Ranger, Warrior of the Woodland! Ranger Bill, Warrior of the Woodland, struggling against extreme odds, traveling dangerous trails, showing rare courage in the face of disaster, in the air, on horseback, or in a screaming squad cover. Ranger Bill is mind alert, already smile, unswerving, loyal to his mission, and all this in exchange for the satisfaction and pride of a job well done.  Hi there, boys and girls. You know, those rangers of mine are the finest men on the face of the earth, except when they get a wild notion in their heads. But then, on the other hand, that's what makes people human. Well, it wasn't too long ago that I was ready to flip my lid as the saying goes, because my rangers were acting stubborn, ornery, and cantankerous. And not only did my men act up, say, I almost forgot, we'd better put a handle on this story, huh? Let's see, what'll we call it, ornery to die? That wouldn't be so good. Hotheads wouldn't fit either. How about scaredy cats? Now, there is a title getting close to the truth. Stampede? Oh, that's about cattle. My men are stubborn as mule sometimes, though. You know, a good title just doesn't come to mind right now, so let's just say this story is about lover boy. One day, not too long ago, we were plagued by a sudden absence of doctors in the area. People, doctors, and animal doctors. It all started early one morning as I was walking to the office with Henry. Hey, look who's out bright and early. Looks like Doc Jones. Hi, Doc. Let's go over, Bill. Okay, Henry. Hello, Buzz. Beautiful morning, isn't it? Beautiful for anything you want to do, Doc, except stay inside. That's right. Well, fellas, this is goodbye for a while. Goodbye? What? How come? You aren't quitting us, are you? Oh, no, not at all, Henry, but I need a vacation badly. He had me worried for a minute. Where are you going? Well, that's top secret, but it's far away, believe you me. Far away and no way to reach me. That's the way to do it, Doc. The only way, sometimes, is how long since you took a real vacation. Five years? That long. You really need a rest. Don't I know it? Well, I gotta buzz along. Hold everything and everybody together until I get back. We will. Say, what'll we do if we need a doctor? All there's one coming today to fill in while I'm gone. That's fine. Have a good rest, lots of fun. And how? Bye. He sure is a nice fellow and a good doctor. I'm glad to see him get away for the rest he needs. Right. I wonder who the new doctor is. Whoever he is, he'll have tough shoes to fill, trying to keep up with Doc Jones. Your attention, please. Flight 11 is now loading at gate 2. Passengers to Chicago, Omaha, Junction City and San Francisco, please board your plane. It's going to be a long two months, Matt. Not any longer for you, but it'll be for me, dear. I still don't understand why you're going all the way to knotty pine. Can't you get good medical experience here? Yes, I don't doubt that I could. But remember, my husband, to be that you're going to be tied up on special research for the same two months. Bad chance I have a thing very much of you. That's true. I won't have the three time I'd like for two months. But how about those good-looking He-Man Rangers out there Dr. Jones was talking about? Oh, my dear. I believe you're jealous. Who wouldn't be? It's not every day those fellas have a beautiful woman doctor to sew up their busted heads. Don't you worry a minute. I guess I'd better go now. Please, dear, don't forget to ride an orphan. I'll ride an orphan. That's a solemn promise. I've heard that song before, honey. Sometimes I wonder who you love most. Me or your precious microbes. Don't forget the one you love, Doctor. Not for one minute. Or me and my microbes will be on the next plane going west. Goodbye. Have a nice time. Goodbye, Dave. I'll miss you terribly. Why, Doctor, your emotions are showing.  Bye, bye, dear. Goodbye. Look out for those rugged, good-looking Rangers. A wire for you. Oh, thanks, pal. Sure it's your business, Demby. The new doctor wants me to meet him at Junction City Airport. Doc Jones told him to contact me and I'd see that he'd get squared away. Airport? How far is this doctor coming from, anyway? New York City. New York City? That's right, Gray Wolf. Maybe the new doctor is a friend. Yeah, probably so. I'd better call Marie and tell her the new doctor's on the way. She'll probably want to dust up the office. What's so funny? I'll tell you. That's pretty good old-timer. Yeah, real cute. I'd better call Marie and tell her to look under the desk and see how much dust is collected. Are you sure the doctor was on this flight? That's what the wire said, Henry. It's possible there's a mistake in the wire, but I rather doubt it. Paging Mr. William Jefferson, please come to the information desk and meet Dr. Benson. That's Mr. William Jefferson. Hey, that's us. I don't see a man waiting there. Just a woman. Hey, I never thought about that. What? A woman doctor. A woman doctor out here? Looks like it, Henry. Let's go meet her, huh? What a sharp-looking dish. Henry Scott, watch your remarks. Okay, so I'll change. Wow, what a beautiful woman. Dr. Benson? Mr. Jefferson, I'm Dr. Benson. Just call me Madge. How do you do, Madge? Welcome to the West. I prefer Bill to Mr. myself. All right. Henry, close your mouth. Yes, sir. This gaping young man is Henry Scott. How do you do, Henry? How, how, how? Is he party Indian? Oh, did I say the wrong thing? I don't think so. Henry's not even a little bit Indian.  You know what I mean. Oh, I'm, I'm sorry I spoke out of turn.  Let's take the ladies' bags to the car, pal, and start for naughty pie. Henry Scott. Oh, yeah, you take the bags. I'll take the lady to the car. Henry, I'm, I'm sure you'll find I'm not a freak. It's happening quite frequently now that a woman becomes a doctor. Yes, sir. Shall we go to the car? Henry, you pick up two of the doctor's bags and carry them and I'll take the other three, and I'm quite sure she can make it to the car under her own power. I'll take the bag, sure. Just a minute. Oh, my. He fell right over that suitcase. Are you hurt? Me? No, I'm all right. Bill, I'll escort Henry to the car. I think you'd better, if you don't mind, a porter or a porter. You called, sir? Yes, help me to the car with these bags, please. Yes, sir. Excuse me, sir. Yes? If that young fella is sick, we can get a wheelchair so we won't fall again. Well, thank you, but he won't fall again. Well, how can you be so sure? Because he's fallen just about as hard as he can already. Batch? Yes, Henry? How long do you have to study to get your degree? Seven years. That isn't long. Well, then there's internship and postgraduate work. Uh-huh. Do you think our fella should always be older than the girl? To what are you referring? Well, when a fella and girl get married, you know, just anybody. Does it make much difference if the girl's older than the fella? Well, I think it all depends on the fella and girl involved. Um, how do you like our beautiful country out here, Madge? Oh, I like it very much. It's really beautiful. I'd like to see more of it in my spare time. I'll be glad to show you're on the country, Madge. Very glad. Thank you, Henry. I'm afraid, Dr. Benson, that you're going to have your hands full. Hmm. I believe you're right. How are you, um, doctoring heart trouble, huh? Oh, I think I can affect a cure. It'll have to be a long treatment, so it's not to be brutal. It's for today. How about you, pal? Oh, me? I'm not tired. What? After riding horseback all day and checking 14 fire lanes and taking inventory of eight fire equipment caches, you're not tired? Nope. Not at all. Hmm. Well, I'd better shake a leg. With Madge? I canceled my date with Murray Lou. Madge? What for? You questioned me about my dates. Oh, um, now you're right, Henry. I'm sorry. I'm taking Madge riding this evening. What's good about it? Hmm? Well, I don't understand. Why isn't it a good evening, young lady? I know why Henry broke our date. Well, Dr. Benson, come on up. Join the party. Good evening. I thought Henry was taking you riding this evening, man. Oh, I didn't think it'd be wise. I have to make a call, so I stopped by on the way. Oh, I see. Madge, this is Mary Lou Thompson. Mary Lou, Dr. Madge Benson. Oh, you are very beautiful. Oh, thank you, Mary Lou.  Well, um, now that the mutual admiration is finished, I suggest we discuss our mutual friend, who currently is suffering from palpitations of the ticker upon meeting one, Dr. Benson. Bill, I hope you don't think I'm being cruel, but I... On the contrary, Madge. But I'm afraid you might find Henry a very persistent young man.  Mary Lou is left out in the cold. That's true, and one more thing. After I'm gone, he'll go back to Mary Lou, or try to, which will only create another problem for both of them. Boy, I'll say it will, because I don't like playing second fiddle. Well, practice a quick way to bring Henry back to earth without doing any damage. I hope so, Madge. Do you have an idea? Oh, yes, I have an idea. You see, it's not very polite for me to announce that I'm already engaged to be married. You're not wearing a ring. My fiance is also a doctor, and he needed the money for a microscope because of his research work. The ring can come later. But my mother has a ring, and I know she'll end it to me. Perhaps that'll be the way to settle matters. It should arrive in several days if I phone her this evening. But what if he doesn't give up? What if he's really in love with you? Henry's infatuated, but not in love with me. Oh, I hope you're right. I know I'm right. You just be patient now and try to help Henry all you can. That'll be helping yourself at the same time. Is she right, Bill? Yes, I'm sure she is, Mary Lou. But, on the other hand, I'm not a woman, so I can't be an authority on these things. This is rugged a place for a woman, doctor. Maybe Doc Jones lost his marbles when he asked her to come here. Let's not pick it on Madge. I mean, Dr. Benson. You have a tummy ache? Billy Goat, your heart will go fumble, fumble, fumble. You're mad, Benson. Henry, not kidding. That's for sure. Bill, you've got me frightened to death to meet your rangers. I didn't mean to, Madge, but I want you to be prepared for the worst. Those men of mine are the finest rangers in the world, but they're also the biggest rascals. And, T, you should know the half of me. Oh, my. It's really not that bad. I just want to alert you so you don't get embarrassed, and so... And watch the old timer. He's a first-class disliker of all female women in a man's domain. I've always said so. They're watching from the office window right now. I wonder what the old timer is thinking up to initiate you. Well, it looks like I'm going to have my hands full. I'll say you are. First, you've got Henry and his crush on you to worry about. And now, all these other men. I feel sorry for you. Bill, this sounds like fun. Is Henry fun, too? Oh, no. Oh, sir. Henry gets my most considerate care to affect a cure. But those other wild and wooly ranges of yours are going to get the business. Medically speaking, that is. I feel well at all. I'm sorry to hear that, Henry. What bothers you? I don't know. I just kind of feel down in the dumps, you know. Not too good all over. Sit down, please. Sure. I want to take your blood pressure and pulse. Anything you want to do is fine with me. Now, just roll still. Sure. Now, let's see. Say, when are we going writing? Shhh. I can't hear when you're talking. Blood pressure's normal. When are we going writing, Madge? Now, your pulse, and please be quiet. Okay, but you still haven't answered my question. Pulse normal? I still feel sick. Open your mouth. Okay. Where are we going lying? Hmm. You have a nasty throat, young man. It's red all over. No horseback writing for you. Huh? I think I'll need some of this. Stuff looks awful. And a little of this. Give that stuff to a horse. And here's for good luck. Who's that stuff for? You. Me. I'm not taking that junk. It's because it looks awful.  Take it. Who did he kill me? He's not poisoned. Prove it. You still haven't asked. Take these pills. I can't swallow those horse pills. Why even an alligator to have to gulp twice to get them down. Take them? Madge. Only because you asked me to. See, I have a horse.  Now drink this down. I have to. Drink it. Who's the doctor here anyway? Okay. Listen. This kills me.  What? That ain't the name of God. What's that? Castor oil. Castor oil? Woman, you're crazy. You're not going to doctor me anymore. You look as though you forgot something. Yeah. When are we going riding? Oh, I don't really know, Henry. I'm terribly bushed and I've got some house calls to make. Yeah, you love about this weekend. Well, I don't think seriously about squeezing some free time for a ride. Now, that's a promise. Yahoo! Horse pills. Castor oil. But otherwise, wow, what a dish. Henry Scott. Bye-bye. I wonder if I'll last for two months. Nice to see you again. Thank you. It's nice to see you. You look so nice in that western outfit. Thanks. Manage, what about Henry? Well, I'll tell you Mary Lou, I'm still waiting for the package to come. It's taken off a long time to get here. Well, your mother probably insured it and it takes longer because the records would have to be made of it as it travels this way. You're right. You know, I never thought of that. But please be patient, dear. Everything will work out fine for both you and Henry. I hope so. And remember this. I'm on your side. What's the matter with your foot, old timer? Yeah, I did a grizzly step on it. Oh, boy, I stepped on it. I could almost believe it. That's really the matter, old timer. Don't nail no doubt. You asked for the bill, isn't that right? You said it, Gray. Well, bye, ask for it. Well, let's go see Dr. Benson.  You're hardly able to walk. You sure must be doing a good job of making it worse. Are you going to the doctor? I'm asking you once more and then I'm going to carry you over myself. Open the door. The old timer is going to the doctor.  Won't have nothing to hang my shotgun. Stumpy. Stumpy, if you don't stop clowning, I'll let the anesthetic wear off. I'll be finished in a jiffy. That is if you'll be quiet. Then all I have left to do is to bandage it up. Timer, I'm warning you for the last... What's that diamond doing on your left ring? What do you mean, Henry? What's it doing there? Why, you know as well as I do. You're engaged? Well, of course. Say it's when? Well, Henry, I was engaged before I came out here. What's the matter? Are you ashamed of it? Why didn't you wear the ring when you got off the plane? Well, I... Oh, Henry, I'm sorry you're hurt, but really, you haven't any reason to be. What do you want? Henry, please don't be embarrassed. I know all about it, and I understand. Ah, nuts. Henry, her fiancé couldn't afford a ring because he needed a microscope.  That's it. The ring is far. She sent for her mother's ring. I think she's pretty wonderful, Henry. She tried not to hurt you. That's right, Henry. You'll have to admit that I've done nothing to encourage you. You're right, Manj. Absolutely right. I guess I got sore because, well, I wanted to tell you that I knew we could never make a go of it. I knew it was infatuation, but, well, I was getting over it. Thanks, both of you. Now, I will go riding with you on Saturday. That is with you and Mary Lou. That's a date. Isn't it, Mary Lou? Oh, yes. I'll say it is. Hey, what about me? Who's going to watch after me now that I'm all bandaged up around the foot? I'll get you a crutch, Stumpy. A crutch? How good would come of a female? They just... Well, you see what I mean. You just can't convince the old timer that Dr. Benson fixed up his ingrown toenail real fine. Well, see you next week for more adventure with... Ranger Bill comes to you transcribed from the Moody Bible Institute in Chicago.


Here we will go over a very simple refinery flow. This is a much simpler scheme than we have included in lesson one, different types of refinery processes, separation, finishing, conversion and support. Here what we would like to do is to connect crude oil feed to these major refinery products starting with LPG, the lightest, gasoline, jet fuel, fuel oil, asphalt and coke. One point to make, look at the number of arrows that go to gasoline which really shows the significance of this product as the major product in U.S. refineries, the gasoline. Quite a few different processes just produce gasoline. Of course jet fuel and diesel also are important refinery products. So let's look at the processes that we can use to connect the crude oil to these major products. Here again crude oil goes through desalting and distillation and through the light ends unit separations we produce the first product LPG or liquefied petroleum gas that is essentially propane and butane. The light state run after coming from the light ends unit go through blending to the gasoline pool and from the atmospheric distillation unit, kerosene and light gas oil go through hydro treatment to produce jet fuel and diesel. So you can see here that using just separation and finishing processes we could produce LPG, straight run gasoline which would be low octane number and jet fuel and diesel without any conversion process. We bring in two additional separation processes, de-waxing and de-ass vaulting. You would remember de-waxing would produce lubricating oil based stock and the wax as byproduct and de-ass vaulting, treating the vacuum distillation would separate out asphalt and produce de-ass vaulted oil for further conversion. So we have pretty much exhausted our separation processes. You can see there are still quite a few arrows pointing nowhere so we need to go to our conversion processes to connect to our final products. Here are our conversion processes in color purple starting from the left hydro cracking treats the heavy vacuum gas oil to make additional jet fuel and diesel. Whisk breaking takes the VDR from the vacuum distillation process and produces fuel oil. Moving to the right catalytic cracking takes the feed from the distillation unit could be a light gas oil or heavy gas oil to produce gasoline. This is the major gasoline production path and the byproducts from cat cracking goes through alkylation to make additional gasoline, high octane number gasoline and the heavy NAFTA, straight heavy NAFTA coming from the light ends unit through hydro treatment goes through reforming to make another high octane gasoline stream. And finally the VDR from the vacuum distillation could go through coking to make additional gasoline as well as the byproduct coke. Finally we will use the two major supporting processes hydrogen production and sulfur recovery to connect all the arrows. You know that hydrogen is used to remove sulfur and the crude oil fractions as hydrogen sulfide and hydrogen sulfide is converted to elemental sulfur in the sulfur recovery unit and elemental sulfur is sold as a refinery product. So that completes our simple refinery flow.


All right, thanks for staying with us. Now, building skills that transcend geographical location has become increasingly crucial in our interconnected world by focusing on communication, digital literacy, adaptability, problem solving, and continuous learning. Individuals can position themselves to thrive in various settings and seize opportunities beyond physical boundaries. So today we're asking, how can we build skills irrespective of our geographical location? That's the conversation for today. Now, please let's hear what you have to say. Remember, you can join the conversation, send us an SMS or WhatsApp to<PHONE_NUMBER>. You can also tweet at us at WeishuaFQ on UTI in a minute. Do you have any skill that you have learned like that can, that you can literally sit in Nigeria and work from anywhere in the world? Or work with any company in the world around the world? Well, I think the work that I do in customer experience can really be done anywhere in the world because it's a strategic role. So I think that can be done anywhere in the world off the top of my head. I mean, if we're talking about the more technical side of the skills, I don't think that I have anything, but if I take my superpowers in the realm of organization, communication, the ability to touch type, all of this kind of things, I probably would be able to be an excellent virtual assistant. But yeah, I'm not a techie. I'm not playing in tech space. Actually, it would be nice for us to hear from the guests what kind of opportunities would be there. A bit, no problem. I mean, the only reason why I'm sitting in this chair today is because I haven't learned how to earn dollars. Right? Right from my seat here in Nigeria. Because there's no better place to earn. That's why I like to earn. In dollars, yeah. I like to earn in forex. I need anyone as long as it's for currency. So Chuka has a career spanning almost two decades as a tech entrepreneur, software architect, engineer, speaker, and author. It has led medium to large-sized teams and delivered multi-sized software engineering projects for different industries across Africa, North America, Europe, and he is the founder of Studiopedia, a production company leveraging technology to help educators and creatives, rather produce and distribute digital contents globally. He's also the founder of Interstellar Labs, a company that builds developers' experiences using blockchain technology, and he's also the author of Newbie to Techie. He is an angel investor in tech, one of 35 Google developer experts from Africa and a mentor in the Google for Startups program. And he's joined us live from somewhere around the world. I'm not sure where now. Thank you so much, Chuka, for joining us this evening. It's my pleasure to be here. Okay, so this conversation around tech, you see, Uti is very, my ears are very like, like we're standing because I really want to understand because I, okay, so on Wednesday, we had a guest that was talking about how they are using AI to influence learning in Nigeria and already Lagos state and Borno state governments have adapted those solutions in the classrooms. So now students can go up in the cloud and they can do a lot of things. And with the advent of 5G, for instance, they can then start to think of bringing, for if we have Uti, she's the best communications teacher in the world. We can just teleport Uti to all the classrooms across Nigeria, she doesn't have to go anywhere. So I mean, there was a fear about teachers losing their jobs and all of that. I know you would address that. But really, are there really opportunities in the tech world, you know, that can truly change the narrative when it comes to economic power? Because one of the biggest problem I think we have as young people in Nigeria, we do not have skills that can earn us good income, right? So that's why a lot of things that we're so struggling with a lot of things in this country. So are there truly opportunities in the tech world that can transform our economy? Absolutely, absolutely. The opportunities are tremendous. They're very massive. I'd say this, right? Giving where technology is today and where we are going in the world. Technology is becoming the new oil or it is actually now the new oil.   Is this gonna keep evolving? So as technology is evolving, so are the people who will support it need to evolve, right? And because it's now becoming mainstream, maybe take away, if you look back in the early 1920s and the early 1850s, you do know that oil was what was the main thing, oil and transportation via rail. These are the mediums that people would then say, okay, because of those roles, people would want to grow up to either become mechanics or engineers or oil drillers, right? I remember when I was much younger, if you didn't want to be one of the five roles, then it means that you didn't have a future doctor, lawyer, engineer, you know, exactly. But the narrative has changed and it has changed because times have changed. We've gone into the tech age, when the technology era. And I think because of that, many opportunities are gonna open up. The question then is, how do you fit into these opportunities? How do you take advantage? How do you find them? And how do you take advantage of them? All right, so Uti, I'll come to you. But let me just quickly give something that I found when you talked on the platform, right? First, you said there's a global demand for tech skills. Second, you said the advent of AI will not take people's jobs. I want you to explain that. Then you said by 2025, that's very short. 2025 is just two years from now. That 97 million jobs will be created by tech. And you then went on to say 133 million jobs, you know, would come as a result of AI expansion. I don't understand. Like, first of all, 2025 is just two years from now. How can 97 million jobs and we're complaining of unemployment in this country? Well, so I hear you. And I think I'm just going to piggyback on what the numbers were has just said.  Not even brain drain. We've had mass reduction of numbers in the tech world.   So I found these numbers really, really interesting. But in the face of that, I really want to hear, you know, how you're working these numbers and what kind of roles, because I mean, this is the tech world that has literally been shedding people like skin. So, you know, so what would your, I just, I found the numbers intriguing. So really love to hear what you have to say about them. Yeah, so, you know, if you go back to my speech, what I was talking about, just what these numbers are estimates, right? These are estimates based on the evolution of technology. Technology is not going to stop evolving irrespective of the economic conditions that the world is facing. A lot of what is happening with the layoffs have to do with the economic conditions, right? Inflation rates going up around the world, cost of living, going up, earning capacity, reducing. So that's what's causing this squeeze that you're seeing now. Not that technology in itself is going to stop progressing, right? It will still keep progressing. The bright minds are still going to keep creating value. Now, what I was getting at there was that, you know, value will always, will always be something that will be created. And as long as value is created, people need to support that value, right? Not just in technology, even in other roles, but because a lot of people are now embracing and adopting technology as like the main step for how they think about their company and how they think about their business or how they think about solving solutions or solving problems, rather, that in itself is what is going to cause the expansion. Now, to quickly address the point around AI taking people's jobs, right? Here's my own, this is my thesis, right? I feel, you know, the way with the advent of AI, just like with the advent of any new tool or the any new, you know, technology, there's always the fear that, oh, well, these things are going to replace humans. But that's not true. I feel like this will enable humans. So which means it will create more opportunities for users to take advantage of the technology, right? Not replace them. I'll give you an example, right? They used to, we used to assemble cars by hand back, you know, at least 50, 80, 100 years ago. But today we have robot factories and those robot factories have not replaced jobs. Those robot factories still need humans to configure them, keep them running, make sure that automation works, do inspection. So just because replacement is coming in one angle where humans don't have to stress to do that work, it still will create the opportunity for other areas that devoid that the AI technology would sort of feel just like in the robotics case. So I'm saying what my own theory is, yes, AI may make some jobs obsolete. I'm not saying it will replace jobs. It may make some jobs obsolete. However, because those jobs are obsolete and because of the advent of AI, new opportunities will come along. You understand, it's like closing out one road, but new roads are going to be open. This is my own theory and I believe it's so strongly. Now, I don't think, there's some things I don't think AI would really ever take away, right? For example, AI will never, I don't think we'll ever get to the point, well, this is me in 2023. I don't know about 2033 or 2043, but I don't think AI would ever get to the point where it will take care of our children or nanny our children, right? No, we're not gonna force you to do it. It's exactly, there's still some fundamental things that humans will still be responsible for. AI will never replace emotional judgment. AI will never replace, well, never is a strong word, but I don't think we'll get to a point where I will replace emotional judgment and so on and so forth. All these things can still be calculated and rationalized, but I don't think it will ever replace it. And as long as that keeps happening, there will still be existence of jobs. Now, that's one thing. There's other parts to tech that people keep, what's the word, ignoring. You don't necessarily have to be a tech person to work in technology. You don't have to be a coder or an engineer to work in technology, right? I heard what Oji was talking about earlier as respect to customer experience. That's a legit role in tech. When people build solutions, they need to support their customers when their customers are not happy. Guess who are the people that will do it? You need to ask them. Exactly, the customers and serious people. When you think about business strategy and when you're thinking about growing a company. Okay, so I built a solution that uses technology to solve one problem, but I want to scale it across the world. Guess who's going to do it? Somebody who's going to do broad hacking for your company. That is a role working in technology without being a techie. Let me use that word. So, and there are many, many instances of it. People need to do product marketing. People need to do product management. People need to do content development. They need to do sales. There's so many roles that will keep evolving just by virtue of people who are creating value by building companies. And as long as that keeps happening, unless you are saying the world is going to stop building companies and the world is going to stop solving problems. And that is what I'm saying is not going to change. That is always going to be a constant, this decade, next decade, and so on and so forth. I like that you talked about creating value, right? Because that really is what this is all about. You're creating or you're taking something new and you're able to ascribe value to it that somebody else sees as well and is able to take advantage of it. Let's talk about crossing borders and the challenges that we have here in Nigeria. So, I mean, if I take a certain part of Lagos that comes to mind, which is probably the equivalent of our own Silicon Valley and all the different hubs we have in Yaba, it's still a very small microcosm. I know we have some other places that I'm aware of around the country, but given the amount of youth that we have and the challenges that we have with unemployment here and education, I love what you're doing with studiopedia, but how many people are you truly reaching? What are your thoughts around scalability? How can we really get on board? I mean, Uwa mentioned only two states, right? And they're 36? Yes, they're 36, plus the FCT, right? Why are we not seeing more of this sort of key shift to being able to, because these are people who are essentially going to bolster the economy, right? If you can transcend geographical restrictions without having to leave your current location, whatever money you're earning is coming into this economy, right? So, what are your thoughts there around one, why we're not scaling? Two, I mean, really, what's the way forward where we can really embrace this as a country? Because we have a huge youth population and very poor unemployment numbers, correct? Yeah, all right, so I'll take a step back. I'll take you to step back, right? Take a look at India, okay? India, in my own opinion, is probably the biggest exporter of tech talent in the world today, okay? And they are maybe three X or four X our size, right? But they're able to put themselves on the map, not just in terms of exporting talents that actually physically emigrates out, but also exporting skills that with the talents staying back home in their country. And they're earning in the currency that they want to earn. So they're at the forefront of where Nigeria should be at, in my own opinion, or should surpass. So, but to answer your question, it starts with literacy, like it starts with not just digital literacy, but access to internet, right? The first thing is if you have access to the internet, the internet's amount of opinion is free university. A lot of using me as an example, what I've learned today is me just going into these and teaching myself, right? I didn't go through a formal body or formal education or so on and so forth, just like in India, right? So I'm saying if we are able to solve internet connectivity problems around the country, you would have solved like 30% of the issue, because now connectivity is no longer a problem because contents is now where there's access to. And once we have our youth have access to this content, they can upscale themselves and then export themselves. That's the first thing. The second thing is I think it's already happening. It's just happening at a much slower rates than anticipated. And I don't think India got to where they got to in one day. It did take, you know, it took years, right? They started by outsourcing to themselves internally within their own country. Then they started outsourcing externally, right? I think right now we need to get to the point where even we are even hiring our own talent. But the problem is there's not enough of the good talent here to hire because all of them are exporting their talent externally. So what am I saying in essence? For us to be able to rapidly get there because it's already happening. So I don't want to discount that it's already happening. We have the CC Hub, which is a cluster in Yaba. We have Technopart. Timber, I can stay and start to list different hubs and in different tech clusters, right? That is already encouraging and promoting self-education and so on and so forth. We also have schools who are helping people. You know, I talked about this at the platform. We talked about DecaCon. We talked about old school. Talked about, you know, university. These are companies that are helping people to get into tech. But how can we do it in mass? Well, we will need to partner with the government. We will need to partner with the institution, private institutions. These people have the kind of funding, resourcing to be able to do it at scale. We need to partner with the educational bodies that we have existing today. I remember a project that the CC Hub and I and two other stakeholders were thinking about doing that. What's the best way to accelerate tech, not just tech adoption actually, but tech self-learning, digital skills and digital literacy and just teaching yourself things that would make you valuable in the tech ecosystem? And we're like, the easiest way is education. It's like, you know, using the formal educational routes, right, partner universities, both public and private, those kinds of partnerships creating programs and not just creating programs. To be honest, actually putting it as part of curricula, all the way down to primary school, right? Giving students the skill set from primary school to secondary to university. The minute we change our orientation, change our curricula, we will see the dividends of this in let's say five years because you have to put the investment down, right? It's not something that will happen overnight. But if we have the kind of policies that enforce technology learnings for upskilling individually in our educational system from the ground all the way to tertiary, I'm telling you that by the time we're coming out the gates in like five years, we won't be creating a hundred, you know, it may be a thousand or 2,000 graduates who have skill sets that they can export globally will be creating millions of students. Millions and millions of students. That is the way because we have educational bodies.   So at least our educational bodies are still there and they're still operating. Why don't we just partner with them, partner with education, whether it's the Ministry of Education, whoever it is that needs to be partnered with, we partner with them, bring curricula in so that we can do mass training and mass upskilling. And then we'll see the dividends in about four, five years as they start to grow. Absolutely. All right, so on that note, let's go on a very short break. When we come back from that break, we'll take this conversation for them. So I'm sure some people are itching to know what can I just learn now? Stay with us, we'll be right back. All right, thanks for staying with us. Now if you're just standing, we're discussing building skills that transcend geographical location and we have with us Chuka Ofili. I remember you can join this conversation, send us an SMS or WhatsApp to the rate one, 803-4663, can also tweet at us at Weissho Africa one with the hashtag Weissho. All right, so I mean, this conversation is really, really interesting. And I love what you said about UTI skills because let's use that as our guinea pig, our lab rats, right? So I mean, there are people out there right now and they have this kind of skills that they've built over the years, 14 years, maybe in a company working as a marketer and all of that. And they're thinking, okay, how do I upscale or how do I start to think borderless? How do I start to plan my life in a way that, especially with harsh economic realities that we have, right? So I mean, what would be the quickest way to start to think of digitalizing your skill and converting it into something that you are not just, you're not limited or restricted by your current geographical location that you can now start to earn income from across any part of the world? Dollars, right? It's the game back, okay. You said it. So, yeah. So if you're, I mean, let's break it into two categories, right? We have the technical skills and the non-technical skills. The stereotype before now has always been you need to be, learn some technical skill to earn in foreign currency. And while that may be true, you can far outend most other roles in technology, but they're still the non-technical ones, right? CX is one of them. Now, which one is the easiest path? Well, it all depends on you. It depends on your personality type. It depends on what you like to do or what you already know how to do day to day, right? If, for example, you're someone, and this hypothetical example, if you're someone who is, let's say, a project manager for construction, okay? What do you do daily? You go to sites, you make sure that, you know, the break layers are there. You make sure that the engineers are there. Like you're sort of like the foreman who makes sure that things happen on a day to day. If you don't see one of your resources or your artisan, you call them, where are you? What's the follow-up or what's the status of this? And so on and so forth. But you're the project manager, right? And then the real owner of the project reaches out to you or the owner of the building reaches out to you and you give them updates. And then the updates you're giving them is basically information based on the fact that you're on site and you extracted all the information from your artisan. That is what a scrum master does, right? And a scrum master is a role that just works with, first of all, organizes and plans the sprints, organizes and plans the cadence for the work that's actually done. The person doesn't actually do the work, but the person extracts the information, keeps all stakeholders aligned, keeps all stakeholders informed, and makes sure that the team is running in a healthy, efficient manner. That is the same thing as what a project manager does. Now, to transition, all you'd have to do would be look for some program online. As many of them, Udemy, Udacity, and so on and so forth, do a short three-month course or short two-week course or what have you, depending on the kind of role you want to transition in. Once you take that, all right, you now have the skill sets. So once you have the skill sets, the next difficult to be okay, how do I actually get paid for the skill set? How do I find my first role? Well, there's many ways. You can find ways to intern locally, give your skills for free, and then when you're doing it for free, you get experience, and when you get experience, you get on your CV, and then now you can actually look for remote jobs and there's sites that you can go to, right, remote.com and so on and so forth. There's so many of them online where you can actually go and look for remote work and take applications. You might not get the first one, but if you keep applying the consistency is key. The one thing you should always do is if you ever get rejected, let them know the reason why they're rejecting you so that you can go and fix it.  Then you can go online and look for a course that would kill that gap, do some work around, make sure you can find experience to intern so that you actually get the experience of the skill set because theory knowledge is different from actual practical knowledge. And once you have that, you can then reapply again and then you keep reasoning and repeating that process until you now realize, okay, I think you filled all your skill sets gaps until you are now actually, you land your first job. You might get 300 nodes, but the first yes that you get, most likely you just become a yes moving forward, right? And hey, I don't want to do shameless plug, but let me do it anyway. I wrote a book. The book is called Maybe to Techie. And the book sort of articulates everything, like the journey from moving from a non, someone who does not work in tech, who wants to transition into technology, whether you are a primary school student, secondary school student, graduates, or someone who already has a full-time job as a doctor or physical, but there's many success stories of people who have transitioned, right?  And it's just because of this same strategy, right? It's just really about finding information of skinning yourself, looking for the relevant experience, rains and repeats, that's it. Okay, I like what you've said. This is our book. I hope we have a soft coffee, or you're going to send us a coffee, which one? It's on Amazon. So there's a physical coffee combined in Nigeria, but then also it's on Amazon, right? I can always send you the link of how to get it. Please do. Please do. Honestly, we would love to have that. Go ahead and see. I like this nice, concise strategy that you've put forward. But I think that we also have a challenge locally, and I guess some of our viewers will be thinking that internships are not the easiest of things to come across in our world, right?  But that transition, yes, there's some transferable skills, then there are things that you can obviously go and learn like all the different things that you teach at Studiopedia, but the fact is it still comes down to that experience. So if I'm struggling to find an internship locally, are there any possibilities internationally as well? Yeah, it's a good question. There are, there are opportunities internationally. They say that sometimes they're not just publicly available, but they are there, they're there. I know there was, I think there was a company, I think it was a student or so that was locally trying to connect people to international internships, but even the international internships to your point are very scarce. So I was even at a meeting, was it not, sometime last week where I was talking about, oh, it was actually at the platform, where I was saying to companies that my charge to companies how they can help is by also creating internship programs. One of the early startups that I did in every science with my partner, Larry, they took your daughter, we did, that was how we were taking in young developers. So we'd sort of like, there was some sort of like, known secrets with the Yabata community and Yila community. Every time it was time for them to do their sewers. They knew that our company used to take interns. So we'll take interns, usually they were green and we'll work with them for three to six months during that internship program. We'll sort of train them. What tend to happen is when they go back to school, when they graduate, they always want to come back and at least take their first year or two with us because they know that this was their breeding ground for them to learn. And that's what kickstarted their journey. I know it doesn't directly answer your question, but if there are a lot more companies that did what we were doing, right? Everybody's always looking for finished products that is shiny and employee who already has all the skills. But someone needs to start somewhere, right? And working with companies to get them to start internship programs, I think is something that we can do to sort of solve the internship scarcity. And it's not a Nigeria thing, it's just a global thing, right? To your point. So one day at a time. Okay, so Chuka, let's come back to the biggest elephant in the room. Yeah. Even though people think that these unemployment numbers is largely related to young people, it's not. There are people that are old, they don't have jobs, you know, and they wish. So is there anything like age restrictions to these skills that one needs to think about? Because somebody might be in their fifties, they don't have any job and they're just looking, what can I do? How can I begin to earn money? Is it too late for me or can I start now? What exactly would you say to that person? I'd say that that is absolutely just not true. That's absolutely not true. So it depends on, but I'll say one thing, it does depend on the kind of role you want to, right? I feel at least culturally, right? In Nigeria, older people find it difficult working for much younger people, right? I'm not saying that there aren't people who do it, it's just a cultural thing. But if you don't have that cultural issue, that cultural bias, then the sky's the limit for you, right? I think all you have to do, you can obscure yourself just like any other person. You have the same brain, you have the same skill set you can learn just like everybody else. And once you've learned, you can get opportunities just like anybody else. The world in general, at least what from where I sit have experienced it. I've seen older people who've gotten jobs at entry-level software development roles. But that's if you want to become a software developer. But if you want to be a CX person or you want to be a product manager or you want to be a project manager or you want to do design or you want to do graphics, it doesn't matter what you want to do. What matters is your skill set and your portfolio of work. It doesn't matter that you are... The technology is not ageist. That's what I'm saying. It's just only the earlier point that I made in Nigeria because culturally, right? It's just a cultural thing. You don't want to go into a company. But if I came to Yutuka and I was 65 years old, I already gathered the skill. Would you employ me in your company? Why not? I would look... What I'm not looking at is your age. I'm looking at your portfolio of work. Am I capable? What matters? Yes, it's the portfolio of your work. If you show me the things that you can do and that you've done, why would I not employ you? Why would I not employ you? I say, you would employ the best candidate for the role. It's just quite simple, right? Who's the best candidate? But in many instances, sometimes, you might not even be employing one person. You might be employing quite a number of people. It doesn't negate age. It's just a number. And the sooner we start seeing it that way, the better. Yeah, absolutely. I think it would be great. I mean, absolutely age is a number. It would be great if a lot of people saw that because when you were talking about, yes, you would absolutely hire the person. I'm thinking a great many number of companies have policies that define what retirement age is.  Okay, let me interject. I'm sorry, I know you wanted to land you, but let me interject. There isn't a rule that says you must work for a company. You can also freelance. There's freelancing. This is a whole world that I didn't even talk about. All the world I've been talking about is exporting your skills to tech companies that are in Netherlands or in Amsterdam or Germany, wherever. But there's freelancing. There's sites like Upwork. There's sites not even Upwork. There's sites like TopTal, Total, right? There is sites like Geekstar. There is sites like Fiverr. All these people are, all these companies are freelancing companies. So if you've learned how to do copywriting, copywriting is something that is needed quite in tech. What's copywriting? It's not even a tech role per se. It's a role. You see people do it. If you learn how to do copywriting, you can go to Fiverr, list your services. They don't, nobody cares how old you are. On TopTal, nobody cares how old you are. What matters again is your portfolio of work, right? I just wanted to call that out here. You don't necessarily have to do a 95 job. You can also freelance. And I dare say you probably will make a lot more money freelancing than you would do in a 95 job. Okay, I'm sorry. I interjected, but I wanted to see. You want to continue? Yeah, well, I mean, you took out the legs from my question very elegantly. So well done. But I think that you've sort of, you've said enough to wet our appetites, right? And I'm mindful that when we have these sort of conversations that we're really trying to stick in that straw and just suck at as much knowledge as possible, time runs out. So I think I would like a paint by numbers, right? We've talked about the opportunities.  For the person who's listening today who says, you know what, this all sounds very interesting. I wanted to work without geographical restrictions. And like I said, I want to end dollar. Where? Give us a paint by numbers. What should I do first? Where should I be looking? What? So we've said the baseline, which is have an internet connection. But then the internet is super vast. Like I could get lost in one Google search for a couple of hours and come out on the other side and still be like, huh? So just a couple of tips to say, you know what, this is what you should do first. This is what you should do, where you should go.  But anyway, I studied product management. I did internship. Let me come back to that. Go ahead. So yeah, just to give something that our viewers can, you know, maybe just take note. Quickly, because I have one more question before I run out of time. Go ahead. Yeah. So, sorry, I'm trying to position my screen. Make sure that the lighting is good. Sorry, they're getting. It's fine. Yeah, okay. So the first things first is I'll say udemy.com. If you don't take anything away from this, what the show you're watching, use udemy.com.  Usually the courses are very, very affordable. Anywhere between, say, $20 to $50, it's all depending on what you want to learn. Now, quite all right, some of the quality of the content might be entry-level things, but it's enough to whet your appetite so that you can then go for the more advanced courses, right? If you want to go for the more advanced courses, then you can then do something like Udacity, which then gives you actually a nano degree, which is very helpful because it then strengthens the quality of your portfolio. So if anything, right, udemy sort of gives you access to thousands of courses, thousands of lessons, which kind of like get you going. The biggest question you have to ask yourself is what do you want to do? And like I mentioned earlier in the show, that is well-dependent on many things about you, your personality type, what you like to do, what you love to do, you always want to go there. Yes, yes, exactly. So those are the things that you have to watch out for. Now, again, shameless plug. I said I wrote a book. So go to books.iamchuka.com. The name of the book is maybe to techie. I have itinerized everything there from beginning to end. I know the show is only taking part of it, but it kind of works you through a journey of how you can start transitioning. I think most of all the questions that we may want to ask, even beyond the show, have been answered there, but I'm still here to take more questions. So one last question. Our daddy, Elon Musk said the remote work is his job. Elon Musk said the remote work is his job. You know, our dad. He was Elon Musk, doesn't he dad? He said remote work is his job, because as it is now, they are beginning to see that, come, everybody fire back to office and don't do remote work and everything. How would this affect? They don't want to hear that. She has come us. So how would this affect tech jobs, right? Especially for people that have gotten tech jobs, you know, like, you know, I mean Nigeria, I'm working for a company in Canada. So how would this if people start to go back to the original structure of going to a physical location? How would this impact it? So first of all, my own opinion, I don't think we will ever really completely go back to return to office. That's the first thing. Elon Musk's saying remote work is his job. Of course it's his opinion, but he's seeing the impact of remote work on his business. And it depends on the kind of business that you're running. For example, CX is going to be hard to do from home. You need to be in the contact center. Like there's some rules that you should technically be around. And I'm not going to deny that there is certain level of quick progress you make when you are in the office with your colleagues, right? There's nothing as good as the tap on the shoulder to say, hey, how about this? Help me unblock, so on and so forth. While all those are true, remote work is not going anywhere. This is the new dispensation. I don't think it's going anywhere. The worst that will happen is that companies will then switch to like a hybrid, situation where people go to the office once or twice a day, sorry, twice a week, and then work from home. But working from home sort of is, I know how much companies sort of saved from closing down a good chunk of their offices. How much that affected their bottom line. Instead, they took some of the savings they do from office and gave their people work from home resources. So it depends on what side of the spectrum you stand. I think there are benefits to working from home and then there are also obvious advantages to coming into the office. But I think where we probably will most likely settle and where the world is going is a hybrid situation, right? And what companies will start to do is they'll have some roles that will be like, okay, this can be remote only. And then they'll have some other roles where they'll be like, oh no, at least 90% or 80% in office. That's where we're going as a product. All right, so we'll watch out to see what we have. But quickly, let's read just one comment. Let's say this comment. I mean, first and foremost, I'm happy to see this comment from the center. I was thinking about him earlier in the show going, I mean, I just wonder what happened to him. So, Daniel, we're excited to see your message again. Thank you for sending it in. And he says, good evening, my dear beautiful sisters of all. Are you saying hashtag ways? Building skills that transcend geographical location. Your guest made mention of something very important. He said that you do not have to be an engineer to be involved in tech. And this is very true and key. He also said something about use, developing skills to improve the internet system. He gave an example of a site manager developing skills in the site with his own ideas. Someone who is skillful enough should partner with the government for support. Or ask a question about age restrictions when it comes to getting jobs with a school full person. And he must confess that we look irresistible today. I had to find time to put that in. God bless you too, Daniel. Thank you, Daniel. Well, thank you so much, Chuka. We are hoping that when you're in Nigeria, you can grace our set physically. Because we had a fantastic conversation. This was really, really worth our time. It's a beautiful way to wrap the weekend. Thank you so much, Chuka, for being a fantastic guest. We are going to look for your book. Me and Google find it because I want to find money. All right, so before we go, I'm sure you follow us across all our social media handles. You can interact with us further. Drop your comment and more importantly, follow all our engagements on social media, like, share, and invite your families and friends to watch and follow the conversation. I've missed our course for today. Here it is again. Skills open the doors to opportunities. They break every economic boundary and empower society to maximize their potential. Nothing else is that powerful. So if you really want to change the status quo today, go and learn a new skill and look for Chuka's book. It will help you out. All right, thank you so much, everyone. Have a lovely evening.


Thank you everyone for joining us today. We hope you will find the event very useful for your own research, and we hope it's also a way of you knowing that you can always contact us. I'm Kristina Magder, I'm the Collections Development Manager at UK Data Service, so I lead on all the acquisitions that we get into our collections, but I also wear a research data management hat and I lead the training portfolio when it comes to research data management. And I'm joined today by my colleague, Hina. Thank you Kristina. Hi everyone, thank you for joining us today. My name is Hina and I work with research data management team with Kristina and I mainly oversee the guidance and training related to ethical and legal issues in data sharing. Thank you so much Hina, and we have quite a lot of content to cover today, so let's see what we're going to discuss. We're going to be looking at data sharing and its benefits, and what is a data management plan, and why is it required? What is usually included in a data management plan, and we're going to be looking at a practical example, the ESRC template, but we're also going to include a number of resources, tools and templates that you can use in your own time. So when we're talking about data, we're thinking data does not exist in a vacuum, we're talking about this data lifespan in the research data life cycle. Usually when you create a project that creates data, that data can be used for so many different reasons besides the project that created them. And as a repository as the UK data archive, we see this happening with large governmental surveys, academic studies, research center studies and so on. So when we're thinking of the research data life cycle, I've included a diagram there. It starts with the planning of the research, we're collecting the data, we're processing and analyzing, we can finally share our results and share the data. By sharing the data, we ensure that the data is preserved in the long term run, and it also helps others to reuse the data, and then the cycle continues. Now, when it comes to benefiting data sharing, we like to present this example to clearly show everyone that we're not here talking just about researchers benefiting from sharing their data. Because of course it does increase visibility of your work, we get the digital object identifiers or persistent identifiers with our data, your data is going to be stored in the long term. And it also helps your publications because we've seen more and more journals are asking about reproducibility and transparency. But it also helps the funding body because that way, different funding bodies can demonstrate they're making optimal use of publicly funded money. Also, it avoids duplication of data collection and we're going to see in the years or see data management planning, it's very similar with others as well. They are actually asking researchers to make an assessment of the data that's already available. But the public benefits as well, because they realize with hard evidence how the science helps society benefit the society, it helps with adoption of emerging norms, norms such as open access publishing, and of course it helps with compliance with laws and regulations. Last but not least, it also benefits the research participants because it does allow other researchers to use the data that was already gathered. It minimizes data collection on the hard to reach population. And my example here is always usually an example we've seen at a workshop done by UK data service. There was a big call around the migration crisis. A lot of different researchers went and gathered migration data. And when we did the workshop, we've actually invited a couple of migrants to our workshop. And the very first thing they said was, please share my data, I want everyone to know my story. Now, when it comes to data management planning, a data management plan, it helps you describe five different things. How the data is going to be collected, how is it going to be organized, analyzed, preserved, and shared as well. Why might we need data management planning? Well, it genuinely helps plan ahead with your research project. It helps if research members leave, we know people might find different jobs, or they might go on sick leave. It helps you identify different support that you can get, including for example, support from UK data service. It helps you plan storage both in the long and the short term run, ethical considerations and legal considerations as well. It shows accountability for your funder, for your institution, and for the different partners in the research project. It also helps make data fairer and we're going to cover fairing just a little bit. And of course, it fulfills funder's requirements and we're going to see there's more and more research centers in the UK that are asking for data management plans, sometimes with different namings, but this also applies to the European community as well. So the fair principle for publishing data means making data findable, accessible, interoperable, and reusable. You can read more about them on Force 11, but I tried to give a brief overview of what making data fair means. So findable, it's all about using community endorsed metadata and documentation standard and actually having persistent identifiers so others can find your data much easier. Accessible, actually including an availability statement, who is the data made available to? Is there an embargo period? Are there any restrictions applicable to the data such as non-commercial use, for example? Methods and tools to access the data, making it clear, for example, you are using CSV because it's an open format or you are using a proprietary format because currently open software were not feasible to use, that the metadata is preserved indefinitely. So even if, for example, it happens very rarely, a data collection must be taken down, it must be removed from a catalog, from a repository, the metadata stays within the catalog forever so other people can discover that this collection existed 100, 200 years ago and they can actually see why no longer is made available. When it comes to interoperability, interoperability, we're talking about standard vocabularies and standard metadata schemas. So with UK Data Service, we use the data documentation initiative metadata schema. We have our HACIP, an electronis desorai that helps us index all the different collections and allows researchers to find data much easier. Reusable, again, we're going back to making sure that the data is licensed so other people know how to use it. You have used established data quality assurance processes and we're going to see there's actually a couple of tools that you can use for your data quality assessment and it ensures that the data is preserved for the long term. When it comes to DMP structures, they do differ from one funder in one institution to another one. So always, always make sure that you check with your funder and your institutions what their requirements are for data management planning. However, overall, they see this brief section, description of the data, both existing data and new data, management and curation of the data throughout the research lifecycle. How are you going to store and back up your data? We've probably all heard of stories when, for example, the data was only on a laptop and the laptop was forgotten in a train, so this is why it's very important to keep in mind back up. Legal and ethical consideration is very important, especially with legislation when it comes to personal data, to bear in mind these aspects and my colleague Hina is going to cover them in more detail. Data sharing, how are you going to ensure that the data is shared but also usable for others? Because just throwing a CSV file up there in the wild might not be the best way of making sure that the data can be used by others and also responsibilities and resources. In this section, it's all about thinking who is going to do what and what type of resources do I need to make sure that my research project is successful. As mentioned, different research funders, different institutions do have different data management planning requirements. We can see, for example, with Arts in Humanities Research Council, they actually call it the technical plan, but they do include sections about the standard views, the preservation of the data, continued access of data sharing and use as well. So just not just throwing that CSV file out there, Cancer Research UK, they call it the data sharing plan. Again, they're talking about the volume of the data, the format of the data, metadata documentation. So we can see all of them are very similar and the end goal of creating a data management plan is to ensure that your research project is successful. And I would say, even if it is not a requirement from your funder or your institution to do a data management plan, following the structure I've just shown very briefly on two pages, covering the different aspects ensures that your research project will be successful. So, for example, with DMP, the Economic and Social Research Council data management plan includes 10 sections, assessment of existing data, information on new data, quality assurance of data, backup in security, management and curation, a section in which we need to discuss all the difficulties that we can see in data sharing and what measures we have in place to overcome them. How are you going to ensure consent and anonymization to ensure reuse? How about copyright and intellectual property rights? And we're going to see this is very important not only for primary research, but for secondary research as well. Responsibility, who is going to do what, and also preparation of data for sharing and reuse. When it comes to assessment of existing data, usually this section, I will compare it with the literature review, but call it the data review. What existing data sources are about the topic that you want to research? And in what gaps have you identified if any, again, data management plans can be done for secondary analysis? If there are no gaps, the secondary data can be used. It's always useful to have a look at the UKRI Gateway to Research webpage. They provide a list of all the different past, present and future research grants in the different outputs they have. And again, more and more research councils in the UK are actually asking for data to be shared. They are mandating data sharing. ESRC was the very first council in the UK to mandate data sharing as a requirement in their grant proposals. A couple of examples of same data sources. So rather than basing data from just Google, I'm going to Google my topic and I'm going to find some data sources. I'm not quite sure if I can use them very well or not. You can always use the UK data service data catalog. We have over 8,500 collections of economic social science data, but also the CESA data catalog can come in very handy. CESA is the consortium of European Social Science Data Archives. So if you're doing social science research and you have not checked the CESA data catalog, please do have a look at it. It only contains the metadata. So with this data catalog, it takes the metadata that we get data service provide in Germany, CESA, CSDA and France and so on, but you can discover much more data that you could use in your research projects. Information on new data. So say we've identified some gaps and we really need to create our own data. We're talking about primary data here. What do we need to include in this section? What is going to be the volume of the data? So am I going to do a survey, two surveys, interviews, focus groups? How many people? What is the data type? It can always be mixed methods, quant, qual, but you need to specify exactly what data you are collecting. What is going to be the data quality and the formats you're going to use? And again, especially in the open science landscape and in the fair data landscape, ensuring that the formats are as open as possible. So again, maybe making sure we have a CSV file, we can of course use proprietary software as well and all repositories welcome different formats to be uploaded, but having an open version is always best as well. What kind of standard documentation and metadata are you going to create for your project? And if you've never done research before, getting in touch with UK data service or your institutional repository to discuss more about what type of documentation you might need or what type of metadata schemas the repositories are using, it's always advisable. What are going to be the methodologies for the data collection and data processing? And also is the data trustworthy? And this is where I'm going back to making sure that we use data from a fair repository, a trusted repository. We have a variety of resources for information on new data available online. So please do make sure you consult our web pages. But again, I can't stress enough, if you have any questions, please do get in touch or email addresses right at the end of the presentation. And we welcome all queries about data sharing and data management planning. Quality assurance of data. What should one include when we're talking about quality assurance of data? Calibration of instruments, if applicable. Again, some of it can be very time of research focused. Taking duplicate samples, are you going to have a pilot, for example, if you run a survey or if you run a focus groups and so on? Are you going to use standardized data capture solutions? Data entry validation. And I put here our QAMI data tool. It was developed in three open source. Everyone can make use of it. The code is on GitHub, but on our web page we have more user friendly. I would say documentation about how to make use of it. And it gives a health check on your data. So once everything has been entered into the database, you could use QAMI data to see whether is it well-labeled, do you have duplicate IDs, and so on. Describing if you're going to use standardized methods of transcription. And again, this is something that we make available on the web. We have a template that can be used in your own project. And also, is your data going to be peer reviewed? It's by no means a compulsory, but more and more peer reviewing is getting more popular, I would say, in the social sciences as well. So if it's something that will happen, definitely mention it under the data quality assurance section. When it comes to security and backup of data, again, people might forget their laptop on the train. So we need to ensure that the data is stored in backup continuously so we don't lose our data. I would say best advice here is always consult with your own institution. So of course, there's so many cloud environments now in solutions to ensure that the data is stored correctly, and it's safe, and it's backed up. But this does differ from one institution to another one. So getting in touch with the IT people at your institution asking, I am conducting this research project. I really need to ensure my data is safe and backed up. Could you please let me know how this would happen on our system? Most likely they're going to have a policy they can refer you to, and you can always use sections from the policy within the data management plan. The second thing you're always to consider is your data sensitive. Do you have personal data? And again, the security measures here will be different from one institution to another one, but you must pay a lot of attention around who is going to be able to access the data. It has that domino effect on the ethical protocols you're going to use the data management, the participant information sheet there, because the participant information sheet that can send form. So always bear in mind, is my data containing personal data, and always mention it when we're talking about storage and long-term storage of data throughout the project. And also bearing in mind that data security arrangements need to be proportionate to the nature of the data in the risk involved. So for example, if you're doing a quick Qualtrics poll, that's the first thing that came to my mind. It doesn't contain any sort of demographics, any sort of personal data whatsoever. Then you wouldn't need so much security information. But again, backup definitely because we don't want to lose that data. When it comes to management incubation of data, it's really important to think from these three perspectives. How am I going to prepare my data, organize my data, and also document my data? I can't stress enough document my data because sometimes preparing and organizing goes so well. Everything is so nicely labeled and the data itself, but then there's no documentation. And that means more resources will have to be involved later on in the research project to prepare the documentation. If we start documenting just at the beginning of the research project, then we're making our data so much easier. So thinking in terms of the types of data, are you using primary, secondary, is it anonymized? Is it pseudo anonymized? Because it depends how you're going to manage it throughout the research lifecycle and how are you going to curate it. So if we're thinking about secondary data, for example, curation would be very minimal. It depends if we take quant, for example, you might want to create some new derived variables. So saving that syntax there of how you've derived the variables is very important. If we're talking about primary curation takes a higher part in the process because we're talking about making sure that our data is put in the context very nicely. Again, transcription, if it's quality, it's done very well. How am I going to anonymize transcription? Metadata for data description is well, making sure and ideally, I know this differs from one research project to another one, but ideally when it comes to metadata, you would want someone that has been heavily involved in the project to create this metadata, data about data, as they say. Because if you have someone that's involved in the project, they will know it so well, it's going to be so much easier to provide, for example, what was the sample of the study you've done? What was the data collection method, rather than trying to get someone else to do that for you? Key documentation. And here, again, it differs from one project to another and from one data type to another. But if we're talking about quant, qualp, having a short user guide, I'm not talking 50, 60, 70 pages, even five pages describing key things. Have you done a pilot? What was the sample? How did you collect the data? Have you used weightings and so on. For quantitative data, having data dictionaries is very important, especially if the data must be made available under access controls, because that ensures everyone can get an informed decision if they need to use the data or if they don't have to use the data, interview schedules, focus group schedules, and so on. It's important to bear in mind naming conventions for data files as well. And we give a couple of examples on the web page. So rather than just naming files A, B, C, D, and then not necessarily knowing which one is which, actually ensuring, for example, I have wave one survey, wave two survey, and so on ensures that we know what data we're working on. And finally, covering the long-term preservation of data, how are you going to ensure that the data is not lost? And again, this is by making it available via trusted repository. So a couple of examples of documentation. And we like to refer to documentation when it comes to user guides. We can see here technical reports as well, or disclosure control reports, F-study level documentation. It describes the entire study. They're usually in PDF format. They can be Excel, Word, or open software as well. Data level documentation. We're here talking about giving variable and value labels for qualitative data, giving a data list that nicely describes who the participants were, what the interview number is, the name of the file. But also for secondary research is very important to have a variable look. And all of these templates are available on our web pages. So you don't have to start from scratch. You can always have a look at them. For secondary data analysis, when it comes to the variable log information, it's important to know what variables have been used and from where, because there might be consequences depending on the license the original data was under. So even if it's made available under a creative commons license, it might be a creative commons non-commercial share-alike. So the data that you're creating must be shared because of that share-alike under a similar license. And finally, we have capital metadata. Keep going on about metadata, metadata. This is how capital metadata looks like. Most of the fields are actually what we call controlled vocabulary. So you drop the list and you select, for example, what is the spatial units? We have government dosage regions and standard statistical regions. What is the observation unit? So who was the data done with individuals but also families and households as well. But we also have three text fields, such as the population. You would just have to name the population of the study or the abstract of the study. Those are three text fields. There's a lot of documentation that can be made available for data. We do have resources online about what type of documentation, different types of research projects should help. But again, I'll keep insisting, if I'm sure, always get in touch with us. We are here to help as much as possible. And now I will hand over to my colleague Hina for the second part of the presentation. Thank you, Christina. Yeah. So much research data, even sensitive data, can be shared ethically and legally. So it is extremely important that you address this section as well as the following sections very carefully in your data management plan. You need to consider any potential obstacles in sharing your data and explain possible measures you can apply to overcome these. And for example, if you are collecting personal information, how you are going to handle it, you need to think and plan ahead, which data could be potentially difficult to share and why. So you also need to explain the reason for not sharing it. For example, if ethical issues such as potential harm or is there any other concern that could cause difficulties in data sharing, you need to mention it here in the section. And you also need to explain your strategies for dealing with these issues. As I said earlier that most data can be deposited for future use, so is the ESRC's position on that. However, this could be achieved only if the researchers pay attention right from the planning stages of research to certain aspects such as including consent for data sharing when gaining informed consent, protecting participants identity by anonymizing data if required to do so, and addressing access restrictions to the data in the data management and sharing plan before even commencing the research. So for instance, you have collected data which has personal information and you are unable to obtain consent and anonymization is also not possible as valuable information could be lost or any other reason. So you need to stay at this explicitly in this section in your plan. So consent, anonymization and access control are the three important issues that facilitate data sharing and I'll go through these briefly. So in this section of your data management plan, you need to explicitly state about the planned procedures as to how you are going to handle consent for data sharing for your data, whether you are planning to anonymize any personal information in the data, if so, how you are going to anonymize it. You also need to make sure that your data can be made available and accessible for future scientific research and at UK Data Service, we advise researchers to employ a three tier strategy which is consent, anonymization and access control. I'll go through each of these now. So I'm sure you all are familiar with what informed consent is. However, when it comes to data sharing, then consent is used for two purposes. We are all familiar with the consent that is used for research participation and is considered as one of the founding principles of research ethics where it is sought before participation in any research activity and for all participants. It usually involves providing information regarding study purpose, risk, benefits, voluntary participation and so on. However, consent can be used as one of the legal basis of processing personal data under the UK GDPR. If a researcher collects, manages and shares personal data, then consent of the data subject can be used as a legal base to process this personal information. So consent form plays a vital role in data sharing and it is very important that you design the consent form, keeping in mind these three important sections. If you plan to share your data, the first section should be about taking part in the study that includes, sorry, it automatically moves. So yeah, the first section should be about taking part in the study that includes some basics such as, I don't know, Kristina, if you can switch off the timer. The first section should be about taking part in the study. That includes some basics such as participants have read and understood information about the project. They have been given the opportunity to ask questions. They understand that they can withdraw at any time without giving reasons and without any penalty. And the second section is all about the information that is being collected will be used. For example, how the data will be stored for how long, how the confidentiality will be maintained. And the final section should be around providing information about future uses of the data such as publications, archiving data and so on. So this final section in the consent form is really important if you are to share the data for future reuse by other researchers. So this is the screenshot from the UK data service model consent form template. It addresses all the three key areas that I have mentioned, breaking down these areas in three different sections on the template for the user fees. And it applies to all types of data including interview, focus group, surveys and so on. You can adapt it according to your requirements. And at the bottom of the slide I have added a UK DS, sorry, consent form link that you can have a look at it later. So some of the best practice for this section is to state clearly in your DMP that you are going to handle consent for data obtained from human participants. You must ensure that your consent procedures inform participants correctly about data sharing intentions and do not preclude or unnecessarily limit sharing of research data either as open data or on a restricted basis if necessary. Award statements such as data will not be shared outside the research team or clearly explain which data is it, just the personal data or all data. You need to be very specific in explaining this in this section of your DMP in your consent form. So you can refer to the UK DS model consent form which addresses all these issues. And another important issue is never set a time limit on the retention of the data collected from participants or state that all data will be destroyed at the end of the project. Such undertakings are not required by data protection law or research ethics policy and they will prevent you from making your research data accessible to others even if they have been anonymized. I have added a guidance on these issues at the bottom of the slide. So in the UK there is a duty of confidentiality that is based in common law and that occurs where confidential information comes to the knowledge of a person in circumstances where it could be unfair if it were then to be disclosed to others. So there are some exceptions when you can disclose information. For example, if participant consents to on one sharing of their personal data then sharing does not preach duty of confidentiality. Sometimes public interests can override duty of confidentiality as well and occasionally there are instances when you may need to give up data such as code order. So the best practice is to avoid very specific promises in their consent form. As researchers we must adhere to data protection requirements when managing or sharing personal data. So if personal information about people is collected or used in research then the data protection regulation applies and data protection legislations that are most widely applicable to the research data or data protection act EU GDPR which is now called the UK GDPR. EU GDPR is the EU white data protection regulation that was introduced in 2018 and it replaces UK data protection act 2018 that was used until that time. However since last year when the transition period of Brexit ended it is now called the UK GDPR. Currently UK GDPR and EU GDPR both are aligned and they place the same legal obligations on researchers but in future the two pieces of legislation may diverge as the UK has now left the EU. So it will be important for researchers to ensure that they gain local support from their university data protection officer when their research project will span across the EU. So if the researcher based in the UK collect personal data about people anywhere in the world or a researcher outside the UK collect personal data on UK citizens then data protection act and the UK GDPR both applies. However if the researchers are undertaking research projects which span across the EU then the EU GDPR will also need to be considered. So if you are planning to collect personal data then GDPR applies. So you need to explicitly mention in this section how you are going to protect the confidentiality of your participants whether you are going to employ anonymization. Anonymization is a valuable tool that allows data to be shared while preserving privacy and the process of anonymizing data requires that identifiers are chained in some ways such as being removed for example you just remove the identifiers such as name address, state of birth or substitute, distort, generalize or aggregate this identifying information in the data to make it shareable. So in your data management plan you need to explicitly state how you are going to anonymize your data making sure that data will be available for future use by others. And if you have any further queries in terms of this you can always get in touch and we are happy to help. I have added a link to the guidance on anonymization at the bottom of the slide. So another strategy that enable you to share your data for future use is access control. For example how you want your data to be reused by other researchers or students you can specify this by licensing the data to match the intended uses. So in your DMP you need to address access restrictions to the data. You also need to consider if you need to restrict data used by others for a certain period as ESRC expects that data should be deposited after three months of the end of the current period. So you can deposit your data and ask for embargo for a certain time in case you have any publication plan. So just to give a brief overview for our licensing and access frameworks here at UK Data Service we facilitated three levels of access for data, open access for the data that contain no personal information, safeguarded access for data that contain no personal information but the data owner considers a risk of disclosure resulting from linkage to other data and it is available under end user license and users need to register to access data. Users also need to agree to certain conditions such as not to disclose any identifying information and then final one is the controlled access which is for the data that may be disclosing and it is only available to users who have been trained and they granted it and the data usage has been approved by the relevant data access committee. So another important section in the DMP is to address copyright or IP right ownership. If you are planning to use secondary data sources for your project then you need to consider copyright or IP rights. Copyright or IP right are assigned automatically to the creator or the researcher who owns the data. When data are shared or archived the original owner retains the right data archive cannot archive data unless all right holders are identified and give permission for their data to be shared. So you need to address this issue by checking the terms and conditions associated with what with the source that you are planning to use. You need to check if you are allowed to use it, if you are allowed to modify it and most importantly you are allowed to share it for the future use by others. If not you might need to obtain permission to share it. Also in your data management plan you need to explain who will be the copyright owner of the data that is being generated. Is it the original researcher? Is it you or both? If you are unsure you are always welcome to get in touch for advice. So if you are using secondary sources then best practice is to assess who the copyright holder of the data set is. Are you allowed to use them and in what way? Are you allowed to archive and publish them in a data repository? Most of the time we encounter problems when researchers are allowed to use data as the data is under open license or they register to use it or they are allowed to use it for their personal use. What they do not realize is that it is accessible to them for their use but they may need permission from the data owner for sharing it or archiving it. So you always need to seek further permission to distribute material. You do not always but most of the time you may need to seek permission to share material you do not own. So if permission is not granted you may need to remove copyrighted variable or content from publishing or sharing. So you can have further information on all the issues I have gone through on the following links in your own time. So there is a guidance on ethical issues, rights in data, data protection and other rights on our website. So in this section called responsibilities you need to indicate in your DMP who within your research team will be responsible for data management, for metadata protection and for dealing with quality issues and who will be responsible for the final delivery or depositing of data for sharing or archiving. If several people will be responsible state their roles and responsibilities in your in this section of your DMP and in terms of collaborative work you need to explain all these across partners in this section of your DMP. So at the bottom of this slide these two links have detailed information on these issues. Final section of your data management plan should address preparation of data sharing and archiving. To do this you need to consider what would be your plans for preparing and documenting data for sharing and archiving and whether these are appropriate or not. Have you considered and mentioned enough evidence that the data will be well documented during research to enable high quality secondary research. So this is the link to the data management checklist on our website which you could find very useful as it addresses all these sections and that Christina and I have gone through yet and all the sections that you need to complete in your DMP. So a very useful checklist you can find on our website. So here are some useful resources that you can have a look at in your own time. These are some of the guidance requirements templates by different funders and then there is another very useful resource which is called DMP online tool and that you can find it useful as well. Yeah so thank you very much.