Everybody Matt here for late in sports cards rip in 2023 tops chrome baseball hobby 12 box full case break number 20 pick your team We have Brett W. Braves Brian H. Blue Jays Brian L Giants and Nationals Chris P. Tigers Chris F. Phillies White Sox Astros Daniel H. Yankees Don B. Metz Dodgers Dustin M Royals Jair W. Mariners Jordan in Padres Josh T. Pirates Karim a Angels Larry P. Reds Mark L. Red Sox Paul H. Brewers Ray G. A's Thomas T. Rangers Tim T. Cardinals Tim L. Marlins and Twins and Rays Wyoming H. Guardians Wenchu L. Rockies Will K. Cubs U2C D-Backs and Orioles. All right, let's do it box number one Moreno Coloss nice Cardinals that is rookie Aqua wave auto to $199 Nolan Gorman Grat St. Louis 65 of $199 Matt Olson refractor Cal Stevenson rookie Prism refractor Pasquantino breath Beatty rookie Wilson Contreras refractor Jose Ramirez 88 Rice Harper Titans Marquitos rookie refractor Lewis Aaron judge negative refractor Keep Ryan Hayes refractor Luis Castillo person refractor Aaron judge 88 James Outland rookie Logan Ohapi rookie refractor Mastaka Yoshida rookie refractor Nate Eaton rookie Prism refractor Spencer Steer rookie refractor Joey Vado tops in Technicolor Christopher Morel rookie 88 Adley rookie Juan Soto Titans Byron Buxton refractor Gunner Henderson rookie Hunter Green Magenta speckled 350 Tristan Casas Joe Musgrove refractor Lloyd Jimenez Prism refractor Oswald Praza rookie 88 Francisco Alvarez rookie future stars Danzby refractor Michael Grove rookie Prism refractor refractor Taylor Ward Technicolor Matt Olson rookie Nolan Gorman Corbin Carroll rookie It's not puka. Yeah, I had a great morning. How are you? Lonzo Anthony Volpe Mirrors is John Carlos Stanton refractor Magenta refractor rookie to 399 Shin Taro Fuji Nami Jose Miranda refractor Tyler Freeman rookie Prism refractor Ronald Cunha Titans Shin Taro, I'm sorry Trump card Osvaldo Cabrera rookie refractor Tristan Casas rookie purple speckled to 299 red socks Jinami Peter Lonzo refractor Josh Young rookie Juan Soto Prism refractor Rara Castillo. That is A's rookie Otto Cal Stevenson rookie refractor Kyle Stowers Logan Ohapi rookie Kodai Senga rookie Prism refractor Starlin Marte refractor CS Suzuki future stars box number three Let's go Donner's basketball team all filled up. We have nine to go Francisco Alvarez rookie von Grissom and rangers rookie refractor Otto to 499 Bubba Thompson your Mitchell rookie refractor Shereo Tani Marcus Simeon Prism refractor Luba refractor Mitchell Alex Pregman 88 when you'll cruise Max Scherzer Titans James Outland rookie Christopher Morel Rookie Jordan Walker rookie refractor Spencer Torkelson future stars in say a Suzuki green refractor to 99 rookie refractor Louis Ortiz Prism refractor Kodai Senga rookie There's Tobar 88 rookie Javier Asad rookie refractor Raryn Cronacion rookie Prism refractor Gunner Henderson rookie Ramon Laureano refractor Tristan Casas rookie Buxton only rookie Titans Garrett Mitchell and Jordan Walker Reese Hoskins refractor. I wouldn't mind seeing the original one Louis Ortiz aqua lava rookie to 199 Austin Riley Fractor Carlos Perez rookie Prism refractor Riley green rookie. All right box number four is coming Nine to go in Donner's team all basketball 49 99 a spot Masatake Yoshida Moreno All-card ship that base is split evenly This is raised rookie Otto Jonathan Aranda barrel blue and a young goal G whiz. That's awesome are not a refractor Simeon Woods Richardson rookie prism refractor Lauren Carnation rookie refractor Nice. Whoa. Look at this Adley Ruchman rookie short print photo variation orange speckle to 25 Orioles with the color match big card Baltimore That is awesome. Grats. Oh Mag that one for you one second here. That's awesome It's Kirby Mullins Jose Ramirez Justin Casas rookie rice Harper Titans Jose Altuve refractor DJ LeMayhew That is purple refractor to 250 Vlad and James Altman rookie the orange speckle image variations One in sixteen thousand nine hundred and thirty eight packs, which is the same rarity as super short prints Kodai Senga rookie refractor Raphael Devers prism refractor Lieber Torre. That's about one in every 59 cases on average Aaron judge 88 Adley rookie Riley Greene rookie future stars Riley Greene rookie Randy Rosarena refractor chair balsam Michael Grove rookie refractor Shohei Otani tops in Technicolor Connor Henderson rookie Martinez Rookie 88 Christopher Morel Juan Soto Titans Stowers Vinny Pasquantino rookie refractor Jordan Walker rookie says Cal Stevenson rookie Greene Sonar to 99 a's Nice color match. Oh That was a Garrett Mitchell rookie Michael Harris Rookie Cal Stevenson rookie refractor CJ Abrams prism refractor Yoshida rookie Parazza rookie 88 Brett Beatty Rookie and d-backs Rookie Otto Buddy Kennedy Cedric Mullins refractor Corvin Carroll rookie Michael Taglia rookie prism Altuve prism Goldie 88 Kunia Titans Ethan small rookie on the Coloss Oswald Parazza rookie refractor Tyler Freeman some magenta speckled to 350 drew waters rookie refractor Jayrod future stars DL Hall rookie refractor and base Rizzo Nolan Jones rookie prism refractor Alec Minoa refractor Aaron judge Technicolor Anthony bull pay rookie Tatis refractor Alonso 88 James Altman rookie Anthony Rizzo refractor Greenway rookie Carlos Perez to 99 and refractor Alex Pregman Ruiz, Randy Rosarena prism refractor Alec Thomas future stars box number six I'm the eight on Don Russ team all Tovar 88 rookie and strider future stars CJ Abrams refractor Ryan Mount Castle prism refractor Jordan Walker rookie Tyler Stevenson refractor Here at Mitchell Mookie Technicolor Moreno waters Miggie 88 Adley Titans rookie Josh Young Ryan McMahon refractor Nolan Gorman rookie negative refractor new Darvish refractor Thomas prism Logan Ohapi Kyle Tucker 88 Gunner Henderson rookie This is Reds rookie Otto Spencer steered Cincinnati on the board There's Casas Springer refractor Rice Harper prism Christopher Morell rookie refractor James Altman rookie CJ Abrams Josh Smith Rageman 88 Scherzer Raphael Devers refractor Strimski and rookie Riley Greene Quayton Kershaw magenta to 399 Kodaisenga rookie O'Neill cruise refractor Chris Sale prism refractor Drop quick link here for Don Russ team all basketball Eight to go for Don Russ team all basketball. It's our only break left to fill If we have more breaks tonight, grab your spots. And also we grab our the spots with 2023 national break at the beginning of the title for today and tomorrow. You'll be entered into that promo. We've had a going since last Tuesday, our Springer We get into that promo and One person going to want to know nine bone chrome draft Mike Trout refractor auto BGS 9510 Adley rookie future stars. One person will win An 86 Flier Michael Jordan rookie PSA eight Miguel Vargas rookie refractor One person is going to win a Tom Brady fanatics Fanatics alphanics Signed helmet half of its box half of its Patriots Salvador Perez They also have boxes A case we have boxes we have packs we have break credits 200 winners Hunter Greene refractor Vlad 88 Nolan Gorman rookie Guardians rookie auto Oscar Gonzalez Mookie refractor Albert Pujols prism refractor JJ Bleday rookie refractor Pujinami Bobby Whit jr. Future stars Josh Young rookie Devers Technicolor Nolan Gorman rookie 88 Robichette Titans Coloss rookie Kay Kevali rookie refractor This is Mitch Hannigar orange refractor to 25 Giants nice color match Josh Bell refractor Rasmussen Prism Riley Greene rookie 88 Clayton Kershaw Titans Rookie refractor Gabriel Moreno Corbin Burns Smigenta Speckle 350 Kenzie Gore Fractor Justin Burlander prism Box number eight Justin Kossas rookie 88 This is Dodgers rookie purple speckle auto to 299 Michael Grove Riley Greene Rookie refractor James Altman rookie Masataki Yoshida rookie you Darvish prism Auto rookie refractor Jay Melendez Cody Clemens rookie Austin Riley 88 Riley Greene rookie Jordon Paul Gulchman refractor Jayrod Future stars Andy Lloyd Jimenez Refractor negative refractor Ezekiel Doran Rookie refractor Gunner Henderson rookie Nolan Gorman rookie prism refractor St. Kossas rookie Sandra 88 Michael Harris rookie Javier Baez refractor Jordan Walker rookie Ezekiel Tobar rookie prism Adley rookie Jake McCarthy refractor Logan Ohapi rookie Technicolor Josh Young rookie 88 Sverera Mike Trout Titans Jay Rodd Laska's Tyler O'Neill refractor Rookie wave to 75 Hunter Brown Astros Logan Ohapi Tray Turner refractor Jeremy Pena prism Box number nine Aaron Judd jd8 Seiya Suzuki Future stars Oswell Prasa rookie refractor Austin Riley prism Royce Lewis refractor Wander Tray Turner Technicolor Christopher Morale rookie 88 Here is Nolan Gorman rookie Titans Harper Cedric Mullins refractor Shohei Otani that is green wave to 99 Nice one angels we're going to mag this one I don't think it's a $200 card but unless he wins MVP then the buyback value on it's 200 So we'll mag that one for you angels Max Meyer It is looking almost like a lock that he is going to be Oh it is Now the last one sold for 200 Never mind then rookie refractor Corbin Carroll Rujinami Danzvi prism refractor Josh Young rookie Yeah by comparison his that's I mean that's why it's selling to that much his green wave from 2022 selling for or sold for 40 bucks so Juan Soto Titans Hey there he is Gratskrieg DL Hall rookie refractor and gold Paul Goldschmidt nice gold goldie Hey thanks Andre We go Cardinals Refractor Ronald Acuna Giancarlo Stanton prism refractor You know 88 and Braves rookie Blu-ray wave auto to 150 Jared Schuster This color match auto for the Braves Rodin Senga rookie refractor Dermis Garcia Mon Loriano prism refractor Logan Ohapi rookie refractor Anthony Volpe Spencer Torkelson future stars box number 10 There's Vlad and Red Sox rookie refractor auto to 499 Jeter Downs rookie refractor Yvonne Herrera Alec Fulm prism Von Grissom rookie refractor This is Nice mariners That is ultraviolet all-stars Gold refractor to 50 Julio Rodriguez Congrats Seattle Is that Jared? Jared Crats Jared W Yep that's right Riley Green rookie 88 We can Kershaw So Karim asked for Ohtani and got it Jared asked for number J-Rod Got it. Any other requests? Chris Sale refractor Hunter Green future stars and Mackenzie Gore Gold wave to 50 Nationals Somebody to request a taco Fractor. I haven't seen one yet Francisco Alvarez That's rookie refractor Jazz Chisholm prism refractor Prism Chisholm Springer Lee sorties and Tigers Topchromothinix Rookie game used Jersey Riley Green I would take one banana split Shoei Ohtani Alec Thomas refractor I have a banana split and probably over a year Xander Bogarts Prism refractor Yeah that was a cool jersey Old-timey looking jersey Jeter Downs rookie refractor It depends on the team. This was Pick Your Team styles. The prices vary by team That is Francisco Alvarez Rookie tops in Technicolor Ethan Small and Coloss Nolan Gorman Rookie 88 Libertor Christopher Morel Rookie Obechette Luis Arias or Luis Arias Fractor This is Danesby Swanson Aquor refractor to 199 Cubs Yeah he is his base car His autos he's in the ribs with the Red Sox his base he's with the Nationals Francisco Alvarez Rookie Sean Murphy refractor They get those autos out early Which is why there are almost no Redemptions in this Von Grissom J.P. Crawford Prism Yahl Hall So then when they switch teams they don't they can't like remake them and then repay them to sign all the cards Probably doesn't make sense financially or in terms of the timeline Yeah I always thought that was weird too But it makes sense now Xander Prado Jeremy Pena J.Rod refractor Rujanati Marcus Strowman Prism Josh Young Rookie Shohei Otani refractor Neal Kareem Yordan Alvarez Technicolor Rookie 88 Josh Young Oh did you nice Travis Yeah that was the Orange to 25 No no It would be there's Mike Trout Titans A terrible terrible decision to put Ellie and anything as a rookie for 2023 Miggie refractor If they did they'd lose almost a whole year a whole baseball year products that he could be a rookie in Alcantra Purple to 250 Corbin Burns Refractor Nolan Gorman Rookie Lexa Stiaz Prism Refractor Austin Riley 88 Yeah that's true Yordan Titans Logan O'Hoppy Rookie Vigaro Oscar Gonzalez Rookie refractor Nelson Velazquez and Green Wave to 99 M.J. Melendez Royals the Chanager Refractor Chiasca Hernandez Prism Tristan Costas Rookie 88 Garrett Mitchell and Jordan Walker It's Cardinals Rookie Otto Matthew Libertor Something on the side here I don't know if that'll wipe off or not right above my left thumb came yeah it came off just a little piece of straight foil or something Castellanos refractor Michael Harris Rookie Kevin Galsman Prism Vanig and C.J. Crom Refractor Riley Green Rookie Michael Harris Rookie Future Stars Four mags already in this case about one more of an open request for a net-tot out here if you don't say we're gonna do that Tristan Costas Rookie 88 I don't know if anybody's noticed but the top chrome cardstock is just a little thinner this year on the base. That is Rockies Rookie Otto Michael Toglia Small Armand Marquez Refractor Marte Prism Brett Beatty Rookie Refractor it is it seems like it anyway I don't know maybe it's just me maybe my hands have grown yeah hit my mid 40s growth spurt Jordans Coloss Corbin Carroll Rookie Nolan Aronato Refractor Francisco Alvarez Rookie Future Stars and Rookie Blue Refractor Sam Woods Richardson to 150 Twins they do look thin Volpe Rookie Austin Hayes Refractor Nolan Jones you know what if I guess if making them more thin results in this type of quality control absolutely take it Xander 88 very few issues I've noticed Beaver Vaughn how about a big parallel here Al Tubey Refractor McCarthy Prism Parazza Ken Waldechuk Rookie Refractor Brett Beatty Rookie and Technicolor Mike Trout Mazataki Yoshida Josh Young Rookie 88 Mike Trout Titans James Altman Rookie Randy Rosarena Refractor Rookie Aqua Refractor to 199 Miguel Vargas Ian Hap Refractor Cody Clemens Leverator Mark Vientos Prism Refractor and last pack that is Prism Refractor Matt Olson Rosarena on the back All right, let's do a recap we had Tigers Rookie Top's Chrome Authentics Game Use Jersey Riley Green Negative Refractors Eloy Jimenez Nolan Gorman Rookie and Aaron Judge Magenta Refractors 399 Clayton Kershaw Shintaro Fujinami Rookie Magenta Speckle 350 Corbin Burns Tyler Freeman Rookie Hunter Green Purple Speckle Rookie 299 Tristan Kossas Purple Refractors 250 Sandy Alcantara and DJ LaMahue Aqua Refractor to 199 Rookie Miguel Vargas Aqua Lava to 199 Louis Ortiz That was a Rookie as well Blue Refractor to 150 Rookie Simeon Woods Richardson There's an A's color match here that was a Green Sonar Rookie Cal Stevenson to 99 Green Waves to 99 Imdian Jay Melendez and Carlos Perez Green Refractor to 99 Seya Suzuki Gold Refractor to 50 Paul Goldschmidt Gold Wave to 50 Mackenzie Gore Orange to 25 Mitch Hanniger Giant's color match there and awesome case here Bassados Paul Rookies That's Rockies Michael Tuglia Cardinals Matthew Libretor Guardians Oscar Gonzalez Red Spencer Steer D-vax Buddy Kennedy Rays Jonathan Aranda A's Cal Stevenson Refractor out as 499 Red Sox Jeter Downs Rangers Bubba Thompson We had Dodgers Rookie Purple Speckle Auto to 299 Michael Grove Braves Rookie Blue Ray Wave Auto to 150 Jared Schuster Mariners This is Ultra Violet All Stars Gold Refractor 48 to 50 Julio Rodriguez Angels Green Wave to 99 Shohei Otani Cardinals That is Rookie Aqua Wave Auto to 199 Nolan Gorman and Orioles That is Rookie Short Print Image Variation Orange Speckle to 25 Adley Rochman Awesome stuff That'll do it for the break Thank you everybody We'll find us stuff next


Welcome to our first CSV keynote. I'm Danielle, I'm one of the organizers based here in Portland. And I'm so excited to be able to introduce you all to Heather Joseph. For anyone who isn't familiar with her work, she's the executive director of Spark, and I have it here on my phone, so I don't mess it up. It's the scholarly publishing and academic resources coalition. And what that means is that she's on the front line of advocating for better data policy in the United States, better access to research data. She's also on the PLOS Board of Directors. And she helps organize OpenCon, which for me was a transformative conference that has changed my career completely. So y'all should go to that conference. This guy in the front is wearing a shirt. So without further ado, here is Heather. Welcome to Portland. Thank you so much. What a great place to give a talk, although I did say that I was really grateful that I walked into a church chapel and the walls didn't automatically burst into flames. So I feel like it's a great sign and it should be a reasonably uneventful talk, hopefully. Thank you so much for including me in this phenomenal conference. I'm really excited to be here today. And if there's anything that's guaranteed not to give you agit or indigestion after lunch, it's talking about data policy in Washington, DC right now. So my apologies for the timing, but what I wanna do today is actually talk about the state of play for open data. I feel like this is echoing here. I feel like a little rock star. I'm gonna step back from my computer. The state of play. And I'm gonna try to do it in three phases to take a little nostalgic look back at the last eight years and sing the way we were in my head while I do that. Take a look at where we are now in the very, very eventful and somewhat transformative months since the recent election and talk about what that's meant to our continued work to open up publicly funded data and then spend the most time looking at where we need to be and where we wanna go and hopefully be able to outline some concrete strategies and actions that we might think about collectively taking together to help us keep the momentum moving in the right direction towards open federal data. And for the majority of my talk, I'll talk about open government data with a broad brush, meaning all government data, but the focus for me is primarily on advocating for open access to research data. And that comes because in my career, I spent 15 years as a scientific journal publisher. And I like to say I was raised by the astronomy and astrophysics community. I spent my first seven years working professionally for the American Astronomical Society. And this has really been important to me in kind of determining how I think about data and how I think about what the default mode should be when we're gathering data. And as those of you who are familiar with the astronomy community know, this is in their DNA, right? From the very beginning, I started working for them in 1989 and they were collecting digital data in large scale from instrumentation, automatically sharing it. This is just the way that that community approach is dealing with data. And my good friend and colleague, Bob Hannish, who worked on Hubble Space Telescope, liked to say, yeah, sure, the astronomy community is all for open data because our data is worthless, right? Which I loved, but which actually is a serious comment at heart because after moving out of the astronomy community, I went into cell biology and neurosciences where data collected has serious commercial, potential commercial value, right? So when Bob was talking about this, he was saying is actually a comment that I've kept in the back of my mind as I've also thought about the fact that not every community approaches data with the same native bent towards, I'm gonna share it unless or until somebody gives me a compelling reason why I shouldn't. And that for me has been really something that's propelled me through the work that I've done since the beginning of my career and particularly the work that we're doing at Spark. As Danielle noted, we're an international advocacy organization, we're nested in the academic and research library community, but our goal is as a global coalition to really try to work to set that default expectation and default mode to open in research and education. So we work on data, educational materials like textbooks, we work on scientific journal articles, but the thrust of what we do is to really try to reset the rules of the road. And there's nothing more powerful that we've found in terms of a tool to help us accomplish that goal than working in the policy environment, right? Policy is very foundational, it's a real lever. Policy is also a long game, which is why I kind of chunk this talk into sort of three different segments to try to illustrate how important it is to have your eye on the long ball when we're working in the policy environment. It's a very incremental game to a certain degree and I'll touch on that in a minute. I swear this is not gonna be a talk that just goes through, here are the policies that were passed and here's the language, but I do have one slide that I wanna show because I think it's really important to understand how we got to where we are now in terms of policy development. Nobody hates to be out on the limb by themselves taking a risk, doing something new more than a policymaker and particularly a politician in DC. So all policy development is incremental and depends on having strong policy precedents to work from. And in the open data community, whether we know it or not, we've been incredibly fortunate to have a very strong set of policy precedents in the United States that our open data policies have been able to be built on. We heard a little bit in some of the talks earlier about the importance of things like FOIA, the Freedom of Information Act and the foundation that it has helped us lay for ways to get access to information. But there's also been a series over, roughly a 30-year period beginning in the 60s and culminating in the late 1990s of other foundational policies that have given us language that we've used and we've relied on to build effective, strong policies for open data in the U.S. And weirdly, you've probably never heard of OMB's circular A-130, right? Live it, learn it, know it, love it because it's actually our best friend in the open data world. Almost all of our open data policy language that we've been successful in sort of imbuing in the United States to underpin the work that we've done comes out of this little circular which basically just sets the expectations for the U.S. government, federal agencies, their operations in how government information and particularly government information as we interpret it in the digital age is utilized, right? And it has phenomenal language in it from a policy perspective. Government information is a valuable national resource, right? And its value is only increased when it's made available to all in a timely and equitable manner. And this little circular also lays the groundwork to say what does that mean? Well, it means it's open, it's unrestricted and you can't charge any more for it than the cost of marginally distributing it, which in the internet age is, you know, should be zero. So it's wonderful that we have this foundational language. It's extremely valuable. It really has, you know, again, built a solid foundation. But going back, you kind of notice that a lot happened during this period, but then in 1998, we kind of went into a little bit of a hiatus. And that's not unusual. You have a foundation. You really need a precipitating event, something that's gonna help catalyze action to keep momentum going forward. And we got one. We got one in a beautiful way when Barack Obama was elected president. This is the open data catalyzing event. You know, he's elected president. He takes office and open data fabulousness ensues for eight years. And I'm only marginally being facetious about this because when I look back and think about the breadth of changes and the progress that we've been able to make because of the dedication of this administration towards making open and open data a centerpiece of their agenda, a priority in the policy environment. It's quite amazing. So I want to talk a little bit about the way we work. I tried to embed, somebody's got to help me with keynote and PowerPoint. I wanted like the little Barbara Streisand music playing in the background and I was gonna toggle back and forth and kind of listen to the music. But next time, next time. The slides are beautiful enough because of the policy. So we'll enjoy the sweet music that they bring to our ears. This administration couldn't have hit the ground running more strongly in terms of presenting the notion that open was a key construct. And you all know that the open government directive was issued on the first day of the Obama administration's coming into office in his first term. You come out of the gate and what he talked about and what this directive did was make open the presumptive mode for the federal government, not just for operations but also for information coming out of the federal government. And at the time, I remember thinking, wow, this is really great. Somebody's speaking our language and it's really nice. Looking back as we'll talk about now, it's more than nice. It is a seminal moment, I think, for the United States and for the operations and the propelling forward of the movement to say at the center of it all, the public deserves access to information that the government produces, whatever it may be and certainly data is at the centerpiece. In the open government directive, there was a few sentences that basically said that in DC speak, each agency should take prompt steps to expand access to information by making it available online and in open formats. No government had talked in the United States about making information available in open formats until this directive came out. I mean, this is really extraordinary stuff. I was in the talk that the lovely woman from the DC city open data government, are you here? Did earlier, where are you? She's not here. She did this wonderful talk on open data and she had, oh, there you are. Sorry, your talk was fantastic and I loved the fact that you highlighted data.gov as something that's in use now for all of its works because I actually went back to the way back machine and pulled out one of the early iterations of data.gov as an example. The open government directive asked federal agencies for the first time in US history to identify two high value data sets and to make it openly available through data.gov. I mean, and that was groundbreaking, right? In 2009, asking agencies to find and make two data sets available openly had simply never been done before. And data.gov came under fire then and rightly, probably rightly so, it's not perfect, but what it did was really sort of set the tone. More of the way back machine. High value data sets in 2009, the most used data set on data.gov was the White House visitors log, which if you're like me and you're nosy, you want to know who's in and out of the White House, I thought it was pretty great, but there were a lot of stories about like really is this high value? Again, we sort of flash fast forward now that the visitors logs to Mar-a-Lago are not being released. It's not quite as funny, but it is I think ever more poignant that this was information that really sort of laid the groundwork. Again, not perfect, but it set the expectation from day one that open data was a key priority. And with this administration, the open data hits just kept coming, right? It wasn't just in terms of putting out policies or edicts or saying that shall share data, we're going to use the right words. This administration backed up the policy actions with specific policy constructs, with specific actions, including sending signals that this was so important that we need a chief technology officer. I love this picture of the three CTOs. Some people like the three tenors from opera. I think that Anish, Megan, and Todd Park are like rock stars in their own right. We had never had a chief technical officer. The message that that sent, however, that this was a key priority is something that's simply never been done and it's unmatched. Ditto for bringing in a chief data scientist. We hadn't had that in the United States. This is so important. We need leadership, we need talent, we need visibility. That was the signal that was sent. That's what helps build momentum, right? You can write all the policies you want, but if you don't back it up with the energy and the cachet that having somebody in a leadership position brings to the role, this kind of stuff dies in D.C. all the time. This movement didn't die in D.C. Do in large part to these lovely folks but also do in part to an infusion of young and talented and continuously moving and growing people into the pipeline through the presidential innovation fellows. Through 18F, shout out to the two people from 18F that I just met sitting over there. I hear there's more. Amazing, amazing, taking that energy, taking the leadership from the top, infusing it with people with expertise and putting them in positions where they can really make a difference and raise the visibility of the impact that open government data across the board could have in a positive way on citizens' lives. I also have to give the props to people like the Department of Commerce, which was the first department to implement an open data advisory committee to a US sitting secretary, the Secretary of Commerce. That little CDAC logo is for the Commerce Data Advisory Council, which brought together leaders in the open data movement from business, from research, from code from America, from civil society, to directly advise a sitting cabinet secretary on effective open data policy. Fantastic, really amazing things happening. In terms of propelling momentum forward during his administration, President Obama didn't just stop and say, I'm doing one thing and that's it, I'm bringing the talent in and then we're never gonna talk about it again. He did this beautiful thing with the administration in terms of starting big with a sweeping open government directive and then getting ever more granular in terms of the prescriptiveness, descriptiveness of policies that were put into place. In the first year of his second term, this executive order making open and machine-readable the new default for government information came out. And for us, in terms of the advocacy work that we've been doing to really try to reset the DNA of a community, of a research community, these words are amazing. They are words that don't just speak to one community but rather to our nation as a whole that says this is the way we should be thinking about it. It's not resetting one small subset of DNA to considering that we should be sharing this stuff unless there's a compelling reason not to. This is in fact the way that the entire country should be moving. And he followed that up just a month later with in case anybody was in my community and our community and the research community was worried that we're not covered fully enough with a memorandum out of the Office of Science and Technology Policy which further described open access to research data and the terms and conditions under which that needed to be made. So a really heady time when we look back and say in an eight-year period we went from no action on open data in the US government, really no policies to having this series of interconnected mechanisms that really helped us move the ball forward. And just as an aside, Congress was in on the action too, lest you think this was only the administration. At the same time we had Congress in flux where we had Democratic control and Republican control at different times, Congress was also moving pieces of legislation that were following the open data ball and helping it to move forward like the data act which went into effect just last year. So the most important thing about those eight years is that it really changed the landscape and helped us make open data to be considered foundational. Foundational for scientific discovery, yes, but also foundational for better health, for innovation, for economic growth, for equity, for all of the kinds of things that are priorities in the federal government. So we were really on a wonderful trajectory and frankly we were spoiled. It was not that hard to advocate for open data during the Obama administration. So things were going pretty well until we had another precipitating event. And I chose this slide because the headline I think for the open data community rings unfortunately pretty true, right? When the election happened, no one really had much of an idea of what would happen in the open data environment to the momentum towards open data under a Trump administration. We're finding out in the way we are. Just as an aside, at Spark, when we say we do advocacy we do pretty heavy duty political advocacy. So we spent a significant amount of time over the 18 months leading up to the presidential election meeting with every single declared presumptive presidential candidate in both parties which meant we met with all 15 of the Republican contenders to talk with them. Someone's laughing. I'm like, you should have been with us. Talk about, I was gonna say Jesus wept. I can say that in here. So yeah, yeah, yeah. We talked with all of them about open data and the importance of open data, open access, open everything. And we had varying degrees of receptivity depending on who we talked to. And we also established a really strong relationship with some of the strategists on the Republican side which we were hopeful would be helpful to us in this new world. We are roughly 103 days into the administration, Saturdays, 103 days into this administration. And I don't think any of us were prepared despite the legwork that we did for the effects that we would see coming out really from day one in January. We've had to kind of work through fake news on a large scale but also fake news and science and in data, alternative facts. I don't think these were terms or concepts that we could have in any way, shape or form prepared adequately to face in January and in February. We've had to deal with 404 errors, right? Things being removed from websites, not errors because oops, we just let the connection die. But things like open government and the information about the open government directive actually being taken down from the White House website. We've had to deal with agencies having data scrubbed from their websites. The EPA is probably the one that people are most familiar with but certainly this was not something that we were prepared really to see to the degree that it's happening. We had to deal with in the first three days of the administration, agencies being told that there was a moratorium on being able to share data and talking to the press about scientific data they were collecting, the FDA, HHS, EPA, really things that were completely antithetical to the spirit of openness in this arena that we had gotten used to under the last administration. And frankly this is really built up to the point where we have a real sense that an empirical data-driven fact-based operating mode that we had enjoyed is really endangered. The world in DC, the world in the US in this environment for open data and frankly for most other things has completely changed. That's a depressing part of the talk, okay. Which leads us to thinking about working on the way we need to be. And at Spark and in the community that the communities that we work so closely with we always try to look for pragmatic, proactive, solution-oriented, action-oriented solutions for how we can deal with the reality that we find ourselves in. And one of the things that we've known, I'm gonna try to give three potential paths forward but before I do that, I think the thing that we've settled on in going through the stages of grief since the election in terms of trying to deal with where we are in the open movement is that we've really come to the conclusion we need to up our ante in terms of being activists for open data. No matter how difficult it may be to speak up and to take a stand for something, we really need people to come out of their shells and be willing to be vocal sort of superhero advocates for not only protecting the data that we've become used to getting access to but also being willing to go out on a limb to continue to ask for more. One of the most effective advocacy strategies and again, I'm really sorry I can't remember your name Lovely Woman from DC who I'm gonna just keep for. Kate, one of the things that you said in the question and answers, someone asked you about how to be an effective advocate what can you do to be an effective advocate and your answer was I ask the government for things like I literally will just ask. That's advocacy and I'm gonna talk a little bit more about how we can do this in a coordinated way but I really do believe that this is one thing that we all need if we care about protecting the momentum towards open data that we really need to become more comfortable with doing because public data is endangered data right now in the US. There's no other way to really spin it. So what can we do? Well first, as I said, I'm splitting this into three buckets. The first thing that we can do is play active pragmatic defense. We don't wanna lose the gains that we've made under the last administration and the gains that we've worked so hard to enjoy. So what do I mean by this? We're already seeing steps that individuals and groups are starting to take. So if public data is endangered data, it's something that we're seeing on a daily basis and early in January, we started to see people really becoming concerned over in particular the fragility of climate change data. And we started to see individuals taking steps and kind of taking the page from the open source, software development community, the open data community in terms of how they were thinking about dealing with it. So I don't know whether you're aware of these but I'm assuming this community has been fairly intimately involved at least some of you in data rescue events. I'm really proud of the library community in particular as they have been sort of at the center of recognizing the fact that these data sets are out there. They may in fact be in someone's spotlight in terms of being vulnerable to being taken down. So what libraries and interested folks are doing is kind of getting together on a weekend. It's like a hackathon but instead it's called a data rescue event. They're identifying data sets, they're bringing in people with the expertise to help scrape the data and putting it into libraries on our campuses around the countries where it can be protected, preserved, and access can be insured. And this happens spontaneously and organically. In the intervening months, I can't believe it's only been four months but in the intervening months we're starting to see a little bit more organization coalesce around these individual events. And this is something that I think is really great, right? Yes, it is simply protecting existing data but as a first step it's super important that we look out for opportunities to do this. The data rescue community is starting to kind of move under the umbrella of trying to communicate, become more organized, get a strength and numbers approach and look to see what we can do to really sort of provision these individual efforts to become more large scale collective efforts to protect more and more data. And there's actually a meeting in Washington DC coming up next week which was supposed to be, initially it was designed to be a meeting of just a small handful of groups who were interested in looking at what infrastructure is needed, what investment is needed, and what we could do to actually make this into something that's more organized, sustainable long term strategy for protecting data. The small meeting now has 50 organizations including US federal agencies, research funders, library organizations, the internet archive, all working together to try to come up with a strategic plan to make sure that this strategy can be enacted going forward. It is a wide open process. So if you see data refuge or you see something that is now being referred to as the libraries plus network and you're interested in being involved, this is the kind of activity that it refers to and wide open invitation and plea, please think about getting involved. The second strategy is that we don't only wanna play defense, right? That's never the position that you wanna have to be in for the long term. And I think the good news is that we don't have to only play defense in this environment. The second thing I really wanna to emphasize is that progress is still possible in the policy environment. We're not just relegated to rescuing data and hoping that nothing else happens. We need to recognize that we can also run positive pragmatic proactive plays. That's a lot of peas in one sentence that just came out there. Yeah, I kinda like that. But we really do need to recognize the opportunities that are in front of us to drive the momentum forward. Single party control of the House, the Senate and the White House is unusual. And we have to be clear eyed and realistic and recognize that it does present opportunities to move legislation. Having those ducks in a row is not something that happens every day. And if you can find ways to take advantage of it, you actually can get things done. And that holds very true in the data environment. So there's a piece of legislation that has been introduced in Congress, identical versions in the House and the Senate, called the Open Government Data Act. And what this piece of legislation does is actually takes President Obama's second memo, making open and machine readable the default for all federal data. And it would codify it into legislation. And it's really interesting to think about the fact that this piece of legislation was introduced. It was introduced with bipartisan co-sponsorship in both chambers. And it is actually moving on a nice clip. It is likely that this legislation, or I would say it is possible too likely that this legislation could clear in this first session of, this first year of this session of Congress. What's fantastic about this is that it shows the way in the policy environment to move from having a directive that's associated with the previous administration. The Obama M1313 memo making open and machine readable. The law, the preferred path forward. To having Congress say, this isn't just the preference of a president, it's the law of the land. And this is actually the game that we're learning that we need to be very proactive in taking advantage of in order to be able to move the agenda forward, not just hold ground, but advance the agenda. Moving from an executive directive which are ephemeral and they are vulnerable as we all know to being overturned with the stroke of a pen to legislation that's codified and is much more difficult to turn over is a really powerful thing. And that this piece of legislation is actively moving in Congress is a very hopeful signal. And it's something that Spark is working very hard to advocate for with a set of coalitions that I'll talk about in a second. As a bonus, right, as I mentioned, that piece of legislation has bipartisan support. Open data in general has garnered bipartisan support fairly regularly in Congress. So this isn't a one-off. This is an opportunity to really kind of hold on to this and to look for other opportunities to move the ball forward. Last week we had two senators, a Republican from Colorado and a Democrat from Michigan introduce a piece of legislation that's giving the data rescue and refuge communities a boost. Which is basically saying, look, nobody was expecting what happened in the first few weeks of this particular administration. Nobody was expecting data sets to be taken down or gag orders to be potentially issued. So let's get our policy ducks in a row to make sure that that doesn't happen. So this piece of legislation has been introduced. I can't remember it was literally just introduced. I can't remember what it's called. But there's information about it on the website. Oh, the Preserving Data in Government Act. Which really basically says, once the data sets up there, we've got to take steps to make sure that it's permanently up there. We don't want this stuff available just for one generation but for future generations as well. To do this successfully, to support or to introduce or to drive, if you will, in a positive direction. One of the things that's a lesson that we've had to learn for how we need to be is that we need to actively understand what the new priorities are for this administration. It was very easy to see the Obama administration's priorities with that directive on day one. And honestly, the message that we have seen as we've done over the last four months, really as deep a landscape analysis as we possibly can is that the notion of open and transparent as priorities are out. We're not gonna get anywhere open. You could get a meeting in the White House.  You know, you would be heard. That doesn't happen with this administration. However, when we look at those, when we look at their priorities and we look at their language, we recognize that other things that are interesting are in, taxpayers are in, in a big way. Good deals are in if you saw the news today. That's the language we hear all the time. Big wins are in. Right. Right, however, yeah, so they are. So how do we take advantage of that? Well, one thing that we're doing is a pragmatic strategy and I issue an invitation again so everybody here is to try to take advantage of this is what resonates. We're re-spinning up a coalition that we actually used under the Bush administration to successfully secure legislation that requires that the National Institutes of Health have all the articles that are reporting on publicly funded biomedical research made openly available online to the public called the Alliance for Taxpayer Access. So taxpayers are entitled to the research or results or outputs, including data of research that their tax dollars support. That is something that no one disputes and it is actually language that resonates in this current Congress and with this administration. So this is a coalition that doesn't cost anything to be a part of but that there's a strength in numbers approach in going and saying we're promoting this particular approach. We're also learning that we have to position open data not just as open for open sake but open as an enabling strategy to achieve the priorities of this Congress and of this administration. So again, open as a calling card isn't going to work but taxpayers being entitled to data that their tax dollars have supported does get you in the door and then once that data is available it can help you achieve a good deal in this way or whatever, fill in the blank here. With this administration again and with this Congress a lot of it is about jobs and the economy and that's fine, right? That simply is what's at the top of the list for them. This is a bill that was introduced this year called the Financial Transparency Act and you may say, what does that have to do with us and open data and this conversation? This is actually a bill that is asking or would require that reports that are filed with the SEC any financial reports that the government produces on the viability and productivity of different businesses and companies in the United States be made available in forms that are structured, standardized and machine readable and searchable. I went to a meeting that the sponsors of this bill had Republicans and Democrats and when I tell you that members of Congress stood up at a microphone and said PDF is not a searchable enough document. We need structured markup language, right? I got a little teary, it was a little crazy. They didn't use the words XML but they're there. Like that's where almost there come little woodlands creatures come to the eat the food. They're almost there and it really is remarkable that this is a piece of legislation that speaks their language, right? Open in order to achieve the aims that they care about, right? It's speaking directly to them and they wanna make this reporting data available for a reason, right? Not just because open is better than closed. What they see is that if these reports are available for text and data mining, they'll be able to find trends and patterns that can help investors find small businesses and companies that might actually return more back to the economy and produce jobs. So that's fine. This helps us understand how to talk about our issues, the issue of open data in a way that resonates with Congress. For those of you who are veterans of the open access and open data policy wars, the co-sponsors of that bill are representatives ISA and Maloney. I don't know whether the names mean anything to people. Robin's laughing because they co-sponsored a bill called the Research Works Act but eight years ago that would have overturned the policy that NIH has requiring essentially the same thing for scientific reports. They didn't understand what we were asking eight years ago but they understand it now in the context of financial reports and that's, I kinda get a gig a lot of that. I think it's great, I think it's funny but I also think it's great because we're now able to go into their offices and saying, yes, yes, yes, you like this for financial reports, you're gonna love it for scientific research. You're gonna love it for, you know, fill in the blank there. It's been an education and a real opportunity to stop and think about using the language, reframing the issue in a way that resonates with the powers that be, if you will. And to support this, I think one of the things that we've really had to do is to think about building stronger cross-sector relationships, right? They care about what's happening with the economy, with jobs. We need to build our partnerships and open up our doors in terms of really being much more inclusive and sort of outward focused in terms of the organizations and the people that we'll partner with. We need to be working with business and commerce a lot more closely in promoting the interests of sort of pure open data or scientific open data. So Spark has actually joined an organization called the Data Coalition, which is a group that has been working on promoting things like the Open Government Data Act, the Financial Transparency Act. And they've been very successful in bringing businesses to the table. So in going to meetings and working with them to promote things like the Financial Transparency Act, they're starting to see us as allies to understand that we understand what they're trying to do. And it's given us wonderful opportunities to try to educate them on what it is that we wanna do in other sectors, including science and research, and we're beginning to build those bridges. We need to do a lot more of that to be successful in keeping the momentum going forward. And finally, I just wanna close with one final strategy that we've been working on and that I think is really important for us all to think about. We concentrate on policy and oftentimes we think that DC is the only game in town or insert your country capital here. Publicly funded data isn't the only game in town. And right now in the environment that we're in, I think it's really important that we look at the whole board, we look at the whole playing field, we look at any pieces that we can move that might help us in our efforts to both preserve the gains that we've made and also to potentially promote the gains, additional gains. In particular, private funders and foundations invest in work that produces an enormous amount of data. And these foundations are increasingly understanding the message that open as an enabling strategy helps them increase the impact of what they're investing in. So for example, the Gates Foundation has an open access policy that went into effect in January of this year that not only requires that articles that report on their funded research be made immediately available, but that the data that underpins those articles also be made available on day one when it's published. And they're doing that because they've explicitly said, look, Gates Foundation has the Global Health Initiative. The aim of the Global Health Initiative is to save lives. Any delay in getting this information out to anybody who can help to save a life is unacceptable. Open in order to save lives, open data in order to save lives. That's really powerful. But they've been able to connect this as an enabling strategy back to their core mission. And we've seen in the news, where's Carly and the Moore Foundation? Because I really wanna say congratulations on your open policy. Lots of foundations are really beginning to get this. And interesting foundations, sort of non-traditional new players like the Chan Zuckerberg Initiative, for example, are showing a real willingness to engage and to jump into this space. The Schmidt Family Foundation, Eric Schmidt Foundation, which focuses on climate change as well and global environmental issues, is also kind of playing around in this area. And I think it's up to us to really work to encourage them and to help them understand what it is that they can do to make a difference in this field. And what they can do is kind of go the route of the Moore Foundation, go to the route of the Gates Foundation, talk about open data as a leveraging strategy to increase the return of investment in what they're investing their foundation dollars on. Really kind of try to take it home. We need exemplars, right? These are organizations that are viewed as peer organizations by the federal government, right? They're investing at the same, almost at the same level that we're talking about, billions of dollars in investments, they care what happens. Seeing other people doing the actions that promote open data is a really important and potentially productive way to also keep pressure on the US federal government to be moving in the right direction. And I do wanna note that the research funders are also talking amongst themselves. They're beginning to coalesce. There's a group that started in December called the Open Research Funders Group that includes Gates, Soros, Arnold, the Arnold Foundation, Robert Wood Johnson, Sloan Foundation, a set of folks who are really thinking about how can they make a difference using open as an enabling strategy? And they're starting to meet regularly to talk about not only what they should be doing with policies covering their own research, but also what collective action might look like if they were to get together and actually think about putting some linking arms and working together muscle into this space. And that's a theme that I think you probably have seen running through this talk. One of the reactions to the recent election that I saw sort of on a personal level but also on a professional level was a real sense that people wanted who are interested in the same kinds of things like open data, like open, but fill in the blank have really sort of kind of come together and at first sort of just taken solace that we could be together and talk about like, wow, this is really unexpected. But as the months are passing, one of the things that is developing is a sense of we wanna stay together and we really wanna link arms and see what we can do together. What are their actions that we can do? We're much stronger together when we think about moving forward. And that is really what I wanna close on. Leadership is local on this issue. Sometimes we think about national politics as being something that somebody else has to do in D.C. And I hope what I've been able to illustrate is that individuals make a difference and we have to be willing to break out of that egg shell and step up, speak up, speak up. Let me try this again, rewind that tape, speak out. We have to learn to speak first, Heather. Step up and take action. And there's lots of ways that we can do it together. The coalitions that I noted before are wide open. The data refuge, data rescue projects are wide open. Ideas that you have, expertise that you bring to the table is sorely needed. Your voice matters, your actions matter more. We have a lovely representative, many representatives actually with us here in the audience from another opportunity. The other group of influencers that I cannot emphasize the importance of enough are OpenCon. I call them the OpenCon kids, right?  Encouraging young people, early career folks, whatever the discipline is, from libraries to research to political science to medical students, there's an opportunity to get them together under the umbrella of something called OpenCon, which is something that Danielle mentioned when she did my introduction. Spark is loosely one of the organizers of OpenCon. This is a spontaneous sort of community organized event, but also year round community that can help interested people develop the capacity for leadership and leadership in advocacy on open issues, including open data. You could get a cape if you participate in OpenCon. I can't guarantee it. Roshan is from, he started Open Access Nepal. So he got the cape for efforts that he had done, but really the community efforts, the linking arms and working together is the most important thing I think that we can do to keep the ball moving forward. So we've got 103 days down by my count. Depending on leap year, we might be able to knock a couple of days off 1357 days to go. So I hope that you'll keep thinking about this and please talk to each other, talk to us, talk to any organization that's in the mix of this about what we can do together. So thank you so much. Questions? I don't have the cape with me. I wish I did. Who has it? Roshan doesn't have it anymore, does he? Juan Pablo? Okay, could be, yeah. One minute. Woohoo! Oh, where am I? Yeah, sorry. I hope so, we're honestly not sure yet. It's been true to, I think, form very low profile, very hesitant to step out and step on anything early. Young leadership is really where we're seeing an emphasis so far in the discussions around the foundation, but I do think this notion that he was responsible for all of these amazing steps, it would be highly likely that it would be something that would be resonant and it would be an amazing contribution to the discipline. We have a, yes, go ahead. Thank you. Yeah, and privacy is obviously an enormous concern. That isn't our specific purview, but we work very closely with organizations who have that like epic, that have that right at the heart of what they do. We try to stay as deeply connected as possible to organizations that have that interest at heart. I mean, I think for us, sometimes we'll say with data as open as possible as closed as necessary, and I do think there are shades of gray in terms of privacy with data that we're not talking about everything open to the 100th degree all the time, but thinking about the default being open unless or until that there's some reason, including privacy reasons that you might not want to have everything available to be aggregated so that identifiers can be found. There's no perfect solution, but we're aware of it and we try to work very closely with organizations who are helpful in that space.


Hello, welcome to this CUBE conversation here in Palo Alto, California in the CUBE studios. I'm John Furrier, host of theCUBE. We are here with a hot startup really working on some real, super important security technology for the cloud, great company Orca, security, Avi Shua, CEO and co-founder. Avi, thank you for coming on theCUBE and share your story. And serving me. So one of the biggest problems that enterprises in large scale, people who are going to the cloud and are in the cloud and are evolving with cloud native have realized that the pace of change and the scale is a benefit to the organizations but the security teams and getting that security equation right is always challenging and changing. You guys have a solution for that. I really want to hear what you guys are doing. I like what you're talking about. I like what you're thinking about and you have some potentially new technology. Let's get into it. So before we get started, talk about what is Orca security? What do you guys do? What problem do you solve? So what we invented in Orca is a unique technology called side scanning that essentially enables us to connect to any cloud environment in a way which is as simple as installing a smartphone application and getting a full stack visibility of your security posture. Meaning seeing all of the risk whether it's vulnerability, misconfiguration, lateral movement risk, work that has already been compromised and more and more, literally in minutes without deploying any agent without running any network scanners, literally with no change. And while it sounds to many of us like it can't happen, it's a snake hole, it's simply because they are so used to on-premise environment where it simply wasn't even possible in physical server but it is possible in the cloud. Yeah, and we've had many CISOs on the cube over the years. One CISO told us that, and this is a direct quote, I'll find the clip and share it on Twitter, but he said the cloud's more secure than on-premise because there's more changes going on. And I asked him, okay, how did you do it? He says, it's hard, you got to stay on top of it. A lot of people go to the cloud and they see some security benefits with the scale, but they're gaps. You guys are building something that solves those gaps, those blind spots because of things are always changing, you're adding more services, sometimes you're integrating, you now have containers that could have, for instance, malware on it, it gets introduced into a cluster, all kinds of things can go on in a cloud environment that was fine yesterday. You could have a production cluster that's infected. So you have all of these new things. How do you figure out the gaps and the blind spots? That's what you guys do, I believe. What are the gaps in cloud security? Share with us. So definitely, you're completely correct. I totally agree, the cloud can be dramatically more secure than the on-prem. At the end of the day, unlike an on-prem data center, where someone can come, plug in your firewall, plug in your switch, change things, and if you don't instrument it, you won't see what's inside. This is not possible in the cloud. In the cloud, it's all code, it's all running on one infrastructure that can be used for the instrumentation. On the other hand, the cloud enabled businesses to act dramatically faster. When I say dramatically, we're talking about order of magnitude faster. You can create new networks in a matter of minutes, workloads can come and go within seconds. And this creates a lot of changes that simply haven't happened before. And it involves a lot of challenges, also from security instrumentation point of view. And you cannot use the same methodologies that used for the on-prem. Because if you use them, you're going to lose. There were a compromise that worked for certain physics, certain set of constraints that no longer apply. And our thesis is that essentially, you need to use the capabilities of the cloud itself for the instrumentation of everything that runs on the cloud. And when you do that by definition, you have full coverage because if it's run on the cloud, it can be instrumented on the cloud. This is essentially what Orca does. And you're able to have this full visibility for all of the risk and the importance because all of them are essentially virtual workload that we're able to analyze. What are some of the blind spots in the public cloud, for instance, I mean, that you guys are seeing that you guys point out or see with the software and the services that you guys have? So the most common ones are the things that we have seen in the last decades. I don't think they are materially different, simply on steroids. We see things that people, services that are launched, nobody maintained for years. We see things like improper segmentation that everyone have permission to access everything. And therefore, if one environment is rich, everything is rich. We see organization where something was dramatically hardened. So people find a way to, a very common thing is that now everyone talks about CIM and tightening their permission and making sure that every workload have only the capabilities that they need. But sometimes developers are a bit lazy. So they'll walk by that, but also have keys that are stored, that can bypass the entire mechanism that again, everyone can do everything on any environment. So at the end of the day, I think that the most common thing is the standard hygiene issues. Making sure that your environment is patched, that things are tightened. There is no alternative ways to go through the environment. It's scale. Because at the end of the day, the hardest thing for a security professional, you need to secure everything. The attacker just need to find one thing that was missed. And you guys provide that visibility into the clouds to identify those. Exactly. One of the top reason that we implemented Orca using the side scanning technology that I've invented is essentially because it guarantees coverage. For the first time, we can guarantee you that if you scan it, that way we'll see every instance, every workload, every container, regardless of if it's running as a native workload whether it's a Kubernetes, whether it's a service function, we see it all because we don't rely on any per asset integration. We don't rely on friction within the organization. So many times in my career, I've been in discussion with customer that has been breached. And when we got to the core of the issue, it was you couldn't, you haven't installed that agent, you haven't configured that firewall, the IPS was not up to date. So the protections weren't applied. So this is technically true, but it doesn't solve the customer problem, which is I need the security to be applied to all of my environment. And I can't rely on people to do manual processes because they will fail. Yeah. Yeah, I mean, it's, you can't get everything now on the velocity, the volume of activity. So let me just get this right. So you guys are scanning containers. So the risk I hear a lot is, you know, with Kubernetes in containers is a fully secure cluster could have a container come in with malware and penetrate and even if it's air gap, that's still there, still problematic. You would scan that. Is that how it would work? So yes, but sorry for cutting, but we are not scanning only containers. The essence of orca is scanning the cloud environment holistically.  We scan the images that are installed and we scan the permission that these images are running. And most importantly, we combine these data points. So it's not like you buy one solution that looked at your AWS configuration. It's different solution that look at your virtual machines that run the cluster. Another one that looks at your cluster configuration. Another one that look at the web server and one that look at the identity. And then you have results from five different tools that each one of them claims that this is the most important issue. But in fact, you need to infuse the data and understand yourself what is the most important items or how they are correlated. We do it in an holistic way. And at the end of the day, security is more about thinking as graphs, as vectors rather than list. So we're able to tell you something like, this is a container, which is vulnerable. It have permission to access your sensitive data. It's running on a pod that is indirectly connected to the internet through this load balancer, which is exposed. So this is the tech vector that can be utilized versus just a tool that you say you have a vulnerable containers, but you might have hundreds where 99% of them are not exposed. Got it. So it's really more logical, common sense vectoring versus the old way, which was based on perimeter based control points, right? So is that right? Is that, you're looking at it like, okay, whole new view of it, not necessarily old way. Is that right? Yes, it is right. We are looking at is one problem that is handled in one tool that have one unified data model and on top of that, one scanning technology that can provide all the necessary data. We are not a tool that say install vulnerability scanner, install identity access management tools and infuse all of the data to work and will make sense. And if you haven't installed the tools to you, it's not our problem. We are scanning off your environment of your containers, virtual machine, service function, cloud configuration using our technology. We understand the risk, we put them in a graph and essentially part is the tech vectors that make it for you. This sounds like a very promising value proposition. If I'm a five workload production workload, certainly in the cloud and someone comes to me and says you could have essentially a holistic view of your security posture at any given point in that state of operations. I'm going to look at it. So I'm compelled by it. Now, tell me how it works. Is there overhead involved? What's the cost to, not suddenly in dollars, but you can, I mean, I want to share the price to be great, but like I'm more thinking of me as a customer, what do I have to do? What are operational things we have to set up? What's my cost operationally? And is there overhead to performance? You won't believe me, but it's almost zero. The Plank Orca is literally quick clicks. You just log into the application, you give it the permission, the read only permission to the environment and it does the rest. It doesn't run a single upgrade in the environment. It doesn't send a single packet. It doesn't create any overhead within our public customer list companies that are very critical workloads which are time sensitive. I can quote some names, companies like Databricks, Robinhood, Unity, Sysense, Lemonade and many others that have critical workloads that have deployed it for all of the environment in a very quick manner with zero interaction to the business continuity. And then focusing on that because at the end of the day in large organization, friction is the number one things that kill security. You want to deploy new security tool. You need to talk with the team. The team says, okay, we need to check it doesn't affect the environment. Let's schedule it in six months. In six months is something more urgent than times fly bys and think of security team in a large enterprise that needs to coordinate with 500 teams and make sure it's deployed. It can't work because we can guarantee. We do it because we leverage the native cloud capabilities. There will be zero impact. This allows to have the coverage and find these really weak spot that nobody has been looking at. Having the technology you have is also good but these security teams are burning out. And this brings up the cultural issue. We were talking before we came on camera around the cultural impact of the security assessment kind of roles and responsibilities inside companies. Could you share your thoughts on this? Because this is a real dynamic. The people involved, I'll say people process technology, the classic, things that are impacted with digital transformation but really the cultural impact on how developers push code, the business drivers, how the security teams get involved. And sometimes it's about the security teams are not under the CIO or under the different groups. All kinds of impacts to how the security team behaves in context to how code gets shipped. What's your vision and view on cultural impact of security in the cloud? So in fact, many times when people say that the cloud is not secure, I say that the culture that came with the cloud sometimes drive us to non-secure processes or less secure processes. If you think about it, only a decade ago, if an organization could deliver a new service in a year, it will be an amazing achievement from design to deliver. Now, if an organization cannot ship it within weeks, it's considered a failure. And this is naturally something that was enabled by the cloud and by the technologies that came with the cloud. But it also created a situation where security teams that used to be some kind of a checkpoint in the way of no longer in that position, they are in one hand responsible to audit and make sure that things are acting as they should. But on the other hand, things happen without the involvement. And this is a very, very tough place to be and nobody wants to be the one that tells the business you can't move as fast as you want cause the business want to move fast. So this is essentially the friction that exists whether can we move fast and how can we move fast without breaking things and without breaking critical security requirements. So I believe that security is always about a trial of educate, there's nothing better than educate about putting the guardrails to make sure that people cannot make mistakes but also verify an audit because there will be failures in, even if you educate, even if you put guardrails, things won't work as needed. And essentially our position within this trial is to audit, to verify, to impart the security teams to see exactly what's happening. And this is an enabler for a discussion because if you see what are the risks, the factor that you have, this is an environment that haven't been patched for a decade with the past with one to six. It's a different case then. I need you to look at this environment because I'm concerned that I haven't reviewed it in a year. That's exactly a great comment. You mentioned friction kills innovation earlier. This is one friction point that mismatch off cadence between ownership of process, business owners goals of shipping fast, security teams wanting to be secure and developers just want to write code faster too. So productivity, burnout, innovation, all are a factor in cloud security. What can a company do? To get involved. And you mentioned it's easy to deploy. How do I work with Orca? You guys are just, is it a freemium? What is the business model? How do I get in, how do I engage with you if I'm interested in deploying? So one thing that I really love about the way that we work is that you don't need to trust a single word I said. You can get a free trial of Orca at our website, orca.security, one scan on your cloud environment and see for yourself, whether there are critical risks that were overlooked, whether everything is set and there is no need for a tool or whether there is some areas that are neglected and can be acted any given moment already been breached. We are not a freemium, but we offer free trials. And I'm also a big believer in simplicity and pricing. We just price by the average number of focus that you have. You don't need to read the long formula to understand the pricing. Reducing friction, it's a very ethos. It sounds like you guys have a good vision on making things easy and frictionless. That's what we want. So let me ask you a question. So I want to get your thoughts because there's a lot of conversations in the industry around shifting left, and that certainly makes a lot of sense. Which controls in security do you want to shift left and which ones you want to shift right? So let me put it that I've been in this industry for more than two decades. And like any industry, every once in a while there is a trend and of something which is super valuable but some people believe that this is the only thing that you need to know to do. And if you know a garden hype cycle, at the beginning, every technology is the top of that and we believe that this can do everything. And then it reaches the productivity of the area of the value that it provides. Now, I believe that shifting left is similar to that. Of course, you want to shift left as much as possible. You want things to be secure as they go out of the production line. This doesn't mean that you don't need to audit what's actually running because everything, you know, I can quote Amazon CTO Werner Vogels about everything that can break will break. Everything fails all the time. And you need to assume that everything will fail all the time, including all of the controls that you baked in. So you need to bake as much as possible early on and audit what actually happening in your environment to find the gaps because this is the responsibility of security teams. Now, just checking everything after the fact, of course it's a bad idea, but only investing in shifting left and education have no controls of what actually happening is a bad idea as well. A lot of people, first of all, it's a great, great call out there. I totally agree, shift left as much as possible but also get the infrastructure and your foundational data strategies right on what you're watching and auditing. I have to ask you the next question on the context of the data, right? Because you could audit all day long, all night long, but you're going to have a pile of needles looking for a haystack of needles, as they say, and you got to have context and you got to understand when things can be jumped on. You can have alert fatigue, for instance. You don't know what to look at. You can have too much data. So how do you manage the difference between making the developers productive in the shift left more with the shift right auditing? What's the context in cloud? How do you guys talk about that? Because I can imagine, yeah, it makes sense, but I want to get the right alert at the right time when it matters the most. So we look at risk as a combination of three things. Risk is not only out pickable the lock is. If I'll come to your office and we'll tell you that your security issue is that the cleaning clothes that lock can be easily picked, you'll laugh at me. Technically, it might be the most pickable lock in your environment, but you don't care because the exposure is limited. You need to get to the office and there's nothing valuable inside. So I believe that we always need to take, to look at risk as the exposure, who can reach that lock? How easily pickable this lock is and what's inside? Is it your critical grunge rules? Is it keys that can open another lock that includes these grunge rules or just nothing? And when you take this into context and the wonderful thing about the cloud is that for the first time in the history of computing the data that is necessary to understand the exposure and the impact is in the same place where you can understand also the risk of the locks. You can make a very concise decision of is this something that makes sense? That is a critical attack vector. There's a pickable lock, a critical vulnerability that is exposed in, that is an exposed service and the service F keys that can download all of my data or maybe it's an internal service, but the port is blocked and it's just have a default web server behind it. And when you take that, you can literally produce 0.1% of the alert even less than that, that can be actually exploited versus the rest that might have the same severity scores or sound as critical, but don't have a risk in terms of exposure or business impact. So this is what why context matters. I want to just connect what you said earlier and see if I get this right. Well, you just said about the lock being picked, what's behind the door, it could be more keys. I mean, they're all there and the thieves know it too. It's bad guys know exactly what these vectors are and they're attacking them. But the context is critical, but now that's what you were getting at before by saying there's no friction or overhead because the old way was send probes out there, send people out in the network, send packets to go look at things which actually will clutter the traffic up or look for patterns. That's reliant on footsteps or whatever metaphor you want to use. You don't do that because you just wire up the map and then you put context to things that have weights. I'm imagining graph technologies involved or machine learning. Is that right? Am I getting that kind of conceptually right that you guys are laying it out holistically and saying that's a lock that can be picked but no one really cares. So no one's going to pick it. If they do, there's no consequence. Therefore move on and focus energy. Is that kind of getting it right? Can you correct me where I got that off or wrong? So you got it completely right. On one end, we do the agentless deep assessment to understand your workloads, your virtual machine or container, your apps and the risks that exist with them. Using the side-skinned technology that some people call it like the MRI for the cloud. And we build a map to understand what they're connected to, their security groups, the load balancer, the keys that they hold, what these keys open. And we use this graph to essentially understand the risk. Now we have a graph that includes risk and exposure and trust. And we use this graph to prioritize the attack vectors that matters to you. So you might have thousand upon thousands of vulnerabilities on servers that are simply internal and these cannot be manifested that will be depolarized. And 0.1% of them that can be exploited indirectly to a load balancer and we'll be able to highlight this one. And this is the way to solve alert fatigue. We've been in large organization that use other tools that add million critical alerts using the tools before Orca. We ran our scanner, we found 30.  No one can manage a million alerts. Well, I got to say, I love the value proposition. I think you're bringing a smart, a view of this. Obviously you've had the experience there. Avi and team, congratulations. And it makes sense that the cloud is a benefit. It can be leveraged. I think security being rethought this way is smart. And I think it's being validated. Now I did check the news. You guys have raised significant traction as valuation. Certainly raised that around a funding of 210 million, I believe, a series C funding over a billion dollar valuation, which is a unicorn status. I'm sure that's a reflection of your customer attraction. Could you share customer success that you're having? What's the adoption look like? What are some of the things customers are saying? Why do they like your product? Why is this happening? I mean, I can connect the dots myself but I want to hear what your customers think. So definitely we're seeing huge traction. We grew by thousands of percent years of year. Literally, we had times during late last year where our sales team, literally you had to wait two or three weeks till you managed to speak to a seller to work with Orca. And we see the reasons is organization have the same problems that we are focusing on. They have cloud environments. They don't know their security posture. They need to own that. And they need to own it now in a way which guarantees coverage, guarantees that they'll see the imported items. And there was no other solution that could do that before Orca. And this is the fact. We literally reduce deployment project that takes months to minutes. And this makes it something that can happen rather than being on the roadmap and waiting for the next guy to come and do that. So this is what we're from a customer. The basic value proposition of Orca haven't changed. We're providing literally cloud security that actually works, that is providing full coverage, comprehensive and contextual in the seamless manner. So talk about the benefits to customers. I'll give you an example. Let's just say theCUBE. We have our own cloud. It's growing like crazy. And we have a DevOps team, very small team. And we start working with big companies and they all want to know what our security posture is.  Do I just work with Orca? Because the more the trend is integration. I just was talking to another CEO of a hot startup and the platform engineering conversations about people are integrating in the cloud and across clouds and on-premises. So integration is all about posture as well too. I want to know, people want to know who they're working with. How does that factor into anything? Because I think that's a table stakes for companies to have almost a posture report. Almost like in the MRI you said, or a clean bill of health. So definitely we are both providing the prioritized risk assessment. So let's say that your cloud team want to check their security with your cloud security risk. They'll connect Orca, they'll see the top risk that are prioritized in a very, very clear way. What's been compromised or fully zero. What's in the imminent compromise, meaning an attacker can utilize today. And you probably want to fix it as soon as possible. And things that are hazardous in terms that they are very risky, but there is no clear tech vectors that can utilize them today. There might be things that combining other changes will become imminent compromise. But on top of that, when standard people also have compliance requirements, people are subject to a regulation like PCI, CCPA, easy on NIST and others. So we also show the results in the lens of these compliance frameworks. So you can essentially export the report showing, okay, we were scanned by Orca and we comply with all of these requirements of SOC2, et cetera. And this is another value proposition of essentially not only showing it in a risk lens but also from the compliance lens. You got to be always on with security and cloud. Avi, great conversation. Thank you for sharing nice knowledge and going deep on some of the solution and appreciate your conversation. Thanks for coming on. Thanks for having me. Avi Shua, CEO and co-founder of Orca Security, hot startup taking on security in the cloud and getting it right. I'm John Furrier with theCUBE. Thanks for watching.


The current school have really emerged as one to watch in the last few years, producing many going on to the national level, and the level of organization was to be commended on a day when they rose to the occasion. In the 150 meters in girls, the early form was shown by Similia of Clark, but in the end it was Kyra Vitalis of Simmons who searched the head to win the gold in a way leaving Similia and Fede. In the boys' 150, there was no catching Millen Mitchell, a star of the day dominating his division. He won easily ahead of Master of Simmons and Fanness of Wolcott. It felt like a sweet summer in the 200 meters division 3 girls, when summer jewels of Simmons' house continued to have them ahead in the meet, as she ran away from the field to secure the gold. In the end, Sinal of Wolcott was second and Auguste came in third for Clark. In the boys' 200 meters, Clark did the one to combination with Sample of Women Gold, leaving Louisa and his weight in second place on St. East of Genesalon's killing field. In the division 2 girls, Kyriana Kaseme of Wolcott, a strong technique, graceful stride, as she walked away to the gold medal behind her, who left in the end Ernest of Simmons and Albert of Clark. In the boys' 200 meters division 2, Francis of Simmons, he had a comfortable lead, but paid the price for clowning around in the homestretch. In the end, had to put in a desperate dive to the finish to win the gold medal, just ahead of Kaldran of Wolcott and Joseph of Monday. In division 1, the 200 meters, a quick display by Simone Mastre, who maintained a composure and hugged the curve very well to win ahead of her rivals in that race, Wilson of Simmons and Charmaine of Clark. In dramatic fashion, division 1, the early running was done by Pierre Lee of Clark, but in the end, on the homestretch, with the superior power of James of Monday won the gold medal, Joseph second Pierre Lee third. In division 3, the 100 meters was the constant stride of just concentration winning ahead of George and St. East. In division 2, girls 100 meters. Simmons came from behind in a special pattern to win ahead of Ryder and Sussie. And in the boys 100 meters, division 2, Stamper Small emerged victorious in an exciting battle to the finish ahead of his rival Jean of Monday and Williams of Clark. In division 1, the battle for the fastest student at the current school. And in the end, the determination and confidence paid off for Chauvin Alexander of Monday-Z, he beat off Albert and Millington. In the girls division 3, 4 by 100 meters relayed. Trong first leg was in evidence. In the end, it was Simmons who would go on to win comfortably. In division 2, girls 4 by 1, we saw a great recovery by Walcott. Great teamwork in the end for them to recover and go on to power home to the gold. The boys division 2, 4 by 100, was very competitive. And a close race to the finish in the end was what we would see, a competitive two to take. In the end, Simmons won Clark in a second. Division 1, the 4 by 100 meters relayed. Among the girls, Clark stood home comfortably in division 1. In the girls, in the end, the challenge was very strong from Simmons and Walcott that Clark revealed. And in the boys 4 by 100 meters senior, Monday-Z Power it was with the colors flashing in a powered home. In that relay, Clark, the 72nd Walcott came in with LeBron. The final point standing in the first place it was Simmons 1206. Number 2 spot going to Clark 1195. The number 3 spot, Walcott 987. And in fourth place, Monday-Z 942. Simmons housed 1 by 11 points on a great day for the current school and school track and field.