 Now I leave the floor to our colleague, Nathan, who is part of our team and he can introduce briefly himself. He will talk about Prosa and so up to you, Nathan. Thank you, Stefania. And that's what we are for inviting me to present as part of this online workshop so I'm very happy to be able to present to you all of you in a document that we've been working on called the progress towards sustainable agriculture. So let me share my screen. So as I mentioned, this report that we've been working on is a product of the statistics division here in FAO as well as the agri-food economics division, joint efforts between these two divisions to measure progress towards sustainable agriculture and give some results. This as a background, so the report has already gone through an internal peer review within FAO with other divisions as well as already gone through an external peer review process. These are mostly people from other international organizations including IFPRI and the World Bank and also researchers from universities including the University of Maryland. So as some background how this report is structured. So countries are classified in terms of four different farm systems typologies. These are referred to as modern food systems, traditional food systems, land intensive mixed food systems and capital intensive mixed food systems. These groupings overlap well with those that were defined in the 2017 high level panel of experts on food security and nutrition. The groupings were made by, for those that were interested in the more technical details, they were classified in turn by a statistical method of principal components analysis of factor productivities in which the first quartile was defined to be this traditional food systems typology. The second and third quartiles were split and classified in terms of either land intensive mixed or capital intensive mixed food systems typologies. And the highest quartile is this modern food systems typology. So a better description of these four different food systems typologies, okay? And here you can see a country mapping of where these different typologies how it's distributed across the globe. So the modern food systems are those countries which have our capital intensive with high land or labor productivities due to mechanization and access to modern technologies, agriculture is highly competitive creating a strong agricultural export market. So these are the countries that are shaded in yellow in this map. The traditional food systems typology on the other hand are characterized by both low labor and land productivities and low capital stocks. The two mixed typologies which are split between land intensive and capital intensive. The land intensive is characterized by higher productivity due to larger land areas which are available to the agriculturally active population whereas the capital intensive are characterized by higher land productivity due to the increased use of agricultural inputs, okay? And higher levels of capital empowerment per worker, okay? Now that's how the countries are grouped and the four different typologies more information on the coverage. So for this report, we included a set of 16 different indicators. The dimensions have some, a lot of overlap with those dimensions that are used in 2.4.1. We have six socioeconomic indicators, 10 environmental indicators and the time period over the, for the report is for most indicators 1961 to 2017 with some indicators such as the prevalence of undernourishment or pesticides use starting in the 1990s. Now for the data source, the data is exclusively from FAO stat with the exception of water use where we are using AquaStat which is another data platform for water use in agriculture available in FAO stat. Most, a lot of this data comes directly from questionnaires that are dispatched to our focal points and process with an annual dispatch collection and dissemination cycle. So an important distinction here with the pros of report is we are working at country level data, okay? So this, all of this data and the trends and that we use in the report come exclusively from country level data as opposed to farm level data for 2.4.1. There is a traffic light approach used also in this report in which there are also qualitative parameters assigned in terms of traffic lights which are this red light, red, green and yellow for each of the pros and sub indicators and these are aggregated using country agricultural area as ways to produce a dashboard by each food systems topology. So an important distinction between the traffic light approach that's used here and is that for this report we're really focusing on progress over time, okay? So while all of the classifications in terms of traffic lights are made exclusively in terms of either gains or decreases, okay? So we're looking at changes in the indicators from one time period to the next. Gains across these two time periods are classified as yellow. If that same gain is maintained for a second period of time, it's classified as green whereas decreases across any two successive periods are classified as red. So as I mentioned when looking, when talking about the coverage, also this data is country level and we're focusing on prop and livestock production systems, okay? I should mention for this traffic light approach, okay? So although it's exclusively gains and or deterioration in terms of how we are classifying the traffic lights across two time periods, for some of the indicators we have defined a physical threshold and gains are defined as moving towards or away from that physical threshold. So we're still looking at changes over time but we have thresholds defined for three of those indicators such as for the soil nutrient balance which you will see in the next slide as one of the indicators listed. We have a physical threshold of that's defined as five kilograms per hectare. Fertilizer use 50 kilograms per hectare and pesticides use 1.25 kilograms per active ingredient per hectare. These thresholds were defined using the existing data with a global medians to define these thresholds. So I'd like to presenting Proza as a proxy for 2.41. Nonetheless, there is important correspondences between the Proza indicators and 2.4.1 and these indicators themselves were chosen in the context of having looked at 2.4.1 and quite in detail and you will see the dimensions for correspond and we have very similar or mostly matching themes. So I can list, I can go through the indicators, at least listing them, at least the progress to sustainable agriculture column. So we have three dimensions that we're looking at. We have the economic, social and environmental dimensions and then we have themes within each of these dimensions similar to 2.4.1, which are for the economic theme, productivity, profitability and resilience for the social, decent employment, food security and land tenure and for the environment, soil health, water use, fertilizer risk, pesticides risk and biodiversity. In addition to indicators that were, we added a little bit late in the process, which we decided were quite important on the less in measuring this progress towards sustainable agriculture, which were some indicators on emissions and land use. So I mean maybe also input from our Bob here on if I can go through also defining more in detail each of the indicators or if you think in the interest of time I can move forward or how do you guys feel as the organizers? Nathan, let's just move forward because if we go into the details of each sub indicator that's been selected as part of the Prosa framework, then it will take us a lot of time. So given that we only maybe have 10 or 15 more minutes, let's concentrate on the next slide. If participants are interested, they can always write to us and we can provide them with additional information on Prosa. Okay, that sounds great then. So I'd like to just give some general results that can be highlighted as actual results looking at this report and the results that we find are the most important. So the available national level statistics across a range of these sub indicators enables a first order and complete analysis of progress towards sustainability, both in qualitative and quantitative ways, in qualitative way being with the traffic light approach which is nonetheless driven with, I mean, the categorizations nonetheless come from quantitative differences in terms of looking at changes over time. So just to mention some of the indicators and themes. So if we look at the social economic theme, we found that across all the typologies, progress has been strong with gross output specialization trends nonetheless remaining one of the most important limiting factors. So let me at least highlight what gross output specialization is. So gross output specialization is the, it's basically a, it's looking at how the value of production is distributed across different crops and livestock and whether or not the value of production is coming from more specialized monocrops or if it's distributed evenly across different crops and livestock categories. Okay, so that's what this gross output specialization is looking at. And this tends to be what we found the most limiting factor. So when we're looking at agricultural land use, we found, so agricultural land expansion is a detriment to natural ecosystems in particular for us. So the deforestation and conversion of forest land to agricultural land. This was one of the very more important issues that we identified across all of the typologies. In terms of biodiversity, so we're looking at crops and livestock diversity. Let me at least highlight these two as it's one of the key things that I would like to highlight in terms of the results. So the crops and livestock biodiversity are defined as genie coefficients. And this is in terms of for the crop diversification index in terms of the equal or unequal distribution with the genie index of area harvested for different crops. Whereas the livestock diversification index is also genie coefficient to measure how well the livestock market is distributed across different livestock categories. So for example, I mean to give you context, the highest level for the diversification index would be when you have a complete equal distribution in terms of those crops in terms of area harvested and which is an important factor that we identified for resilience. Because these countries are less susceptible to market fluctuations having their crops equally distributed across many of them. So it doesn't always coincide with resilience in particular what we looked at, for example, if you look at gross output specialization, so the value coming from crops and the diversity in terms of crops. But we found that these two are not always coinciding and the relationship is more complex than just higher value and less diversity or the differences are really typology specific. The soil nutrient balance and chemical pesticides, we remain significantly limiting factors to agriculture sustainability in all food systems. So at both low levels and high levels of inputs. So the soil nutrient balance indicator that we use in the report is, as I mentioned, is baseline level that we're using of five kilograms per hectare of what we're considering healthy soil, yes. And for countries that are using high levels of fertilizers or and or manure to in their soils can have way too high levels of the soil nutrient balance, which presents a environmental risk in terms of leaching and other environmental risks. For other countries instead that are not, that don't have the access or are not using enough agricultural inputs that are below this baseline, it also remains a limiting factor. And work needs to be done to aid those countries to have better access to the agricultural inputs that they need for productivity in agriculture. So there's another section of the report which is looking on drivers of change on the path towards sustainable agriculture. This was the part that was done by our colleagues in the agro food economics division. And this was a combined assessment. So the first step in the way that this section of the report was made was a broad review of literature to identify quantitative indicators and select the drivers to analyze, use computational selection procedure and for those interested in the statistical component, this is procedure is known as lasso. This is the least absolute shrinkage and selection operator. And after looking at all of these relationships between the indicators, a final selection was made of those indicators to look at for the driver analysis. So the main outcome or the main thing that I would like to highlight across this entire section was that perhaps the most important message is government support is one of the most important and direct mechanisms available to policymakers to encourage sustainable agricultural development and cooperation across these different sections will be needed to identify and address all of these issues. So the drivers of change were split into these five different sections which are looking at demographics, inequality, farm-sized structure, global integration of agriculture, looking for example with foreign direct investment and agricultural exports and this government support. That's pretty much it from my side or Bob. I have, if there, or as Fandia, if there is additional time, I'm happy to show graphically or the display, for example, of the traffic light approach, for example. I mean, let me just show, for example, yeah. So I mean, in the report that is gone through a storm review and will be made publicly available soon, these are the dashboards that we've developed by food systems typology that are included in the report. So for each of these food systems typologies looking at changes over time, have their own sustainability hotspots is what they're referred to and each of them have their own areas that need to be better addressed. So for example, capital intensive food systems, those that are using very high levels of agricultural inputs, those are the ones that need to be most critically addressed for sustainable agricultural to high levels use of these agricultural inputs, such as fertilizers and pesticides. Okay. I will give the floor back to Stefania and or Esfandiar and thank you all for your time. As I mentioned, the report will be made available soon, already gone through external peer review and we're, we're, we're, we're, we're, we're, we're, we're, we're, we're, we're, we're, we're, we're, we're, Anita, thank you very much. We have one question from Mrs. Bata. So the question is, can this module capture qualitative and quantitative interaction effect between two or more subredigators? As for example, higher use of fertilizers may interfere on the market resilience. Yes. Okay. I'm not muted, right? Sorry. So, okay. Yes. So thank you very much for that question. And the, of course the, the interrelationships between these indicators is very complex and is nonetheless, quite important to address these issues and look at them together. So, yes. While the report is structured by looking at each of these indicators separately, but nonetheless, we, we do draw some important connections between the, the different indicators. So, one, yes. You mentioned resilience, for example. So for example, yes. I mean, we look at it more specifically the land intensive and modern food systems and we look at diversification in terms of crops and livestock and gross output specialization. What we found for these two food systems, for example, is that they have moderate levels of gross output specialization, meaning and low levels of diversification, which these two together can mean higher exposure to climate risks on the overall agricultural sustainability of these two food systems to apologies. And we do draw some other connections, important connections between the indicators. Nonetheless, as you all know, as well as I do, this multi-dimensional looking at all of these different aspects together of a sustainable agricultural is a complex issue. And we're happy to see also the work that's being done by 2.4.1 to look at all of these dimensions together. Okay, thank you very much, Nathan. We don't have any other questions for now. So I think we can thank you once again, Nathan, for this intervention. And we pass to the, we move to the next presentation then. Okay, thank you very much. You're welcome. Okay. So you can stop the sharing on your screen. Okay. I suppose I should do that. Okay. You can't? I think I can stop. Okay, you did. Okay, great. So now I'm going to no, sorry. I'm going to give first the floor to Asfandiyar. So thank you very much, Stefania. And indeed, thank you, Nathan, for making time to present very well the pros and pros approach that FAO is currently working on. So for the sake of participants, I mean this, as Nathan mentioned, this is still work in progress. So we are in process of reviewing the report with both in-house and external experts and will be available soon. One point that I would really like to emphasize and explicitly highlight is that the pros framework, as Nathan mentioned, is based on available data, national data that it's been shared by countries with FAO. So all the information that we use for this framework is already available with us. But this doesn't mean that, you know, this framework is gonna replace or substitute two for one in terms of the monitoring of or reporting on SDG indicator two for one. So from this perspective, what I'm trying to say is that this is a complementary process that is initiated by FAO. While we are waiting for data on SDG two for one, we thought that we may want to understand as to what's happening with sustainable agriculture globally and regionally. And hence, so we are looking into other approaches that could later on, you know, be complemented once two for one is implemented and operationalized at a country level. So with this very small, you know, talk, I will now show you the SDG two for one web page, which is basically, let me just, can you see my screen now, Stefania? Yes. Okay, so let me just, so can you see this web page? Yes. Okay, so basically, as I was telling you yesterday, you know, as part of my presentation, the all the sustainable development goals or and the indicators that FAO is custodian for, we have a dedicated web portal. So here, you know, we can provide you with this link, though it's already there in the presentations. So here you can see all the relevant information that you need to know about the SDG indicators that we're responsible for. So as you can see here, the indicators are clustered by different goals. So, you know, all the 21 SDG indicators are listed here. What you need to do is basically, you just pick any indicator as we are discussing, you know, our today SDG two for one. So I will click this indicator and it will take me to a dedicated page of SDG two for one. And if once you scroll down, once you scroll down, you will see all the necessary documents that we have been talking about throughout our presentations over the course of past two days, you can find it here. And you are just by clicking on these documents, you can readily download this. So we have the methodological note. Then we have the FAO data collection questionnaire, which I was talking about yesterday, which Stefania in fact was talking about yesterday, it's available in three languages. Then we have the survey module that I mentioned in my presentation yesterday, which countries can use to collect information, from the holdings to basically measure and monitor SDG two for one. Now, as I mentioned earlier, this survey module can be administered as standalone survey or it can be integrated at appropriate places within your current agricultural system. Apart from that, we have been talking about other related or background documents. So the sampling guidance for two for one, those who may be interested in understanding more about it. Guidelines on data analysis and reporting. So once information is collected, how do you then analyze information and then report on the respective subindicator by sustainability status, this document also give information about the construction of the dashboard and the aggregate indicator. Then we have instruction manual on data into operation. This is soon after once information is collected, how, what softwares can you use for you to basically enter your data into and all the steps afterwards. Like say, for example, in terms of coding, in terms of cleaning the data, et cetera. And then the numerator manual, which is well before the data collection process. This manual can be used to train the numerator servers and the supervisors before their field deployment. And you can, this is a very helpful document because each and every question which is given in the survey module is then explained in the numerator and manual step by step. All the details related to how the question should be asked, whether to probe the respondent more for further details, all those kind of details and nitricities has been captured in this numerator and manual. So you can access it readily by going here. Plus, all our capacity development efforts back in 2019 and for the previous years have been captured in this part. So by clicking on these links, you will not only see the concept notes, but as well the presentations that were presented back then due to these countries. And of course, the e-learning course that we have developed for SCG 2.4.1 by clicking on the e-learning course, it will take you to this resource and you can take this course at your own convenience for you to be able to report on, to familiarize yourself more with the indicator. And then of course, other related stream of work that we took into account while developing the methodology of SCG 2.4.1. And of course, the focal point information is given here as well. And then the contact details. So this email address is for the office of the chief statistician. We will update this page with our email address as well. So I will request to Fania to basically note this down. And we will have our own email address which is SCG 2.4.1-indicator at FAO.org. So, you know, and not only 2.4.1, but all other 21 SCG indicators have been covered to a larger extent in their dedicated web pages. One other thing which I would like to show you because you haven't seen it until so far is the survey module that we have developed for SCG 2.4.1. So when I was telling you that basically all the information on the sub indicators, you know, the data items and the variables are captured through a survey questionnaire, you know, the questionnaires here. So you can, you know, as mentioned earlier, you can administer it as a separate survey dedicated only to 2.4.1, which is not advisable from our side, but if you are still interested, I mean, you can do that. But, you know, you can take the questions from here and plug this in into your current agriculture surveys or other data collection instruments using which you collect information on, you know, about agriculture production for crops and livestock. And based on this, you know, you can collect information on 2.4.1. The similar kind of exercise was done for agris, which Flavio or Koli from the survey team presented yesterday. So we took the agris questionnaire and then we mapped the agris questionnaire against, you know, this module of 2.4.1. And then we checked as to what is missing in the agris questionnaire, which needs to be there for it to be SDG 2.4.1 ready. So as you can see here, you know, we have section on area of the holding. Then we have questions for the economic dimension of the holding, which will help you basically report information on, collect information on the three subindicator within the economic dimension. Then we have a section on environmental dimension of the holding, which will collect all the information required for the five subindicator in the environmental dimension. And then of course, we have questions on the social dimension of the holding, which will help you collect information on the three subindicators of the social dimension. So with this, I will stop, but you know, just to again reiterate, you know, if you want, we can share with you this documents, you know, independently as well, but as all the information is provided on this webpage, I would really urge you to go there. And apart from these documents, we will find many much more interesting information that will be helpful for you, for you to familiarize yourself, not only with 2.4.1, which is the focus now, but as well other SDG indicator under FAO mandate. So with this, I stop. Now we should see, well, okay. So you know that this virtual training is focusing on the SDG 2.4.1, which we know it's a very new indicator. So the data collection is a process that we just started. But FAO, in particular the statistical division, has a very long experience in collecting the data. The analysis carried out based on food and agricultural statistics is a pillar for the, for FAO activities. Indeed, this is explicitly mentioned in the article one of FAO constitution. We have found that for food and agricultural statistics. We have fish stat for aquaculture and fisheries, and we have aqua stat for water and irrigation. They all in globe and established and well-known process of data collection and reporting mechanisms. They are part, in fact, of the organization's mission to improve the data collection and dissemination for the development and the fight against anger, and malnutrition. The focal points for reporting all this data are expert staff from the national statistical offices, the minister of agriculture's, and all the relevant agencies of which some are in attendance today. Within this context, FAO gets regularly the national data on crop and livestock production, on environmental and social economic issues. They are all relevant to the two for one indicator. Looking in the details on FAO stat, which is responsibilities, as I said, of the statistics division of FAO. It is FAO stat, it's a database that is disseminated on the web. It is based on an open source software platform called Phoenix, where data are free and available in all UN official languages for over 245 countries and territories. It covers all FAO regional groupings from 1961 to the most recent year available for the specific country. We have on FAO stat more than a million statistics. All this data covers 15 domains, which are listed here. So production, trade, food balance, food security, et cetera, they are listed here. Finally, the data are disseminated through web pages, through publications, working papers, and statistical e-books. You have here the link to the webpage. And just for your information, we have approximately 160,000 users per month. They are using FAO stat platform. How we collect the data. So we have seven questionnaires that we dispatch annually, so every year. And the responsibilities for those questionnaires is divided by three teams in the statistics division. We have the environmental team, which is the team where I spend the year and myself are working in, that deals with the land use questionnaires, pesticide and fertilize the questionnaires. Then we have the production teams that is responsible for the production questionnaires. And finally, the third team is the social statistics team that send an analysis of the trade and government expenditure and the prices questionnaires. Of course, the environmental team is the one more linked to the SDG 241, since many sub-indicators are calculated through data that comes from these questionnaires. Although the primary method of data collection is through these questionnaires, some teams sometimes consider also external sources. So for example, they use the official ones like the national statistical offices website, but also some other semi-official. So for example, the oil world website for prices. Just to mention one. These are snapshots on how the questionnaires are visualized. So they always come in an Excel format. Similar to the questionnaires we have seen on the SDG 241 indicators. So let me show you now an overview of the focal points for some of the questionnaires in your country and the responses that we have got in the last three years. So we kindly ask you maybe to have a look and just in case you know that one is not anymore the focal point, you just inform us. Let's see, so how, for example, this is the questionnaire of the length use. So how the data are linked to the 241 indicator. They are linked and they are used to calculate the denominator of 241. And they are linked to the team five, in particular through the indicator. So variation in water availability and to the team number, team eight, which is the sub-indicator use of agobiodeversity supportive practice. The year indicated in the columns is the year of the dispatch of the questionnaire. So asking the data for the previous year. So in these last three years, we have got data from almost all the countries with the exception of Kazakhstan. So we hope to receive data from this country also on the next dispatch that is planned in a couple of weeks actually. So it's expecting very soon. This is the situation for the fertilizer questionnaires. So the fertilizer is linked to the 241 with the team number six. So sub-indicator management of fertilizers. Here we have a couple of countries that didn't send any data in the last three years. In this case, they are Afghanistan and Indonesia. Pesticide linked to the team seven, which is the sub-indicator management of pesticide. This is clearly the question where we lack mostly the data. We can see a lot of N, which means that we didn't receive any formation from many countries and for mostly all the years, the last three years. The production is probably the opposite. So they always more filled the questionnaire. Indeed, many data seem available for the team one, team one, which is the farm output value predictor and the team three, which is the risk mitigation mechanism. For this questionnaires, the next dispatch is planned for May, 2021. Finally, the price is questionnaires is linked again as the production questionnaire to the team one productivity and team three resilience. Pakistan here didn't provide any data in the last three years. So concluding, when we dispatch the two for one questionnaires and you need to respond on the 11 sub-indicators, please remember that the relevant national statistics already reported to FAO because you will probably find many formation on top is that relevant already today SDG for one. As Canada explained us yesterday very well, some of the national statistics could be used for an initial proxy reporting. So this proxy approach can be used while capacities to collect and analyze more detailed farm level data improve over time in your country. And that's of course, the reporting on the two for one indicator. Finally, leveraging on existing expertise can be used as a basis to strengthen national statistics processes and plan, of course, improvements to national surveys and census process. So that was a very quick overview of the FAO stat. And so the reporting tools to FAO. We move immediately to this presentation that as far as Pandeir is showing you now on the short, medium, and long-term expectations. So I give you the floor, Pandeir. Can you hear me now? Yes, now, yes. Okay, perfect. So thank you very much, Stefania, once again. So just to recollect as to what we have covered over the past three days. So we discussed the conceptual and methodological basis for SDG 241. We discussed and thoroughly showed you its data collection instruments, tools, and the background documents, as well as mechanism for reporting it to FAO. Now this presentation will cover the progress made by FAO until so far, our planned future course of action and expectation in terms of country's readiness to report on the indicator in the short, medium, and long-term. Our ultimate aim obviously is to maximize country reporting on the indicator amongst the 21 others and thereby gradually classify it as tier one over time. Tier one means that majority of the countries are reporting on the indicator to FAO. In summary, we will as part of this presentation we will cover the following aspects, the methodological front, capacity development undertaken and envisioned, activities on the data collection side, already undertaken and the one planned for the rest of the year and next year. And the reporting of the indicator to FAO. Towards the end of the presentation, we will openly discuss the issues and constraints that impede countries implementation, data collection and reporting efforts and deliberate the means and ways on how to overcome these constraints and challenges. So by now you may have a very good idea that the methodology of 241 is based on a farm survey that is used as a main data collection instrument for all the sub indicators. Reaching at this stage where the methodology is approved now has been a long participatory process that involve discussion with experts both from countries like yourself and as well as experts from international organizations, private sectors, academia, et cetera. And several round of tests and follow-up technical work on the development of the support documents. So the methodology as I mentioned to you earlier in my previous presentation was approved and endorsed by IAEG STG November 2018. There were a few other areas which the IAEG STG wanted us to improve on. So in this respect, we constituted this informal group of countries which I explained with respect to the biodiversity sub indicator yesterday. And then we worked the entire 2019 with the selected group to refine the criteria of the biodiversity indicator. And in November 2019, once again, the group re-approved and re-endorsed the refinements that we proposed. So in total, for the development of the methodology, we organized three expert group meetings. We presented it regularly at the Scientific Advisory Committee of Global Strategy to improve agriculture and rural statistics. We carried out an online global consultation where at one stage the methodology was shared with the national statistical offices of all the member states of all the countries across the globe for their comments. And thereafter, we conducted several webinars with the IAEG STG members on the refinements for biodiversity sub indicator. Now I mentioned that we tested the different aspects of the methodology thoroughly. So we conducted desk tests in Bangladesh, Kyrgyz Republic, Ecuador, Belgium, and Rwanda. These were carried out back in 2016 and 2017. We carried out cognitive tests in Kenya, Mexico, and Bangladesh for the survey questionnaire that I showed you a little while ago. We field tested the survey questionnaire in Bangladesh in 2018 that I showed you as well as while we were covering the respective sub indicator. I was showing some examples of the Bangladesh data. So that was that. Then we tested the FAO data collection questionnaire which Stefania showed you yesterday in 45 countries and she showed you the findings as well in terms of response rate and in terms of other aspects and findings of this testing. Now, all the background documents have been finalized and uploaded to the FAO STG portal which I showed you a little while ago. That is the methodological notes, survey questionnaire, sample design, enumerated manual calculation procedure or analysis guidance, et cetera. On the capacity development front, we have trained more than 50 plus countries on the indicators methodology already. The methodology of 241, as we were progressing on developing it, was presented at African Commission on Agriculture Statistics in 2017, FAO Committee on Agriculture in 2018 and in 2019, then it was presented at Brussels Briefing organized by the European Commission in 2019 and International Conference on Agriculture Statistics in India in 2019. Of course, we conducted some bilateral trainings as well whereby we went to the respective country to train their staff on the STG 241 methodology exclusively. In this respect, in 2019, I went to Bangladesh, Vietnam and Oman to basically train their national staff on the indicator. There was a training organized for 10 African countries in collaboration with UNICA and Ethiopian Ministry of Agriculture in 2019 and the following countries participated in that training which included Ethiopia, Ghana, Kenya, Namibia, Nigeria, Rwanda, South Africa, Zanya, Uganda and Zambia. Then we trained 17 countries from Asia and North Africa in 2019. That included Algeria, Egypt, Jordan, Lebanon, Mauritania, Morocco and so on. Then last year as well, we conducted another training which was organized for Asia and Pacific region which happened in Japan, Chiba last year whereby many of the country's participants who are gracing us with their presence now were represented in that training. Just to exemplify Nepal, Indonesia, Vietnam, Pakistan, all these countries were there as part of this training. In 2020, apart from the first batch of the virtual trainings that we are having now whereby we are training you guys including Afghanistan, Indonesia, Kazakhstan, Nepal and Pakistan and Vietnam, we have two other lined up for the second and third batch. One is happening from 22nd to 24th of September primarily for Latin American countries as well as Russia. Then another round scheduled in October from 14 to 16 which will primarily include countries from Middle East and Africa. In terms of additional trainings, additional capacity development efforts, I spoke about it. We have developed the e-learning courses. We have translated the key documents into Arabic, Spanish and French which may not be relevant to most of you. But then again I mean because of the coverage of the SDG indicator because it's applicable to all countries across the globe. At least we wanted to cover the Arabic, Spanish and French-speaking countries. Of course we will translate into Russian and Chinese as well. We also took advantage of other in-house colleagues while they were taking missions for their own work to countries to raise awareness about SDG-241 and to confirm information on the national focal points and to assess national data availability on the indicator. In 2021, we will continue to arrange and organize virtual trainings for the rest of the world given the COVID-19 crisis because of which traditional travel arrangements are no longer possible. So from this perspective, it seems like the virtual training can serve some purpose. Provided if the situation in 2021 is improved, then we will also definitely look into organizing in-person bilateral training based on requests from the countries. These trainings will not only involve the methodological and conceptual details that we discussed during this training but to really sit with the countries open their agriculture questionnaires and their sampling documents and really, you know, roll our sleeves up and try to integrate the questions from the survey module of 241 into the country agriculture statistical system for them to be able to collect information on 241. Of course, as I mentioned earlier, we have plans to translate all the documents including the e-learning material into all official U.N. languages. And we are also planning on developing digital lectures on SCG 241 which will be available hopefully by second or third quarter of 2021. On the data collection front, that's our data collection questionnaire and reporting protocols have already been developed and put in place. In 2020, as Stefania covered in detail from December 2019 to April 2020, we carried out the testing of the FAO data collection questionnaire on 241. We tested in 45 countries. We received a very thorough feedback, a very valuable one based on which we adjusted the questionnaire and it gives us very useful insights in terms of the data availability at the country level. In August of this year, we sent a comprehensive global dispatch. By that I mean to say we send the FAO data collection questionnaire to all member states. If I'm not mistaken, we send it to 213 countries. Stefania, correct me if I'm wrong. And then from September to November our idea is that once we start receiving the information from countries on the questionnaire, we start the analysis, gap filling quality assurance and quality control processes whereby we may again come back to you regarding the data that you have reported using that questionnaire. In December 2020, our idea is to draft analysis and finalize it for reporting to United Nations statistical division. That is a process that we have for all the 11 indicators. Once we receive data from the member states, we estimate the regional and global aggregates and we develop storylines and then share it with UNSD. Of course, this year reporting on 241 will be conditional as to whether we receive sufficient data from countries to prepare the storylines and of course the global and regional aggregates and trends that I just spoke about. For 2021 data collection cycle we have the following recurrent activities planned. I mean from January to July of course we will be busy in preparation of and then we will send a dispatch to countries as planned in July or August and then from July and November again the same process which I spoke about so we will do analysis gap filling quality assurance and quality control and then by December 2021 we will report it to UNSD. Now again referring to the presentation from yesterday the low response to 2019 as 241 pilot questionnaire were both expected and indicative showing in general the complexity of the indicators methodology. It's not an easy indicator. There are 11 subindicators as part of the framework and thus the lake of sufficient and relevant data required to report on the indicator. And thus in the very short term that is 2021 we expect that several countries if not many will only be able to report on the partial dashboard for 241 based on the current farm survey level data approach. So we don't expect you to report on all the 11 subindicators of 241 for us a very good start would be if you start reporting on the subindicator on which data already exists it could be one it could be two it could be three it could be like you know the indicators can be spread in different dimensions or it could only be from the economic dimension doesn't matter at least we have to start somewhere in terms of in terms of reporting the data on 241. So if you come back to us with only one or two or three subindicators or any subset of the subindicators of 241 that is just fine for us we would from this we will know that where the problems are with some indicator the country is still struggling to report data on and then we can engage with you more intensively on how to bridge the data gaps for the rest of the 11 subindicators on which data is available. Now as highlighted yesterday in the medium to long term, however, in addition to existing farm survey based methodology we have initiated and embarked on a work program to explore the possibility of developing a solution based on alternative data sources. Of course the solution will be for selected subindicators where the combination and complementarity with farm survey will facilitate countries reporting on SDG 241. We will we will cover this point in more detail in the upcoming slide particularly on the alternative data sources. In parallel our outreach and capacity development activities will continue of course in close coordination with aggressive program and 50 by 2030 as well. So we will continue to work on this initiative that was presented briefly by our colleague Flavio Bolliger yesterday and and we also are reaching out to potential external partners to support us, you know, basically implement the detailed farm level data as highlighted yesterday and this slide is more of you know taken from yesterday presentation but it's very good to have this for it to be shown again. The methodological note of SDG 241 once you thoroughly you know read through it discusses the possibility of using a combination of different data sources as an alternative option for reporting on 241 if the country wishes to do so. So some of the alternative data sources apart from agriculture surveys that have been proposed by countries is administrative records crops and livestock census environmental monitoring systems such as sampling soil sampling laboratory testing etc geographical information system or remote sensing or earth observation household surveys and other dipstick studies or specialized studies that have been conducted by the countries in order to investigate certain aspects you know which are listed here. Now the methodological note do propose these alternative data sources but it doesn't go into the details of how can countries utilize this so I will cover that part in my next slide. Though we are proposing alternative data sources there are several challenges that are associated with this option because the sources vary widely both within and across countries due to different objectives of the alternative data sources different scale of assessment you know for 241 the scale of assessment is farm level for these other sources the scale of assessment may be agro-ecological zone or distrate or tassel or you know maybe some other level the scope may be different because the scope of 241 is crops and livestock and a mix of both these production systems for these other data sources the scope may only be you know crops or maybe a sub-sector within crop focusing primarily on certain crops that are important for the country or maybe these studies are focused only on farm level stocks and plus you know they may imply different definitions and different terminologies apart from that the second challenge is temporal resolutions of these different alternative data sources so maybe a study was conducted back in 2015 or maybe 2010 and was not repeated afterwards periodically and hence it could you know basically complicate the reporting processes because then it will involve interpolation and extrapolations and using growth rates etc. and coefficients so it's not that straightforward excuse me and plus the periodicity of the data sets may vary as well in terms of like say for example the recommended periodicity for 241 is is three years in some countries the agriculture or livestock senses the periodicity is five years or maybe ten years or you know for some other surveys these are ad hoc survey which were conducted one time and they are not going to be repeated so how to address those issues of periodicity in terms of the data sets sampling issues again it's closely related with the alternative data sources you know the sources may have a sample which has different designs different sizes there may be under or non-coverage issues of agriculture holding particularly this may be the case if we decide on using labour force survey to report on decent employment or wage rate in agriculture but then the question would be as to whether agriculture households are properly covered in those surveys for us to say something about the situation on that particular sub indicator for agriculture holdings there could be different unit of measurement of course the unit of measurement in case of 241 is form survey and we are interested we administer this question to the agriculture holding and then we relate that to the agriculture area of the holding so in these other studies or in other surveys or other sources of information the unit of measurement may be different and hence how do we relate that information to the agriculture land area of the country may pose a challenge then of course the issue with adjusting and harmonizing different baselines across different countries for the same source or different baselines for the different sources within the same country so how do we adjust those differences and how do we set baselines that again is another issue and plus on top of this integrating data from different data sources is usually complicated due to lack of efficient coordination mechanisms for inter and intra institutional coordination so usually what we see at the country level is that NSO is the basically NSO and Minister of Agriculture are the two are important agencies at the country level who are responsible for generation of and then basically use of the data one is collected for policy making however given the wide variety of teams and sub indicators that we capture as part of 241 there may be other institution involved they may have the requisite data and hence this coordination mechanism needs to be and the level of challenge now given these challenges that I just described several aspects we carefully considered prior to using alternative data sources in order to produce consistent and reliable data and set the thresholds as per recommended periodicity of the indicator so we cannot say that basically we have information available in our alternative data sources and it rests with certain institution but then that information may be basically may not be sufficient to basically construct the indicator and then set the threshold for us to assign the sustainability criteria and then basically assign proportion so before using alternative data sources it is advised that the use of these sources may be considered when the available data set fulfill the following criteria first and foremost it should be demonstrated that the alternative data sources give at least the same result and quality as the farm surveys can be reflected in or attributed to agriculture land area in the country considering the different farm typologies and agriculture regions this is a very key point because if you even if you have alternative data available in some institution how do you link that with the agriculture area of the country which is the basis for assigning sustainability status to agriculture in a country furthermore the fact that it can be associated with agriculture production systems particularly crops and livestock and the combination in between so the problem is that there may be studies or focus only on crops or another focus only on livestock so how do you integrate that information and what about the holdings which are in a way specialized in both these production systems the alternative data sources should capture at the same aspect and phenomena as proposed in the farm survey as described in the indicators meta data sheets plus it should be made sure that these are representative of the situation at the national level with respect to agriculture land area taking into account the major agriculture regions and crops and livestock so it could very well be the case that a particular source of information existing source of information is collected only for a certain region of the country and not for the entire country so in that case how do you generalize that information to a national level then the fact that data needs to be available at the same level of territorial as proposed in the farm survey and data collection here and periodicity or homogeneous across the sub indicators I mean this is at least recommended even if it is not homogeneous we can still live with it by you highlighting that you know information on the XYZ sub indicator is available for for air X or a Y but then again if it is homogeneous across all the sub indicator then that would be excellent finally using alternative data sources implies that mechanisms should be put in place at the country level to coordinate regularly the flow of required information generated by by various various institutions and of course lastly that the alternative data source needs to become compliant with or adhere to international and national standards and classification systems in order to ensure the indicator to be internationally comparable otherwise if every country is using a source of information which is not consistent in terms of standards and classification then the sole purpose of us comparing countries internationally is because of the fact that we you know we are not going to be comparing apples to apples and oranges to oranges so on top of this you know as as was evident in Canada presentation yesterday alternative data sources can certainly be used to complement farm data information that was a very excellent presentation which gave us very good insight as to how developed countries are going about using alternative data sources in combination with farm survey so anyway the countries can replace you know using alternative data sources they can replace the farm survey questions with alternative data sources of information once available and respond to the criteria that I just mentioned these can also be used to complement farm survey data sources this can also be used to complement farm survey questions by providing additional contextual information that is helpful to probe the right answers from the respondent as I was mentioning yesterday this can be done or during the data collection by providing contextual information to the numerator before going to the field to identify any inconsistencies and to ensure its robustness this exposed information can be used to triangulate and validate survey data after the data collection analysis has been completed as I just highlighted so we will soon kickstart work on developing practical guidance on how alternative data sources can be used by the countries for sg241 measurement and monitoring there is a first step that we have already undertaken between October and December we will work on exploring the potential use of earth observation that is remote sensing for reporting on selected indicators of 241 we have also a plan to expand this effort in January and March 2021 to include other data sources that I just showed you on the previous slide like administrative records household service monitoring systems etc for reporting on selected sub indicators and during the same period with the help of of course international experts we will draft a proposal and test protocols and select countries for testing the approach develop using the alternative data sources and from April to June we will test and analyze the proposed approach by collecting information on using both the farm survey and earth observation approach and then triangulate the results to see as to whether it makes sense and then from July to August we will we will work on drafting the guidelines on how and how these sources can be used to report on on sg241 the guidelines will be finalized hopefully by December 2021 and you know we will then disseminate it to countries by publishing not only on our website but reaching out to the focal points of sg241 that we usually do at different intervals and we will share it with them so with this I will stop my presentation through the next two slides these are summarizing the next steps so again let me highlight that we have shared with you the stop taking excel sheet I am referring to it again and again because this is really the key so what we would like you to do is to basically fill it in and this will not only help you but as well as us to assess the data gaps with the sg241 requirements then you know the second point is that we have sent you know Stefania mentioned and I have been mentioning time and again we have sent you the file data collection questionnaire in August last month we would like you to respond to that I mean once you fill in the stop taking exercise filling in you know the data collection question is not going to be a big problem it is not going to be a big problem because of the fact that you will have all the data reflected here we have given you all the methodology that you need to know about 241 which we explained to you over the course of three days for you to fill in this questionnaire then you know an important step for you guys and this is what we expect from you maybe like say for example Stefania for step 3 and step 1 both let us give them some time tomorrow they are not going to be able to report on this okay so let us aim for the end of the next week okay or maybe if you want to keep it more flexible than today is the 10th let us aim for the 20th of of September for them to give us feedback on point 1 and point 3 so point 3 is basically about what we have been discussing this is part of the questions that we raised so these questions which I showed you on the previous slide we would urge you we would request you to encapsulate to cover these in a three page action plan two to three page action plan it can be more pages provided if you want to give more details for implementation and reporting on 241 so again I mean isolate and identify the constraints that inhibit reporting on the entire dashboard okay which was again from the question and what actions do you believe you will take and by when for the countries to be able to collect data on 241 and report it to FRO again to answer these questions you know maybe two three paragraphs along with a table whereby you enlist the actions that you need to take you plug in some kind of time frame as to when you will be able to undertake those action and complete those actions and then you know you have a responsibility column whereby you say that you know this is the support that we need from FRO and these are the tasks that we are going to carry out on our own now so this is your task this is what we expect from you and for future information as an outcome of this training this action plan will be crucial for us for us to understand as to how do we structure our work plan for the next year for us the next steps would be we will send you all the final presentations that got presented once again because there were some trivial changes in the presentation as we were progressing I mean, Stefania has had provided you with all the links, I showed you all the resources where you can find it on the FAO SDG portal. So we will do that. We will send you a summary report of this training, you know, highlighting the basic aspect that we covered, the discussion points that you raised and possible next steps that we showed you, you know, on this slide, the action plan and the stock taking exercise and responding to the FAO data collection questionnaire. And then as I mentioned to you, we will plan activity based on the action plans and stock taking exercise submitted by yourself. So that this is really the key. This is really the key. So please don't take it as a training whereby, you know, it happened and, you know, it's another thing that I took care of. And, you know, so we need to carry forward this process. We will continue to support you in this process because this is the very first step. It's not the end, but it's the means to an end. So we have to go a long way before you can start reporting on sustainable agriculture. Of course, the ultimate aim is not for you to report two for one, but the ultimate aim is to use the information that will help you report on two for one for national policymaking because that's what matters. So we really want to address the core issues of poverty, hunger, malnutrition, that is the objective of the ultimate aim and objective of FAO. And this indicator will help us, you know, take care of those issues. So the ultimate goal remember is not reporting on the indicator, but the ultimate goal is to improve policies and decisions at the country level for you to improve the food and agriculture situation of the countries and address the hunger, malnutrition, and poverty related issues at the country level. With this, I thank you. I mean, thank you very much for your time, for your interaction, for your very rich discussion. It was very nice to have this meeting with you guys. And yeah, I mean, if, Stefania? Yes, so we will share also this recording, of course, so you can see again all the trainings in case you need it.