So with that ladies and gentlemen, without taking any more time, let me quickly move on to the next special address. The Mr. Ekmanchu, Baxi Managing Director, Dano in India, speaks on the topic of Nothing India to Eat Healthy. Now, this is an interesting one. I'll hand over to Ekmanchu to take you through the journey. All right. Thank you so much, Tavi. What an interesting session. I was not there for the entire bit, but yes, I did hear about the currency bit. And now we're going to talk about the real wealth, which is health as we all talk about it. And a very important topic to address for us in India. I'm really glad to be here to have this discussion. I'll be taking you through a few slides and then maybe we can have a larger discussion around it. So, we're talking about this interesting topic, which is really about Nugging India to Eat Healthy. And this is absolutely in line with what we do at Denon, especially in India, to really try and inculcate these healthy eating habits in people. It's really important we do that right now in address certain areas which are there of concern for us as Indians. If you really look at the landscape today, when it comes to the health status of most Indians, it is quite worrisome. There have been a lot of talks around health, wellness, lifestyle diseases. But when you really look at data, when you really look at numbers, some of them are really shocking facts that come to the table. Just a few of them that I've just put on screen for all of us to see. Look at the lifestyle diseases that we're going through. 20% plus people having cholesterol, India now becoming the diabetic capital of the world, 40 million plus. A lot of issues that we see on cardiovascular diseases, hypertension. While these are all diseases that impact us physically, I think the input is important. What we eat really defines what is going to happen to us. So a few stats, if you really look at the screen, for example, 70% plus having insufficient physical activity. And that's not great. 91% of people in India having protein deficient diets. And I think we always have a lot of assumptions and myths in our mind when we say that we are eating very well. Most of my diet that I eat, the Indian Thali, yes, of course, it's pretty good. But is it what your body really requires? And these are times when we forget that there are large scale deficiencies we need to cater to. And I think it's the responsibility of food organizations, companies, brands, to bring all of these out in the open, address them and really make these very meaningful journeys for the consumers in the future. Yes, there are profit objectives. Every organization, every brand will want to deliver on their objective of revenue and profit. But the question is, is that enough? As a brand, is that what you really want to deliver? I think what I feel and what's the large thinking here at Denon is very clear. It's not only about profits. It's not only about getting your top line in. What's really important is how can you as an organization, how can you as a brand play a very positive role and impact people's lives positively? If they can have healthier people out there, I think that's what the real success looks like to us. And that's where it comes to how we see a brand versus a stand. A brand can be the what, which really talks about what will the brand answer. But I think what's important is the why behind it. Why is the brand there? Why is the brand existing? What's the larger scope that the brand wants to cover? I think unless this is clear, we're not going in the right direction. When we talk about brands, you always talk about points of difference. How is my brand better than you? How is my brand better than the category leader? But I think it's important brands have a point of view. A market share fight is something that will always happen. But what is it that the brand stands for? What is it that the organization stands for? I think that is something that's really important to define right at the beginning before you start on this journey with the consumer. There are a lot of points here. I won't go with each one of them, but I think the point which I want to really make is as a brand, it's very easy to play tactically. It's very easy to start thinking of brand as a property which will go out there, try and answer some consumer needs and get your profit out of there. I think brands need to stand for something. Brands need to have a clear purpose. The brand needs to answer something really big for the society. And unless any brands does that, I think there is no real meaning of a brand being there out there in the market. I think these are thoughts which resonate with us quite a bit when we have our discussions internally at Denon. It's important that I set this context before I really tell you what we've been doing so far. And I'll pick up a couple of examples to really showcase what we've done so far and what our journey has been. So let me start with the mission, that we have at Denon. And then it's very important that we spend time on this. It's bringing health through food to as many people as possible. And I think the key words to see out there are health and food. We don't see food as something which is there to fill people's stomach. We don't just see food as something which will give you satiety versus hunger. I think we're talking about a larger platform. I think whatever offering that comes from Denon in India, whatever offering that comes from our portfolio should be addressing a strong health need. And unless it gives a tick mark on that, I don't think we'll be launching any brand in the future. So most of our products and whatever we have on the portfolio today is completely in line with the mission that we have, which is to bring health through food to as many people and of course, as many Indians as possible. And because of that, we do have our strategy and a lot of commitments that we make as an organization. For us, as I said, success is not only growing very good on top line, getting great profits on the business, but really push people or nudge people to adopt healthy eating and drinking habits. And I think that's the role that we intend to play in India and that's what we've been doing globally. And it's a step by step process. It doesn't happen overnight. I think the first thing that we need to convince people or offer people is better quality products. I think whatever we have on the portfolio today, we need to continuously improve the nutritional quality of the brand so that people get food, which is the most nutritious, which is the most innovative new technology and which makes their life a lot better than what it is. It's also about being very local. There are a lot of local nuances that are there, a lot of local benefits that brands have. And I think it's important to recognize these needs. At the end of the day, I think it's really about being proud of the portfolio that you offer to people. Something that I can be proud of to sell, something that I will give my family to have, something I will have. And that's in a way is the epitome of success that I see personally for us at Denon. So better products. I think that's the first basic fundamental we talk about. The second one is better choices. When it comes to food, I think India is one geography which is unique when it comes to the choices that we have. The question is, can we drive people to healthy choices? There's always this fight between taste versus health. We've had many discussions around it in terms of what's healthy, can healthy be tasty? I think that's where the role of innovation comes in. And we call it innovation, which is innovation in India. I think there is an opportunity definitely to give people options through a lot of innovation. To people in a way that they get better choices to make. At the end of the day, what's important, I spoke about certain statistics in the past. If we can have a positive impact on people's diet, on people's consumption and have their quality of life being better. I think that's what we as a food company want. And that's something that we're going to keep promoting, which will of course help people adopt it, help people nudge their choices more towards healthier options that are available. But I think the whole responsibility and obligation lies with companies like ours. To start this whole journey, to start this movement, to make sure that people follow. If you look at our portfolio, you would have seen most of these brands in the market. Brands like ProteinX are legacy brands in the Indian market. Almost 100% of our portfolio lies in health today. So while we talk about it, we make sure we deliver on it. So whatever we're going to launch in India, whatever we have launched so far in India has always been extremely healthy. And that's the choice that we want people to have whenever they talk about Denon, whenever they talk about nutrition, they should know that anything that's coming out of this organization will always follow health. So nutrition for all is what we talk about. And all our portfolios, even in the future, and some very exciting launches that are going to happen, are going to fall in the same line of health for people. I'll just share an example of one of the agendas that we have picked up as an organization. And it's an important agenda to address. Around four years back, there was a big survey that happened which showed that more than 70% of Indian diets are protein deficient. And protein is one of the key building blocks for each one of us. I think there are a lot of myths that are associated with protein. A lot of people think they're getting adequate protein. But I think protein deficiency is a big agenda that we need to address. And not only us as Denon, but I think all of us together need to address this. Because unless we do that, protein deficiency leads to a lot of issues. And that's something we want to address. So the last five years, we've been doing a lot of work to make sure we educate people, take holders. We work with a lot of agencies to make sure there is enough noise around the fact that people are made aware that there is lack of protein in their diet. They need to look at this extremely seriously. And this is something that should in a way help us in the future if this improves. Because once this improves, we know that you're going to have a better physical life and a better physical life means better quality of life. So it's very important to address this. And we at Denon have picked up this as one of the core areas that we want to work. We have been working on it and something that we'll keep on working in the future. Now, what do we do about it? One is just talking about this whole protein deficiency bit. But what do we need to do and what have we done so far to make sure that there is enough noise around it? I think there are three ways that I look at it. The first one is as a responsible food organization, we need to give better products to people. Unless you do that, you're not really living up to the mission that you have. And this is 100% our responsibility. So I think better products. The second one is the power of partnerships. One company alone cannot take this entire journey forward. It has to be a holistic approach. So stakeholders are important and a joint stakeholder movement, which means companies, which means HCPs, which means retail, which means credible industry bodies. We all need to come together to make enough noise around it to make sure that this is heard. And the third one is more to do with consumers. How do they get to know? As I said in the beginning, most of us don't even know we are having lack of protein in our diet. So we work on certain tools and services, which will help people understand their deficiency and which will help them make the right choice in terms of how much they should be having in terms of protein. So the first one, better products. We need to continuously improve. We need to continuously make our brands more healthier. We need to continuously innovate to make sure whatever we are offering is impacting lives positively. So the brand that we have Protein X. We've continuously improved its nutritional profile year on year. Last year, we had this whole discussion around sugar being the big menace and the Indian population racing towards diabetics. Having sugar on the portfolio was not the right option. So we did work around it. Now the entire portfolio is zero sugar, which makes the product even more healthier for people. So you're not only getting protein, but you're also saving yourself from the menace of sugar on the portfolio. So this is just one of the examples, but even on the overall nutritional profile, we keep on working so that people get better options for the future. The second is power of partnerships. So we work very closely with the FSSAI. They have the Eat Right India movement and we were amongst the first few organizations to sign up on that, which is a pledge to make sure that whatever comes from our portfolio is healthy. We also work very closely with CII, which is a very credible body to really talk about protein and the protein adequacy that's required. We are right now in the midst of the protein week. Now it's an annual affair. It doesn't mean that we don't talk about protein the entire year, but this is one special week where we make heightened noise around protein and we come together with all these stakeholders to make huge communication around the need of protein so that people are sensitized on its need. The impact has been quite good. We've reached more than 100 million people so far. Yes, when you look at the scale of India, still a lot needs to be done, but I think we are on the right track. We're in the right direction to make sure we bring this message going forward. And the last one is on the tools. Now, as I said, how do you really know or how do you assess there is a problem? I think most people in India don't have the tools to assess it. So we started this whole thing around the Immunonutrient Calculator. It's available on our website proteinx.com. It's a free of cost calculator that you can use. You just have to key in the daily diets that you have and you will find out what key deficiencies you have in your diet, not only protein, but all macro and micronutrients. I think once people see that, once people get assessed, that's when they really realize that there is a problem in the diet and they need to take corrective action. So think as brands, as companies, we also need to be enablers for them. It's not only just going to them with an ad campaign and telling them, oh my God, it's really great. Please choose us. But I think you have to be a partner in this journey. You have to be enablers to them so that they can understand, they can assess what's really happening around their diets and finally take corrective action around that. So this is what we've done on proteinx as a brand. We've been doing it continuously. We are seeing some excellent results in terms of protein awareness going up, which is, as I said, completely aligned with the topic that we had today, which is nudging people to eat healthy, to have healthier choices. That's something we really want to do. And yeah, finally, I think it's important that all stakeholders come together on this one. It's not one company alone who can make a big impact. It's all stakeholders. The more we talk about it, the more we create a dialogue around it through key stakeholders, the more people will be aware. So they assess themselves, they get awareness, and finally they take action. I think if we can do that, I'm sure the nutritional profiles or the health profiles of people in India will be much better and their quality of life is much better. And I think that's one commitment that I take forward as the managing director of Denon, that we will continue to keep working on it. We will make sure we keep giving you healthier nutritional choices and really get India to a great state. Thank you very much. Thank you. Thank you, Mr. Bakshi. So that was Himanshu Bakshi, managing director of Denon, India, talking to us and we really appreciate your time and joining us. Thank you. Thank you so much, Dabin. Appreciate it.


Welcome to JSA TV, the newsroom for tech and telecom professionals. I'm Jamie Skadokataya of JSA. And here with me today in lovely Honolulu, Hawaii at PTC 2018, Mr. Jonathan Rungi, he's the CEO of Vostronet. Jonathan, welcome to JSA TV. Thanks for having me. Well, thanks for being with us and I was researching what your company does. Very exciting. You focus on building a better internet for student campuses, buildings, residential, throughout Australia and New Zealand. Is that accurate? Yeah, that is. So purpose-built student accommodation, student campuses, and residential as well. And so you publicly stated on your site that your goal was 200 buildings by 2020. Are you still in gear for that? We mostly are. So as of last week, we even expanded our network out to San Jose, so big plans for 2018 and we're definitely on track. What's your building count now? Currently, we've got about 25, 30 different buildings and campuses. So still got a bit to go, but many of the campuses have lots of buildings in them at the same time. So rapid development here. And you still got two more years, so yeah, for sure, a lot of room to grow. Now catering to the educational and residential markets, very tricky today. Everyone needs everything on multiple devices, up all the time, past. How do you do it? Yeah, so it's definitely a challenging market. The student market is low cost, high demand, and we do well in terms of maximizing value for our end users, through to each of our buildings that we deploy into, we deploy at least 10 gig a second. And all our student accommodation has whilst throughout using less technology. That's brilliant. That's brilliant. So obviously, high bandwidth needs, always growing year after year. What other trends do you see impacting the telecom arena? Okay, so we've got a few different things coming in. We've got 5G coming in. We've got more high demand in terms of devices and number of devices. So the average user has moved from about two to three devices to an average of five devices. And that's expected to grow over the next year to two, up to even up to about 10 devices to each individual. So we're seeing massive growth, especially with the internet of things coming in as well. So big challenges ahead. Absolutely, big challenges ahead. Same here in the States, IoT, 5G. How do you keep up with the growing ambiguous demand of need for bandwidth? So thank you so much for our viewers who might not know, but want to know more information about Vostronet. Where can they go? Go to our website, so vostronet.com. We also have a blog that we currently publish out, so just blog.vostronet.com as well. So definitely we are happy to answer any questions from people out there. We're definitely expanding rapidly growing market and we're capitalizing on that really well. Blog.vostronet.com, I'm definitely checking that out. Thanks for the tip. And thank you also for joining us here on JSA TV. And thank you viewers for tuning in.


So my name is Tom Hutchinson. I'm an engineer with the tri-college libraries. That's a Brynmar-Harriford and Swarthmore colleges There are three small liberal arts colleges outside of Philadelphia All right, and so today I wanted to talk about preservation The the technical aspects I know preservation is is largely a non-technical issue It's organizational and financial Still there's many, you know technology related decisions And even if you're following the the strictest guidelines, there's still it's not clear how to do everything There's also pretty fuzzy boundaries some technology decisions involved in preservation quickly bleed into other areas, you know certainly Repositories come up very quickly and then also just your kind of technology in general So I'm gonna lay out a Few just simple ideas and try to motivate them and then apply those Like simple principles to some situations and see see how far it gets us So my main underlying theme is just the UNIX philosophy There I'm a You know big big idea they have is let's make Solve problems as broadly as possible With with very narrow solutions That are constrained they do one thing and one thing well and hopefully it's even simple and that not just simple to use But simply implemented They're big on good is better than You know all-encompassing Let's just make something work pretty well So this this narrow constrained problem We see in a tool like grab You know, we're we're searching text. It does this kind of pattern matching really well, and that's it nothing else But it's also we can apply this to any text. So it's not such a bad utility We also see this, you know in more our world with something like fedora You know, we're solving a pretty narrow problem. It doesn't do too much. They're very disciplined about Not adding things. So you most people have some other software sitting on top Because we're just solving some some simple problems and we're composing those solutions together And we can see this compose together simple pieces in your regular web app so most of our apps have a web server like Apache a database like Postgres a search engine like solar and So, you know now we're we're getting out of the realm of solving some kind of library problem Some sign of preservation problem, and we're just you know Farming it out to just all people who need to store and retrieve data, you know, that's a big win You know, we can just use these these basic building blocks and kind of plug them together and that works, you know pretty well It also lets us reuse our skills This is this is how we're set up. We actually try to line up all our applications So they have a lot of overlap and so the application specific stuff. We try to keep really small And this this works out in practice, especially we're a small team. So we're using some some solutions works out pretty well Okay, so another principle is there's no magic You know the the sales people they try to tell you there is you know, we've got a fancy thing But you know, there's there's also no magic. There's a lot of hype, you know fashion is big Oh, did you you know see this new thing? Let's get into it. There's a lot of excitement around certain products Also, you know people can fall into a trap of thinking Oh, there's one super technology that'll solve all our problems You know, we can we can fill out the matrix and it checks every box. So it's gonna be the super thing keep Let's just add more stuff in it You know in in practice, you know, I argue that's not always the best way to go so Yeah, now I'm gonna have a side ramp on the cloud Because this is coming up and a lot of our technology decisions is You know local hosting cloud hosting We're a consortia. So You know, we have three different IT departments one we the libraries work very closely with but the other two They're still, you know, very present at our colleges You know, and I hear a lot of Of different reasons for for using the cloud I You know, no one ever gets fired for putting something on Amazon, you know, but it is a good line item to say, oh, I You know directed us in our transition, you know to the cloud, you know, that sounds pretty good You know and and it's not it's not bad stuff you know and a lot of cloud usage comes and just a lot of our Technology, you know enthusiasm is coming out of this big startup culture.  So they Start with nothing literally maybe a few people maybe a little money They have no code no staff no Nothing and they want to get big they want to go from really small to really big so right from the start They're thinking scalable So they're going to use weird cloud technologies, but the because the cloud is weird things are different there We're thinking how to scale really well And so, you know, we don't have a normal regular database We don't have a regular normal file store. Everything's all kind of weird And but you it's kind of a part price you pay to be able to scale. So for right out of the gate They're building an app from scratch using scalable technologies and they're willing to pay the price And they're really it's great for them because they can start with very few resources And so their costs are low in the beginning and then they want to be scaling up a good one, you know Exponentially for a while You know, and that's just kind of different, you know our needs are much more stable, you know, we won't have extra capacity to You know take on a new big collection that drops out of the sky, you know, that's always good We want to be able to to spin stuff up and try things out but You know, but we're not scaling up a thousand times and then another thousand, you know, just I don't know. Maybe you are but our needs are much more modest You know the cloud so for a startup it works. It works great It's these are good technologies to be using for them. And it's like a good fit They really need a lot of Dynasticism and they're willing to pay a high price for how they architect their applications and also how they orchestrate because they want that scaling to be automatic and dynamic and So there's a they're willing to put in the cost of a lot of tooling too You know clouds also really good if you're running at the data center level You know your Netflix and it might make more sense to form that out to even a bigger player You know, but you know, I don't know that's not me So let's go for our recent decision that we're making in the tricor You know, I want to this the principle here is use what you have so we were Looking and evaluating. Oh, what do we even have? You know, because we're thinking about all let's do maybe Amazon or you know, one of those other guys or you know But let's let's kind of evaluate what we have internally Well, we have land and server rooms power cooling redundant high-speed internet Servers a virtual erasing stack storage hardware a backup system You know kind of a lot of stuff You know, we also have staffing You know, we have IT staff and they keep our infrastructure up There's the basics like network availability in 24-7 We have a little web development team. It's not exactly what we do but Close enough We also have a lot of librarians You know, they're super knowledgeable and excited and want to do stuff How can we take advantage of all these these resources both the physical infrastructure and the people So for us we were looking to set up a new repository and set up some preservation And so initially we thought like cloud cloud cloud cloud But now we're thinking. Oh, maybe we should like Double down on what we have, you know, local infrastructure and local management and Save a bunch of money But still have the capacity and nimbleness to spend things up toss storage at problems You know, we can we can still be dynamic up to a point So and we found for us since we've already have these other very high fixed costs that we're gonna pay no matter what The additional costs are low compared to the You know we're thought to be quite low cloud prices You know actually also that's a point is we really want to take advantage of The pricing war on the cloud Especially on the storage side. There've been a very aggressive price wars And most recently, you know oracles get into it and they were trying to undercut and you know You get the Google and Microsoft and Amazon all being very aggressive on pricing and having deep pockets to do that And so, you know, maybe we should take advantage of that, you know cheap storage. That sounds pretty good But we should watch out have an exit strategy. What about, you know, maybe the prices probably are gonna stop Dropping radically, but you know wouldn't be so wild if they Rose in a similarly fast manner as they fell and will be will we be ready then, you know that's one one thing I worry about with cloud stuff is If you don't use it like a dumb commodity and you start using all their fancy tools, which are, you know, great technologies You're they get really have your hooks in you and you're really locked into that vendor and it's very You know expensive to switch out technology wise So Yeah, so we're gonna expand out our local storage and then have another copy of our data locally And then have that backed up in our backup system. And then we're gonna stick in the dark cloud a preservation copy of our assets and metadata But we're you know for us it made sense to to go local heavily You know in my vision for the the next level of what, you know, local infrastructure looks like is Not just doing this with one IT department that we're working closely with but we have three colleges We have three to IT departments. What if they each had a copy of our data? This actually got a lot of pushback because of NDSA guidelines, you know geographic dispersion our colleges are close together You know to me, that's kind of overly rigid if I Don't know the greater Philadelphia area is destroyed. I mean, I don't know. Maybe that's a bigger problem And we can still hedge by having these cheap Dark copies off-site. So that's that's what I would go through. It's like each each college have its own copy of our data and Then we have some kind of cheap off-site that we don't use that much Also this doing local storage is great because we can do all the access we want We can do all our preservation activities without thinking about how much is this gonna cost to check our our files So that can be a continuous process For free, which is pretty nice Okay Shoot I had a couple question and answers Someone maybe those are further anyway one question I had was Where should everything live we're trying to figure out Where should preservation be? You know, we were thinking about preservation storage we're thinking about maybe the repositories You know what? Or should that stuff go? Let's see what I have And so with respect to Built into the storage You know, that sounds pretty appealing You know, we're trying out we're trying out dirt cloud. You know, it's a good product There's there's other ones out there that you know pretty nice. There's other ones even more featureful You know dirt cloud.  So it sounds restrictive You know, I was also thinking about how about in the repositories There it kind of makes sense, right?  It could be a spreadsheet and some, you know, scripts or something You know, DIY gets you pretty far You know, we get we get look how far we get with Hashes and backups, you know, that's not a lot of technology, but we can kind of do at least this losing the bits part of preservation, you know, not everything else, but So so I like I like to be able to just plug into our pools of storage plug into our repositories But have just one one place and really I'm You know, one thing where I see a lot of places grappling with is you maybe they've been doing preservation for a while, but They haven't necessarily gone through multiple generations of a preservation system So how to to keep that going Through different repositories as a for instance You know, so I think that Keeping it as its own kind of separate thing is isn't the worst Okay, so now this is the ramp portion of my talk Hashtag Ramp for Lib So just one one thing I think is to build bridge people, you know, a lot of these Navigating the preservation waters You know, I've had these different camps of the the IT folks and the librarians and Really, they're oftentimes I find they're talking about the same kinds of things But you know, they have sort of different languages and You know different levels of comfort with each other So just building up these bridge people who can kind of communicate what we're trying to do is is crucial That's way more important than you know, our specific technologies Another little tidbit is plan for anything failing, you know, we're have a release Bought out of you know, like what if a hard drive fails? Okay, we got that covered or you know, what if one file gets corrupted? Okay?  Will you be able to realize? You know, do you have some other kind of metadata a database or some headers somewhere?  Can't we just like do that or isn't like a checkbox we can click somewhere on something?  That's that's good You know, we should be using those modern file system technologies But we want to do all our preservation Ourselves it should be independent and verifiable, you know, we want to leave a good paper trail Okay, another rant I'm talk to your CS department You know, they've a lot of the problems involved in preservation, you know, they've been thinking about from before there was physical computers They just thought of the idea of of these problems, you know, how how much information can you store? How do you fix errors? I'm just the simple stuff. They, you know, the computer science electrical engineering They have a lot of experience And they call these things Things like coding theory, information theory, Claude Shannon, people like them You know, so these were things like I don't know 40s, 50s, 60s kind of problems that were solved And put into practice in software often, you know, then or but maybe 20, 30 years So it's not, you know, groundbreaking stuff Another opinion, you know, know your materials just like if you're working with a piece of paper and doing conservation Um, you know, we work with text a lot. Oh, you might want to know a little bit about text. It's not that hard You know, figuring out how to debug the tofu problem. You get that little square tofu character like, oh, what happened? Um, well, you know, we can know about like ASCII and those other kind of regional encodings I recommend knowing about utf 8, you know, just those two get you very far Even just knowing a text encoding exists. The other kind of text encoding, not the librarian kind, but the At the lower level Yeah, just even knowing that's a thing is this very helpful We can also up our game in fixity checks You know checksums, hashes, those are good You know that plus backups kind of does a lot You know, it's not perfect though So a problem with a checksum is You know, how can you tell if it's bad, you know, it doesn't match the file Which one is the bad one? I don't know. We look for the backup and compare Hopefully a couple backups and we do a consensus But actually we can we can have a Kind of, you know, run a big file through a program and it spits out a little code and We can have properties like oh, we always know that code is well formed or not So we would be able to detect if the code is wrong We can store redundant information in the code So this is called error correction so we can have kind of self healing files So it's not You know, this is a big problem, you know With a physical piece of paper you tear the corner off you can still read the rest But a lot of times with a file you mess up one little part. The whole thing is bad Well, we can store redundant information our code can be a little bit big So if we store 10% redundant information We will be able to recover from 10% disappearing And if it was more than that we would still be able to detect it had gone wrong You know, I I think the The codes we really want might not exist yet, but there's very usable software right out of the box today A bunch of people are talking about p archive or part two Last year Jeff Spies did a talk That was one of the technologies he mentioned You know, you hear it whispered in you know, maybe on pacing or So this is you know, 20 year old software and 60 year old problems So we can use that right out of the box and the same kind of technology that's in raid or zfs or an error correcting memory Where you have just a little redundant information. So if some of it goes bad, we can kind of self heal All right, well, um, you know, I have I plenty of other, you know, rants and hot air But um, you know, I like to open things up for for questions Thank you


Well, thanks for the introduction. It's interesting how you found out some background on me. And yes, Leland Stanford came from the same area where roughly where I grew up. It was also an area where George Westinghouse once lived and grew up. So I guess I have the electricity in my blood from a number of years ago. The topic of our talk is resilience revolution. And the idea here is really to focus on them, the idea of resilience and how it's challenging the traditional aspects of reliability. As Leland was saying, my name's Gil Bendewalt. I'm involved in research on the grid side for over 20 years. With me is Stephen Walsh. Stephen. Hi everybody, very glad to be here. Looking forward to the presentation and some really good question and answer session at the very end. Thanks Stephen. So if we can go to the next slide please. So we thought we'd couple different topics that might be of interest. The first one was really focusing a little bit on the DOE work and resilience. I'm gonna try to cover some of the portfolio that I've been involved in both within OE and in the past. The other, and then Stephen's gonna pick up and really talk about applying that in terms of both the hurricane recovery as well as sort of some of the priority setting. So hopefully you'll get sort of both aspects, some of the theory, some of the understanding of where some of the research is going, as well as also I'll say direct experience in terms of how resilience can be applied both at a local level and also in coordination across federal agencies. And so please we look forward to your questions in the end and next slide. So the first thing I wanna do is talk about how reliability is defined. So for those of you who are less familiar with the grid, NERC or the North American Electrical Reliability Corporation is the one that's basically charged with maintaining system reliability across the U.S. and much of North America. And they defined sort of the reliable bulk power system as one that essentially meets the electricity needs of end-use customers, even when unexpected equipment failures or other factors reduce the amount of available electricity. And what's really important to know is there are two aspects, one's adequacy, one's security. The first one really deals with about having sufficient resources to get it to where you need it, when you need it and the amounts that you need. The second is security. And the reason why I'm touching on that just briefly is because that's in the language that mirrors a little bit of the sounds like resilience, which is the ability to sort of withstand sudden and unexpected disturbances. But much of the focus, as I mentioned here as well for decades is really about the, what I'll say, natural causes, unanticipated loss of system elements like a short circuit, a conductor and being able to see how that would affect it. So you're building in redundancy or aspects into the planning process to help operations to ensure that if you did have something, what I'll say, a single point of failure, that that was not affecting the overall ability to get electricity to where it needed to flow at the bulk power system level. Over the last, I would say decade or more, I'd say there's increased interest in terms of being able to not only look at these natural causes, these uncorrelated events, but really starting to be able to also look at things like man-made physical or cyber attacks. And I think what that does is it really starts to change the understanding of what risk is and how that affects the ability to keep the lights on within the broader sector. Next slide, please. So then how is resilience defined? So at a federal level, the termination, the definition or terminology is based upon this directive. It's called a Presidential Policy Directive 21, came out in 2013 and it's defined resilience is basically the ability to prepare for and adapt to changing conditions and withstand and recover rapidly from disruptions. So resilience includes the ability to withstand and recover from both deliberate attacks, accidents, or naturally occurring threats or incidents. So hurricanes, ice storms, tornadoes, those all fit within the realm here. But again, also physical or cyber attacks would be something that would also, the system has to be able to withstand or be able to recover rapidly from. In 2017, the National Academy's released a report, pictures on the right. For those of you who really are interested in this particular topic around resilience of the nation's electric system, I would really encourage you to download a copy. DOE was the sponsor of this, but it brought together thought leaders from across the country. It really, I think articulates well, a lot of the challenges and opportunities as we think about what resilience means and how we can be able to enhance it and promote it broadly. Next slide please. So these are a few graphics that I put together. They are illustrative, I want to emphasize that. I was concerned I'd get all these Q and A questions about how these curves were derived, but really I wanted to put out there just a couple things. The first one on the left is really trying to capture the idea of what is resilience. And again, you see in terms of a disruptive event, you're going along, you have an event drops down. The whole point is to be able to either reduce the magnitude of that disruption, bring you up to that dotted line or improve the speed of recovery. So you're mitigating the effects that an event would have on the system. The graphic to the right, I would say is my attempt at sort of describing the difference between reliability and resilience. Reliability is really driven about trying to understand how to keep the lights on, right? How to keep under a variety of circumstances to get that adequacy and security piece. When I think of resilience, it really starts to play more into the tales of this curve. Really understand the nature of risk, how that affects the system and how you can assess and make adjustments in terms of decision-making about how to improve that ability to withstand and recover. Challenge with that as you look at the tales are these are low probability events, so often at least, and so they're subjective. There's little or no empirical data. So unlike reliability, where you may have treasure troves of data that you can do statistical analysis around and understand what reliability implications are, the resilience piece is really event-dependent. And the other challenge with this is the further out you go is typically the incremental cost in terms of managing risk is something that goes up. So it's this balance between how do you focus a portfolio of risk or investments related to reduce the risk in terms of improving resilience in a way that tries to, I would say, cover as much of the spaces as possible. The traditional way for reliability, of course, is redundancy, et cetera. I'm using the term manage risk here in particular because it's almost impossible to eliminate risk. Our system is amazingly reliable, 99.99 or they're about the percent reliable. It's the challenge is the, I think is, and I think that's a testament to what the operators and designers have put into that. But I think, again, there's more recognition now or attention around sort of the tails. And by understanding those tails, it helps to better understand how to maintain, well, I'll say it's a healthy system and sort of how that plays out. Next slide, please. So as we look back at that, PBB, the Presidential Policy Directive 21, PPD 21, what are some of the words that came out? Well, the first is this ability to prepare for, right? That really gets into the notion of planning capability. The second piece is withstand. So when you see an event, how are you able to withstand it? A lot of that deals with strengthening, hardening, looking at infrastructure approaches that allow you in itself, the system to be able to tolerate and withstand events that I may see. Recover rapidly. I mean, that really gets into things like redundancies and building in efficiencies in that regard. Adapting to changing conditions, again, this isn't a single point, right? You're not optimizing for a single scenario, single set of conditions. The grid really is in no same state twice. It's always changing. So how do you adjust for these multiple equilibria? And then the idea of the multiple hazard piece, right? The deliberate attacks, accidents are naturally occurring. So that gets really into the box at the bottom, which is that a lot of people think of resilience as in the moment, right? I'm resilient. I've seen an event. I'm able to bounce back. But really what only makes that happen is the idea of having robust planning, preparation, and food investment. So the time and effort that you put into it upfront to be able to be well-prepared for when you need it to adapt is what is critical in terms of the ability to achieve the resilience that's desired. Next slide, please. So how is OE focusing on the resilience? Well, I sort of broke it into some themes and then I wanted to just break down some of the areas of both research and some of the coordination. The first is sort of understanding the context. Again, we're trying to understand the tale. These are determined a lot by particular events. So that gets into things like the threat and event characterization. But it also really comes down to understanding the demand and behavior profile, the needs. I mean, one of the things that's coming out of the current COVID situation is the ability to better understand how loads are affected, which has consequence in terms of operational challenges, whether it's managing voltage or power flows or even controlling and operating the system. That all ties into understanding the context of what you're trying to look at. The second piece across our portfolio within OE is sort of looking at how, I would say, analyzing existing flexibility. So some of that is very data-driven, right? You have a system. You're trying to understand that. So sensors, being able to have a higher level of fidelity in terms of the different dynamics that are occurring. Resilience metrics, being able to understand how resilience is measured and evaluated. And then there's things like maturity models, which again, different entities and stakeholders will value resilience in different ways. And they may be at different positions in time of where they are in that maturity. So how do you balance resilience maturity models in terms of the technologies you're in and the goals and attributes that you would have? Resilience, in a lot of ways, is very much at a local and regional level. And so some of what we've talked about, there's some projects that we're working on with the National Labs, one of them particularly at Sandia. In that particular project, they emphasize this balance between community resilience, visibility needs versus utility reliability. And I think that really gets the heart there. The third piece is really identifying gaps and solutions. So part of identification of the gaps comes down to modeling and ability to have a framework that allows you to assess and compare some of these options. And then there's also the investment in solutions themselves. When you identify the gaps, what do you do? And so that's work in areas like energy storage and microgrids, as well as more advanced software architectures and other approaches. And then finally, I think this idea of coordinating objectives and facilitating decision making. There's a portion of our office that's focused on technical assistance. And so it's working with the states and other decision makers about how to consider and value these. And that also plays in some work on the architecture side. Next slide, please. So I mentioned modeling. And I think, again, if we go back to that one, we don't have to go back in the, if we think back to the graphic with on the right hand side where it talks about where resilience was and looking at the tails. I mentioned there that there really isn't a lot of what I'll say data. Again, if these are low probability events, you're not necessarily data rich. So how do you understand both the data? How do you simulate potential events? It comes down to modeling. And so these give some examples of five areas that I thought of and highlighted in terms of some of the work and reason why we're focusing on grid modeling as a key part of our overall research portfolio, not only within the office of electricity, but also looking how to also characterize and model areas like solar and DER and wind technology or even hydro resources. It's really helping models become a platform for helping to understand complex data, which the grid is a complex system. And then it's also being able to understand the physics that govern the dynamics of the system. It also comes into understanding parameters and values that you don't have measurements for, right? You need to estimate those. I mentioned the simulations. And then I think finally, I think models give you a platform to evaluate options. So if you're trying to understand what resilience means and you're trying to, for example, understand where storage may play, a model gives you an ability to look at those and be able to understand where a likely place would be, either to maybe do a demonstration or to deploy a technology to have a system effect that's desired, excellent place. So a key area that's developed under our assistant secretary in coordination across the department is something called the North American Energy Resilience Model. And this is an area that is leveraging a number of laboratories across the United States, including labs like Livermore in California and Oak Ridge, PNNL and others. It really is about, I mentioned models and a lot of those seem like singular domain models. But when you talk about resilience, resilience doesn't stop at the generator or the wires, right? You need to be able to understand that if you're talking about the resilience of the broader power system, the energy system, it goes into the generators and it goes into understanding the nature of the fuels that feed those generators, that then flow through the electricity, the options that are on the load side. So the NARM or North American Energy Resilience Model is really focused on these interdependencies. It's being able to understand, for example, how natural gas and electricity flow together or communications. It's at the bulk power system and it's deploying, what I would say is engineering class modeling. First at the planning level, but it's also geared towards understanding how near real-time data can also help both situational awareness and decision-making as well. Next slide, please. So the workflow, again, this sort of is an overview, but it really begins with understanding the threats. I talked about that or the events themselves, how you characterize them, feeds into this sort of integrated modeling environment. And then really on the end, it's all the different ways that the models can inform decision-making. So understanding outages or impacts, understanding resilience in terms of being able to assess it. We talked about metrics and economics, what might be most appropriate for a particular region or type of investment that's needed. Operational planning options or, again, near real-time situational awareness just to know what's going on. And next slide, please. And then the unique part of what NARM is, it's really about an interactive modular approach. So it's not a single model. It's about being able to know the same way that events are evolving and threats themselves. It's being able to have a framework that can also scale, extend, and expand in ways that continue to address the needs that may evolve. And so that's where, again, we're looking at how different pieces are coupled together and being able to leverage those capabilities to the fullest extent. So this interaction and interoperability, this interdependence piece is really what NARM is about. It's not a singular model. It's about being able to couple these. And through that, also, I think understanding how the various domains also relate to one another and the stakeholders that are involved in those. And then I think, next slide, I think it's the breakpoint. It is. So, Liang, I'll turn this back to you. Thank you, Gil. Very exciting. So for audience, if you have any simple and the clarification question, please click the button, which is raise hand in the button, then I'm going to unmute you and allow you to ask question. So we have one question from Martin Morph. You are unmuted. Martin Morph, you are unmuted. Okay, I think he mute himself. Okay, any other questions? Okay, I think we can move on, Gil. That sounds great. I think Steven, you're up. Okay, and everyone can hear me. Good. Yes, it's good. Okay, good, thank you. So thank you again for helping me. Gil did a wonderful job of trying to give an overview of all of the varied efforts that we have in resilience. And I will take the baton from where he left off in identifying NARM as a basket of modeling tools that we can apply to learn more about resilience and talk about how we use some of those tools for Hurricane Irma and Ria recovery work and what we've learned along the way. What you see here, this slide is essentially a citation network of peer reviewed papers on resilience from the early part of the 21st century. And you can see one that there's a lot of different disciplines that have talked about resilience in peer reviewed literature. So that's a good thing. What you see is environmental and psychology being the two biggest bubbles. I know the ecology peer reviewed lit on resilience goes back to at least the early 70s. And psychology talks about resilience of the individual and how it copes with different stressors. When you see in a faint circle on the bottom is the engineering and other hard sciences talking about resilience. It's the much smaller dots and they tend to connect back to psychology or environmental psychology or environmental and ecology. And next slide please. You can see on the chart on the right here how much the literature has increased on resilience in the past few years. And you can also see a few more definitions of resilience. And we're not gonna go through all of these. It's just to point out that there are many extant definitions, working definitions of resilience. As feds, we use PVD 21, which Gail went over in depth. And it does a pretty good job of defining what resilience means for us. And in the chart here, there's just some definitions that reflect the different perspectives on resilience from the previous citation network chart. When you see this, I think these slides will be distributed. You can read these at your leisure and go to these other papers and find other definitions of what resilience means in different contexts, and particularly with regard to engineering. Next slide please. One thing that kind of jumps out once you look at all of the different disciplines and think about it through an infrastructure perspective, these common elements of resilience emerge. Gail talked about some of this, so I won't go into it too much in depth, but there's three temporal phases, usually pre-events, in other words, what are we doing to prepare for on-tail events, these low-frequency, high-impact events? Then of course, there's during an event that's actually happening, and immediately afterwards. And one distinction here that I think psychology and ecology have with regard to resilience is that immediate post-event is not quite long enough in most of the lit. They tend to think about things in years following a particular event and the stressors and how those dynamics play out over years, whereas most of the literature on the infrastructure and engineering side is really looking at how quickly can things go back to normal. In order to become resilient or have a resilient infrastructure system, these other capacities that you see here are either explicit or implied by the definition. Two things that I think are interesting to note are and have some impact on our hurricane recovery work, that the resilience definitions imply that there's some sort of pre-event capacity to address the concerns that are out there. So it's one thing to have a bunch of rich, high-quality data and to feed that into a world-class modeling capability and get outputs that are intelligible, that are mathematically sound, and also can translate into real-world action. That's all well and good. If you can't, though, act on those insights, then resilience will be just outside of your grasp. So one thing that's important to keep in mind is that a financial capacity to act on resilience gaps or needs is important. Another thing that's implied is that resilience tends to be viewed as just a bit more than asset performance. Gil talked about that as well. We've got the planning capacity beforehand. We also have the ability, how quickly can you bounce back? But one thing that gave me a little bit of trouble with that limiting resilience to just that framework, kind of, it started bothering me a little bit as I was doing the recovery work because if it's just infrastructure performance, then that's not a full explanation for what we were seeing. Next slide, please. What you see here are some of the software tools and models that we were able to apply to recovery work following hurricanes and Maria. You see they range from the bulk power system and the fuel system all the way down to distribution and edge. A little bit later, there's a link to a website where if you're curious about any of this work, you can go and get a bit more detail. Our email addresses are at the end. So if you have specific questions about this, either Q&A or if it comes to you later, you'll have a way to get in touch. The point of this slide is to show the breadth, I think, of the tools that we have available to understand what resilience needs an infrastructure system might have and the different scales and levels at which those models provide insights. Of course, they each need different datasets. Luckily, there's some overlap, but there's a lot of unique data needs for each of these tools. The tools don't have a really clean handshake between the outputs of one and the inputs of another, which I think Gil and the NARM team have been working really hard at. But for now, I mean, when we're doing this recovery work, we're running each of these almost completely separately. Next slide, please. It's just a little bit more detail on the tools that we deployed. There are links to some of these. You can do a little bit of deeper dive on your own time. If you're interested, the one thing that I would like to draw everyone's attention to that Gil mentioned in his portion is the resilient community work that Sandia does. Then the name of that tool that they use in-house is RENCAT, so that's the third one down that you see there. Another element from this is it's not just about the existing assets. It's also looking at what other tools and what other technologies can be brought to bear to make the system more resilient. What can be done to make sure that next time the infrastructure performs better and it's a lower stress on the community than what we saw with Hurricane Maria. So if anyone's been following the news there, they may have seen that Puerto Rico passed a 100% renewable energy target, which is very ambitious. And some of these tools, particularly PVWOTs and Festive and Mafrid there at the end from the National Renewable Energy Lab in Colorado, will be really helpful in making sure that different capacity, different technologies that generate electricity all play well together and will actually keep the system up and running and keep the lights on. So we have everything from making sure at the top, making sure that there's gonna be enough natural gas, that understanding with the head-out tool, for example, what the different failure probabilities of different assets under different wind speeds, all the way down to what will a 5kW PV system do on a residential rooftop. It's a pretty impressive array of tools. Next slide, please. And we've been able to produce a number of deliverables. Many of these are official use only, but what you'll see there on the right, left, yes, left, is a link that I can make available afterwards, but where there's a bit more detail on what's public, the information that's publicly available. Since one implication also of resilience work that we often don't think of, is that compiling all of this data together actually creates a bit of a sensitivity with regards to how that information is shared and who has access to it. Each of the data sets on their own might not be all that sensitive, but when you put it together and you get a very complex, rich picture of how the different infrastructure systems interact, you might have a data set, outputs that aren't safe to just be broadcast publicly and you wanna be a little bit more careful about who you share things with. But as we were doing all of this work, next slide, please. It occurred to me that a lot of what we were looking at was how quickly it took an infrastructure system to return to normal following an event. And that I think is at its core what many resilience definitions in the engineering and infrastructure space look to do. Take a system as it is before something bad happens, examine it, its performance or model its performance as something bad is happening and get a sense of how quickly it will return to normal operating conditions and normal parameters and how that might be improved. Ultimately, when you simplify it down and distill it, you end up with something that as Gil showed earlier, looks like a resilience triangle. And there's a paper here, Ayub, that I think does a very good job of describing this concept and I highly recommend everyone take a look at it. There's a full citation on the next slide once we get there. But this is at most simple or most straightforward, what many resilience analyses look to do is describe this triangle. Systems operating normally at point A and then B, event happens. How long does it take to get to D? Next slide, please. And these can get very complicated as you see here. I think this paper does a very good job of making a complex resilience triangle. It provides for pre-event mitigation. It provides for different performance depending on the threat that you're looking at. And it also allows for improvements back to an equilibrium that's different than the one where you started. And of course, looks at cost and time. This is a wonderful model and a great paper, I highly recommend and I think this is, this might be in some ways the height of what the resilience triangle can do. Next slide, please. We see here some of the strengths and weaknesses. The approach is consistent with the definition that GIL laid out. It allows for comparison of system performance in the three phases of a resilience event that we talked about earlier, pre-event, during the event and mitigation. Different failure rates and modes. So you can optimize based on different constraints and it provides non-negative outputs, which for those of you deeper into the math will appreciate that it will actually converge and give you a unit that makes sense. On the other hand though, it's only as good at the system level logic used to define the components of the system. And what does that mean? Essentially it's at its core that's junk in, junk out. So if you don't define the system well, you won't get useful outputs. Or if you define the system well, but you don't characterize the component of performance in a given threat well, you won't get useful outputs. Which means that as you get more and more useful modeling specifications and outputs, you then have more and more specific models and outputs, which we kind of talked about earlier with the different buckets. Each of those tools great on their own, useful, give you very good insights into whether it's the bulk power system or micro grids or storage. But in order to be good and useful, they have to be specific. And we know when we're thinking about resilience, as Gil mentioned, it's multi-threat, it's multi-equilibria, and it's low frequency event. So we don't know exactly what's gonna happen, what the event will look like, what it will do. So we have very specific models that are giving us great outputs for specific conditions that may or may not be the ones that we actually need with the time comes. And then of course the last one is a charge that you could probably levy at any mathematical model that attempts to look at things in the monetary way, but that essentially, the cost of making a system resilient might not actually be a useful thing to measure at all. And that's sort of hit home for me doing the Hurricane Maria recovery work. I mean, there was very little pre-event financial capacity to mitigate. The storm was worse than people were expecting. And while there was a great amount of suffering and the infrastructure performed fairly poorly, the community itself continued to survive and will thrive again. And so the investigations of resilience that we had been undertaking sort of rang a little bit hollow in the moment. Next slide please. And so it made me try to find another way to think about resilience. And there's some good literature talking about resilience as an emergent property. Mathematically, that's essentially there are changing boundary conditions. And so you're never quite sure in one moment what the next boundary condition might be. And so the path from the pre-event to post-event isn't exactly, isn't very easy to calculate. But it also means that it's hard to characterize. I mean, when we think about resilience in the context of an individual, there are many different stressors that you might imagine and someone goes through whether small or large, frequent or not, that we go through and we can say and feel that we're resilient for having gone through them and responded in the way that we did. It wasn't about how much money we had at our disposal, although that often helps. And it certainly wasn't just the amount of time it took us. It's something more than that. And I think that's why I'm kind of settling on this idea of resilience as an emergent property. It still leaves us with the task of assigning, defining the system that is to be resilient. Is it a power grid? Is it the distribution level? Is it the bulk power system? Is it interdependent infrastructures like you was talking about? Gas electric communications? Or is it something that includes a bit more of the human element? How quickly can small businesses reopen? How quickly can a population displaced by the event return to normal life? Or to a new normal like in New Orleans? Things certainly changed there due to Katrina, but the city is thriving. I don't think anyone would argue with that, but it's also very different. So we can say that New Orleans is resilient, but it certainly wasn't, it's not the same as it was. And so it's more than just measuring how long it took this place or this community to get back to normal because normal means something else. And those last two bullets are really about how the federal role is impacted. States traditionally exercise police power. So the things that we think about as absolutely necessary during an event, fire, hospitals, police, all of that's controlled at the state level. Of course, the feds have influence over certain things, but that's really state domain. Next slide, please. And so through the course of the Hurricane Marine recovery work that we were doing, we combined all of these tools, specifically a team at Pacific Northwest National Lab, combined tools in the way that you see here. And this, I think you can characterize this as an adaptive robust optimization, where you have on the head out at the beginning, you get assets with different probability distributions for a given threat. Those are maps and also looked at, put through a time sequence based on actual events that have happened over essentially hurricanes that have happened over the past century. Then you do an optimization Monte Carlo analysis sampling of what assets would survive under a given threat. And then it looks at dynamic contingency analysis, looking at what things will fail, whether there's a cascade failure based on the assets that are damaged as identified as damage based on the analysis up to that point. And then it kind of cycles through at the end until the event ends. Very good work, publications forthcoming, but for anyone who's curious, if they look for adaptive robust optimization, you'll see some fairly recent literature on that. I think this approach has good legs. It's just very data intensive. It's time intensive. It takes a lot of computing power. And we're still at the stage where it's a single threat and a fairly small foot geographical footprint. But it's very promising. I think there's some good potential with this approach. Next slide, please. Which takes us to where the federal rule is. And I know Gil talked about some of these things. Even though we're not, the federal government doesn't have the police power that the states do, we can still help build local capacity in a number of ways. One of those is data collection and standardizing data sets so that baseline system performance can be measured and compared from one place to another. Building that planning capacity so that people can take the data that they have and view it in a way that makes sense and is robust given their circumstances. We can also help with an accurate prognosis capability like NARM that Gil was talking about. In other words, when something is happening, the ability to understand what has happened and what the near-term consequences of that might be very helpful for identifying what needs to be done to mitigate those consequences. And in another way, if something bad is happening, you need to know exactly what those impacts are gonna be with specificity so that you can avoid them or solve them quickly. And then of course, through FEMA and other agencies, we can complement the local response capacity. And the final bullet, I think is something that is there's increasing awareness of this need for the federal government to finance resilience assets. There are probably others as well and I encourage you all to think about them because this is a complex space. There's a lot of work that is ongoing but there's also a lot of work to do. And I think that includes everything from understanding what resilience means in a given context and how to help communities be more resilient. So all of your brains will be very helpful in helping us do this well. And with that, next slide. Happy to answer any questions along with Gil and thank you all again. Thank you very much, Stephen and Gil, very informative talks and a lot of useful information, especially for the students who have not think about this area or may plan to jump into conduct research in this area, especially a lot of free access data sets and tools are extremely valuable to the researchers. So with that, I would say if anyone has question, please submit your question through the Q&A portal or you can use the raise hand function, then I'm going to unmute you so that you can ask question. We have about 10 minutes for Q&A and I would start with a question about the last slide Stephen mentioned, so the data collection. So at the previous couple of slides, you talk a lot about third party accessible or free accessible tools like the Sandias resilience community and the microgrid tool and others. So how about the data sets? Because Stanford students, I talked about last week, 80 or 90% of them took the class which is machine learning or AI 101 class and they are struggling about any use for data they can play around. They're very curious about any data sets available for the resilience. Can you elaborate a little bit more about available data sets related to resilience? Yeah, it's a great question. I'll start and then I know Gil will have thoughts on this as well. Several federal agencies collect data that would be of relevance. The energy information administration collects a lot of data about the energy system in the United States. That's electricity and fuels, location, volumes, prices, et cetera. There's a lot of good information from them. FERC, the Federal Energy Regulatory Commission also has some data sets available. They might not be obvious but you can ask them for certain things if there's a need. You can't necessarily code an API and have it scraped but there's some good stuff there. We're also working on essentially like a data collection primer where we identify high value data sets for this kind of analysis and who usually owns that data. That's not quite ready yet but hopefully it'll be done soon and it would be out there. And I know that's... Because when it gets right down to it, a lot of times these data sets are scattered in different places and there's really no, unfortunately, no replacement for the legwork of going around and getting them. But Gil, please chime in. I know you've thought about this harder than I have. Gil, you probably mute yourself. I am, Liang. Can you hear me now? Yes. Okay, so that was my redundancy. I muted my screen and my phone so I had to stop or unmute them both. So I was just gonna agree with Steven. Couple things that I was gonna say is I think you highlighted an issue that's really important. This is one that has come up in multiple seminars and briefings especially under the Advanced Good Modeling Program as we coordinated with the Office of Science. As you know, things like open data, as you pointed out, provide an opportunity to be able to do analysis and research and there's no second to them. So as a, I would say across several different offices including OE and particularly RPE, the Advanced Research Project Agency, we've started to try to create some open data sets that would anonymize what I will say specific power system characteristics but allow, for example, the ability to do some fundamental analysis. So under the RPE office, they had the Grid Data Initiative which allowed some approaches to the way different algorithms would allow unit commitment or security constrained up in Power Flow or other different types of approaches to the way you would do analysis on a system. Within our Office OE a couple of years ago, we actually had a funding opportunity announcement that allowed the provision of some open data specifically targeting machine learning and AI. Basically recognizing that there's a need to be able both to have data sets to train those algorithms and then broader deployment and demonstration around those. And it's one that we're trying to continue to grow. So I know all things like natural gas domain and others were looking for what that appropriate balance is to support the innovation and to support the research that you're talking about, Leon, balanced against again, the sensitivities around some of the system-specific data. But we're working hard to try to be able to create some opportunities there for being able to help students and others specifically or particularly in academia be able to do what they need to do to help the industry and the sector move forward and transform the place. One question from the Q&A portal, I think it's a little bit vague. Let me try to interpret it in my own way. A lot of useful information you presented here and how can a local town office of emergency service and to know this kind of information and to have access to this kind of information? Steven, did you wanna start with this one or do you want me to? Please go ahead. So I think one of the things from a department standpoint, if I understand the question, Leon, it's really about how do you access this? That gets into my earlier comment about technical assistance. We talked about it at the state level. But there've also been projects and demonstrations that we worked with the, well, say individual communities. Steven mentioned New Orleans. There are other communities that we've worked with at a local level to balance and understand, again, community resilience versus utility reliability, for example. We've worked in the past with some organizations that were focused specifically on just like a hundred resilient cities-type initiatives, but again, and I think it's an area of a good point. It's about recognizing that a lot of these decisions and priorities are made at the local level and being able to figure out ways that this information is accessible is something that we're continuing to do. Part of our hope is the things like the models, not only are a platform to do the analysis, but they actually can be linkages that show how coordination across those different layers, fed state, local, can be improved and coordinate the insights that help all of those get the appropriate stage decision-making to support resilience and reliability. And I'll just add that it's a tough problem that we've got with this space. There are a few thousands local governments around the United States and it's next to impossible to reach all of them in an efficient way. But FEMA works with state counterpart, state emergency management agencies who have, and the states have varying degrees of successful relationships with their local governments, whether it's city, county, township, et cetera. So we try to get what we've learned out through that network. And then we have some people dedicated to technical assistance whose job it is to try to find states who need this information and help them learn how to use these tools. But it's a problem that we'll never fully solve. And it's just, it's another one like data collection that ultimately boils down to hard work. Thank you. We have one guest raise a hand. I'm trying to clean up as many questions as I can. So I'm going to unmute Nori Rudravesh. Hi. Thank you. Can you hear me? Yes. Okay. So my question was about the metrics for resilience, right? I think Gil mentioned in his section that one of the efforts that Office of Electricity is doing is also working on new metrics for resilience and I was wondering if you could speak to that a little bit. And a follow-up was that we know that we have well-established metrics for resilience and Nor can fork are responsible for implementing these metrics. Is there any effort to do similar implementation for resilience? So that doesn't be a question. Thank you. Yeah. You're going to see us? I know, yeah. Go ahead. Yeah. So I'll take a start on this one and then maybe Steven can highlight some of his thoughts. So the report, there's actually a series of reports questions well timed. Just came out last week. They were released. They're part of something called the Grid Modernization Laboratory Collaborative or consortium. It's sort of if there are a series and I can send this link maybe to Yuliang or if somebody specifically wants my emails in there. But they include an assessment of the different metrics not only in terms of resilience but they include reliability as well as other attributes and try to put together, we'll say decision frameworks on what they may mean to different localities and communities and help them think about what might be most appropriately structured for their particular interests. But yeah, it's been a, I'll say a very labor intensive process, one that's acquired a lot of coordination but I think it's a good synopsis of a lot of the discussions and work that's been, I will say cutting edge in terms of being able to think about and assess these. I think one of the, I'll say the challenges is how you start coupling these different attributes together. How do you weight them? Because that often becomes a very individualized thing. So part of what we're I think looking at in terms of some of these projects called the Resilient RDS Projects under GMLC but Resilient Distribution System Projects is exactly that. How do you look at resilience but look at other attributes such as affordability and reliability or security and balance these in terms of the priorities and investments that may need to be made. Steven, I'll turn it over to you if you have additional thoughts. Yeah, I'll just add that. I recommend the report that Gil identified. There's some really good work represented in those papers worth a read for sure. I think you also touched on the heart of the issue with resilience with regard to metrics is that the threats and risks from in one place aren't going to be the same as they are in another. The risks in Miami aren't the same as Omaha, Nebraska. They both face very real risks and threats but they have different risk profiles, infrastructure needs, community sizes, and so on. So it's hard to identify ex-ante what metric should be used to measure or indicate resilience that can be used in both places. So right now, I think we're kind of stuck on the idea that in order to do something measurable, you have to have a local context in which to apply some of these frameworks. Terrific. Thank you again, Gil and Steven for your presentation. I really appreciate it. Thank you everyone for attending today's webinar and Gil and Steven, when time is allowed, I will definitely invite you back to Stanford. We have an amazing museum here. You'll be able to see something that's from your old town.