Even the best, the most honourable and the most honest, do things which would land the rest of us in jail. Nemihaus in France is a large grain silo. After the harvest, farmers deposit grain in it. The silo gives them a certificate for every ton of grain that they deposit. They can withdraw that amount of grain whenever they want by presenting that certificate. If the silo owner issued more certificates than the grain he kept in his silo, he would go to jail. But that is effectively what bankers do. They keep as reserves only a fraction of the money deposited with them, which is why we call the system the fractional reserve banking system. Murray Rothbart, a much-neglected Austrian economist in this country, therefore said very flatly, banking is fraud. Fractional reserve banking is fraud. It should be outlawed. Banks should be required to keep 100% reserves against the money they lent out. Now, I actually reject that conclusion because I think there is a value in what banks do in transforming short-term savings into long-term investments. That is socially valuable and that is the function banks serve. But we need to recognise the second distinctive feature of banks which arises directly from the fact that they only have a fraction of the reserves against the loans they make. That is that banks individually and collectively are intrinsically unstable. They are unstable because they borrow short and lend long. I have been constantly amazed throughout the financial crisis hearing intelligent people say that the problem with Northern Rock or RBS or H-Bars or the German banks or the Swiss, French, Greek and other banks which ran into problems was the result of them borrowing short and lending long and they shouldn't have been doing it. As if this was a deviation from their normal role. But of course banks borrow short and lend long. That is what banks do. That is what they're there for. If they hadn't done that, they wouldn't be banks. Banking works so long as too many depositors don't try to withdraw their funds simultaneously. But if depositors retail or wholesale withdraw or refuse to renew their short-term deposits, a bank will fail. Now if normal companies fail, there's no need for the government to intervene. Their assets will be redeployed in a more profitable use or taken over by a better managed company. But if one bank fails, depositors are likely to withdraw deposits from other banks about which there may also be doubts. And a bank facing a run, whether or not initially justified, will be forced to call in loans or sell collateral causing asset prices to fall, thereby undermining the solvency of other banks. So the failure of one bank may lead to the collapse of the whole banking system. The third distinctive feature of banks is that which was highlighted by my Honourable Friend that banks create money. The vast majority of money consists of bank deposits. If your bank lends your company £10 million, it does not need to go and borrow that money from a saver. It simply creates an extra £10 million by electronically crediting your bank account or the company's bank account with £10 million. It creates £10 million out of thin air. By contrast, when you repay an existing bank loan, that extinguishes money. It disappears into thin air. So the total money supply increases when banks create new loans faster than old loans are being repaid. And that's where growth in the money supply comes from normally. It's the normal situation in a growing economy. Ideally credit should expand so that the supply of money grows sufficiently rapidly to finance the growth in economic activity. But when a bank or banks collapse, they will call in loans which will reduce the money supply which in turn will cause a contraction of activity throughout the economy. So that respect banks are totally different from other companies, even companies which also lend things. If a car rental company collapses, it doesn't lead to a reduction in the number of cars available in the economy. Its stock of cars can be sold off to other rental companies or to individuals. Nor does the collapse of one rental company weaken the position of other car rental companies. On the contrary, they then face less competition which should strengthen their margins. So the collapse of a car rental company has no systemic implications. Whereas the collapse of a bank can pull down the whole banking system and plunge the economy into recession. That's why we need a special regulatory regime for banks and above all a lender of last resort to pump in money if there is a run on the banks or a credit crunch. Yet this was barely discussed when the new regulatory structure of our financial and banking system was set up in 1998. The focus then was on consumer protection issues and systemic stability and the lender of last resort function was scarcely mentioned. That's why the UK was so unprepared when the credit crunch struck in 2007. Nor were these aspects properly considered when the euro was set up as a result established a currency and a banking system without giving the new central bank the powers to act as lender of last resort. It had to usurp such powers more or less illegally. That's their problem. This analysis is not one of those insights which come from hindsight. Some while ago Michael and our noble Lord Howard reminded Parliament and even me I completely forgotten that I was shadow chancellor when the bill that became the Bank of England Act 1998 was introduced. He pointed out that I then warned the House of that and I quote with the removal of banking control to the financial services authority it's difficult to see how the Bank of England remains as it surely should responsible for ensuring the liquidity of the banking system and preventing systemic collapse. And so it turned out. And I added setting up the financial services authority may cause regulators to take their eye off the ball leaving spivs and crooks to have a field day. And so that turned out too. I could foresee that then because the problem was not deregulation but the regulatory confusion and proliferation introduced by the former chancellor resulting from failure to focus on the inherent stability of the banking system and to provide for it. This failure to focus on the fundamentals was not a peculiarly British thing. The EU made the same mistake in spades when setting up the euro and at the very apogee of the world financial system they deluded themselves that instability was a thing of the past. In its global financial stability report in April 2006 just less than 18 months before the crisis erupted the IMF the international monetary fund no less said and I quote there's growing recognition that the dispersion of credit risk by banks to a broader and more diverse group of investors rather than warehousing such risk on their balance sheets has helped make the banking and overall financial system more resilient. The improved resilience may be seen in fewer bank failures and more consistent credit provision. Consequently the commercial banks may be less vulnerable today to credit or economic shocks. Supreme irony is that the pinnacle of the world regulatory system believed the very complex derivatives which contributed to the collapse of the financial system would render it immune from such instability. So we need constantly to be aware that banks are unstable that they're the source of money that if they are that instability lead instability leads to a crash we lead leads to a contraction in the money supply and that can exacerbate and intensify a recession. I give way too many books and I thank my honorable friend for giving way and I'm listening very carefully. Does that mean that the banks are also uncontrollable as things stand? No, they can be controlled. They should be controlled. They're controlled both in being required to have assets and ultimately in the measures government should take to ensure they don't expand lending too rapidly and that's the point I want to come on to because the other thing that are failure to focus on the nature of banking and the nature of money creation the other confusion it's caused is a confusion about the causes inflation and the role of quantitative easing. Because we don't understand or too many people don't understand where money comes from there is confusion about quantitative easing and to some extent the monetarists of which I am one are responsible for this confusion. For most of our lifetimes the basic economic problem has been inflation. There have been great debates about the causes of inflation. Ultimately those debates were won by the monetarists. They said inflation is caused by too much money money growing more rapidly than output and if that happens inevitably and inexorably prices will rise. The trouble was all too often monetarists use the shorthand phrase inflation is caused by government printing too much money. In fact of course it isn't government's printing the money it's banks lending money and creating new money a too greater rate for the needs of the economy. We should have said inflation follows when governments allow or encourage banks to create money too rapidly. The inflationary problem wasn't who created the money but the fact that too much money was created. We're now in a situation where the banks are not lending enough to create enough money to finance the growth and expansion of the economy we need. And that's why the central bank steps in with quantitative easing. And that is often described as the bank stepping in and printing money. And those who've been brought up to believe that printing money was what caused inflation think that quantitative easing must by definition cause inflation. It only causes inflation if there's too much of it. If you create too much money at a faster rate than the growth of output and therefore drive up prices. But that isn't the situation in which we find ourselves oppressive and give way to people. He's making a very good explanation of the different circumstances of the money creation. When it comes to a situation when there is a demand required and he's spoken about the morality and he's spoken about quantitative easing what is his view on the theory of helicopter money and where does money then get spread? Well, I'm rather attractive as a disciple of Milton Friedman, the idea of helicopter money. I think it was he who introduced the metaphor that it would be just as effective if the money were sprayed by helicopters if it were created by banks. And hopefully, since I live quite near the helicopter route to Barsie I will be a principal recipient. But I don't think there is a mechanism available for us to do that but I'm not averse to it in principle if someone can come up to it. But the point I'm making is that either the banks spontaneously or the banks encouraged by the central bank through quantitative easing must generate enough money to ensure the economy can grow steadily and stably. I give way. Given way, it isn't a form of helicopter money. It could be argued that increasing welfare payments because the people are more likely to spend money and that people with very little money and the economic multiplier of putting money in the pockets of those who have little money actually is very positive as it gets spent and it circulates very quickly. Well, I think there are far better reasons to give money to poor people than the idea that their money will then circulate more rapidly. Actually, there's no evidence for that. I invite the honourable member to read Milton Friedman's theory of the consumption function which showed that that's all nonsense. But there are good reasons for giving money to poor people, namely that they're poor and they need money. And whether or not the money should be injected by the government spending more than it's raising rather than the central bank expanding its balance sheet is a moot point. But all I want to argue today is that we should recognise that the economy is as much threatened by a shortage of money as by an excess of money. For most of our lifetimes, the problem has been an excess of money. Now it's a shortage of money and we therefore need to balance in either occasion the rate of growth of money with the rate of growth of output if we are to have stability of prices and stable economic activity. And I congratulate my honourable friend again on bringing to the attention of the House these very important matters. Austin Mitchell


All right. I just started recording. My name is Arun. I work for Yahoo. I've been at Yahoo for more than, what, four years now. I also contribute to Federal Project. Not that active anymore, but then I still send bug reports to these people because I mostly work on themselves these days at Yahoo. I also work on the OpenStack team now. I do a little bit of contributions to OpenStack Project as well. This talk is about how to customize Anaconda, like add your own custom patches and how to rebuild Anaconda for Fedora. I have done a couple of patches for Anaconda because one thing is like, okay, it is challenging to work on Anaconda because the first thing you search on the internet for Anaconda, you get this one. So it's really a distracting experience. Like you keep clicking this and then it never goes away. I don't know whether the Anaconda does here experience the same thing. But yeah, it happens. So why we should modify Anaconda? I mean, a lot of people never even use Anaconda these days. They just use FedUp to upgrade their software and distribution. So why? So if you're building remixes, so you might want to replace the name of the installer with your own branding and own name. And if you're adding new packages to Anaconda runtime, so why we need to do this? So at Yahoo, so we have like several hundreds and thousands of servers. And most of the hardware comes with like four hard drives. And most of them comes with more than four hard drives. Like you have multiple hard drives. The moment you have multiple hard drives, it comes with the RAID controller card. And the RAID controller kind of comes with its own radio treatise. So the person, the property, the project that wants to deploy to this hardware, they want the hardware right configured. So only way to do with Anaconda right now is to either include that hardware utility in the Anaconda runtime so that they can run their whatever prescripts, and configure the hardware right in the way they want and then install the operating system. So this is one of the things that we can, or you can include your custom utility in the Anaconda runtime where you want to do something in your post or prescripts. So I don't know why these people can answer. Anaconda never added hardware right support.  Yeah, so hardware right is really important because for us, a person who works in a big environment because on a day we have like a normal day, it's 200 machines coming up and going down. On a like a really active day, you have like thousands of machines coming up and re-imaging. So like new soft new, you know, product launch or something. So you have 1000 machines. So every 1000 machines, some person in the data center goes there manually raise a ticket and then somebody goes there and manually contrives this rate with a special RAM disk. And it's really, I mean, it's really time consuming. Like a week in advance, the particular person has to say, okay, I want to write a file on this, you know, this, and then they go there and manually modify it. This is like really, really bad problem for us because it makes like, you need to prepare a card, you know, you cannot just go and deploy software without configuring, right?  If there is a way to do instead of script running script, if there is a way for in an account that to do the right configurations with like, okay, hardware rate, put this on rate five and 10, that'd be very useful for a company like Yahoo where we have several thousand machines. There is one. Another one is adding new features to Anaconda. So you might want to add, so company like Yahoo, sometimes we always try to point out bugs and submit to Red Hat and folks to Anaconda team, but sometimes it takes a loop, you know, it takes a while to further bug fix to come in, but we cannot wait around for that. So we will time to time add patches to Anaconda and, you know, push it out. So this is where you add your own patches so that you'll be like ahead of what comes from Red Hat or what comes from Fedora. Another thing, so one more thing, this is a little bit Yahoo, we noticed is that when you are, you know, building 1,800 machines, most of the machines, you know, like the failure rate is like, the failure team style is like, let's say one percent, still it's like, what, one percent of 1,800 is 10 to 20 machines, 18 machines, yeah, 18 machines, thanks. So the person who's deploying the operator, who's deploying, has to actually go into console of this machine. We do not use Graphical User Interface, it's all text modes. So the person has to go into Graphical User Interface, look into the console, into the tool server, and figure out what the heck happened there, whether it's a bad hard drive or something blown up. It's really, again, a time consuming job. So we are looking for something like, okay, the Anaconda when it starts installing, so it starts a service where you query from a centralized dashboard where say, okay, why it failed, what's the status of the current installation, and some kind of a status API. So there are other installers that do that right now. I mean, we are trying to add this feature to Anaconda, but we might, we might, I don't know, it's a tricky thing, we might implement it or we might use the other installer. So there is an installer called IPA, which does that. So they have an API where it keeps telling, okay, what's happening in the machine, whether it's, you know, formatting files, file system or a particular hard drive went down. So that kind of status messages will be very useful for data center use cases in case of Anaconda. I don't know what's he thinking. I think it's the wrong model. What do you think is the right model? Did you see yourself with the Nebula GIFT of what they uploaded on their private cloud stuff? So the way it works is you've got one, like you've got a rack of systems, right? It's a brand new rack. You employ one system manually to pick it away, and it's a pixie server, basically, and you tell your hardware vendor to be able to configure the pixie for the first time.  The agent runs IPMI tool, sets the IPMI password, and now everything happens from the top on IPMI right now. And so it can ask, what, it's never appreciate this status, this status, what's that status, and it's running from the reverse crossing. So basically they have a custom agent running. Yeah, okay. And then we can configure it to the loader to do whatever and sort of install it into whatever we get after that. Which is a stuff above where Anaphonda is involved, right?  It's completely automated process. Rack, machine, and five minutes later it's running as well. Okay, so these are some of the things that, I mean, we can discuss about it, like what, how we can do something like monitoring of the installation status of all these things. Okay, so what are the tools people use normally to build Anaconda? So there are three tools we're going to use, we're going to use Mark. So Mark is, you know, is used for RPM building. So if you want to build on a, if you have a Fedora machine, if you want to build for L6, you will need a Mark Sherwood to build Anaconda on that. So we'll set up Mark Sherwood and run Anaconda in there. And then in case of, REL6 used to use this tool called building style, he might know a lot about it. It's a shell script, oh gosh. So you have to modify shell script if you want to add another package, anything to this runtime installer, you have to modify shell scripts. So it's a totally building style. We'll, we'll look briefly about it. We'll mostly focus on something a low-rex, for a sense. It's so much better. Yes, low-rex is nicer version of building style. It's, I think REL6 uses building style, REL7 uses low-rex. And Fedora, if you're today, want to build images for Fedora, you'll be using low-rex. Okay, so this is important. So I'll be like switching between terminals. It's not a demo. I already built a stage to SquashFS outside because with this internet, I cannot build anything right now. So, so this is like a mock configuration file. So we need additional settings.  Okay, I'll set it down. So basically, we need to enable bind mounts to lose SquashFS images. And, and also some people want to lose they, so mark every time cleans the children. So they, what to do is they bind mount their Anaconda directories into the mark zero so that it doesn't clean anything. So, if you look at my, I have a custom mark configuration file. They have, you can see mark, flock. Yeah, so I get a new mark configuration file, flock 21. So because yahoo compose some yahoo stuff here. And the important point point is the line 10 to 10 to 13. So we have a bind mount enabled and we just buy more, buy more, better and previous and same. So we, we do not use the existing mark file. So we create another one so that when, when you're building RPMs, you don't really need all this. We also do some Jenkins magic for, you know, get the environment variable and precedent. This is something related to yahoo. All right, so, so what are the installer components? So once you build a, build an installer, there are three components in installer, like as usual the pixie kernel that you won't need. And one of the, one is called RANDisk. So RANDisk, Anaconda is a big installer. It's a two-stage installer. RANDisk has your breaker stuff that actually prepares the stage two, downloads the stage two, downloads the kickstart file stage one. And there is a stage two. Stage two is a splash of this image that is in the install tree. So it's a three-stage installer. So we'll be building all these three. We'll not be building but I'll be showing I have logs of the build slip. What happens? Okay, build install. So what's the problem? It's shell script. Let's look at build install. The problem is not that it's a shell script. What is that? The problem is not that it's a shell script. The problem is that it's a really bad shell script. Yeah, let's look at it, like, see how bad it is. I had to work on this to fix it. Yeah, I do. I wrote a lot of it. So. So, I was like, why do we do that? Matt and Jeremy have been. Uh-oh. What? You've done them last. Oh, Vim. Control save, yeah. Yeah. Skateboard, skateboard here. Now, demo or less? No, both. What's the command? That's not correct. Demos. Go into 13. So this is, this is the one comes with rel. Centaurs. Scripts. Oh, it's hard. Build install. Okay, so this is a build install shell script. Actually the main build install stuff is everything is in something else. Another shell script. Which is called up-instrued. So if you have to add a new package. So you have to modify this shell script. So, up-instrued, it's hard. Yes. Okay, I'm going to sit here. Yeah. So, this is the, so that shell script calls this one. And it's almost the same as, so if you look at this packages, these are the list of packages. That's fair. So if you want to add a new package into your Anaconda runtime, you edit this thing and add this. And make sure that you use the right build install to build this. Because I mean, the build install, there is a build install outside and there is a build install part of Anaconda. So, these are the set of packages that gets insert in the squashes and images and then this is the place where you edit it. All right. Yeah. That is the reason they created, I mean, I don't know what's the exact reason. Is this the reason, like, is the, every time you guys have to do a release, you have to modify this? Is that, what's the reason for Lorex? The reason for Lorex is that if you keep on reading a build install other than that, there's a terrifying code. Actually, it might not be an intro, but it does things like try to figure out which LDSOs you need to have by guessing and entering through LVD with the thing that makes it do, uh... Yeah. And then it does a depth sorting of it, a depth solving thing and tries to sort them to try to make sure we've got all the right things in it, but it doesn't actually break up the, the, the, the requirements loops. No. No. So, so I think it's, it's written by Willem Woods, right? Lorex. Um, you know my, uh, my name. Oh, okay. So, so it's called that, it's called the tree builder. So basically it is used to generate the, like your DVD tree in there. What do you see in a federal DVD? This is what the use is generated. So why build install is hard to customize? That's what I heard from the IRC in places. And Lorex is Python based. And it uses a system called template system. So everything is a template. So they have a template file. I think it's the, what, what's the template system? Is it Jin? That's Jinjab. It's something else. Um, um. I don't know the name. Yeah. It's just in here. Okay. Is, it uses a template system where it's the templates are customizable. And if you want to add a build step, you can add your own custom templates. So it's, so it's more modular if you want to customize it. Um, yeah. It's the. So let's look at the templates. Yeah. Use the share Lorex. Make up. Make up. Yeah. So, so if you look at these pvmpl files, these are the, um, templates that are used to customize the whole image. Um, so by default it's based on the actualizing first x86 template. Um, let's look at what it is. What's that? So all the stuff for x86 stuff. A bootloader and the runtime image, the squash of this image is created by, you can go through the core layer. Um, runtime. Install post install cleanup. So everything is a template. So if you look at here, this, the instead of like having a, uh, bash variable you have like, uh, yeah, it's kind of easy to, uh, you know, add, modify things here. So, so if you want to add a new package to on a color runtime, this is the place you add, or you add your own template and pass it on, uh, here. All right. I'm going to, I think this talk is going to be like, very, we'll complete, you know, you know, soon. Uh, okay. So the patches. So what patches do we add? So I have a small patch, like a welcome patch.  Like they modify the, um, modify the, you know, trademarks and all the names and stuff. So let's look at this patch. It's called the welcome patch. I actually applied this patch on a machine. So what, what this patches does is like, it just says, um, welcome to flock 15, from welcome to Fedora. And I think this, this, I don't know. I didn't get it working. I think it's only works on a live in live image. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. But, but when you're building with Lorex, you can say the product name. So it changes the product name. We'll at least see that in the demo. And, uh, so, so these are the, uh, two patches. I ordered, I have another patch.  I can show you. So this patch is actually running, running in production at Yahoo. So April 2015. Um, okay. So this is a patch that adds top payload support for a well, six in seller. So the concept is that we have a lot of, we don't install into the lot.  So we do a lot of tar balls.  It just reduces time. So, uh, we currently have support. Thanks to our kind of team. They have added support for tar balls on some point one nonversal. Yeah. Some point one. It landed on some. So even before they added, we, we've been running that patch now. Well, six, we needed, we needed real, we have had a customer in seller and, uh, we wanted to move away from it, try different things. So Anaconda is one of them. So we added a patch to Anaconda, to add support for top payload. How it works is that you, uh, you specify during installation, you specify the current command line top payload equals the URL of the top ball. It automatically passes this top payload argument and downloads this top ball, creates partitions and extracts them onto the disk. So it's very simple like a, and, but it kind of, uh, we have to hack into the installer to divert to do this. Otherwise the installer will do something else. So I think this is some form of change. I did, I don't know why. Okay. I shouldn't have. Yeah. Oh, old codes. Like, uh, the old Anaconda code is lately a little bit hard to read. The new code is really good. I mean, uh, from looking at the old code and the new code, it's well-organized and obviously well-organized. The new code is well-organized. But I, I mean, working on OpenSec, you see like things like docs and unit tests, but I don't see anything, anything here so far. Do you guys have plans to add it? There's, there's some unit testing out of the test group. Okay. There's some stuff that they've been involved with. Yeah. Oh, really? Yeah. Okay. I'll talk to you guys. I mean, with that, I'm also going to send a picture of the key to the RunOpen group. Okay. So I'm going to ask the group, it's happened to touch the whole thing out of the unit tests, but... Yeah, so this, this after applying patch, what we, what I do is normally, uh, create a ISO image, and then boot the whole thing in a VMS like a test. Uh, if the VM works, we just push it to, uh, like a centralist or positive, and then it goes to production automatically. It's like a small dump test, but, um, I think the current team does more tests where they actually deploy the installer, use the installer on a bare-model machine, and do the tests. Um, so, so this flag actually comes from, uh, is sent by the code that process the, the kickstart files, sorry, the kernel command lines. So if you find the top payload flag, it calls the top payload back in. It's both for Fedora and Dell. And if you look at the top payload back in, um, so you just, what it does is it finds out the size of the, uh, top ball, see if it can write it to the temporary file system on the disk, and it downloads it, and, uh, uses a progress bar that's a progress bar. It's almost like equaling to the one that you guys have in live image payload, uh, except it's for L6, which is like the older installer, and it extracts the whole thing, um, onto the disk. So this part is little important. We use no ACLs because there's a bug in tar. If you use ACLs, it sets the default ACLs on all files. So we got a, this, we had to disable it because it's kind of a security vulnerability to set the default ACLs on all the files. Um, so we extract, uh, actual, uh, files, the top ball onto the disk using this command. And then are you, are you certain that we label or what? Um, no. Okay. Should we? I don't know. So we don't use, we do not have ACLinux enabled on any way. Yeah, so, but the ACLinux flag is just there, you know, in the future if we decide to do that. We should probably trigger it, relabel. Yeah. So there was two bugs open on, uh, against redact. So it's fixed on Fedora. That patch is not, yeah, the patch was not never put back to tar. So to, I think it's tended to, I think it would be released with 7.2 and 6.8. I don't know why 6.7. Um, but, um, let's see. Yep. So we do some sync and then, uh, we, you know, this, this all runs in a thread and this is the patch. So this patch is supplied against rel6. Um, okay, let's go here. Okay, this is the command actually, uh, to build the, um, stage two scratch ups image. Um, so what it does is this is a product with, I have a make find that does this. I mean, I have published everything on my page. Um, I'll give you the link later. You can go look at the patch and all they make for if you want to do it yourself. Uh, so Lorex command is the product name. So this is your new distro. Uh, and this is your, uh, version of your distro and the release. So this, yes, this is the report. So normally it points at the upstream report, which is Fedora. And this report is probably the updates and the final one in Anaconda. So you have built Anaconda. So I, what it is, it is like, I applied the patch to Anaconda. I built Anaconda. Now the Anaconda version has to be a little bit like you bump the release so that it's a little bit higher than the one that's available at, you know, the Red Admirers or Fedora. Yes, to get in the image and, uh, you point your, um, appoint this to the Anaconda. And finally you say it is final. This is a little bit important. Otherwise, Anaconda will keep telling people that, oh, you're running a pre-released version. Yeah. And another important thing, another thing I noticed is, uh, uh, if you're building and building this on a RL6, but you're building for a RL7 on Achirud, sometimes this, um, I think it's the Fedora image. I think if you're building Fedora on a RL6 machine, what happens is that, um, the Mac good stuff. So basically the HFS, uh, they don't have HFS drivers. So you probably need to say no Mac good, uh, in the low-res tamales. Somebody added a patch recently, I think like a month, two months ago I added a patch to disable no Mac good. It wasn't there.  We certainly never built it on RL7, but that would add between the two and so that it would be a Fedora feature before the RL7 was built. Yeah. I, I, I totally understand what it comes but when you're like working in working in an enterprise company, like you, you have like RL6 popular thing right now at RL7. We are just adopting into RL7. Um, so no, no Mac good options there. That's for people. So it writes all the things into trees. So let's look at the Mac file. That's the like, uh, important thing. So how do you build the whole thing? I, I'm not going to run the Mac file. I just ran before this talk and I have the logs and the image. I'll show you that because if you run it, it will take another hour with this entire connection. Um, so I have a Mac file named macfile.lorex. So as you can see the, all the files are like, uh, it's a plot and 21 and exactly 64 and, uh, so I have a command called a small macfile variable called ranmark. So it uses it's going to use the block 21x664 compass uh, mark configuration file uh, which has the bind mounts enabling everything. And, uh, so I have a one I'm not going to use the updates mirror. So I have a, um, mirror study of MIDI. I think a MIDI is closer here. So just a little faster. So I have a Fedora mirror, which is like a 21 mirror here, base mirror, no updates. My Anaconda, I have a web server running and I copy it on my Anaconda 2. I mean, I don't know. I try to use the file flag. It just didn't work. File, colon, colon can. What is it? Uh, I didn't. Yeah. Yeah. I forgot. Sorry. I don't know why it didn't work. Yeah. Okay. So, um, so this Anaconda mirror, um, so right now, so to work around that, I just started my HDTBD. So you can see, um, I can have one more WWW STML Anaconda, so it so it just has uh, all the Anaconda RPMs with the bump release pump dash 2 which has a patch in it and then I put it up. Um, yeah. So it will retire from that. So I also, I'm also going to test this image. So once I have the image, I will just start an EM and see if it works.  Okay. You can ignore that. So the main, main thing is the mock tree. So I should have run like dash dash scrub all. I normally scrub everything and you need the mock tree again, but with this internet connection I cannot afford to scrub anything. Yeah. So what I do is I, uh, install, uh, low-rex into the mock tree first and then I copy my current working directory which has the actual, this main file and the actual code to build the whole thing into the into the, uh, mock tree. And then here I can do, you know, do the seeding to the work directory and then I call make file dot low-rex to, I don't know why you play. So I call them low-rex clean make, uh, and I don't know what's there. I think it's probably uh, low-rex, uh, tree. It's probably clean and tree. So it's probably first clean. Clean the whole thing and then again, uh, because the tree it builds, uh, the low-rex it uses the low-rex command to actually build the thing into the tree and then, um, finally, uh, this is the clean. So it just cleans, just deletes all the unwanted stuff and, uh, this is where the whole thing runs. Oh, this is important in case of Fedora. So... Oh, yeah. Yeah. Okay. So this is, uh, so if you don't exclude this, um, you know, product, this package is, it'll, it'll, you'll, you'll run into Depsol when you're creating the runtime image. Um, so the product of this is right now stored here. So we have EFI images, ISO Linux, and Live OS. The Live OS has the squash of this image, which is stage two. I think EFI... ... So that, I think ISO Linux has the kernel and the round disk. Um, so, so this is basically, uh, and then, I think images, images has the boot.iso. ... Yes. So this is basically like a DVD tree, uh, the whole thing is created. Let's, let's test this. So this is created, um, I have the build lock here, um, I don't know, I don't think I have to show this, but, um, so I'm gonna just, uh, do a meek. So what I did is, I built the ISO and, uh, I patched the whole thing up, and I, I'm gonna run from here. Okay, I have the, I'm just going to do a quick test using VM. So I just created a boot.iso. I'm injecting a kickstart file in there. But it will show you like the actual boot and say flock 21, um, I haven't replaced the, you know, the logos and all this, but just want to show you like flock 21. Uh, yeah, there you go. Just gonna go show the actual graphical UI, so it'll show flock 21 there as well. So, I don't know, a lot of people may not have, you know, don't need to really like do all this because, uh, Anaconda just works most of the time. But, uh, if you're working in a company, big company enterprise, which you want to use, wants to use Anaconda, if you want to reduce dependence on, uh, red ads, you know, release model, they take a little bit of extra time, you want to fix it fast because internet companies are like fast. Uh, things move fast. Um, so, uh, we, uh, you have to do this. Okay, any questions? Uh, so, if you're just adding an RPM, would it ever just, uh, for hardware? What is that? Uh, instead of building a whole, uh, new image with your back RPM, would you just, uh, use the stocking there for the hardware? Updates that image? Yeah. Certainly, we have the ability to add updated images, but I mean, it's just normal, like, um, Oh, with the driver? Yeah. Okay. So, maybe you guys can send me the instructions on how to do that. Uh, yeah. Documentations on this, I think most of the things I brought up from BCL, BCL is here? No. No. So, he, he, he has a tricky page, his user page has some instructions. And, uh, if you guys can send me stuff on, like, uh, the driver image. Yeah, it's a little hard. It's hard to find.  If anyone wants to get started with, uh, playing with Anaconda, want to contribute to the Anaconda project, um, it'll be a good point to start.  Okay. Maybe you guys are here, right? Maybe I can talk to you guys about it. Huh? I'll, I'll catch him. He's not hiding. All right. I'm going to stop the presentation and thank you everyone for coming and, uh, despite the uh, Fesco. Yeah. Yeah.


Welcome to today's webinar on DMP data management planning lessons from Europe. My name is Liz Stokes. I'm coming to you from the University of Technology, Sydney. And I am part of the skilled workforce team of the Australian Research Data Commons. As we begin, I would like to acknowledge the Gadigal people of the Eora Nation and pay my respects to Elders both past and present recognising them as traditional custodians of the land on which I'm standing here. Our guest speaker today, Sarah Jones from the Digital Curation Centre in the UK, is joining us from the traditional lands of the Boon Warung people of the Kulin Nations where she's visiting the University of Monash Caulfield campus in Melbourne. I'd like to pay respects to any First Nations people who are present here today and acknowledge that Aboriginal sovereignty has not been ceded in this country. So, on with our program today. So I'm very excited to introduce Sarah Jones to you who has been working as part of her work. She's the Assistant Director of the Digital Curation Centre and she has been involved in data management planning on a lot of different fronts, most specifically with her work in the DMP online. Sarah is going to share with us some lessons from Europe and what's been happening with DMP infrastructure and machine actionable initiatives. Sarah, I'm ready for you now. So thanks very much for being for Liz. What I'm going to do is talk about data management planning. It's an area as Liz mentioned that I do a fair amount of work on and I'll reflect on what's happening in Europe. So I'm based at the DCC in the UK but we do a lot of work in the European context. These slides are actually already online if you want to grab the slides but they will be shared afterwards as well. So I wanted to begin by just setting the scene. I don't know to what extent you're all familiar with data management plans so I'll give a bit of introductory context about what plans are, kind of the drivers for these and some of the recent developments and then what I'm going to focus on is talking about some of the trends from Europe, how that's informing our work and potentially it could be useful in your context too. So first off I thought I'd start with a definition of a DMP. At a very basic level, a DMP is a formal document which outlines how research data is going to be handled both during the project and after. And certainly in the UK and the US context, data management plans have often come up when people are applying for funding. They're something that goes in as part of a grant application. What we're seeing is that people want to make sure that there's proper benefits that come from data management plans and that it's not this kind of static, secure document. So you can see a second definition here that we're talking about dynamic inventories of research methods and outputs that evolve over time. And I think some of the work that's going on in Australia is more aligned with this definition. You're often having tools that are more like data management systems that are really capturing everything about the output being created. And then a third definition you'll see here, this comes from the Fair, Learning Fair Into Reality report. And this talks about DMPs being active and enabling information exchange across different tools within the system. And that we tie the DMP to its implementation. So really what we're seeing in terms of the definitions is that this kind of machine actionable agenda is coming more to the fore and that people are thinking about data management plans beyond just being a document, something that is tied to the implementation of a plan that evolves. So the vision for data management, machine actionable data management plans is really going beyond this static document into something that is a lot more useful to the different stakeholders involved. And in these bullets here you can see some of the data better and discover data more easily because the DMP is really the first indication of what data is going to be created. Having a kind of machine actionable DMP can help infrastructure providers to plan their resources. They know what the requirements are in terms of storage for example and plan the capacity that's needed. So it's really helping people provide more effective data services and actually having something that's more machine actionable can help funders to monitor their data related activities as well. There have been a couple of papers that I would point to. A couple of years ago we did a workshop where we tried to gather requirements for machine actionable DMPs and since then we've done a paper on 10 principles for the MADMPs. If you're interested in this area there's some background literature. There are a number of drivers for data management plans and I think these vary in each context. So I mentioned earlier that in the UK and the USA the requirements are really coming to the fore. That's the way most people hear about big management plans. It's usually when they're doing their grant applications. But universities are also putting expectations out around DMPs. And I think particularly in the Australian context that seems to be the biggest driver. And there it means that the priority can be quite different for different institutions. It might be about risk management. It might be about their capacity planning and making sure that they actually provide the right kind of environment for the different research projects. All people might be completing a DMP to achieve another goal. So in Australia you seem to link your DMP to the storage allocation often. One of the big drivers that came up in university in Singapore they actually don't release the funds from different research projects until the DMP is completed. So the research office has quite a strong mandate there. So that's why researchers are engaging. They want their funds released. And also it might be to try and engender good practice. So often data management plans are starting to be created by HDR or PhD students as a way to try and get good practice in early on. In case people aren't familiar with a data management plan it's typically something that's covering the whole lifecycle of the data. So what's going to be created? How that data is going to be created and managed? So what standards will be used? How the data will be stored and backed up? There are usually questions around ethics and intellectual property largely in terms of any restrictions on the data any sensitivities or restrictions on sharing and then the DMP usually covers the longer term plans for sharing and preservation as well. There are a number of tools available for data management plans already. So ourselves at the DCC we offer DMP online and in the States there's a tool called DMP tool. We actually came together and joined up our code base so we have a common open source code base that we run each of our services from. There are also other tools in the European context like RDM Organiser which comes out of Germany and in Australia you have several tools like Redbox which is offered by QCIF or the research data manager at the University of Queensland. I think it's probably about a year ago now we set up a site called Active DMPs where we're trying to hold together the different requirements for data management plans and the tooling specifically and also to record the different initiatives that are going on. So I'm conscious that we don't have the CYRO RD plan at all in this list so if there are other activities you're aware of this is actually, you can update it yourself by submitting a pull request on GitHub so please share information about other tools or correct any mistakes in this. So I've been here on placement for I think about four or five weeks now and I've learned a little bit about the Australian context and these are just my reflections. You seem to have a much less formal funder requirements here. There is a code and it doesn't mandate DMPs there's an encouragement in the kind of guidelines associated with the code but you don't have very heavy drivers from funders so it's typically the institutional perspective of driving your DMPs here and as I alluded to before I think your tools are quite different to what we have in Europe because they have a much broader coverage. You are often talking around data management as a whole concept and having tools that cover the allocation of storage and link to lab notebooks and have integrations with that wider ecosystem rather than just having something that's about the plan. I think that's a really positive step. I think there's a lot that we could learn from you as well as you learning lessons from Europe. In discussions with a number of the tool providers the key piece of work that seems to still be going on in your context is the end of the life cycle. So once you've got all your data in your system figuring out how to select or keep and how to publish that data and link up with your repository infrastructure. I did a blog where I've made some reflections on the Australian context and ideas of how we could potentially collaborate further and I'll pick up on that again at the end. So what I want to do now is talk about some of the emerging trends in data management planning specifically looking at what's going on in Europe and elsewhere. So as I mentioned for ourselves in the UK and for the USA the funder requirements is a very big driver but globally there are lots of funders that are asking for DMPs. It's not just UK and Europe. This list isn't comprehensive but it's just to show you the breadth of funders. It's from all different areas of research all the different kind of supplementary funders as well as big national ones like NSF or the Academy of Finland. What we're seeing is that the requirements from funders are starting to change so traditionally they would always ask for a DMP at the application stage but increasingly funders are shifting their policies so they either require a DMP during the project or they expect the DMP to be a living document that's updated. So NERC in the UK for example they have a very basic requirement literally I think three or four questions for the DMP application stage and then they expect a full DMP to be written in conjunction with the designated data centre once an award has been made and the European Commission they don't actually ask the DMP at the application stage although some details can be submitted about the data plans. They view the DMP as a deliverable and they expect that it's something that's updated at least at project review time but whenever significant changes arise. With the European Commission I think because it's a deliverable that's changing people's attitudes to DMPs a lot more people are publishing their DMPs because they expect to publish their deliverables and I think that's actually quite a positive shift because if information is available there's more we can do with it. The other shift we're seeing particularly in terms of funder policies is that the owners are starting to be placed on universities a lot more. So in 2011 in the UK the EPSRC which is our Engineering and Physical Sciences Research Council they released quite a different policy quite groundbreaking because they weren't saying that research is needed to develop DMPs that's the typical policy statement in the UK. They said that the research organisation has a responsibility to support data management and uni should ensure DMPs are in place and maintained by funders but really what they were looking for was a response from the institution not from the individual researcher and they expected institutions to show that they had policies and infrastructure support for data management and that led to the growth of a lot of data services within UK universities. More recently our Arts and Humanities Research Council has updated its policy and it has a similar on us on institutions so now when a research organisation is within a grant they have to pick this statement which confirms a whole series of things that they agreed to and I've put a basic summary of some of those in this quote and I have a sign that the institution is able to store the data appropriately during the life cycle of the grant that the relevant people are being consulted as you know the research team has spoken with the library or IT services and that the plan that's been put in has been considered and agreed by the institution so that's quite a big step and you know it makes sure that you know could put the institution at risk if there are things in those plans that they haven't checked but this again is driving new approaches within UK universities they're starting to more proactively check data management plans before they go as part of grant agreements and another funder in Norway, Research Council in Norway, they have introduced the policy and again this is expecting the university takes more control really that they will check the MPs and make sure they're made openly available it's only these for these policies certainly the HSE and Research Council Norway ones some of the bigger institutions more proactively responding but I think it will take a while for a shift there because this is a lot of work and responsibility on institutions I think what we've seen so far in light of this is that institutions are starting to use these policies or these shifts to make a case for more support for resources internally so that they can provide this support the other shift we're seeing in terms of the coverage plans and more than welcome trust issued new guidelines in 2017 that asks for an outputs management plan rather than the data management plan and they ask that this OMP covers the data sets any original software new materials like antibodies or cell lines or reagents and also that it considers the IP so what's going to be patented or copyrighted and what kind of confidence know how there is that's going to come out of the grant the EPSRC has a requirement in some of its programs for software management plans too I think it's really what I would like to see is that we start to broaden out in the way that welcome trust has that when we're thinking about a data management plan we're not just thinking about the data because actually it's kind of meaningless in isolation you need the code as well you need to know you need to have all of those different outputs and that wider context I want to reflect on some results we got from a survey we did in the European context through openair which is one of our big infrastructure projects and the third day expert group we looked at the Horizon 2020 DMPs so we did a survey I think we got a couple of hundred responses that were from researchers that put PIs on Horizon 2020 awards as well as support staff within institutions that were working with these research groups and I was really surprised that we got 60% positive response to whether a DMP is useful or not I expected a much lower figure because the Horizon 2020 template is really quite long and complicated but these quotes that I've highlighted here even when it is like that people can still find it quite a useful exercise so there is this concern that it's administrative but on reflection people have found it useful or they found that it's a bit balanced it was frustrating, it was cumbersome in part but they actually found that that reflection on the potential issues and how to address them within their project was a valuable activity so I think it's actually good that people are finding the process useful and what we need to learn from this is that we need to make sure the DMPs we have are on a burden so we need to keep them as short and simple and as kind of tailored to the local context as possible so that we're not just asking for various information we're actually using that information as much as we can and pre-inputting information where we can do one of the concerns that came out of that survey we did was that language is a real barrier so in the European Commission context under Horizon 2020 the DMP template is essentially structured around fare and the respondents of the survey mentioned 40 terms that were unclear to them and you can see the primary ones in the word cloud here and I think sometimes we don't realise that a lot of the terms we bandy around are really not clear to researchers so asking them how their data is going to be improper or asking them what ontologies they're going to use can leave them confused and I really like this quote at the bottom one of the respondents who said that without the help of their Swedish National Data Service they wouldn't have been able to do the DMP so I think this shows that we need to think about how we define the DMP to make sure it is clear but also we do need support services to understand and complete those DMPs in some cases the other thing that came out quite strongly is that the priorities for support from the users were really to simplify the DMP so we gave them a whole series of options that they could prioritise and the things that came out at the top were suggesting relevant standards giving example answers providing more dropdowns based on what's good practice for given discipline or more disciplinary guidance and tailoring so people are really wanting these recommendations they don't want a free text box they want I'm in engineering give me some clear pointers as to what I should be doing or what's the good practice for my field we're interested in things like prefilling information or sharing information with other services but they came lower down so I think we need to make sure that some of the basic are in place decent templates and good guidance go a long way another thing is that universities are requiring potential plans from HDRs or PhD students and this is really to try and make sure we have good practice early on in research careers and one of the things that's come out that's working really nicely about this is that often universities are asking supervisors to review the DMP and that's a way to try and get PIs and more senior academics aware of good practice in research data management and sharing so they're not asking them to complete the DMP themselves but they're kind of training them via the back door there was a whole discussion on the research data manager and they all list about this a couple of years ago and actually that just got reinvigorated just a couple of days ago I think it was Anna Clement or somebody had asked for updates so there's currently a discussion thread going on about this and I mentioned that more DMPs are also being published nowadays certainly under Horizon 2020 because it's a deliverable project seem quite keen to make their DMPs available some publish them via tools like DMP online others put them in repositories like Zenodo or publish in journals and I think it is good if we can encourage people to share their DMPs early and openly because that enables us to reuse more of the information to inform service delivery or to help the discovery of data sets it also helps to provide examples of good practice for others to learn from and I know a lot of universities in the UK and elsewhere are trying to have libraries of good practice DMPs as a training resource so I want to close by thinking about what you can do and where you can learn more and I think if you're engaging in data management plans I think it's good to offer a range of services you don't want to just offer one thing, one tool or one approach because researchers will vary and will want different types of support so I've given this example from Stanford University obviously because it's in the States they have a lot of funder requirements so they have information on the different funding agency requirements they've got some good practice guidelines, they have an online tool, FAQs and workshops and they also offer DMP review service so people can submit their planning and feedback and I think it's good to offer a range of different types of support I think that data management plan can also be a good talking point this slide comes from Marie Lisa Kuznieny at the University of Helsinki and there they kind of have an RDM consulting service where they bring together different stakeholders from the institutional services but they also will help research teams think about the best ways to manage their data and it's a way for them to raise awareness of the different expectations that a researcher might have to meet from their funder or publisher or elsewhere but also to help them understand the different areas like research ethics and to point them to relevant services from the institution or elsewhere and sometimes that discussion can be a really good way of actually fleshing out the DMP another impression I really like there was a project in the US called Dart which is DMPs as a research tool this was a three IMLS funded project and what they did they developed it's something analytic group it reviewed data management plans so they loved to watch it be covered and talked about you know what is a good answer, what's a reasonable answer what these entities are poor answer what kind of gaps need to be addressed and they find a whole series of DMPs to allow good examples and poor ones and use that to analyse you know where communities were at and to use that to inform their service delivery in the different academic libraries that were part of this a group of institutions in the UK and across Europe have kind of copied this approach in terms of developing rubrics so we have evaluation rubrics for various UK and European funders and they're often used by institutions to try and review DMPs and to give pointers and you can see information about this online I mentioned before about sharing examples of DMPs and there are already some out there that you can use for inspiration LIBA which is the League of European Research Universities has a catalogue of data management plans on DMPs in Odo and they're using a rubric to evaluate these plans and to give pointers as to what strength and weakness of different plans and through tool site DMP online you can also provide kind of catalogue I've noted here the different visibility settings we have are DMPs private by default but organisation or individuals can choose to make them visible within their institution so you have a kind of internal library university or they can also make them public and the other thing that I think is really important is connecting with peers and sharing information with others who are kind of involved in data management plans and I wanted to give the example of how we do this through DMP online so we have regular user groups where we bring people together and we talk about what features they need and kind of flesh out the idea for new features and consult them on how we develop that we have various socials around those user groups as well so the picture in the middle here is which we did wait for and to build rapport across the community I think that's really important because we want people to be able to approach any kind of issue or a small niggle so that we can try and address that within the school we obviously have help desk in various ways for people to get in touch with us mostly drop-ins and one thing we've been doing is a knowledge exchange so we have a blog post every month that comes from somebody in the community about how they're supporting DMPs and in our drop-ins we're also having them give a brief chat so we can start that discussion and promote sharing the cross-institutions about how they do this work we've got a newsletter as well you're welcome to sign up that comes out of the UK efforts of interest to you there is also an ARDC DMP interest group and this is to enable information exchange across all of those working on DMPs so in a similar vein to what we do in the UK and this connects up Australian and New Zealand initiatives with other international efforts I think one of the things that would be useful to discuss on this call is what you want to see from this group so it could provide information and link to the RDA and other global initiatives happening in the DMP space it could offer that kind of monthly knowledge exchange so that you can all share what you're doing and learn from one another or it could provide training and guidance resources so it's really for you to steal what you want from this community and I'd encourage you to kind of put your ideas forward to ARDC there are also international initiatives through RDA which is an active data management plans interest group which is a kind of umbrella group to look at what's happening in terms of DMPs globally and promote coordination and that interest groups are now a couple of working groups one that was about developing common standards for DMPs and one that was about exposing DMPs by taking certain information from DMPs like storage and volumes and sharing that with relevant information and developing essentially an understanding of the different use cases who needs access to what content and when you do have two Australian co-chairs of these groups so Peter has been from Melbourne has been involved in the common standards work and Katharine from Cairo in the exposing DMPs group so I would encourage you to reach out through them but also to join these RDA groups and get involved in the work because the Research Data Alliance is coming to Australia next March I personally think it would be really interesting to do a co-located event on data management plans I've been really impressed to see what tools you have in your context and I think there's a lot of ways that we could exchange internationally it would be good to understand the different requirements landscapes obviously you're not driven as much by funder policies but you do have different user groups and community needs it would be good to share what are the key features or a bit of functionality we're adding to each form what are the trends that are emerging I think it would be good for us to share information on the different tools we have so potentially where it's feasible sharing code but just learning about the functionality in each form what the development roadmap is trying to promote tech exchange so that developers have a forum to share ideas and have a wider sounding board and I think there's lots of ways that we could explore different options for global collaboration so around things like the common standard or integration between different tools DMP tools with other services creating registries of DMPs or different peer support networks so if people are interested in trying to coordinate an event please do reach out to me that's something that I'll be discussing with a number of people and trying to get set up so this if you haven't seen it already is details about the next RDA plenary it will be in Melbourne on the 18th to 20th of March so I can't remember what place of the week that is the co-located events are usually the day before and after and the final thing I wanted to flag if you are delivering services I'm looking at doing data management services we actually have a MOOC that's starting in oh my god not too many days from now and this is about RDA services as a whole it does have sections on data management planning but it's about the broader services at the institution it's run by the DCC together with research data Netherlands so if you're interested by all means sign up and join in the discussions and that I think was the final slide so I can hand back to Liz okay I am going to show I'll show some of my screen but I'm going to bring it over to the over to that and move that along oh no we can just stay here for the moment so oh but if I show my screen then you get to see my terrible google doc that I've collated from the questions that people have brought together before I'm just going to embrace this on the wing here and so these were so here we've got some of the questions that have come in as people registered and Sarah I think that you have your presentation has answered quite a few of those but I thought I would just like to highlight a couple of the more practical questions that came through so if I might ask you one how I thought this question about what are some ways to keep data management plans down to a manageable size for researchers or are some common redundant or less useful questions like what when we're talking about optimising these what kind of advice would you have yeah so I think one piece of advice is thinking about when you're asking for the DMP and what people can realistically answer each stage so I do like that it's very minimal at the grant application stage and then the DMP wants an award to be made because really at that early grant application stage you only really need to know a few key things like is there a large volume of data are there key sensitivities have people costed in relevant support and it's kind of later on when the project's underway you're actually starting to create the data that you really need to think about the best way to create that data the relevant standards and how that data is going to be shared so you can make sure any agreements enable that sharing what typically happens and I think this is why sometimes there's a lot of resistance to DMPs people are given all the questions right from the off and half the time they won't have the answers till later because they either aren't starting the work yet or it's very early days and they haven't determined exactly what will be shared or how or where so I think trying to have the DMP evolve with more questions coming in at a later stage is a good way to do it and I also one thing that I've been struck by here is that you because your data management tools are connected to other systems you pre-populate things a lot more definitely good the more you can have pre-filled and have researchers either just correct or not have to complete the better because if there's empty boxes and you already have the information somewhere else that is really frustrating true and there are also some questions as we can see there about some ways to keep about pre-population another question that's just coming from the chat now have you come across DMP tools that are integrated with other research management services at the University of Canberra we use a research management system called PURE I'm keen to know if there are tools that are already integrated or DMP tools that can speak with other tools yeah so the three examples from Australia the RD Piner SIRO UQRDM are all integrated with other tools within a given institutional context so the UQRDM is at the University of Queensland obviously and SIRO is within their own organizational context the QCIP tool I don't think they have a pure integration but they've been connecting with different lab notebooks and other things I can't think of any tool that's connected already with PURE but there are tools that are working across different systems and exchanging information but at the date they seem to be mostly within one given institutional context although the QCIP tool is open source so you could reuse integrations that others have done can I also ask a question about let's see I'll just go over to the chat box he has a comment about I like the idea of a tool agnostic working group who would help an institution to drive the agenda on support and simplicity of a chosen tool recommendations could then be used as a case for change Christopher I have just got my brain's not working so I've forgotten where you're coming from but you say that you have always presented the DMP tool as something that is a working document and can be revisited over time but the machine actionable concept shows great value and therefore more engagement over the life of the project it's Deakin University thank you Chris okay yeah I think I think having two agnostic working groups as much as possible is best and the RDA groups try and work like that so it's not so even though you know I have a code of one of those groups I don't do it for the DMP online I'm trying to look broader than the tool per se because I think there's a lot in common across all of these tools and we think about the underlying requirements it helps affect the whole more hmm can I um I'm going to bring in a question now who's made a comment that it's definitely good to make DMPs as small and frictionless as possible but it's difficult to change the format slash template once created or to make completely ad hoc DMPs so how do you balance that future funder requirements yeah so I think one thing that impressed me when I've been having meetings here is that people seem to have taken a long time to think about what's in that template and I strongly encourage you to do that so when in the UK we kind of went through a transition that all of these different funders had multiple well they all had one template but you know they meant that we had seven or eight different templates that different unis were using and then universities also introduced their own templates and most of those were very long it seemed to me that it was more about oh what could we ask oh we could ask that and there's a million and one things you could ask so I would really encourage you to think about what you need to ask and how are you going to use every piece of information because you don't want to be asking things just for the sake of it you want to make sure that you do things with that data that actually a researcher providing you with a piece of information about the data they'll create or how they will manage it or how they'll share it either get sped off to other systems or informs something you provide back to them and I think that's really the way to try and keep it minimal and I would take a lot of time to develop that template and test it and develop the guidelines that go with it because the kind of best templates have seen a number of iterations so ESRC for example they had a template they've had one for years but they have looked at the DMP that have come in they've looked at the responses and they've gone ah people are not understanding the question and then they've revised the question or the guidance and I think that's an important thing to do and they take time when you go through the development process certainly there's an example the DMP interest group previously has heard from the University of Technology Sydney where they have turned to their DMP tools so they're using the QCIF red box software and that uses the DMP as a foundation for future data management description for archiving and for publication so there's certainly which I think is a really great method of being able to move from being able to pivot I guess if you will an administrative form that then can be reused in other circumstances and answering other stakeholder comments I wanted to also follow up with a question just note that there was a question in there about changes to the Australian code for the responsible conduct of research and how to accommodate some of those in the Australian context there has been this code strongly encourages the use of data management plans although it doesn't necessarily enforce that however the authors of that code the National Health and Medical Research Council here in Australia have also published a policy on ethical an ethics policy which requires data management plans for research on human subjects so there have been questions on how that can be managed especially from the point of view of people who support researchers within a hospital setting who may not necessarily have access to their data management that hospital organisation or their research centre may not necessarily have data management planning infrastructure in place yet our our response from the ARDC is that most of those researchers will likely have an institutional relationship who are required to provide that kind of infrastructure through the code as a responsibility of institutions but I wondered if you had any other comment on that in terms of DMPs for for research that includes human subjects or potentially sensitive and confidential confidential data does that make things more or less difficult for the sharing and progressive DMPs Yes I don't know exactly what your ethics requirements are here but what we see in the UK and Europe is that sometimes there's duplication because what people are asked to do in a DMP can be similar or fairly close to what they're asked to do within an ethics approval like an ethics statement that they have to submit so I think if certainly if it's being pushed that the projects that have sensitive data are the ones you need to do DMPs I would strongly encourage trying to align any forms researchers have been asked to fill in so they're not then having the same set of questions as twice I think with sensitive data yeah it's certainly more critical to make sure that it's handled well that people are aware of some of the risks and make sure that the data is stored appropriately that it's only shared with relevant people but also I think with sensitive data it's much more important that people will really do the planning from the outset because if they don't get consent to share or if they don't think about that along the time reuse then often they can't do that so there might be an expectation from the Australian funder or HMRC or whatever they're called that the data is shared but if people haven't got consent for that then they're not able to so I think this is why it's important to consider it early on to include that in the kind of research project design and the sensitive data yes it's there's more restrictions that may need to be placed in terms of the sharing anonymising the data or having sharing agreements that control who can use the data for what purposes or how the data can be accessed it might be in a secure data service so these things are important to consider it doesn't necessarily mean the data can't be shared but it does need more thoughts and more planning so it's certainly good to encourage that early on okay well thank you very much for that Sarah and I I'm just going to switch over to some information now in terms of wrapping up about the data management planning interest group so I encourage everyone on this line if you're not already part of this interest group you can join our Slack workspace there at choosing that bit.ly link which will take you to a workspace called Data Librarians but it's not just for Data Librarians where you have there is called DMP Hyphen IG so we have a current community project on building data management planning advocacy one pager resources which are tailored to different shareholders there this project we're going to launch at the birds of a feather session the first round of one pages that we've produced at the e-research Australasia conference in on the 21st to the 25th of October in Brisbane this year that birds of a feather session is quite interesting and we're certainly being innovative in that it will be a project runway style reality TV birds of a feather session where DMPs and their builders will compete for various prizes such as most fair DMP and best demonstration of machine actionable action and other such very serious categories so watch out for that and I encourage you to join us on our Slack channel to continue this conversation so I'll put some of those questions that came in through into that channel following this webinar and we will endeavor to share this webinar with people in the next couple of weeks ok so thanks very much again Sarah for sharing with us lessons from Europe and your thoughts on data management planning advocacy and machine action ability and I hope everyone has had a great time in this last hour excellent thank you very much and with that I guess we're saying goodbye bye bye ok bye everybody thanks for joining


Good morning everybody. Today is September 12th, 2018. Just getting to my computer, 10 minutes into the opening bell, and I see that we got a signal here. I literally just saw this here. And we're getting arrows here, but there's no momentum on the 15 minute chart. So I'm going to go ahead and skip this one here. Just because, well, the moving averages aren't to my favor. Sure they're moving up here, but they're just not to my liking. The 15 minute chart, the momentum is still fairly red. And the moving averages, they're not to my favor either. I rather sit on my hands here and just wait for a better looking signal. With that being said, I just pulled up forexfactory.com. I do see crude oil inventories coming out at 10.30 today. So that's another reason why not to trade until it gets closer to 10.30 eastern time. That's 8.30 my time. We got about an hour. Okay, 50 minutes until that report comes out. So let's just sit here, watch it, and see where we go with this. I really like puts right here. I really, really do. There's my signal. I got filled on the 288.50 puts that expire in two days. I got filled at 78 cents. And I'm looking for 7 cent move. Oh wow, let's go ahead and mark it, verify, trade. Oh wow, I sold out at 84. Sold out at 84 cents. Awesome. I didn't mean to do that. Yeah, I bought at 78 cents and sold out at 84 cents. So what ended up happening is I bought in at 78 cents. I was going to set my sell order in at 85, 86 somewhere in there. But instead of setting a limit order, I set a market order. And it actually sold me out at 84 cents. So I made 6 cents on that trade, which is okay. I'm okay with that. Had I traded with, let's just put it 10 contracts, which is $780. With the exact trade that I made, I would have made 60 bucks in 26 seconds. I mean, you can't go wrong with that. Boy, that's looking really, really good there. But anyways, thank you so much for watching everybody. Smash that subscribe button, smash that like, share my videos, guys. It'll help me out tremendously. See you again here tomorrow, guys. I will be able to watch the markets from the opening bell. So I'm excited about that, guys. Thank you so much for watching. Have a great day.


Learn English with pictures, 22 Things in the Kitchen, from espressoenglish.net Measuring cup Use a measuring cup to measure how much of each ingredient you need to use in the recipe. Many measuring cups are labeled in cups, ounces, and milliliters. Can opener There is also an automatic type called an electric can opener. Peeler Use a peeler to peel. Remove the skin from fruits and vegetables. Grater Use a grater to grate or shred food into small pieces. Colander A colander is often used to drain, remove the extra water from cooked pasta. Siv or strainer A sieve or strainer is often used to separate liquids from solids. Wisk A whisk is used for mixing. Spatula Ladle A ladle is a big spoon used for serving soup. Pan A pan is often used for frying food, cooking it in oil. Pot A pot is often used for boiling food, cooking it in water. The top part of the pot is called a lid or cover. It can be made of metal or glass.  A baking pan and cookie sheet A baking pan is used for baking, cooking things in the oven. A flatter version is called a cookie sheet. Tongs You can use tongs to pick up food. Utensils Knife, spoon, fork You use a knife, spoon and fork to eat food. Together these items are called utensils. Bowl You can serve soup, salad or fruit in a bowl. Plate You can serve food on a plate. Plastic container You can put leftovers, food that you will save for later, in a plastic container. Sandwich bag or zip lock bag. You can also preserve food in a sandwich bag. One very popular brand of sandwich bags is called zip lock, so some people call these zip lock bags. If you want to learn a lot more new words, check out my vocabulary builder course, which will help you learn and practice more than 500 words in each level. Click on the link in the video or in the description for more information.