OpenTEAM Data Interoperability Webinar
3:30PM Jan 27, 2022
I'm sure we'll get started in a couple of minutes. But in the meantime, we have a zoom chat open and feel free to share with everyone where you're calling in from and what organization you represent or the reason you're here. We'd love to hear from you
so again, welcome. Feel free to add in your, where you're calling from the organization you represent and or what reason brings you here today. All right. We've got Organic Valley on the line. Hey, Nicole. We've got Andrew from the Naval Research Institute in Ardmore, Oklahoma. Carbon a list. Great. Dennis Buckmaster Hello Dennis. Got Klaus from from planetary care and yeah, no report in USDA ARS precision, sustainable ag thanks for being here. New England, Connecticut. Awesome. Um, keep those keep those come in. We're all about building community. At OpenTEAM. So again, welcome everyone. After a few minutes, we'll be really transitioning to our panel. And then we'll just be welcoming you to use the q&a function mostly. And of course, we'll keep we'll keep the chat function open. If you wish to more so directly have a discussion with others. And the q&a will come later on today. So again, welcome. This is a third and a series of webinars this been on data interoperability and architecture. Next week's webinar on Thursday at 1pm. Eastern will be on open teams work around equity and practice and technology and agriculture. And our final webinar in the series will be on the 10th of February on how open teams community driven process and approach to a tech tech ecosystem is really cultivating deep community and breaking down silos. I'm Laura Demmel, Gilmer supporting our GOAT global community and operations at OpenTEAM. I'm signing on from rural Virginia where my husband manages a large legacy branch. So my work is really grounded by the challenges in agriculture and if you pull out any Farm magazine, you might learn that farmers lack confidence in carbon markets. They've they're up against rising input costs and equipment costs. And markets are quite volatile. And with these real everyday challenges that farmers face, what we need as a band of those serving land stewards is a cohesive technology system that relies on collaboration and on data. So I've arrived at open team knowing that our approach and that's really grounded in open source development holds tremendous power for supporting the pre competitive collaboration that's essential to supporting farmers and ranchers. Like my husband to move from where they are today to where they want to be in transitioning to more regenerative agricultural practices. So OpenTEAM are open technology ecosystem for agricultural management is diving into this endeavor head on. So facilitated by Wolfe's Neck Center for Agriculture & the Environment in Freeport, Maine. We are a collaborative global community of farmers, ranchers, scientists, researchers, technologists, farm service providers, and food companies that are creating the framework and a tech toolkit to support this type of ecosystem.
Today we have a really fantastic panel of OpenTEAM members in our tech space that are going to dive deep into the topics of data interoperability, architecture and sovereignty. When we talk about data interoperability at the ground level, the reason this matters is that farmers don't like paperwork and they don't like data entry, but they do want access and and deserve access to decision making tools. And economic incentives for better agricultural practices and environmental product declarations. And all of that requires data collection often as well verification and monitoring. And that's when data interoperability comes comes into play. Using an open source approach, organizations like the ones here today can use common publicly accessible software design that can be modified and shared by multiple users, allowing the source code to be inspected and enhanced by anyone because open source utilizes multiple collaborators and allows for more control, increased security and stability and the foundation of communities like ours centered around software design. Today's panel will dive into how OpenTEAM and our organizational members have taken advantage of solving common challenges through shared approaches to systemic technology challenges we find in agriculture. So with that, I'm going to turn it over to Dr. Ankita Ratterree. She's an assistant professor and the director of the agro informatics lab at Purdue University, and she'll also be moderating our panel discussion today. So um, kita I'll turn it over to you. Very cool.
Thank you so much, Laura. And thanks so much for joining us, everybody. I'm really excited for this discussion. For those of you who don't know me. I am a professor at the agricultural informatics lab at Purdue University. And my research really looks at the human experience of technology and results in the design of critical technologies to be able to support different kinds of stakeholders from farmers to food system, stakeholders of many sorts to be able to adopt more regenerative and resilient agricultural practices. So I'm going to talk hopefully not as much as my fellow panelists. And so I'm mostly going to try and set the scene a little bit for each of the different phases that we'd love to go through with you today. And I'm really mostly hoping that my panelists will be able to just really share a lot of what they're doing. There's some really exciting work that each of you are doing, and I know that there's going to be lots of hopefully really interesting questions out in the chat. And so let's kind of just dive into it. I'm going to set the tone with three different concepts. As I invite you to introduce yourselves. And the first is going to be this idea of interoperability, right. We're all here to talk about data interoperability, but what are we interoperating right, what are we connecting? I argue that there are sort of three things functionally, technically that we're trying to bring together, right? It's data, it's tools, but it's also processes my method and your message should be in sync. And I know that many of you have not only adopted each other's technologies or trying to think about connecting each other's technologies, but we're also learning from each other, trying to think about interoperability of methods and processes to build tools together. The second concept I want to seed this conversation with is this idea of interoperability with people interoperability is essentially a human problem as well, because in a lot of ways, if you and I don't talk if we don't try to figure out what our common ground is, we're never going to make our tools talk to each other. And so it's not just about people, right? It's then also thinking about interoperability with ecosystems and infrastructure, right? It's not just humans on this planet. It's not just our technologies. It's not just agriculture, but we are within this larger context of people ecosystems and infrastructure. So the third piece I want to see this conversation with is this idea of open access to data versus open source software, and I want to make sure that we at least have a shared understanding about the differences between these two. Right? When we talk about interoperability on the data side of things, it's usually talking about trying to make sure that data formats are exchangeable across different platforms that I can export my data from one tool and import into another. It does not necessarily mean that I'm saying all public, all data should be public, but it means that I'm empowering people if they choose to provide open access to their data. And so what we're really talking about on the open access side is this idea of giving people agency on the open source side, as Laura mentioned, is this idea of opening up the hood into our software, showing people how it works, right. The best way to reduce bias in the tools that we build is to allow our diverse community of stakeholders or participants of people to be able to look at it and say, Hey, why are you doing this with that piece of data? And I know that a lot of you do a lot of work in a very participatory fashion, bringing lots of different kinds of community members in and I really hope that you talk about some of these efforts. So these are the three things that I want to seed our conversation with. And I'm now going to ask each of you and I'll just kind of ping one of you at a time to tell me a little bit about what you do. Right. So tell me what you build. Tell me what you do. Tell us who the community of practice that you work with is and sort of what that ecosystem of technologies and people and everything is. So why don't why don't Andrew and beneath from digital Greenwald and y'all kick us off and tell us what's going on?
Sure, thanks, Ankita. And really happy to be here and thanks, everyone for joining. So I'm Andrew from Digital Green. We primarily work with we're a nonprofit organization primarily works with farmers in the Global South. And what we do is is we develop technologies to enable farmers to better harness data to improve productivity to improve resilience, etc. Um, my role Digital Green is supporting mostly our East Africa programs but also our global rollout of our farm sex solutions for farmers. I'll hand it over to Denita
Hey, thanks. Thanks, Andrew. Thanks again for for a lovely lively setting up the phone. Ivan either I'm based out of Bangalore working helping build farm stack a Digital Green from technology as well as product side farm strikers we really a deep customizable data integration tool and has different components about you know, one at the farmer level about the consent second at the at the participant level where the participant organizations can exchange data and the third at the network orchestrate a level where, you know, the government bodies or the consortium can create or bootstrap these data sharing networks. The idea behind Formstack is basically to make what you just said that, how do we make data more usable and create data centric solutions for the farmers especially in the geography that we work with? And really happy to share my thoughts and also learn from others? Others experience. Mike, do you want to go next?
Sure. Thanks. Thank you. Yeah, thanks everyone for joining us. My name is Mike stenter. I work on a project called farm OLS which is an open source farm management and record keeping tool. And so I basically I started farming as a number of years ago as kind of a side project basically in the same for the same reason that a lot of open source projects start is sort of just to scratch my own itch. I wanted a system that I could use to manage my own records and be able to visualize that with a map and and also to be able to record kind of the breadth of different types of operations that are out there. There's there's a lot of non open source software out there that all kind of specialize in certain things. And so recently, there's been kind of a Cambrian explosion almost of of software options out there, but none of them have really a standard to them. They all kind of design their own solutions to two individual operations. There wasn't really one that covered, you know, everything. So that's kind of what inspired FarmOS us to start. I've got my three year old here. And yeah, so I'm just excited. To talk about to talk about that today and see what the questions are.
Over to you Greg. Hey, I'm Greg Astec, co founder of RSI our mission is to support communities who want to ask hard questions about the world. And it's a very broad kind of mission that we have as a company. But what it really comes from the fact that we think that the future of of science is going to come less out of academia less out of corporations and more from groups and communities of mixed experts and non experts investigating the world in ways that that they're interested in and asking the questions that they're interested in. So our goal as a company is to support that as it emerges, and hopefully make it emerge. Faster. So in the context of this, we do a lot of work in agriculture. And we support a lot of communities like the bio nutrient Food Association and OpenTEAM and and others to help groups of farms effectively collect information in a way that's appropriate. To them and customizable, and but then also store that information in a way that's going to be effectively shareable. So we have a really nice collaboration with FarmOS for the projects in agriculture, where we we tend to use FarmOS as our data storage, but we use our software SurveyStack to be able to intake that data in a way that's appropriate for each of these different groups and communities. So yeah, that's me. Cool. Well,
thank you all so much. I'm gonna try and have you dip in a little bit more on the human side of things first, right we talked about this idea of human interoperability being part of a challenge as well. And one of the ways in which we hear people talk about this notion is in terms of the update of self sovereignty. And so when I think of data sovereignty, I think about a couple of different things but mostly tied together by this tension. On the one hand, we're interested in allowing people to have agency over their data, empowering people to be able to upload data, use it downloaded access different kinds of data, right, trying to really open up the data landscape. On the other side, we actually do want some rules of engagement with the IRS data, right? So governance is a big part of it. If we, if we don't have codified rules, then that's how we end up with data that don't have either authentication mechanisms or different kinds of privacy protections. And so there's this push and pull between these two ideas of agency versus governance. And I'd love to learn more about what each of your practice of data sovereignty looks like. And I'll start maybe with Greg, you, especially because you're working with a pretty broad group of people, even outside of agriculture, and often are folks who are actually trying to do their own management of data.
Yeah, well, I think I think the first thing that, that we can do as a provider of a tool, so you know, SurveyStack is like a survey, a general purpose survey tool, but it's also used in agriculture, is ensure that users have the appropriate suite of options to share in the way that they want. So, for an example, there's a lot of survey tools where you can make a survey private or public. Well, you don't you don't necessarily want that you actually want a tool that allows you to take specific questions and make them anonymized or private, but leave the rest of the survey as public. So, again, you know, step one is having the options available to even share in the way that people want to share, too. I think the analogy is or, you know, to is presenting people with the thing that they want to do but may not select and the analogy here is like there's certain states everybody you know, you have a like blood donor organ donor check on the back of your of your license, some states pre check that and some states don't. When it's pre checked, 80% of people do it. When it's not 20% of people do it. Most people want to donate their organs, right. But having it pre checked means is there so so I think the second piece is structuring your options. So that sharing is kind of the default. And that and that people understand why they're sharing the value to that cheering and then allowing them to back off from there. And I think a lot of pieces of software do the opposite. It'll prevent present private as default because users it's something that users feel like they want initially, but then once they understand the value of sharing with intention, then it's something that you can do. So I think there's just a lot of design on our side that's involved in supporting, you know, additional shared data in a way that feels positive and intentional for everyone in the system.
Yeah, I can speak a little bit to the sort of motivations around data sovereignty and farm the last two. So you know, the way the way FarmOS is structured is every farmer who sets it up has their own database, so they're from the start in control of that data. And that, you know, gives you a lot of power to, to kind of keep that how, you know, share it with only the people that you want to, but we also see that there is to Greg's point, a lot of value in sharing certain types of data. So we've also, you know, been exploring ways of pulling that data together aggregating it from multiple farm instances. And this is really where I think it ties into interoperability too is how do we start ensuring that the data that goes in is comparable with with other farms, and so controlling the, the format that they go in is really important, and we'll probably talk more about this particular point in a bit, but I think I think it one of the one of the thing that's been important to me is just giving that choice to the farmers from the get go. There's a lot of there's a lot of like free options for for software where you can enter a lot of data. But in a lot of in many of those cases, the value is going to whatever company is is gathering that data because then they have more information about how to kind of market to those farmers are advertised to them, as well. So I think that's a bit problematic because it affects the relationship and it affects the way the services that they're providing to. So I think it's important for those to be disconnected a little bit more. There's still value in sharing data, even for marketing purposes and that kind of thing. But there needs to be more choice involved.
Go ahead, Andrew. Yeah, I was just gonna add on on top of what Greg and Mike are talking about here one one concept that that we've been exploring a solution that actually the meat and his team have been building is something we call a consent manager. And that's something that enables farmers or users when they are sharing data with a survey app or with you know a piece of software from from a service provider to more conceptually and realistically understand what data is that they're actually giving and how that data may or may not be used and, and make a really informed choice versus what maybe a lot of us are used to have, like, you know, long legalese and click a box. And so I think that that's, that's another layer of, you know, enabling, enabling users enabling farmers to have a say and what their data gets used for. And I think that's an important concept in sovereignty. When we think about all the different services that that we're exposed to or engage with.
Yeah, I love that I'm hearing these themes around also thinking about the usability of some of these different kinds of consent management or privacy controls, right. So trying to actually have it be easy for people to be able to engage with So Greg, I love the example of the license, right? It's a classic example that we use in in human computer interaction classes, where we talk about how opting in differs from opting out and what that does to actually encourage people to participate in a particular process. The other piece I'm hearing y'all talk about is this idea of understandability right? The legalese that we see in terms of services are notorious, but I know that there have been a lot of really interesting efforts, at least on the consumer electronics side of things to try and make these sorts of things more accessible. Are there things that you all are doing and your specific technologies to try and sort of break down some of those understandability and usability barriers?
Yeah, maybe I can chip in on the Content Manager bit. Yeah, definitely. And so as Andy was just said, so the the part of the content when we're talking about the consent to share the data itself, the three parts essentially, one is the interface itself, where the user can really understand and what user needs to know is what is the data in the first place today, where we work the communities that we work with? The farmer is not even aware about the data. The data is in fact, the data is with different people different set of information about the farmer. So first information is just it also enables farmers to understand what data is there in the first place. And the second is how they can benefit if they share the data. And the third is they need to know how they can control the sharing of data that that's important that they need to get the regular notifications. And I think the first bit of it is about the the interface itself, the and, you know, the interface has to be in a way that is sort of universally understandable. It's not in the, if you're operating in India, they're like 30 Odd different languages, different dialects, it's just impossible to to explain these complex terms. You cannot have a big legal document where you scroll down and say I agree and go on. So how do you want to get that as an informed consent so that the farmer is able to realize value and come next time and say that yes, I want to share with XYZ GMO and the real value. I think the what you're getting from the from the part is you know the second part is a is a backend of the how the consent is treated. And third is how the data is transferred. But the real value with the farmer is when they see a bundle of service. So it's not right now if they go to a place they take a service, let's say with a domain system, the domain partners that you work with the Aveda service, they get that service let's say get their produce certified now they get this certified certification. They go to the buyer and they have a better negotiation power. Now if using that they can get on boarded on a different platform on ecommerce platform where they can get access to the more buyers or also input providers. That's you're getting an access to the entire network and not just not just one service. So you're getting a bundle of service with this entire mechanism. And to add to that what what you know Greg and Greg was saying so we need to think of the data in three broad aspects. There's one is profile data. One is a summary data. And the third is sort of transaction level data like what I'm doing every day in day out, not a transaction level data is very difficult to capture a and be validated and also shared. Whether we're looking at the profile data in the first place and summary data in the first place, so that the farmer in one system can get on boarded in another system and everyone in the ecosystem has a value with that kind of system itself. Yeah. So
is important. Yeah, it's, it's beautiful. You're using one specific use case also as a mechanism of creating awareness and education in a group of users to be able to then for them to be able to do the same thing and other platforms too. So it's almost like there's a little bit of training. There's a little bit of that understandability and it matches I love that breakdown of right profile summary and transaction data because it's also like when I think about sensitivity of data or what types of controls on my want, I would have very different answers to each of those. That's really cool. Um, I want to maybe, unless Greg or Mike you want to add on to that. I might want to ask a little bit about methods of inclusion. Any other additions or should I move? Cool.
I actually have something that sort of connects the two if statement. I think I think another key there's kind of like there's a universe in which everyone's data is by default private. And then we have to take intentional action to share and there's a universe in which everyone's data is by default public and and we have to take actions to not share and you know, this universe over here you think of as like company controlled, but it doesn't have to be right it doesn't there's nothing that says this has to be company controlled. And of course, like the right universes is somewhere in the middle and we've talked about the details, but there's one element that I feel like it's really important for producers to think about understand is that we also need, like standard structures around which groups can share and like that's something we've been really focused in the coffee shop when we talk to people about sharing, you know, they're nervous in a world and it's just me versus the world to share anything, right? But But when it's me versus my community of 30 or 40 people that all work with this agronomist versus the world, all of a sudden, they have this new layer to think about and talk about in terms of what they want to share and how and then that layer has a communication with the broader world. So just thinking about these intermediate layers as a really important tool and how people think about sharing and that goes to this question of like, how do you engage with communities, but we found you know, and I think Mike can speak a lot better to the, you know, using forums and building a traditional open source developer community, but in terms of how our communities talk to each other. It's almost always through existing organizations. Right? And every anybody who's tried to organize farms or farmers or really anybody knows that, like, the history of an organization itself, has an immense amount of value. People put value into the name, they have some shared conceptual understanding, you know, posso, or no part of the BFA or these groups, like people put trust into those things. And that is a vehicle for discussion and improvement and understanding and feedback and so much so I think, from my end, you know, how do we communicate and include people in the development process and also have them talk to each other and improve their craft or skills or whatever they're trying to do? I think those those communities are just Central.
Oh, I love that, right. It's this idea of these trusted networks and trying to think about data sharing within these trusted networks, my community, my history, my people. I want to put this into a question perhaps then. So each of you are working with different communities, you have very specific practices that you're actually doing, whether it's calls or using chat forums, or doing workshops. How are you cultivating trust with these different groups? How are you trying to connect with these trusted networks and help foster a little bit more trust in technology as well? Which, you know, if we've grown a little weary and skeptical of
Yeah, I mean, I can speak a little bit to the FarmOS project, at least. So far, most we we've been open source from the beginning. And that's kind of been a high priority for the project. So everything every line of code that's been written has been public, and you can see you can look back and see the whole history of it going back to the beginning. And the the decision making process has been public the whole time, too. Sometimes if you don't know where to look, you can't find it easily, but we've gotten a lot better at that. And making things more visible in terms of where where to go to find that, where's the Git repositories are? And we've recently, while a year or two ago set up our forum, which has been a great place to get more people involved. And all along we've been hosting monthly calls and more recently, weekly development calls to for anyone who wants to come in and like learn how to build on top of FarmOS or you know, in the forum and on the monthly call, how to use it to manage your records and it's just sparked a lot of great conversations about how best to do things and how to kind of develop conventions for record keeping which has been really nice. And so that's kind of speaking to the the farmer less community, the project that we're building, but then also within farming communities, you know, we've been working directly with a number of them. And this I think, is where I'm really excited for next steps especially working with Greg and the coffee shop, to create these little community bubbles of information sharing using things like the FarmOS aggregator and SurveyStack to collect information and then give it back to people in a summarized format, so that they can kind of to the you know, as the name implies, sit down together, like in a coffee shop, and see and look at how they compare to other people in the community and what and also talk so you can see, you know, well how did you when did you do your seeding of onions this year, or did you have trouble with this like I did or things like that. So I think that's that's one thing that that we've been really intentional about in this process is just trying to build the community because the the software is just lines of code, you know, anyone can anyone can do that. But But building and maintaining a community is a lot more work. Yeah.
Can I punt to Digital Green? Next? Andrew Infineon, I know that you guys do a lot of work of a global scale as well, but it's very local, still in the instantiation of your work. And I think it adds a really different and interesting perspective to the way in which you approach some of these things. Maybe tell us a little bit more about your community engagement at the local level in the global space.
Yeah. Yeah, I think first we look at different layers of community. So, Farm Hack, I think formulas share a very common philosophy in that sense. So we are we are open source. So there is a developer community that you're trying to build and we are very, very early in that in that particular layer. The second layer is more of you know, where we speak with the partners, trying to create the use cases and it is typically through a lot of our existing, you know, networking partners that we have worked around in a lot of these places. And And incidentally, the India itself with the Ag tech sector is like booming in terms of you know, a lot of startups coming and stuff like that. So, really great set of people. You know, a lot of people are trying to disrupt in some ways. And third is really at the user level. When we're talking about the farmers and the farmers. I think one of the things that we go around with, you know, we try to build around is what we call as farmer producer organizations of farmer producer groups, where you know, farm formal or informal farmer groups can come together, they can interact with each other. And they in itself, they share a common set of resources, they can pull their demand and supply so that they get a better benefit. So I think that is one of the focal entry point focal place for us to, to have this adoption to raise the awareness and to catalyze that at the farmer level itself. But but really I think we need to think about all the three different aspects. The developer community is extremely important, and the use case and then the farmer and would you like to add something No, well, so
cool. Yeah, I think it's such an important thing for us to at least share a little bit about what it means to be collaborative means to be participatory. This idea of forming partnerships with existing groups, I think is such a key part of this right? There's no point to be queried organizations instead look to leadership from others who have already done the work. I want to maybe now switch to hearing a little bit about your leadership. But on the technical side of things. I know that each of you have been doing a lot of work on interoperability from development of data schemas perspective. I know that a lot of times when we talk about data interoperability on the technical side, it can be a little vague. So there's a little bit of, you know, well, we'll just make things talk to each other. I don't just want to know up here how things are talking to each other. let's instantiate this a little bit. Tell me about your data schemas. Show me a little bit of how technology's working in your brains and anyone can jump in if you're super excited.
Yeah, I mean, I'm happy to kick this one off a little bit. Because it's a very hard problem. This. So I mentioned earlier during the introductions that one of the things I saw in in farm record keeping software was that they were all very specialized, and they were all focused on one or two different things, because there is such a huge breadth of different operations. There's, you know, even within so there's, there's livestock, there's crops, but then there's also tons of others maple production, mushroom production, milk production dairy, and then in each one of those, there's so much variation to so you can either choose to go the route of like, we're just going to focus on this one thing, but then you're siloed in that thing, and you really can't be interoperable with anything other than that thing, basically. Or you can try to take a more general approach and then develop conventions within that and that's kind of the approach that we've taken with FarmOS is this idea that let's create some let's create a, a base to build on we'll define some some general buckets to put information into, but then let's have a community process where we decide what is the best way to represent this kind of operation in these buckets kind of thing. And what new buckets do we need to add? What new data fields do we need to add to collect this thing we didn't think of or this thing or this thing and where do those best fit? And let it be a community process. So over time, this you know, maybe one researcher has a set of questions that they're asking that they're focusing on. Let's fit that in somewhere. And then someone else has a set of questions that they're asking which are very similar and might have a lot of overlap. Let's find where they do overlap and try to come to a consensus on that and over time, develop conventions for how to record these things so that they can be comparable and I feel like we've been doing that a lot with with with certain pieces and over time, more and more of that will just kind of naturally come together. That's kind of my hope, is how that will work. Yeah,
I I've always appreciated the farm, the data model of farmer less. I remember even when I was in grad school coming across the FarmOS data model and being like, Yes, this is super interesting. And I was working on modeling frameworks at the time. So it's just like somebody speaking my language. Super cool, right? Because it wasn't this idea of like, I'm just gonna throw out an entire ontology. That's going to be just something that speaks to academics, but it was super functional. Your work is very much right. You're structuring data in a manner that is most meaningful to your users and you're iterating over it so you don't kind of build the entire monolith. But it's very much as the need arises, you're iterating over this data model. And I think you some more iterations are coming down the pike with some of the work that you're doing with Greg, if I'm correct.
Yeah. And the important point to to that is that, you know, we're, we FarmOS can adopt ontologies and it can adopt multiple ontologies. So that those become almost like a convention for comparison to so one person can adopt ontology version one and one can do ontology version two, and over time, you know, come to agreement on which one works the best
Yeah, I'm super excited about this year because we're, we're kind of just like, we're just doing it. We're just, we're just trying it out, and we're gonna see what happens. I think, you know, to Mike's point, you know, our structure that we have is, you know, step one is how do people come to consensus about these data structures. Right now, we're working on common onboarding. So if you have a project and you're bringing farmers into the project, what questions do you need to ask? You know, so we've gone through a bunch of organizations and tried to standardize those. So, you know, basically, where's the place in which people are going to come to consensus about the thing, right? So we're doing that right now in SurveyStack, using this question, Set Library, and once you have that consensus, make it easy for other people to utilize that in many other places. So that's that. And then once you have that consensus, what we're doing currently as we're then building a map data structure in from iOS using a FarmOS module, so now we have this nice thing that everybody consents to. Now we have this nice data structure and firm iOS, and then we just push between the two. So now they can fill out the surveys in a lot of different ways and forms and combine it with other things but it's all going in the same data model. And then from that, we pull it out into the farmer coffee shop, which is the visualization layer. But the reality is this, this now FarmOS instance, which has this, this data that's been consented to, is a really nice jumping off point for communicating with lots of other services and that's where, you know, digital greens work comes in so importantly, because all of those connections need to be understood and managed over time. So then that that's where those connection points come in. So, you know, we're just this here really getting those things in place. So they're really genuinely usable. We have a couple of different implementations of them. And then just this so excited to see it because we've been talking about this now for a while. And it just takes time to get the pieces in place and actually try it at scales.
Yeah, and one one additional point. On just building on kind of what Ankita was saying about the FarmOS data model. It's it's something that we've also tried to adopt in some of the tools that we're building and you know, not to go too much into the details of the model but that Mike in the community who built that, it is very, very practical and based on you know, assets at the farm level and logs and what is done to those assets. And we've actually are using it in a farmer registry product that's operated by extension agents in Ethiopia. And what we see is that you know, it's such a flexible model that is able to be used in different in very different environments. And I think that what that's going to allow us to do is is to connect those farmers with all kinds of different services and then have that flexibility and so we're Yeah, we're also very appreciative. Yeah.
Yeah, I think when we started, I think, building Formstack we had a huge discussion on the data schema, and we pop that question. So that's and so happy that we can we can use the formulas, data's, you know, the schema, the standard, the model that that Greg was telling, and I think there's a natural synergy. You know, in Formstack Farm Hack is based on a on an ontology that is already there, that makes it interoperable. Another form stack provides a connector, so it's a it's a ontology about that resource, which is a connector and a connector is basically encapsulating any kind of application which is calling all these API's. So we said that, okay, data can stay the way it wants, but the way you are sharing that data that tool needs to be interoperable. So, so, we we try to try to address this problem. But the problem with the data standard is still there. And and what what it does is we can build these applications, you know, which can, once we have this, this common data model, and these applications can actually do that combining and joining in, you know, I can create much more value that can be built in terms of these applications. And by application. I mean, just a piece of code, which which is just joining on the basis of like, you know, get this from here and get this from there. It might be a basically a Graph QL COVID For that matter, but get this, but have this in a connector and that can then interact with each and every node in the network or whoever wants to share. So I think, really excited. If we, you know, in the coming months, we are hopeful to at least build certain certain use cases and proof of concept thing that we can really be proud of.
I think we're all looking forward to at least seeing some of these pieces connect is so much interest in motivation and trying to start to actually have our tools talking to each other. I want to bring in one of the questions from the q&a, but couch it in terms of sort of the different levels of interoperability that we've talked about. Technically, so far, we've talked a little bit about these data sharing permissions, right? So that that ability to allow people to control the data sharing for different types of data. We've kind of not explicitly but a little bit talked about this sort of what I'm going to call auto interoperability right having our data naturally move from one tool to the other, using tools like API's, which are just programs that allow for us to actually have data pulled and pushed between tools. But Dennis Buckmaster in the chat brings up this interesting problem that I think it was never going to go away. And it's the idea that we are always going to have data housed in spreadsheets, especially in agriculture, if not in all of our lives. So tell me a little bit about how you're approaching interoperability with spreadsheets, other legacy tools and other tools within farmers and other food system stakeholders toolkits.
Yeah, so i i I love spreadsheets. First of all, I think that they're extremely powerful and a great way to experiment with things. You know, a lot of my original prop planning was done in spreadsheets, and still is sometimes. The obvious problems with spreadsheets are that they're easy to break. They're not easily not always easily shareable. There, they can be kind of siloed. So you know, I often tell people, if you feel like you've outgrown spreadsheets, then maybe get FarmOS to try but they're still so important for for doing quick calculations and planning outside of FarmOS as well, too. So one of the you know, one of the things that we try to support is CSV exports and imports so that you can import data from a spreadsheet and also export it from a spreadsheet. And there's different ways to do that. Right now. You can write Python scripts that will scan a CSV and put it in via the API. And then we have CSV exporters for everything too. So I think spreadsheets will always be around and for good reason. But yeah, we try to a lot of the times what we'll do is take use spreadsheets as a way to kind of sketch something up, but then kind of harden it into into a feature or into a module that has its own UI, and just kind of uses the same calculations and structure behind the scenes, I think.
Yeah, I'll say also, we work with a lot of different committees in and outside of Ag and in the survey world, everybody starts with spreadsheets always. And they should to your point. And it's just a question of scale. Like once you get to a certain level where it's more effort than look worse, and then you look to other solutions. So I think spreadsheets are great. Yeah,
yeah, I think, very valid question. And an interesting one, I think. Yeah, I think we have all got got to that particular point where ultimately it has come down to a spreadsheet being used for data. And in our case, a lot of data that we are talking about, especially capture is human and entered sometimes. So what what makes it really difficult is you know, you don't have any data model. It's just difficult. So, so one of the things that that we, we have, we have built a very basic kind of an app, but we have not yet released it which is I can I can upload the speech, not even upload. It's something that you can run that app as a on your own system, where you can just map this to the data headers now if we have this data model. So let's say I have something like you know, name, so someone would have written in surveys, so you just match at least the headers on your spreadsheet to the data model, and have that particular stuff. And then, you know, the the font stack will provide or make it like a like an API kind of system so that it is available for anyone to consume. In fact, to that particular extent, the consumption of the data itself, we are we are in fact very much making it available on spreadsheet and we have this testbed with with video library that we have which is a non personal data, all the videos that Disney has created on farming. And if you go on this particular link, you can see get data through Formstack. And you can get on your Google Sheet, really, with this connector. So So yeah, so that's what it can enable. I think the problem will remain in terms of interoperability itself. The solution would lie on a mix of data model that needs to be there and sort of apps that can create or modify the spreadsheet into something that can be used universally, that that that I think would be the natural progression of this stuff.
Yeah, yeah, spread spreadsheets are delightful, but also hard. I I'd love to maybe talk a little bit more about some of these challenges, right? There's lots of pickles and problems that we face when trying to resolve interoperability. Legacy systems and other tools notwithstanding, sometimes are easy fixes. Sometimes this is the point of your work for the next five years. Tell me a little bit about your long and short term challenges, something that you think you can fix in the next. Let's call it a year, and then others that you think are sort of open challenges that you're like looking for someone to play with.
And I'll just invite folks from the community to please feel free to put questions in the chat while I buy my panelists some time to put together some some critical answers. I'm monitoring the chat and both the q&a So you're you're welcome to come jump in over there. And I'll just add that for me part of my interest with questions like this, as always, you know, as a researcher, I'm always looking to hear about really interesting problems, the different kinds of community members face and so one of the ways in which we end up deciding what to work on is I hear you know, Vinnie, Andrew, Mike, Greg, talk about something and they say this is a real problem. This is something that we're working on. And sometimes it's something we can collaborate on. Sometimes that not that's that's not something that we have the capacity to, but ideally others in the community can jump in, whether you're on the farming side of things, or whether you are in the technology side of things, and so it's just always helpful. To hear, you know, what are some of your biggest, biggest hurdles to interoperability both long and short term?
Okay, I'll give you the one that I always give. I think this year, we're gonna have an maybe not the best, but I think a very good process for people to input data effectively and put it in the right place and the right format that's effectively structured and open using open source tools. That's super exciting. That's like a huge milestone, that I'm excited about long term. We could do that perfectly. And we're still forcing people to fill out forms. There is a fundamental problem with people filling out forms. No one wants to fill them out. No one likes to fill them out. No one wants to have put information they don't even we say enter data once use many times they don't even want to enter data once. So like so like we failed already to start so my long term thing that I would love to see and I know, I know there's a set of answers. And I think especially a certain sector of ag tech is going down this route where when you drive around in your tractor, it magically knows what you're doing where you're doing it. It's gonna communicate that so then you don't even ever tell it what to do. I think to Mike's point about FarmOS. That's a great solution for a very first for a small portion of overall firms. But I think actually a better solution that I'm interested in is just just effective. voice to text and sort of AI so I can just walk out and say I did blah, blah, blah and blah, blah, blah and blah, blah, blah, blah, blah blah. And it ends up in the data structure that I wanted to end up with. So that all my tools sound on line work. That's someone should figure that out on this call.
Yeah, I'm gonna have to agree with Greg data entry is always the number one hurdle I think. And yeah, to your point, Greg, I think there's lots of ideas out there for technical technological solutions to that meaning, you know, how to automate it voice, voice recognition, drones, monitors, sensors, and that kind of thing. But it's also it's also a you know, a personal problem, too, in that there's just not enough time to, to do those kinds of things manually. Now for most farmers, and it's a complexity problem. Going back to my earlier point about just the diversity of of different types of operations and different types of data that that could be useful to collect. Sometimes it's just hard to know where to start, you know, and what, what you should be collecting or what would be useful, and oftentimes, you don't really realize what you needed until you need it, you know, later on so it's kind of an always ongoing process to learning what what is helpful for you to be collecting. Yeah,
I couldn't agree more with what what Greg said. Because this is what what we also feel. I think there's a there's a sort of a conflicting force. We as backend users of data, like where we want to analyze and do whatever stuff that we want to do. We want the data to be in a structured way. But the the end user wants it unstructured that makes the usability grow exponentially high. So think of what happens with WhatsApp. I can send a photo a video I can send a location by moving on the map. If I ask you know, send to me your location I've five decimal places have a latitude and a six decimal places of longitude, that that's, that's not there. So so the way people want to use those interface is in a much intuitive way. Voice video photos. So in fact, we are doing this things with a where we are trying to do the climate smart practice trying to promote that is within the farming community. Now if I have to get the feedback, whether they did something, it just very difficult. If I have to go on a day to day transaction level like this is what I did. This is what I did. This becomes way more easier if I can just go there, take a photograph, I can geotag it and give it back. Not this itself, I think is a biggest hurdle of interoperability because here we are talking about so many different stuff about how to organize all these stuff about the data model. But now I have this information that is embedded inside this, this image or this voice modal text node that has been developed. So I think that's the biggest I think, challenge I would say, because you need to go towards usability on the user side.
I am actually I was typing that answer to the chat question that just also asked the question about user experience and design and how that fits into interoperability. I know that my team does some work on that front. But we are also coming to the close end of our discussion and so I'm going to kind of just punt us over to just maybe a very quick give me like 30 seconds. I want to learn more about you. How do I engage with you tell me what comes next and then I will try to close us out with handing over. So Andrew Finney. Why don't you guys kick us off and then Mike and Greg.
Yeah, thanks. Um, the best way to stay connected with us is to basically sign up for our newsletter at farm stack.co. And we can put the URL in the chat here. We won't spam you. We're not trying to sell anything. We're, we're trying to build a community. And so that's a great way to connect with us. See what we're working on. We have some new features that we'll be releasing soon with Formstack and ag data wallet, consent manager etc. That will we'll share there and then for if there are policy folks or people are interested in governance, we will soon we'll be releasing our kind of like governance document governance documentation on Formstack. We'd love input and feedback on that as well. So that's probably the best way to stay connected with us. Anything anything to add on that Vinnie comers.
I think we are we have released our first testbed with video library. So video libraries, there's I've posted that link, you can go there and there's a link of get data to Formstack. So you will be taken to the to the entire installation procedure you can install from stripe get your get that data in your spreadsheet we are we have also have the GitHub, you know open source GitHub repository there where you'd like to get feedback and we will be coming up with a Slack channel soon so that we can really get the community feedback now. Yeah. Like Mike.
Yeah, I would say just really quickly, if you want to learn more about FarmOS Just go to farmos.org. There's a community menu section which has links to our chat room, our forum and the monthly Scott call schedule. So yeah, all are welcome. We'd love to have you
Greg. Sure, yeah, I just put in our we have a newsletter also same kind of same as was previously stated. And then I put my email in there really were interested in people who, especially this year are interested in creating farmer groups, and benchmarking. We're really excited about that. We're always looking for more farmer groups. We'd love to get your input on that now, to try to make sure to design around it and make it effective for for what you're doing and also people who were methodology developers, so you make so methodologies, biodiversity methodologies, and we would love to implement them so they're available to all these farmer groups. So if you do any of those things, yeah, especially please let us know.
Thank you, ah, and you can learn more about us and the link I just put in the chat. I will hand over to Dorn I think you are here to close us out. And so thank you for your time and give it over to you.
Thank you so much Akita it's just such a pleasure to be able to work with this. This crew at OpenTEAM. And I'm just so excited to be able to share the work as it taps into this much more ambitious effort of transitioning agriculture into a public science and all the all the nuance and detail that goes into that, that process. So it's to bring this diverse group of folks together to really problem solve in creative ways and to hopefully engage all of you in that process as well. So, again, deep gratitude to all the panelists today, and the skilled and motivated community members that make this all possible. So feel free to keep the questions coming after the fact. But we're also there are some questions we didn't get to. We're gonna post in the chat a link to some after hours so we can get to that directly. But also, we'll happy to answer those questions online and after and going forward. And really what we hope is that you'll engage and ask more questions with us so we can creatively come up with those answers. So keep coming back to the next set of webinars are so pleased you bro. You come along with us and look for the progress report and and other updates on our website. subscribe to our newsletter at OpenTEAM dot community. And I think we'll leave this open for a second. So if you are looking for those links, we won't shut it down immediately. And we're look forward to seeing you all again in the very near future. Thank you
Thanks, everyone. Thanks, lovely panelists. And we'll see you at the coffee our knee
I can stick around here. Make sure everyone gets links and I'll join you guys at the coffee hour.