also got listings of some affiliated organizations who are perhaps running sessions that relate to some of the services we offer. So if there's a conference coming up, for example, on datasets that we hold, we'll put those up, or once in a while there's some training related to data reuse that we'll post on our events page as well. There's quite a bit of information there, so do check out our events page. Somebody has asked if you need to pay to register or use the UK Dataservice. This is a completely free service. Again, it's funded by the ESRC, so everything that we offer is freely available. In terms of datasets that are safeguarded in some way, you will need to register, but you don't need to pay to register. We just basically, we need you to register, so we know what you're doing with the data to ensure that it's a non-commercial use, and so on and so forth, but you won't need to pay for any part of the service. I'll stick around for a few more minutes. If there are any other questions that come up, we're solely filtering down here, I think in terms of the questions coming through, but I'm still here, so if you do have something that comes up, please feel free to type it in. Someone's asked an interesting question related to clinical research, so looking at how using qualitative data can guide or assess recruitment processes, specifically, certainly methodological advancement, I think, is a huge part of the analysis that can be done with qualitative data. So I talked a little bit about the five different ways that you can reuse data, and one of these was to look at and critique certain methods. Ross Edwards has recently done this with surveys that were conducted, and she looked specifically at marginalia that was squalled in to the side. It's called paradata, but the notes that were squalled in by interviewers on the side of survey data, and using this she was able to sort of analyze and critique the way that we formulate and pose specific survey questions. So this is certainly a way that you can reuse qualitative data in terms of actually looking at recruitment processes. Again, you'd have to have a search through and see if there's a specific data set on the topic that you're interested in, and that might be a project actually in and of itself that you reuse that data set to explore better ways of recruiting participants. And there's documentation that will be deposited alongside the data, and you can actually look at the methods that were used and what kind of participants they were able to recruit as a consequence of those methods. So again, it would just depend on the specific data that you're looking at and what specific research question you're interested in, but certainly you can reuse our data for methodological advancement. We've had a couple of comments of people who are specifically interested in mixed methods rather than strictly qualitative research. We do hold mixed methods data sets as well. So again, it's just work having a look through Discover. Unfortunately, our filter doesn't actually pull out mixed methods from qualitative. It will be lumped together, but by looking at the abstract, you'll see on those catalog pages right away whether it's a mixed method study that's got a bit of quantitative data and qualitative data or if it's just a qualitative study. Okay, I think the questions have more or less dried up. If you do have a question that comes up, please feel free to email us. Again, it's help at ukdataservice.ac.uk. You can also fill out a query form through our website. Yeah, so hopefully this has inspired you a bit to think about how you can reuse qualitative data within your research projects or just to see what sorts of resources are available to you through our service. Thank you for listening, and we hope to hear from you soon.