The rise of research entrepreneurs and why it matters

How can researchers who have developed innovative solutions begin to commercialize? What makes a great research-entrepreneur? And how are universities and organizations helping to bridge the research-to-commercialization gap? We will learn those answers and more in this episode with Laure Haak. A neuroscientist by training, Laure has a BS and MS in Biology and Ph.D. in Neuroscience from Stanford University, and she did postdoctoral work at the National Institutes of Health. Her career includes diverse experiences: serving as founding Executive Director of ORCID; leadership roles at Thomson Reuters, The US National Academies, and Science Magazine. She is currently founder and CEO of Mighty Red Barn, a consultancy that supports impact-based organizations building digital infrastructure, and helping research innovators go from discovery to startup. Laure carries on this work as a Research Scholar at the Ronin Institute, and Board Chair of Phoenix Bioinformatics and the Green Bay Chapter of SCORE. You can learn more about Laure and Mighty Red Barn here: https://www.mightyredbarn.com Learn more about Oracle for Research: http://www.oracle.com/research    --------------------------------------------------------- Episode Transcript 00;00;00;00 - 00;00;26;12 How can researchers who have developed innovative products begin to commercialize them? Why are digital persistent identifiers important to researchers? And who are some of the partners that can help researchers get their products to market? We'll get those answers and more on this episode of Research and Action. Hello again. Welcome back to Research in Action, brought to you by Oracle for Research.   00;00;26;12 - 00;00;47;27 I'm Mike Stiles. And our guest today is Laure Haak. Laure is a neuroscientist by training. She has a B.S. and M.S. in Biology and a Ph.D. in neuroscience from Stanford. And she did her postdoctoral work at the National Institutes of Health. She's done a lot over the course of her career, including serving as founding executive director of ORCID leadership roles at Thomson Reuters,   00;00;48;00 - 00;01;14;09 the U.S. National Academies, and Science magazine. She's currently founder and CEO of Mighty Red Barn. That's a consultancy that supports impact-based organizations that are trying to build their digital infrastructure. And it also helps research innovators like many of our listeners, get from discovery to startup. Laure carries on this work as a research scholar at the Ronin Institute and Board chair of Phoenix Bioinformatics and the Green Bay chapter of SCORE.   00;01;14;09 - 00;01;38;01 Laure you're obviously a very busy person, so I'm really glad you're on the show. Well, thank you for the invitation. I'm really looking forward to this conversation. Us as well. So we're going to talk about innovation to commercialization, because we do have listeners who are researchers and PhDs. They've got the research discovery part down. But starting and leading a startup, that's a whole different thing.   00;01;38;02 - 00;02;02;28 But before we do that, what did you want to be when you grew up and what motivated you at each step from Stanford, to ORCID, to Mighty Red Barn? Yeah. And so, I think whenever people ask about careers, it kind of depends on what you had for breakfast, how you answer the question. So, I think the best way to explain my career is that I never grew out of the childhood fascination with how things work.   00;02;02;28 - 00;02;24;19 I never stopped asking why, which has it's endearing and annoying qualities, depending again on what you had for breakfast. I was and still am fascinated with how the brain works. And after college I started graduate school in neuroscience during what was then the decade of the brain. It was a big deal. So I studied hibernation. I studied sleep wake cycles.   00;02;24;19 - 00;02;51;12 I studied how our bodies internal clock responds to light. I was also at the same time involved in the Association for Women in Science as well as Women in Neuroscience, where I managed a quarterly or a quarterly newsletter back in the day when you actually mailed things using stamps in the Postal Service. You know, we couldn’t look at how many people opened, but we had a list of about a thousand people were sending out to.   00;02;51;15 - 00;03;21;14 So during my tenure as president of Women in Neuroscience, that particular group was folded into the Society of Neuroscience. And it is still an active initiative today, which is really awesome to see. So from my postdoc with that portfolio of three years of these newsletters, I joined the Next Wave team at Science Magazine and triple-A US, which is now called Science Careers, and I worked on post-doc policy and career development for science graduate students.   00;03;21;14 - 00;03;39;15 And there's so many really smart people that are so focused on their research, they couldn't see the vast opportunities for applying their passion and skills. I think this gets back to your question, Mike, about, look, there's folks that do research, but how can I be an entrepreneur and start something? And part of it is kind of looking up.   00;03;39;18 - 00;04;04;07 So when I was at the Next Wave team, I helped to support the founding of the National Postdoc Association and then went on to be a study director at the National Academies and working with esteemed scientists to research and produce reports on research workforce issues, including interdisciplinary research, international students. And on the last report I did when I was there was on women in academia.   00;04;04;10 - 00;04;28;15 So from the academies I again moved to something completely different and a tech startup where when I started there was no job description and no job title. It sounds like a tech startup. Yes, but you have to really you know, I came out of academics in that I went to two places where there is a lot of structure, right?   00;04;28;17 - 00;04;53;26 So the tech startup was like, okay. And I was also the only peer there. So I crafted my job and my job title and became the chief science officer. And I help the company build an analytics consultancy that brought the data that they were kind of collecting and munching together to these pressing research policy issues where, you know, you could kind of look at some amount of data.   00;04;53;26 - 00;05;15;07 We didn't have, you know, a lot of it that we needed to really answer these pressing issues. So this was this time was right as compute power was really starting to take off. So I have to admit, during graduate school, we had a computer that took up the size of a room. We had an old one of those things.   00;05;15;09 - 00;05;35;29 And so now a few years later, you can now crunch terabytes of data in hours rather than weeks. And I know these days you can do petabytes in microseconds. But, you know, we're getting there in the machine, sit on a desktop, Right. So this is like this wonderful period of time when people are like, oh, my gosh, what can we do?   00;05;36;01 - 00;05;55;01 And one of the wonderful things we did was work with the National Institutes of Health on a number of program evaluation projects. We had data on grants, we had data on papers, we data on people, we had data on patents. We brought all that together to help the NIH understand what is the impact of their funding in certain portfolio areas.   00;05;55;03 - 00;06;30;27 One of the projects we did was with the NIH leadership, and it was to examine what was thought to be potential bias in the awarding of research grants, a hot button topic and lots of anecdotes. So we were able to bring to bear the compute power and the data that we had to a study which led to a publication of a paper in Science magazine demonstrating a substantial gap in the likelihood of award for black NIH grant applicants, other measures being equal that spurred the NIH to examine their review process.   00;06;30;27 - 00;06;53;26 I'm really, really proud of this work, and I'm proud that the NIH took action, both partnered with us on the work and took action to try to remedy or at least further study and remedy the situation. So some of the stuff I've done, so at the same time all this was happening, startups, right, like to go through and sell and, you know, get money for the investment they've made.   00;06;53;26 - 00;07;24;26 So I was actually part of the startup's management team that was pitching for our acquisition and we were eventually purchased by Thomson Reuters. And overnight we went from a team of about 50 people to a team of about 50,000 people. It is a really big change and I'm the kind of person that really likes the scrappy energy of startups where you can be super nimble and change your mind and oh, maybe we should do this today and started looking for an opportunity to build something new.   00;07;24;26 - 00;07;44;25 So I did the kind of spin in, you know, with the the group. So I did the spin out with the National Post Association. I did the spin in with the evaluation team and analytics team at Discovery Logic, Thomson Reuters. And then it was like, okay, I want to try something else. And this would actually be Let's start a company from the beginning, right?   00;07;44;28 - 00;08;12;29 And I had the phenomenal opportunity to come on board at as ORCID was just starting. And so I became the founding executive director and I was the first staff hire. There was already a board and bylaws and all these other things, but they didn't have any staff. So I became the founding executive director and it was just awesome. I cannot tell you how wonderful that it was, just every day on my hip pinch myself.   00;08;12;29 - 00;08;46;06 I can't believe I have this. Jobs is great. So I helped to. I have to build the operational infrastructure. I built a team and with the team, a globe of community and technology infrastructure for researcher identifiers. So ORCID is essentially a digital name for researchers that connect us with all of our professional activities and contribution. So in eight years we managed to reach financial sustainability is this is a nonprofit and we had over 10 million registered researchers, a thousand members and national consortia in 40 countries.   00;08;46;13 - 00;09;07;28 I was delighted, but it was also time for me to move on because we got where I wanted to get to. It was built and now we had to move into more of a maintenance mode. Then let's build, build, build, right. I was ready for my next build project and I stepped out in 2020 to create Mighty Red Barn, which is, as you said, a consultancy for social impact startups.   00;09;07;28 - 00;09;32;05 So here we are. Well, I'm worried that you're going to go start another company before this podcast is over, but your role at ORCID seems like a pretty big deal when you think about how critical digital persistent identifiers are. Tell me what you're trying to get done at ORCID or what you were working on at ORCID. Why digital identifiers are so important.   00;09;32;08 - 00;09;53;09 Yeah, So I guess the way to explain that is, you know, as you move from print, you know, people going to the library, when I started graduate school, we would go to the library, have a lot of time at the photocopy machine, photocopying stuff from journals. You know, people don't do that anymore. And everyone's looking for stuff on the Internet now.   00;09;53;09 - 00;10;14;06 You can't find things on the Internet unless you have a good key for finding things. Right. And for researchers, anybody with the name notices in my name, I have a fairly unique name, but it's not unique enough to be able to find all of the things that I've done and attach them to me. Even Google still gets me wrong.   00;10;14;06 - 00;10;47;00 I get messages every three weeks saying, Could you please update your record? So what ORCID does is it provides individuals with essentially this digital name, a unique digital persistent identifier that they can use as they're going through their regular workflows. Right. So for example, when you're applying for a grant, when you're registering as a new graduate student, when you're submitting a manuscript or a dataset to a repository, part of that transaction is you including your name and your digital name, your ORCID I.D, as you're going through that workflow process.   00;10;47;06 - 00;11;11;10 So it's not asking you to do any additional work other than basically using ORCID single sign on to go log into these systems, the systems, collect your ID and then attach that ID to the transaction. So now your paper includes your ORCID ID, now your grant includes your ORCID ID, your record at your university, includes your ORCID ID, etc., etc..   00;11;11;10 - 00;11;34;24 So part of that workflow and one of the things I was really, really big on since graduate school was this idea that research outputs are so much more than just journal articles, right? This huge motivation for me, articles are how we talk about the work we do, right? But there's datasets, there's software code, there's instruments made. This committee is mentoring, teaching.   00;11;34;24 - 00;12;05;14 All of these things are integral parts of the research process. So ORCID was not just about, Here's my ORCID IDs. I publish a paper. It was a way to say to the individual, here you have power in determining what to include in your professional body of work. This is your idea. You decide when and where to use it, and you can also decide what is available on your ORCID profile for public view or sharing with trusted parties.   00;12;05;14 - 00;12;34;03 We were all about providing that power and agency to the individual and based on this presupposition, that individual should control what information is shared publicly regarding their digital reputation. And yeah, so I'm I'm proud that ORCID was has been and continues to be part of the story of providing a way for research as an agency over how they are viewed on the Internet and how people can find and see what they've been doing.   00;12;34;06 - 00;12;58;24 Yeah, it sounds like the way an artist would sign their painting, right? Except providing a digital way, a digital recognition of that. Right. And you started to see more artists using digital identifiers at DMS, things like that, to say, this is my work and essentially coded in the back end. So you can't steal or repurpose the art without some recognition or citation of the artist.   00;12;58;24 - 00;13;22;07 That's all of what this is about. Yeah, the applications go way beyond researchers. Yes. Yes. Now, as promised, we need to get these folks from research to commercialization. I've never seen science and research move so fast as it did during the pandemic, and of course, with good reason, we didn't have a lot of time to putz around with red tape and bureaucracy as we had to get a product to the market.   00;13;22;13 - 00;13;46;22 Now it feels like on university campuses around the world, there's a sense of look up our support and resources because we might have to do that again or produce spin outs. What does that framework look like today and what is the level of support? Yeah, and so I think, you know, part of this is how do folks in academics do commercial work, right?   00;13;46;23 - 00;14;14;22 And so I think starting off with how do we talk about ownership? And one of the big differences between academic and commercial research, of course, is intellectual property rights. Who owns the research output shapes how information is shared and how and what can be moved into a product, right? So for me, during COVID, one of the most impressive demonstrations of the power of open collaboration is the National COVID Cohort Collaborative.   00;14;14;22 - 00;14;46;04 Also known as NC three. And I love identifiers. They used open identifiers including ORCID and dyes and organization identifiers to attribute who made what data contribution, which is really awesome. And they also coupled that with this this really strong metadata framework that enabled the combination and the combination of contributed datasets and components of dataset. Talk about awesome. This is not something you could do in one company.   00;14;46;04 - 00;15;33;05 This requires a collaboration across labs and across corporate. This work was instrumental in driving early data sharing during the pandemic, so you couldn't have gotten the product without that data sharing, right? And part of that data sharing happened, at least in part because everyone who contributed data to the collaborative knew they would get credit, even if another group did the analysis and knew that if some missed study that was contributed or some dataset that was contributed was later withdrawn, that that data could be withdrawn from their analysis as well because of the way that persistent identifiers in metadata had been that that framework had been set up at the get go in NC three.   00;15;33;12 - 00;16;00;12 So the group managing the collaborative actually won the inaugural Data Works and Challenge Prize for data sharing earlier this year, and I encourage you to check it out. Is really phenomenal piece of work. And I personally think that's the way we need to start thinking about getting product to market is the step before that which is how do we enable data sharing that allows people to collaborate on these problems?   00;16;00;14 - 00;16;18;28 Yeah, after this, I think you should go work in Hollywood because, you know, you are you see these screenplays that were written by about 11 or 12 people and it's like, okay, who contributed what? Right now that industry kind of has the same problems of people being, you know, the collaborations and what was mine versus what was else's.   00;16;19;01 - 00;16;58;05 Right. But, you know, the world needs solutions. And the younger you are, the more you've gotten used to near instant gratification. We're used to seeing things happen. So have expectations and research shifted as well, or our research institutions moving as fast to commercialization as they can? What's driving that need to commercialize? Yeah, I mean, you've got the by dual act that shifted everything, at least in the US and there's been a strong push ever since then was in the mid-eighties right of where universities set up tech transfer offices and you know have patent attorneys on staff advising people.   00;16;58;05 - 00;17;23;14 There's a number of universities that have spin out incubators, things like that. If I don't think it's getting faster, if anything, I think some universities are realizing there's a huge amount of effort and money that they're putting into these centers that they may not be recouping there. It hasn't been a fast win for many universities in this space, but it's certainly active.   00;17;23;17 - 00;17;49;08 I think, again, coming back to my previous comment, I think in addition to these spin outs and commercialization, where academic IP intellectual property is acquired by a commercial entity, I think what I would love to see is more people considering this collaborative model, right? One in which there is incentive baked in for data sharing by all parties.   00;17;49;08 - 00;18;16;24 Right. And I like to see this civilly. Is it science fiction? Right. We can look at how high energy physics is done, right? There's this large inter-country collaboration at CERN using shared equipment and management. And, you know, researchers can openly access this facility, you know, by applying to work there. And three, this a covered example I just mentioned proved this concept in biomedical sciences.   00;18;16;24 - 00;18;43;18 Right. What I see that similar in both of these models is both the intent to collaborate on big Thorny and of course, expensive like really crushingly. You need to answer the question right now. Problems. There's also the willingness to fund at the highest levels. And I think this might be what is changing a little bit where you see and an agent and a NSF starting to fund these larger collaborative efforts.   00;18;43;18 - 00;19;09;27 I'm really happy to see these things happening. And then also what, NC three and to some extent CERN and others have done is operationalizing attributions using these open and persistent digital identifiers, not just for people, not just for the papers, but for all of the things and the places that are involved in the project so that you can kind of deconstruct and tease apart and understand, Hey, I did this part and I did that part right?   00;19;09;27 - 00;19;35;15 So everyone participating gets credit. Whether you build a detector, develop the methods, collect the samples, perform the analysis, curate the dataset, or even fund the initiative or house the researchers and the equipment. Right? All of that. Everyone understands your different part of it. And I think there is room in this collaborative model for academic and commercial and government entities to work together.   00;19;35;18 - 00;20;02;18 Collaboration. It reduces the upfront development costs for companies, It enables broad talent sharing, which is pretty awesome. It allows, like the postdocs in the academic lab to get some corporate experience working in these collaborations. And it also leverages the strengths of each sector the ideas, the innovation product to market, which most people in academia never think about product to market as well as risk reduction.   00;20;02;18 - 00;20;31;14 Right. Which again, most people in academia are thinking about risk reduction. And I would love to see more research groups looking into these cooperative business structures as an option for bringing products to market. We provide recognition, operational frameworks and I think also really important is this idea of equity for all of the parties involved in this. And you asked for some practical examples and there's actually a co-op accelerator program at START that co-op.   00;20;31;14 - 00;20;52;24 So it's not like you can only get startups through a venture model. You can also get or a venture for profit model. You can also get startups moving through these accelerator programs that are really focused on the co-op structure. So something to look at. If you've met a lot of startup founders, you start to see they have a unique set of talents and drivers.   00;20;52;24 - 00;21;20;16 You know, research entrepreneurs, PhDs may not be like them. That may not come naturally. They've got to learn product market fit, funding strategies, sales, marketing, regulatory compliance, business skills. It's kind of not fair. It's like that, Is it not enough? I'm not a research genius now. I have to be Richard Branson on top of that. Right, Right. So our grad schools, are anyone helping train them to be entrepreneurs or is it assumed they probably don't need to be?   00;21;20;17 - 00;21;42;02 Yeah. And it's funny because, like, our entrepreneurs are actually trained to be entrepreneurs is like, where does that come from? Well, it's almost natural inside me, right? I'm going to say it probably wasn't natural. Looking at any number of things is exposure to certain ideas and concepts and ways of thinking and doing that happen. Right? And so I'm going to tell a story.   00;21;42;02 - 00;22;05;08 I can tell a story here. So back in the day when I was at Science magazine, working on Next Wave, working on postdoc policy, that was when my first kid was born. Okay, fast forward 20 years, several stops later in my career, and I returned to pursue our policy in an early career workforce conference sponsored by the National Bureau of Economic Research.   00;22;05;08 - 00;22;27;04 This is like two years ago. So the very same issues were on the table. And I just like, Oh my God, I feel like I stepped into the Wayback Machine, right? There's perceived poor career prospects by the postdocs. They felt stuck long terms in low paying apprenticeships, no substantive change in the ability to attract and retain diverse talent into science careers.   00;22;27;04 - 00;22;52;28 It was really frustrating even to just sit in the room and listen to the the economist talking about this. I'm like, I can't believe things haven't changed in the last 20 years. This is insane, right? So one of the key skills of researchers is our ability to focus on a problem and give it all we've got. Even if it looks hopeless, we give it all we've got.   00;22;53;04 - 00;23;17;08 And to some degree, that's a parallel skill with entrepreneurs is just like hammer away and make it happen. Right? But it also means it's really hard for us to look up and around and see what else might be good or fun or wise for our career, right? It's even more difficult to do this when the culture of science is driving for speed above all else.   00;23;17;08 - 00;23;39;27 We've got to answer this question right now. Right? Publish or perish. Publishing is so important, right? And because of that, people hold their findings really close for fear. If they're going to be scoops they don't want to share. They're not they're actually disincentivized from sharing. And they're, you know, in their cubbyholes working on their stuff. It's really not a great way to think about how can I be an entrepreneur, right?   00;23;40;04 - 00;24;06;07 So when the structure of science does not prioritize credit for all the people and it doesn't include the necessary components of the research process and what you get credit for collaboration and career development more in your question is not the outcome. So we do need entrepreneurial researchers, whether they spin out a product, run a lab, work in research policy, run a nonprofit.   00;24;06;09 - 00;24;35;06 All of these things are good skills such as team management, data sharing, budgeting, strategy and operations are all essential. And of course, looking at business, these are the same skills. Entrepreneur Sorry, entrepreneurs need to start a business to right? So these you have to have these skills, but it's not what you learn at the university, right? So the big questions are who provides the training and when is this training provided?   00;24;35;06 - 00;24;58;06 And then how? If you have the training, how do you get researchers early career and the supervisor is to prioritize participation in the training. You're supposed to be in the lab. What are you doing outside the lab? How dare you? Right. So one shining light here is the National Institutes of Health launched a program called Best Broadening Experiences in Scientific Training.   00;24;58;06 - 00;25;23;18 And this is one example of a science agency actually providing incentives through a funding program for these training experiences for grad students and postdocs. And I can tell you, I was on the review panel for one of these best sessions, and it was really interesting listening and reading what the universities were trying to do to get people just to come to the training courses that are part of their training program.   00;25;23;18 - 00;25;50;20 As a grad student and a postdoc, it was incredible the amount of resistance that there is in the university setting for having researchers do anything other than their particular experiment. There's a massive cultural challenge there. I mean, it sounds like because you're right, again, the research is doing the research because that's their passion. And it's the old thing of, you know, if I just don't think about this other thing, maybe it'll go away, right?   00;25;50;23 - 00;26;11;20 If I don't think about the fact that there's not a job for me at the end of this, maybe it'll materialize magically. Somewhere in there. Yeah. Okay. So I'm a university dean that could never happen. But just play along with me for a minute. I come to you and I say, Laure, I want to build programs and a culture around turning research into innovative product.   00;26;11;25 - 00;26;34;20 What resources do I need to make available and how do I build a supportive community around that? And I guess that speaks to the challenges of fighting that resistance, you know, getting community to pull people in. Right, Right. And so I think, you know, the other question at universities is anywhere is always cost rate. How much more do I need to invest to create these programs?   00;26;34;20 - 00;26;58;02 I think the great and wonderful answer here is that universities don't really need to invest a whole lot more to create a program. So there's a number of universities. Many, many of them already have something called a small business development centers. These are associated with the Small Business Administration, and they're staffed by business and technical advisors that can help problem solver access capital and help with business planning.   00;26;58;04 - 00;27;20;04 Woo Right. You know, I think anything new, it's already there. And they provide services to people at the university and actually at SCORE are we we collaborate with folks in the SPDC as well and we can send people from the community over to these groups at the university to get the technical assistance they need. That is beyond the scope of what we do in this program.   00;27;20;04 - 00;27;45;13 So I think it's less a matter of the university setting up more resources. It's really more connecting entrepreneurs with the resources that are already in the community. And I mean, frankly, we run into the same challenge with data sharing. There's tons of resources available through the university library, but researchers often have no clue to reach out to the librarian for help with data sharing.   00;27;45;16 - 00;28;18;21 So I think all of us researchers have myopia, but so do research administrators and services like SDB sees and score as well. Right? How do we reach and run the workshops, walk the halls? Right. We have to be really proactive and go out and engage with the researchers, meet them where they're at, and engage with these groups of people about entrepreneurial skills, practices, meeting with mentors, things like that.   00;28;18;21 - 00;28;37;01 So I think all of us need to do better at looking up and out, asking for help, listening. And, you know, it's not just product market fit. It's like the focus groups that we always tell entrepreneurs to do. I think the services that are out there for entrepreneurs also need to do the same thing. I think about biotech and medical research entrepreneurs.   00;28;37;01 - 00;29;09;15 They've got like an extra bucket of problems because they have to work with the health care industry. Highly regulated, very complicated, not big risk takers when where innovation is concerned, can the sharing of data be a difference maker in all that? What data should the researcher bring to the table and how to smooth process? Yeah, so there are two wonderful sets of guidelines that are out there and people are working on implementing them and they have really great acronyms.   00;29;09;15 - 00;29;31;29 One is called CARE and the other is called FAIR. Right? So I think this this comes back my to your question, there is no one way to answer that question. I think the ways you answer this question is by providing a framework that allows people to use a framework to answer the question for their particular situation. Okay, So FAIR stands for findable, accessible, interoperable and reusable.   00;29;31;29 - 00;29;48;27 And it tells us how to share. It tells you how to create your data set, use persistent identifiers, you know, make sure that this is there is some way for people to request access to your data set, whether that it's in a repository of a landing page, make sure it's interoperable, that there is a good set of metadata.   00;29;48;27 - 00;30;10;29 Well, describe to explain what the heck's in your dataset. Right. And then make sure it's reusable, right. That there is some way to pull it down into a file, share it. It's already in a database or our code, whatever it is, right? That that's all there. So that's FAIR. How do I create and curate my data set so that it is accessible and usable by other people?   00;30;11;01 - 00;30;37;02 But there's also another component that is as important, and these are enshrined or encompassed in the CARE principles, and these were developed through the lens of Indigenous data sovereignty, and they provide a framework for what to share, right? So CARE stands for collective benefit authority to control responsibility and optics. And like when you're working with biomedical data, you know you can't share personal level data, period.   00;30;37;08 - 00;30;58;10 That is ethically wrong. To share personal level data, you have to identify it. So that's a component of, for example, what you could put in CARE. Do you have the authority to control the data that you're sharing, or does somebody else have the authority? For what benefit are these data being shared? These are all really important questions to ask when you're when you're sharing data.   00;30;58;10 - 00;31;18;01 So as gets to like, I'm really big on attribution, right? So I think and I don't think it's even I think I'm just going to make the bold statement that we have to recognize the rights of the people from whom data are collected. I think for too long we've only recognized the rights of the people who are collecting the data.   00;31;18;06 - 00;31;42;15 Right. And I don't think that finders keepers should be the ruling ethos for how we share data. I think we can do a lot better and the CARE principles get us there with that collective benefit authority, control, responsibility and ethics framework. And so between CARE and FAIR, we address for people and purpose, and together the guidance is share your data as openly as possible and as closed as necessary.   00;31;42;15 - 00;32;06;28 So there isn't just open data shared with everybody. It's like, let's really think through what's in this data set. Do I have authority to share it? What is my responsibility for protecting the information that's in this data set, and how can I collectively benefit the community by sharing? How can I do this in an effective way? And I really, really love how these two sets of principles work together and foster this way of thinking.   00;32;06;28 - 00;32;35;02 This framework about intellectual property that is intentionally respectful for the full set of stakeholders and rights holders of the data that's represented in the data set. So that may not be as specific as an answer as you want, but I think that's the best way to address this is using these frameworks. It does. It sounds like it. Oracle for Research has actually provided research to commercialization support for a handful of researchers like University of Bristol biotech spin out Halo Therapeutics. Is that a good role for a big old tech company like Oracle to play? Is that appropriate? Oh my God. When I met you guys at the Research Data Alliance meeting, I was so excited to know that there's Oracle for Research exists and that you guys are providing tech support for founders. I think it's awesome.   00;32;54;07 - 00;33;23;23 I do. And this is part of the collaboration I'm talking about. You have skills and resources that startups don't, and to be able to share those resources is for the collective benefit of all the parties. Awesome, right? So I think, you know, this small grant funding and technical support that you guys have done with the community, support those folks that are our need to use or want to use cloud computing, super important community building is also a big one for me, obviously, right?   00;33;23;26 - 00;34;00;19 Bringing together aspiring entrepreneurs to share their stories, to meet with mentors, to meet with other entrepreneurs. It may be a little bit farther along the pathway. Super important to do that and you're starting to do what you're doing that a bit right? Supporting collaborations. One of the things I've heard over and over again in this data space is, yes, there's these cloud computing services, but one of the big challenges is the middleware that's needed to enable access to the data in the cloud server that's respectful of privacy and any like data sharing challenges that you might have.   00;34;00;19 - 00;34;25;28 Right. In that that federated sign and piece is really challenging for a lot of folks building these data infrastructures. So there may be some some role that you can play in helping to support collaborations to answer some of those questions. And it's not saying that there's a particular product that you guys can build, but maybe say, hey, here's some options, here's how they can be implemented, here's some folks doing it right.   00;34;25;29 - 00;34;52;09 Why don't we have a meeting or something to help others figure out how to also implement those? And then the thing you guys have been doing, again, partnering. We talked about research, data Alliance. I think you also participate in these giant and TNC meetings looking for opportunity is to work with research networks and identity federations and data sharing alliances in developing these cross-platform solutions that work on a global scale.   00;34;52;15 - 00;35;22;04 All of those are great. So I think when I look at this, is providing some hope right. We have this great idea as an entrepreneur and is like, Oh my God, how am I going to do this Right? Providing some hope to those of us who who want to start developing a tech-based product for the research community, that someone out there is willing to share some resources to help us test our idea.   00;35;22;04 - 00;35;51;10 I think that that would be the way I would think about it. Yeah, well, technology as a driver, it's an enabler for nearly all research entrepreneurs and biotech founders. There's no way around that. But as we're seeing with AI, technology appears to pop up and move at incredible speed. So what do you think researchers should be doing to make sure they understand what the right technology is and how to use it for things like cost, performance, security, flexibility, scale, those things?   00;35;51;13 - 00;36;14;02 Yeah. And so I was thinking about this and, you know, tech is necessary for everyone, as you know. Right. And, you know, I work with a lot of small businesses through my SCORE mentoring volunteer service. Right. And these are people starting restaurants and hair salons and retail outlets. And, you know, they're like, how do I do this? They also have to use cloud-based solutions, right?   00;36;14;02 - 00;36;38;18 Accounting, e-commerce platforms. They have internal external communication platforms like the storage slack and other things like that, discord on customer management systems out there. All of these things people think of tech and they think of cloud computing and massive compute resources that you need for time. Actually, yes, you need that, but you also need these other cloud solutions.   00;36;38;18 - 00;37;00;14 If you're going to run a business, you have to have all of these other kind of operational pieces as well. Right? And there's other things like, Oh my God, I have to look at mileage tracking and receipts management, inventory control, all the things no one wants to think about, but they're all essential parts of running a company. And all of these to also have cloud-based solutions.   00;37;00;14 - 00;37;20;21 You don't have to do stuff on a spreadsheet that's only on your computer. You can have it in the cloud, you can move around. This information comes with, you can easily share, you can collaborate on documents. And I think Mike, to some degree, I think people need to pay attention to this as well, right? They have to do this as well.   00;37;20;23 - 00;37;42;06 Things like SCORE, right? Used to be only face to face mentoring now is almost I think over 90% of mentors now in the space of three years shifted from face to face to virtual meetings and like it was like, oh, I didn't do this earlier. An orchid was run as a virtual office From the very beginning. We never had a building, never.   00;37;42;10 - 00;38;12;28 And my consultancy is also virtual, right? So it's how do we use these wonderful cloud-based resources to really expand how we can do our work, where we do our work and open up time that we didn't have before because we were running around or trying to share documents through email or trying to collect all these things that the cloud is made possible for us that really enable collaborative work I think is great.   00;38;12;28 - 00;38;34;14 So your question, what tech do you use? And this is a question that can't be answered easily. Again, it depends on the stage of your company, the size and scale of your team where you're operating and of course your product, right? So I will always take an iterative approach, have a conversation. Where are you in your evolution as a company?   00;38;34;14 - 00;38;55;19 What is your product? What are your needs? And then also make sure my big advice is make sure when you pick a technology for whatever it is that, it is something you can evolve and adjust and iterate with. Then, you know, if it's one particular platform, make sure has an API, make sure you can get your data in and out of it.   00;38;55;23 - 00;39;18;21 So as your needs evolve, you can transition to something else if you need to. That better suits you need as a company. Don't get locked into a particular solution because you'll find like if you get locked into one, I don't know, customer relationship management system or fundraising system. And then you can't move as your company gets bigger, you're kind of screwed.   00;39;18;27 - 00;39;44;25 So you have to make sure you you plan for, in my opinion, to plan for flexibility from the very beginning to allow you to grow and evolve as a company. And then that last thing, it comes back to experience at work. It ensuring privacy. What did you actually need to collect? Right? And if you have to collect personal love with data, make sure that you're ensuring the privacy of the people you're collecting it from.   00;39;44;25 - 00;40;06;10 So that's always a big one for me. And that's where Cloud Solutions not putting this stuff on your laptop are. So, so important. Well, we talked a good bit about partners and partnerships. Some people like to try to partner with our friend, the federal government. Federal funding is critical for academic and nonprofit researchers, the NIH as a funder.   00;40;06;17 - 00;40;28;16 It's driving change in the research space with things like the updated data management and sharing policy. And that policy is that researchers now have to plan and budget for the management and sharing of data when they apply for a grant. Are these mandates going to lead to real and meaningful changes or is it window dressing? What's your take?   00;40;28;18 - 00;40;50;25 Oh, another story. So one of the early community stories we did, ORCID had a question about mandates. There are always these conversations about mandates and the folks that would do put in place the mandatory oh, we couldn't possibly put in place the mandates or just irritate the people who would use it like the publishers can't put in place mandate because then the authors won't come to our platform.   00;40;50;25 - 00;41;18;20 We'd want to put up any barriers to, you know, to people using our stuff. But we did the survey and one of the questions on it was, Hey, would you want work it to be mandated by publishers? And since surprisingly, something like 80% of the respondents said mandate organ, we're like, okay. And that in turn, the funders and publishers are like, Oh, I had no idea people would be into this.   00;41;18;20 - 00;41;40;14 So that, you know, it was like researchers asking for a mandate in in a way with the researchers were asking for was would the publishers and funders please use ORCID? Please just use it so we can use it as researchers and gain the benefit. It was an interesting kind of reverse way of doing the mandate. So I think now we see these two stories about mandates.   00;41;40;14 - 00;42;08;28 You know, no one ever mandated Google search, right? It was remains as elegant and easy solution of finding things on the Internet. People still use it in droves, even with problematic privacy frameworks or revenue model. Right. It's because it's so easy. This just does what supposed to do. You get in and out your data, right? So why do we need to resort to mandates to get people to use things and do things that should be good now, which gives me to my second comeback, right?   00;42;09;02 - 00;42;32;21 Things like ORCID and data sharing are usually promoted or marketed as quote unquote good for us. It's like eating broccoli. Some people like broccoli. A lot of people don't like broccoli or they will not go out of their way to eat broccoli like a guy eats broccoli because it's good for me. But given this choice between green vegetables and I don't know, chocolate, I'm sure most people will head for the chocolate.   00;42;32;24 - 00;43;08;16 So why don't we design things and workflows and incent dev structures that provide the sweets that people want? Right? So these research policies that are enforced by mandates are usually ways getting researchers to do things that, you know, I like broccoli, I got to eat my broccoli. And then if they don't work very well because the systems haven't been designed in the workforce, haven't been designed to make it a delicious experience for the researchers, where you might I actually need to use the mandate because everything just works well.   00;43;08;19 - 00;43;47;10 Right. And the other problem here is that the culture of research is also about kind of protecting experts in this. Right. And so when you're talking about data sharing, if there isn't something that's done with data sharing that makes it attractive to share data, not just you must do it, but it's actually, hey, this is going to help me in my career, then the mandate, you know, it's just going to be this that people put up with and will find ways of getting around and delaying because they don't see the benefit to them in actually sharing the data.   00;43;47;16 - 00;44;32;19 And some people actually see harm. And that's a lot of the conversations that are happening at NIH today and over the past couple of years. It's like, what is that, that harm reduction that can be done to kind of reduce the barriers to data sharing. And so one of the projects I worked on that my consultancy was with the Federation for American Societies of Experimental Biology, also known as Faseb, putting together a program that kind of worked side by side with the NIH to see how can we as fast of this Federation of society is support the community in sharing data and make it an attractive prospect for researchers, not a grudging thing to do.   00;44;32;20 - 00;45;04;15 Right. So that gets back to I mean, you guys talk about this all the time, I'm sure. How do we work with our communities to design products and workflows that work for them, that are seamless, that are delicious, that provide a benefit? This is all user centered design. And I feel like sometimes what happens in the research community is people forget some of these basic design principles and they use these sticks through the form of mandates to get stuff accomplished because those design principles just aren't practiced in the community.   00;45;04;15 - 00;45;25;19 And so again, coming back to NC three, that big COVID collaborative, it made data sharing easy for users with this metadata model that was partly automated and also a service to help researchers with the curation process. Instead of saying you must curate your data, they'll say, Hey, you need to curate your data and we'll help you with it.   00;45;25;21 - 00;46;03;14 Huge difference, right? And at facet of this Data works project actually provided a substantial award, $100,000 for two teams that could show their data sharing and the impact that data sharing on a community that's not just a $5,000 prize, it's not just a little ribbon you get. It's a substantial award. And they had over a hundred teams submit applications for these awards and get a fabulous recognition by the NIH and the broader community and can show the way for others, Hey, we made this work.   00;46;03;14 - 00;46;31;16 Here's how made it work. They become ambassadors in the community and provide that incentive and mentoring for other people who are interested in sharing data. So I think that's what needs to happen. So you asked about, you know, what will mandate help? Yes, it has raised the urgency of data sharing in the biomedical community. Right. There's still a gap between this desired state and operationalizing how we share data.   00;46;31;18 - 00;46;54;13 And there is this series of surveys called the State of open data that happen to be going on for four years now. They've found a consistent desire among researchers to share data, but also a consistent need for more and better pathways to do so that also embed this attribution and respect components we've been talking about. So I think that's where we need to go next with the competence will make progress.   00;46;54;20 - 00;47;25;15 We're already making progress. We need to celebrate success and we also need to collaborate on a user design system and mandates like NIH is doing could be part of the solution. But they're not the solution. They're not the only thing we do. I've convinced myself I like broccoli, so self-delusion is very underrated. Yeah, well, Laurie, this has been a great conversation, super useful to those listening that are in that place of I've researched an innovative product.   00;47;25;15 - 00;47;42;14 Now what you know, thank you so much again for making the time. And if people want to know more about you or what Mighty Red Barn does, is there any contact info for you? Yeah. So you can come to my LinkedIn profile. Probably the best way to get me. I mean, I have a Twitter profile ID at Hack Yack.   00;47;42;17 - 00;48;02;11 Probably the best way, however, to get me is through my website at www dot mighty red barn dot com and there's a contact us form on there and I'm happy to talk to folks where you can contact me through LinkedIn and you to send me message that way. So yeah thank you very much I really really enjoyed the conversation today.   00;48;02;11 - 00;50;14;27 Really good questions. That's great. Me too. If you are interested in how Oracle can simplify and accelerate your research, all you have to do is check out Oracle dot com slash research and join us next time on Research in Action.