 Michael Cruickshank. He's a freelancing journalist and analyst coming from Australia and his talk is Mapping Doomsday using open source intelligence to monitor and predict environmental conflicts. He will talk about investigations and crisis checks purely based on publicly available data and open source intelligence. Please welcome him with a huge round of applause. Hi everyone, glad you all came in here despite the hate. I suppose it will add a bit more. So it's poignancy to this particular presentation. As was mentioned, I'm going to be talking about how we can use open source intelligence to monitor and predict environmental and climate conflicts. To start with on the screen here, you can see three images. All of these images here have two things in common. The first is that they're all examples of data points taken through open sources. And so they form open source intelligence. The one on the left is an satellite image of Lake Chad taken in 2004. And the two images on the right are from Nigeria and Yemen both taken in more recent years. And the ones on the right are both from social media, I think in this case Twitter. The other thing all of these images have in common is that they're all related to environmental and climate conflicts. So when we talk about climate conflicts and climate change, it's very important for us to remember that climate change is not a future problem. When the media talks about climate change, more often than not, it talks about okay in 10 or 15 or 20 years, it's going to be this bad. But we need to remember when we're using this kind of investigation that climate change is already here, the climate crisis is already impacting many different parts around the world. Indeed, scientists say that the world's global temperature on average has risen by about one degree since pre-industrial times. Moreover, even in the best-case scenario where somehow the nations of the world get together and manage to cut emissions in time to make their targets for the Paris Climate Agreement, this will still not be fast enough to avoid significant catastrophic effects from climate change. And among the most catastrophic are these effects of these effects sorry, are the conflicts which are caused by it. Now when we talk about climate change and conflict, it's important to understand that climate change can either be an initiator or a multiplier of conflict. By initiator, I mean that a singular, I suppose, climate disaster or a anomalous climate event caused by climate change can be something that sets in motion at I suppose cascade of escalation that starts a conflict. However, more often than not, climate change serves as a multiplier of pre-existing tensions or conflicts that are already running in regions. So in the case studies that you're going to see further on in this presentation, we'll be looking at two forms where climate change is playing the role of a multiplier. But why are we doing this? The reason is that when we're reporting on climate change, I myself am a journalist and I've reported on both conflicts and wars as well as environmental issues in the past and often it's mentioned as a side note in articles, okay, there's this conflict that's going on and there has been some perhaps talk about how it is linked to climate change. But what I'm proposing today is that there are better ways that we can go about this through doing a more thorough investigation using open source intelligence, we can make this link more clear or disprove it as it may be and therefore, we can make stronger political and media narratives. So here are some visualizations of the kind of link between climate vulnerability and conflict. Up on the screen, you can see a map of Africa. The areas which are shaded darker represent areas of higher climate vulnerability and within the numbers within these red circles represent catalogued conflict events. As can be seen in this image, there is at least a weak correlation between the areas that have higher climate vulnerability and higher amounts of conflict. Moreover, the same trend also appears in South Asia. This time in the red circles you have fatalities from conflict and again in places like Pakistan, Myanmar, you have vastly higher numbers of fatalities which correspond to the higher climate vulnerability. Now here you have a quote from Rosemary DeCarlo who is the UN political affairs chief and she noted that major armies and businesses have long recognized the need to prepare for climate related risks, rightfully assessing climate change as a threat multiplier. But how can we analyze climate change as a conflict multiplier as we discussed earlier? One way is open source intelligence. What is open source intelligence? Also known colloquially as OSINT or OSINT depending on how you pronounce it. What it is is information and investigations based on information that's taken from publicly available sources also known as open sources. Now what kind of things are we talking about here? Well in the last 15 years or maybe a decade or so, there has been an absolute explosion in the amount of data that can be accessed openly through social media. It's probably the most obvious implementation of this, but then you also have a large and growing number of open databases. In the last three or four years you've been able to access vastly more and better quality satellite imagery than in the past. The kind of things that two decades ago only nation states would have access to. Now a single person sitting in their bedroom can have access to what militaries had 20 or 10 years ago. Moreover, you've got things like position monitoring systems. Many large ships and aircraft can all be tracked actively on certain platforms. Now once you have all of this information, this can be boiled down into investigations and used for certain things. Among the more common, I suppose, strategies that you find open source intelligence being used or applied with are geolocation, which you can see an example of on the screen. This is from an investigation that I did into a bombing in Yemen. And this is an example of how you can take a single image, identify visual elements within this image, compare that to a satellite image, and work out exactly where it was taken. This is very useful for proving that something did or did not happen. And even when you're going from a source, which isn't particularly good in this case, Mint Press News, which is a particularly conspiratorial website, in my opinion. However, the information contained in the image is not, it doesn't matter whether the source is propaganda, the information contained can be proved. So this is why techniques like geolocation are useful. Similarly, you have chronolocation, where you use other elements within images to determine the time that it was taken of. The most obvious way of doing this is via shadows in the position of the sun in the sky. And then finally comparative monitoring, where you monitor a region or a particular city or a town or even a very small area over a long period of time and observe changes. Here are some common tools which are used within open source intelligence Obviously, Twitter is a really good source. So tweet deck is a great way of accessing huge numbers of tweets at once. Facebook groups often have a whole lot of hidden information that is, I suppose, semi-open that one can access if you join the group. And this is also a very good source of information. Then you've got telegram channels, similar deal, location-based Snapchat searches, which is also sometimes interesting because people often feel that Snapchat is a more personal thing and they're not sharing it with as many people. But sometimes you can, again, search based on location. Then with satellite imagery, the most obvious tool is Google Earth, which is very powerful, especially given that you can access historic imagery. You've got WikiMappier, which is kind of like Google Earth, I suppose, or Google Maps. However, any person can annotate what they're seeing on the map. And also you can access different kinds of satellite images often, especially in places in the Middle East. Bing Maps, for some reason, has more up-to-date satellite imagery. So using WikiMappier, I should say, you can switch through the different imagery providers until you find one that has up-to-date data. Then you have more commercial systems like Planet and Digital Globe. Both of these are paid services. However, often content can be accessed through them without having to pay huge amounts of money. Then one final one, which I'm going to go into quite a bit of depth on how to use today, is called EO Browser, which is very useful, especially in the context of climate conflicts, because you can use environmental monitoring satellites and the data from these satellites in order to track huge areas of the globe and some of the climatic changes that are happening both on a macro and a micro scale. On databases, you've got things like ACLID, the Conflict Live Events Database, which I'll also use later in this presentation or show you how to use. It has information and data points on almost every conflict zone around the world, and it's incredibly detailed, and I would highly recommend anyone doing sort of investigations into any kind of armed conflict, really look into these data sets. If you're looking at anything kind of related to U.S. military equipment, NSN now is a platform where you can look up the serial numbers of particular items and to try to find out where they're from, who makes them, etc. You've got business registries, which is also interesting if you're doing a more business-focused OS investigations, and then one final one is leaked ID databases. There are a large amount of databases of people's IDs, which can be accessed online. Whether this counts as an open source, I suppose, is up to your opinion. However, it can be used to make your investigation more powerful if it can help you find a missing link in an investigation. Then finally, two other really important tools. Reverse image searching, which I'm sure most of you are familiar with. It's basically just searching an image and finding images that are really similar, and that way you can find how genuine an image is when it first was published, etc., and often find similar images that look like it that can help you find where it was taken. Then finally, you have a tool called SunCalc, which you can see up on the screen, and it enables you to see the exact position of the sun in the sky at any given point in time. You've got visualized there the position of the sun in the sky now over this town. I forget what it's called in German. So, now let's go on to some case studies of how we can actually apply these tools. The first we're going to look at is the water crisis in Basra in Iraq in 2018. So, the story that was reported, and it did get a fair amount of attention, was that there were a series of violent protests which turned into riots and then crackdowns that killed at least 15 people in the Iraqi city of Basra, which is in the south of the country. It's a predominantly Shia city. Now, during this unrest, government buildings were torched as well as the HQs of pro-Iran Shia militia and the Iranian consulate in Basra. Now, we'll get onto why particularly Iranian areas were targeted. And then finally, a bit later in the presentation, I should say, and then finally, the catalyst for these riots or protests was allegedly poor sanitation due to a lack of clean water and government corruption and mismanagement. However, what actually caused this poor sanitation in the city that drove this protest? Well, during the summer of 2018, the Tigris and Euphrates rivers, which flow into a waterway known as the Shatt al-Arrab, which Basra sits on, the water coming from these two rivers decreased in flow. And then this set of a chain of events where because of the low amount of water coming down the river, saltwater from the Persian Gulf intruded its way up the Shatt al-Arrab, and the area around the water around Basra became too saline for water treatment plants to handle. Indeed, the water wasn't drinkable, it wasn't even usable. And this is one of the key catalysts that got people out onto the streets. Now, during this period, the Iraqi government blamed a series of dams in Turkey and Iran for these low water levels. The first is the Elisu Dam, which is up here in Turkey, and then the other is the Daryandam, which is approximately here in Iran. The Arian Green here used the watershed for the Tigris River. And these here you can see the images of the two dams. Both were completed very recently. The Elisu Dam in Turkey is substantially larger than the one in Iran. So if we wanted to know, did these countries really start filling up these dams and cut off the water supply to Iraq, how would we do this? The most obvious way from an open source intelligence perspective is using satellite imagery. And this is very easy, because dams are such huge structures, and even a very low resolution imagery that can be taken every day, you can see what these dams are doing, and you can see water filling up. So using this approach, sorry, yep. And then other questions that we also might want to ask are how can we establish a chain of events that lead from these dams if they were cut to protests in Basra, and then finally what role did climate change play? So now, onto these satellite images that I spoke of a few seconds ago. Here you have images taken from the planet constellation. They're three images of Elisu Dam. It may be difficult to see what's going on here, but the main structure in the middle is the dam wall, and the low side of the dam is on the bottom of these pictures. They're all North South orientated. June 30, which was at the beginning of this crisis in this unrest in Basra, you can see that there is very little water on either side of the dam. And then by September 2, the image in the top right-hand corner of the screen, the water level has not changed very much at all on either side. Then finally, by December 15, you can see the dam has begun to fill, and there is more water on the north side of the dam than there was in the past. You can actually access vastly larger numbers of these images that more or less confirm the same progression, and you will see the same thing happening over a longer period of time. But from these images, what we can say is that during the height of this crisis between June and September, this dam was not filling. This is despite the fact that the Iraqi government was continuously saying that they were. Moreover, this actually congrues with what Turkey was saying about this particular dam, in that they'd originally planned to start filling it in June, however, decided to delay the filling of the dam because of requests from the Iraqi government as well as trying to, as a gesture of goodwill towards Iraq. So what of the Iranian dam? There's another set of four images from the same source, the planet constellation. And this dam is interesting because it's got a very obvious spillway, which you can sort of see here, and then a lower outlet pipe. And these are the two ways that water can go from the holding pond down to the river below. And the river that this sits on is the Suwan River, which is a tributary of the Tigris River that eventually flows to Basra. Now, in April of 2018, you can clearly see water flowing down both the spillway as well as the lower outlet. Then by June 13, little water is coming down the spillway, and a smaller amount of water is also coming down out of the lower outlet pipe. Then this is when it starts to get interesting. By July 22, the water level in the dam has noticeably dropped. There isn't any more water coming down the spillway, and indeed down here where the lower outlet pipe would be, you can see that the water level is also much lower and much of the river is dried up. So most likely there is little or no water coming out of this pipe. This trend holds true through to September, where again you have a lower level of water and nothing coming down the spillway. So based on this, could we say that this entire crisis, this riots and all these people dying in Basra, was this caused by this dam being shut off? Was this man made? Well, yes, it is man made. However, it's bigger than just these dams. Here is another kind of sort of open source intelligence that you can use. These are images all taken from social media, and they all show different sections of the Tigris River in early June. Important facts about all of these images. They're all taken in areas that are north of the confluence of the Suwan and Tigris River. So if the water was lower from the dam in Iran, it should not affect the water level in these pictures. However, the water level in them is all very low. So from this we can say that the water level coming down the river or the amount of water coming down the river was already low, and that even if this dam was shut off, the dam wasn't the primary cause of this particular crisis. But what was? The obvious answer here is the drought in the region. You've got a series of different quotes here from sources talking about the extent of this drought. Firstly, in the winter of 2017-18, they had one-third less rainfall than average. The Iraqi Minister of Water Resources blames this on climatic conditions and lack of rainfall. Then you have another source, the Jerusalem Center for Public Affairs talking about a six-year-long ongoing drought characterized by erratic rainfall. And then finally, a scientific source from the Journal of Earth Sciences talking about how climate changes due to global warming have influenced the weather there and have caused a general decline in precipitation, not just in the last few years, but indeed the last few decades. So this is a long-term trend which reached an acute point in over the winter of 2018 that reduced the water levels and then caused this crisis. So what conclusions can we make from this particular case study? Firstly, through open source intelligence and investigation based on this, we can say that the drought in Iraq and upstream countries played a significant role in the unrest. The drought itself is linked to climate change. Moreover, the blocking of flow from Dharian Dam in Iran likely exacerbated this, and indeed the closure of this dam was perhaps also linked to this overall drought. Iran is in the same drought conditions, or at least it was at that time, as Iraq. Finally, it's important to note that this event did not happen within a vacuum. Iraq is a war-torn country with very weak institutions. It's divided across religious and ethnic lines, and even a small thing can act as a multiplier that suddenly catapults it into further violence. So within this context, it's more likely to be able to say that climate change played the role as a multiplier rather than an initiator. Let's look at one further case study. This time, I'm moving to Nigeria. We're going to talk about attacks by Fulani herdsmen. Now, the Fulani are a group of mostly Muslim cattle herders who live across several nations in the Sahel region of Africa. The Fulani herdsmen have been grazing their cattle further and further south, bringing them into conflict with farmers. In Nigeria alone, the death toll from this violence is over 3,500 people. The violence itself is often blamed on climate change due to low rainfall in the Sahel region. And because the rainfall is lower, it's commonly thought that the Fulani herdsmen are moving their cattle further south into more lush areas. So we want to do an investigation into this. What are questions we need to answer? Again, we're looking at are the attacks related to climatic patterns? Does violence speak, does violence spike in periods of low rainfall? Was the intensification of violence in 2018 caused by an anomalous climatic event? One further thing that I forgot to mention is that this year there have been significantly less attacks than in 2018 where there was a massive spike of violence and then in 2017, again, it was lower. So was that particular spike caused by an anomalous climate event? That's another question we want to answer. So how do we do this? I mentioned earlier a tool called EO Browser. Now, this is a platform that enables you to access imagery from a huge number, well, not from a huge number, I suppose, from a limited number of remote sensing environmental monitoring satellites. And the data from these satellites can be visualized in a number of different wavelengths or different things where you can see things like pollution or water or in the case of what we're going to do here, something called Normalize Difference Vegetation Index. And what this does is it enables us to see effectively how green an area is. And we can use this relative greenness as a proxy for how much vegetation there is and also in a place which is fairly arid and not irrigated, like the Sahel, we can also use it as a proxy for how much rainfall there is. And through EO Browser, we can access this via the Sentinel-2 satellite. So what areas of the country do we need to focus on and to look at how much vegetation there is, how green it is, when it's looked at from satellites? So up on the top of the screen, you've got a map of the area, the general area where Filani herdsmen live. Then as you can see in Nigeria, it's sort of the top third or quarter of the country. Then what I've done using EO Browser is I've drawn a rough sort of polygon over the area where the Filani approximately live. And then I use the tools that this program has in order to look at hundreds or probably even, yeah, probably hundreds of individual satellite images. And then graph over time how much greenery there was, how much vegetation there was, and also by proxy how much rainfall there was. And the graph you can see on the bottom right hand corner of the screen. This is over, I think, three or four years. And quite clearly, there are seasons that you can see. There are peaks every wet season. And this can be seen in a sort of cyclical pattern. Part of the reason why there are data points missing during this sort of period where it's going up into the wet season is because I've used a tool that enables me to remove all of the images that have high cloud cover. And as you'd expect in the wet season, you're going to have lots of images where you can't see anything because it's covered in clouds. And I've removed all of those data points. This slider bar that you can also see in this image can be increased and decreased. And you can see to sort of see more or less data points. However, once you start including all of the images, you get a lot of outliers. So we've got the data on over the last few years, this point of time that we want to look at, what the relative levels of greenery and rainfall in this region were. Then we need to compare this with the number of attacks and conflict or the amount of conflict in the region. So we turn to another source I mentioned earlier, which is the armed conflict location and event data project. And what I did then or what anyone can do is just go to their website and then you can generate huge databases of all of the recorded attacks by one group, by two groups, or by region, or another field of your choice. And then you get all of this data. It's displayed kind of like what you can see here. They've got information on fatalities. You've got information on things like where exactly the attack took place and what the sources were, et cetera. And then through all this data, you can get an idea of the intensity and the deadliness of a conflict over time, which is what you see here. This is for 2017, 2018. And it's the number of philani attacks and casualties over this two-year period. And as you can see, this spike of violence in 2018 is very prevalent here. It's very obvious. And then finally, in the bottom right, it's kind of difficult to see, but this is also a map of the agricultural calendar of a typical year in Nigeria, pointing out some of these sort of important seasons. And it's worth noting here that the livestock migration, which particularly pertains to the philani, is between February and August. So let's compare it all. We've got the index of vegetation, which is a proxy for the rainfall. And then we've got over the same period of time, fit to the same scale, all of the attacks. And from this, we can see some interesting things start to happen. Firstly, there does appear every wet season to be a decline in the number of attacks. And given that this conflict is driven by herders, as I mentioned a few minutes ago, moving their cattle further south in times when it's dry and there's not much vegetation in the north of the country, it would make sense that during the wet season, when there's more vegetation for their cattle to graze on, they will not be as frequently in conflict with pastoralists further south. And then in the dry season, you can see that the relative levels of violence are higher. However, this 2018 spike in violence, was it precipitated by an anomalous event in terms of rainfall or the lack of vegetation? Looking at this data, it doesn't look to be the case. There is not any significant reduction in the amount of greenery in the time preceding this spike of violence. So, what does this tell us? It tells us that more likely than not, this particular spike in violence is not related to a climatic cause. Rather, the actual, the spike itself or this acute amount of violence was instead instigated by a political development in the region. And indeed, this is backed up by, I think, a study done by Crisis Group, I believe it was, that looked at this particular conflict and came to the same conclusions through a very different kind of methodology, more by talking to people on the ground. However, the overall conflict is driven by the area drying out. And this is something which has been catalogued over a long period of time. So, some things need to be considered here. Firstly, that based on this remote sensing data, the attacks are driven by low vegetation and low rainfall. And indeed, the continuing desertification of the Sahel region will intensify this problem. However, up in large spikes or outlying years, can't always be linked to particular climatic events. Because clearly there are political factors at play. And then given all of this, it's more, I suppose, more correct for us to say that climate change only appears to be playing a role as a background driver of this conflict, which is interesting given that often the media narrative overall is that the single cause of this conflict is climate change, which is certainly a large part of it. However, there are other factors at play. So, how do we use these techniques and apply them into the future if we consider that climate change and climate conflicts will get worse? The first thing we need to know is where to look. According to the World Economic Forum, there are three primary factors that make countries vulnerable to climate change and climate conflicts. The first is a history of conflict over the past five years. The second is that over 40 percent of the country is involved in agriculture. And then the third is that over 20 percent of the population is excluded formally from political power through discriminatory institutions. Now, you can see two maps on the screen. They show the confluence of climate exposure and fragility risks. And in the second map, you can see the sort of hotspots marked out. Most of them are in places like Central Africa, West Africa, as well as the Middle East and South Asia. It doesn't appear on this map here, however, I would say that likely the Philippines also is another spot that it would do well to keep an eye on because, firstly, it's got significant amounts of internal conflict that's already been going on for many years. And secondly, it's incredibly vulnerable to climatic disasters like typhoons. Then, when we have these places that we want to look at, then what can we do? We can choose one of them, for instance, and apply a number of approaches. Some of these approaches are things that we've already used in this case, studies. Firstly, you can use remote sensing to develop a relationship between weather and conflict and extrapolate predictions. In the last few days, it's been talked a lot in the media about these fires in the Amazon and whether they're caused by policies of the Bolsonaro government or if they're caused by a drought or something like that in the region. Such approaches that were used for the case study on Nigeria could similarly be applied there to look at whether it really is anomalous in terms of weather or whether political factors are driving this instead. Another approach we can use around the world is using satellite imagery again to monitor day-by-day changes in large assets like dams, reservoirs. Also, you can use things like you can look at crop fields and see how much growth there has been in food and then use that to monitor on a very, very large scale whether that's going to cause disruption to food prices in a region. On the issue of food, you can also use social media to monitor key terms and keep an eye on things like food prices in a country. You can monitor over time particular accounts to verify that they are indeed in the region and using approaches like geolocation to make sure that you can actually prove that they are indeed in the place they claim they are. Similar things can be applied to water quality. I didn't include it in the presentation but there was a very good image that was shared on Twitter of someone who was actively monitoring the water in Basra during the height of this crisis and pointing out how polluted and saline it was. These kind of images could also be applied to a number of other places. Finally, you can use, as I mentioned, things like Akled have also location for all of these events. Over time, especially when you access these kind of huge data sets, you can map the location of all of these attacks and then you can see if they are changing over time and use that to see if that corresponds to perhaps changes in climate or political changes or other things. This is also a different thing that can be applied. Based on all of this, I hope I've given you a good first introduction to OSINT, open source intelligence and how this can be applied in terms of climate conflicts. Is there any questions that anyone has on these topics? Thank you very much, Michael. If you would like to ask a question, do we have two microphone angels in the room? Please come to the ASL parts and ask your question, line up there if needed. We have the first question, please. Yes. Hello. Thank you for the presentation. Very interesting. Have you considered doing some starting some kind of project or collaborating with somebody already who could map this stuff over time and essentially point out that an internet using coffee drinking first world place is about to be overrun by a certain event because every time, every year, something moves closer and closer to where people with internet are, so to speak. It's certainly an interesting concept. I suppose the problem with this is that if, like, given that these changes are happening over an accelerating time frame but still a very long time frame, it's really difficult to make sort of accurate predictions beyond a year or two. We can say that, you know, okay, in a certain amount of time, there's going to be a greater likelihood of conflict in a region. However, at such long time frame, it's very difficult to say, okay, in this year, you will be, there will be this many climate refugees. However, we can project it and say that there's probably going to be like an overall increase in conflict and then each conflict then might generate X number of refugees and use this to make predictions. But again, it's quite difficult to actually do this in such long time frames. Thank you for the answer. The next question over there. Please go ahead. Hello. Have you predicted any upcoming events yourself already in the future? Like any catastrophes or something? I mean, okay, this, when you're doing this kind of thing, it's not like you're some Nostradamus who's saying, okay, this will definitely happen. All you can do is measure overall levels of increasing risk and say there's a higher likelihood that this will happen. I mean, when we're talking at things at time frames greater than a year. However, there is an opportunity that in cases where you can see, when you've already established a relationship between the climate and conflict or between climate and political disruption, once you've established that relationship and then you notice that there is a significant anomalous event like a drought or flooding, which has caused significant disruption, you can generally make a fairly good prediction that this will indeed at maybe a few weeks from then or a few months from then lead to actual violence or political disruption. So on those kind of time frames, it's possible to make better predictions, but longer than that, all you can really do is probabilities. Thank you. To my friend over there, your next question. Hello. Thanks very much for your talk. It seems like this is a lot of manual effort to to do the calculations and to check if where and how much conflicts are affected by climate change. Is there a way to do an automated monitoring of some sort? Do you have any ideas on that? It's a good question. It's possible that you could. I'm coming from a background of journalism, so I suppose from like my sort of go-to approach would be doing it from like doing it human-based, doing it myself, do you know what I mean? Hands on. However, there probably is a way of automating at least some things, especially a lot of this data crunching, data sets and things like that, and then making a way to display all of these events on a map. I mean, these, if we go all the way back here somewhere, if you remember where these maps were, where we could see Africa or South Asia, these were all generated through sort of algorithms, which were just plotting every single event, and these are live maps. My computer is very laggy, so unfortunately maybe these will come from the screen a bit later, but these are live maps where you can zoom in and they get more and more detailed as you zoom in. The screenshots that I showed you were just sort of an overview of what's going on, so it is possible to automate this. However, the analysis itself, which is kind of the important part, generally has to be done at this stage by a human. This was the map that I was talking about. This is on the source down here. You can access this online, zoom in and sort of see all of the events that are mapped. Okay, thanks very much. My friend over there, your question. Thank you so much for your presentation, Amir. I wanted to ask you, since you have to monitor a lot of social media platforms, how do you deal with the discourse of privacy and surveillance? How do you protect also the privacy of the people while you're doing this act of investigation? That's a good question. I mean, the sources, the people who are sharing all of this information are doing it publicly. I'm not, generally, when you're doing open source intelligence, you are not collecting information that's on people's private pages or something like that. Moreover, you're generally not trying to identify the people who are actually taking the footage unless it's absolutely critical to the story, because the story, unlike traditional journalism, where it's all about your sources and the seniority or the trustworthiness of your sources, whereas in open source intelligence, it's all about the content itself and whether that can be used to prove something. It's less important that you need to link the information to an actual person. Generally, when you're doing an investigation, it can be avoided. There are, of course, cases where it's not, but in general, it is avoided. Thank you for your answer. On my left hand side, please, your question. Hi. So you have a bunch of data sets and then you have a bunch of tools to analyze those data sets. Do you feel like the tools are lacking and could be improved or combined data sets together? Certainly. I mean, if you could automatically combine something like the two data sets that I combined, the EO browser and the armed conflict location event database, if those two things could be combined, then it would be a very powerful tool that would speed up these investigations immensely. The problem is they're owned by two different people, so actually combining the two would probably require either a lot of money or a lot of negotiation. Okay. Thank you for taking your time and answering all the questions. Oh, one more? Different. One more question. Okay. Thank you for a nice presentation. I loved it. Besides the verbal part, also, your slides are amazing, the way you did the layout, but also the content of the slides. So I'd ask, will you be making the slides available like for us maybe? I can do that. However, some of them have images that aren't for use, so I'm not sure how that works from a rights perspective. If that's something that's possible, then I can share them. Okay. Thank you so much. Finally. Thank you for answering all your questions, all the questions here. And will you still be available at the conference if people have questions further on? By all means, contact me. All right. Thank you. Thank you so much, Michael.