Silo Fighters Blog

Crowdsourcing the campfire: how our data visualization contest opened doors

BY Abigail Taylor-Jones | November 14, 2018

“Visualizations act as a campfire around which we gather to tell stories.” - Al Shalloway, founder and CEO of Net Objectives. Telling our story well is key to ensuring we can influence policy and other key decision-making processes. In order to do so, it is important to get new insights from the evidence we generate from the data we collect. To give a sense of the scale, we collect data from 130 UN Country Teams, serving 165 countries. The types of data we collect ranges from operational data, socio-economic data, financial data, data on coordination and results. Sitting behind the walls of the UN can sometimes be lonely ploughing through all this data (other times it is quite daunting). So, we have to think of creative ways to gather new insights to tell a good and compelling story. The UN is known as an organization that brings people together globally to participate in various ways, for example working towards realizing the goals set for 2030 Agenda. For us, being open and inclusive about the UN’s work is always at the forefront of our minds, even when it comes to data. We started thinking about ways to include others from outside the UN in our analysis and data visualization process. As the Secretariat to the UN Sustainable Development Group (UNSDG) we have access to a wide range of data, so we thought, why not launch our first ever UNSDG data visualization contest and find out what others can see in our data? So, my colleague Kana Kudo and I did just that. In collaboration with Tableau, we launched the contest and invited data scientists and anyone interested in data visualization to use our data from the UNSDG portal, which pulls UN specific data, published by several agencies, using the International Aid Transparency Initiative (IATI) standards to report how the UN is contributing to the global development agenda. Data is powerful but we don’t always know how to tell a story with it After launching the contest, we realized there were blind spots that we failed to see. For example, some of the submissions did make use of the IATI data sets, while others did not. The guidelines we provided were clear, however the research questions were a little unclear. We ended up receiving several stunning visualizations, but they were not exactly what we were looking for. We learned that when it comes to data, it’s best to be specific. Another learning was that data scientists wanted the option to work with other data visualization tools and not be limited to Tableau; so we had to broaden the scope of tools for the contest. We brought a selection panel together to assess the submissions, and we selected two winners. The first winner crafted “Visualizing Malaria: The Killer Disease Killing Africa,” an impactful visualization that analyses malaria deaths in the world, how they have changed, and how funding has evolved over the years, particularly in Africa. The contestant explained that she had been inspired by the experience of a dear friend who had been infected with malaria. We also liked this visualization on malaria because it focused on both the positive and negative aspects of the fight against this diseases. Whilst lives are been saved through the use of mosquito nets, there’s also a downward trend in other aspects, which means more still needs to be done. [caption id="attachment_10399" align="alignnone" width="542"] Visualization by Rosebud Anwuri[/caption] The second data visualization titled “Leave no one Behind”, included the UN’s spending on each Sustainable Development Goal (SDG) per country, looking at the financial distribution among the SDGs. The underlying calculations were just as impressive as the visualization itself! We liked this visual and we were interested in how the participant highlighted the leaving no one behind aspect, which is the central promise of the 2030 Agenda; and an overarching programming principle. Looking at how we are doing from a financial expenditure perspective is key to assessing the UN’s contribution to the SDGs. Behind the scenes, our team in Headquarters was tinkering with developing UN Info, a tool that integrates the UN contributions to the SDGs and the 2030 Agenda. This is an important aspect because it keeps us accountable and helps UN Country Teams with programme management. From this contest, it was clear to us that data is obviously powerful but we don’t always know how to tell a story out of it. We were very impressed with the contestants’ interpretations and the visualizations. As a bonus, we also gained unexpected and useful insights that helped us refine our UN IATI data set.   [caption id="attachment_10400" align="alignnone" width="570"] Visualization by Pedro Fontoura[/caption] One of the things that we also discovered, is that data scientists like to get involved. Chloe Tseng, founder of Viz for Social Good contacted us to find out how she could collaborate with us. Although she didn’t participate in the contest, we were keen to work with Chloe and her team of volunteers just as she was to work with us. Goal 17 of the SDGs relates to partnerships and we know how important it is work with others to realize our goals. We gave Viz for Social Good a particular set of data related to the partnerships that the Country Teams have beyond the UN. If you haven’t read Viz for Social Good’s journey working with us, and the beautiful visualizations that came out of our partnership, check it out here. Our data was too fat! The contest was a great learning opportunity for us. From our collaboration with Chloe and the Viz For Social Good network of over 2000 data visualization experts, we learned that our data is good but we need to look at ways of improving the way data is parsed through our systems and ensure that it is formatted in a manageable and easy way for data scientists to work with it. Chloe also gave us feedback on moving from larger chunks of data to smaller chunks. We took these recommendations very seriously and have made significant changes in our data systems for optimum use by data scientists. We trimmed down our data in smaller chunks that requires little time for data cleaning which allows for quicker analysis. This experience was definitely an eye opener in terms of telling a more powerful and compelling story than we will ever be able to do if we stick to large sets of data in an excel format. The campfire is still with us Collaborating with Viz For Social Good and with the contest participants inspired our team to adapt our digital strategy work.  Seeing the way these artists take data and communicate with it opened our eyes. Our taste has changed and boy have our standards gotten higher. We are designing dashboards for future projects and seeing the artistry has upped our game for the long run.   Photo: Wenni Zhou

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Mining alternative data: What national health insurance data reveals about diabetes in the Maldives

BY Yuko Oaku | November 7, 2018

An island nation consisting of 1,190 small islands, the Maldives is clustered around 26 ring-like atolls spread across 90,000 square kilometers. For many centuries, the Maldivian economy was entirely based on fishing. Tuna is one of the essential ingredients in the traditional dishes of the archipelago. But between 1980 and 2013, the GDP per capita increased from $275 to $6,666 due to the success of the high-end tourism sector. With the rapid economic growth and a wave of globalization, there have also been changes in the dietary preferences and lifestyles of Maldivians. A staggering 30 percent of the Maldivians are overweight due to unhealthy diets and lack of physical activity, according to data from the Global Health Observatory.   Consuming sugary beverages is also a big problem among Maldivian youth and young adults. According to a study by the World Health Organization, in 2015, 4.7 million litres of energy drinks were imported to the Maldives, which is a very high volume for such a small population (around 410,000 people live in the Maldives). These unhealthy habits are drivers for the increase in non-communicable diseases, such as cardiovascular, cerebrovascular and hypertensive disease.  These diseases are the main causes of death among Maldivians. According to the National Health Statistics from 2014, diabetes is ranked as the ninth overall cause of death in the Maldives. [caption id="attachment_10393" align="alignnone" width="450"] "Drinking energy drinks is not cool" Health Protection Agency Maldives[/caption] Analyzing the prevalence of Type II diabetes with Insurance Data All Maldivian nationals are covered under the Government’s universal health insurance plan called “Aasandha”. Since it began its services in 2012, the plan gives full coverage to all health services from most health care providers and up to a certain amount for some of the private health care providers. The plan also covers care in affiliated hospitals in neighboring India and Sri Lanka in case the treatment is not available in the Maldives. Aasandha data provides personal data records and insurance data for all Maldivians. Since the usual data source for non-communicable diseases is the Demographic and Health Surveys, which is carried out every 6 years (most recently in 2015 and before that in 2009), we thought we could get more up-to-date data on diabetes if we looked directly at the health insurance data. Our team assumed that analyzing this data would serve as proxy indicators for the SDG indicators 3.8.1: Coverage of essential health services. Initially, this indicator was labeled as Tier 3 indicator, meaning that no internationally established methodology or standards were yet available for the indicator. As of 11 May 2018, however, 3.8.1 has been upgraded to Tier 2 indicator, which means that the indicator is conceptually clear, has an internationally established methodology and standards are available, but data are not regularly produced by countries. Our idea was to have an anonymized look at the data from the universal health insurance plan to see what else we could learn about non-communicable diseases. We at the UN Country Team in the Maldives, UNDP and WHO, partnered with the Maldives National University (MNU) research team and with the National Social Protection Agency (NSPA), the custodian of Aasandha service in the Maldives. What we found out about Type II diabetes in the Maldives: We dug into the anonymized health care records for 2016, including information about: 1) what diseases the Aasandha coverage is used for 2) the cost 3) where the medical procedures take place Together with the research team, we decided to focus on Type II diabetes for the scope of this study. We found some interesting facts about the prevalence of Type II diabetes in the Maldives: More than 3 out of every 5 people who have diabetes are women. The mean age of patients with Type II diabetes is 57, while the youngest age is 13. Females get diagnosed with Type II diabetes at a younger age compared to men and there is a relationship with gestational diabetes. Of those seeking care, 79 percent of the people go to private health care providers, whereas only 21 percent seek services from public health care providers. We also discovered that the Aasandha data was also incomplete. For instance, there were missing records from some of the largest regional hospitals in most populated atolls in the country. This may suggest that data from government hospitals are not entered into the system because patients don’t need to make a claim for the payment, whereas in private hospitals, the data is needed to allow patients to make a claim for their payment. It could be that more people are using public health care providers, but since the data is not entered into the Aasandha system,this information is unavailable to us. [caption id="attachment_10395" align="alignnone" width="393"] WHO Maldives[/caption] Next frontiers in proof of concept for alternative data With this pilot study we found some interesting facts about the prevalence of Type II diabetes in the Maldives as well as some possible data gaps in the Aasandha insurance data. We will be sharing our findings and challenges of using Aasandha data with the members of the UN Country Team as well as relevant ministries and agencies, including the Ministry of Health and the National Social Protection Agency. Reflecting on this pilot study, we will continue to support the country to explore alternative sources of data that will enable us to track more SDG indicators in the Maldives. According to an internal assessment done on data availability for all SDG indicators by the National Bureau of Statistics, there’s currently no mechanism for data generation for 56 indicators and for another 51 indicators, additional efforts will be required to make the data available. With all this data missing, we’ll need to tap into additional resources to make the data available because if we don’t know where the Maldives stands on Sustainable Development indicators, it’ll be hard to plan to achieve them. There is definitely a need for new data sources and having this data gap in mind, we have another pilot project in the works that’s going to use call detail records data to track population mobility to the urban centers of Male. Stay tuned for more in our work mining alternative data sources for the Maldives!

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Untangling the complexity of the Sustainable Development Goals in Moldova

BY Ana Moraru, Valeriu Prohnitchi | November 1, 2018

The Sustainable Development Goals (SDGs) are a beautiful vision for a better world, where people have equal access to food, health, public services, education, equal rights and pay. It’s a world where oceans and air are clean, fish are happy, and forests are preserved. Comprehensive? Certainly. Complex? Beyond any doubt. No matter how you want to see it, the stakes for achieving the SDGs are high. The clock is ticking. How are governments going to make the SDGs happen in the next 12 years? How do policy makers translate these goals into real outcomes for people? Look at things differently: think systems At first glance, it might be tempting to eat the elephant one bite at a time. The standard approach for analysis is to decompose phenomena into manageable pieces, which can be easier to grasp. The puzzle is then solved when all the pieces are put together. With this approach, the whole equals to the sum of the parts. However, this is not the optimal strategy in complex systems, where a standard approach would only encourage silo-based and piecemeal solutions. In complex systems, the uncoordinated actions of actors would result in suboptimal outcomes for the whole systems. Let’s take Goal 1: No Poverty, for example. How do we expect to achieve Goal 1 without touching upon Goal 3: Good Health and Well-Being or Goal 4: Quality Education? At the UN in Moldova, we looked at the Global Goals from a different lens, that of multiple causes, effects, feedback loops, and actors. With such an approach, the whole may equal more than the sum of all parts.  Our hypothesis was this: by uncovering the fundamental causal loops and relations among the SDG targets, we can help the government and the UN in Moldova identify the “leverage points” – policy priority areas. In turn, this will help us to make progress over multiple goals at once, and prioritize policy actions and investments of scarce resources in the short, medium, and long term. In our last blog post, we shared our experiences working with the government in ‘Glocalizing’ the Sustainable Goals in Moldova. After that exercise, we supported the Republic of Moldova to update the national strategic planning framework to encompass the SDGs. During the early stages of the strategy development, the apple of discord happened to be a persistent one: among of the many development challenges, how should the government decide which ones to prioritize? Once again, the systems analysis perspective came in handy. If we look at SDG targets from the perspective of systems dynamics, we can analyze the connections and the causal and feedback loops among them. Some targets will even prove to be more connected than others; progress on these targets would most likely generate a multiplier effect. We like to call these “SDGs accelerators”, or “leverage points”. If we attained progress on these accelerators, then we would help the country progress on the Global Goals as a whole. This was our theory of change. It takes a village to raise a child (or a country) One of the criticisms of the national strategic planning policies is that these don’t reflect the needs of the people and vulnerable groups. This time, as we say in Moldova, we tried to avoid stepping on the same rake twice. We convened different players, including representatives of ministries, MPs, governmental agencies, civil society organizations, including representatives of vulnerable groups, academia, donors, and development agencies. This process helped us to reach a common vision and understanding that helped us set the priorities for the actual National Development Strategy. The systems thinking approach was helpful, yet again. What we did to untangle the SDGs To untangle and analyze the SDGs, we used the stock-and-flow and causal links diagrams, an approach from the field of System Dynamics developed at MIT. Within this analytical framework, a stock of some elements varies due to inflows increasing the stock and outflows diminishing it. What does this mean exactly? Let’s take Goal 3: Good Health and Well-being (see Figure 1). The rectangle “Healthy People” denotes a stock variable. In systems dynamics, stock variables represent variables that accumulate or that can be depleted. To better understand how it works, imagine a bathtub.  The inflow from the “Wellness Rate” increases the stock of “Healthy People”, while the outflow of “Disease Rate” or “Accidental Death Rate“ will decrease the stock because more healthy people will get sick due to diseases or die of accidents over time. Arrows represent a primary or secondary causal direction moving from a cause to an effect. Figure 1. SDG3: stock-and-flow causal loop diagram Source: Moldova SDGs system map. The solid lines conventionally denote that the cause and effect move in the same direction holding all else constant; e.g. an increase in the “3.8 Universal Healthcare Coverage” will cause an increase in the “Treatment Rate”. A dashed line denotes the cause and effect moving in the opposite directions, e.g. an increase in 3.3 Communicable Disease Reduction will decrease the Disease Rate. In the SDGs complexity mapping, the first major decision was where to begin. In our case, we started with the SDG1: No Poverty, for which we have conducted a prima facie analysis of the immediate causal links (Figure 2). The central stock we are trying increase is “People with Good Quality of Life”. People move from the stocks of “People in Extreme Poverty” to “People in Poverty” and then to “People with Good Quality of Life”, following the flows of 1.1 Extreme Poverty Eradication Rate and 1.2 Poverty Elimination & Quality of Life Improvement Rate. We then add a new layer of analysis, by incorporating the SDG2: Zero Hunger. The target 2.4 “Resilient Agricultural Practices” shifts the “Vulnerable Food Production” towards “Resilient Agriculture Food Production”. Further on, an increase in “Resilient Agriculture Food Production” will help raise 2.3 “Agricultural Productivity & Incomes of Small-scale Food Producers”, which in turn increases 10.1 “Income Growth of Bottom 40 percent”. Therefore, the resilient agriculture looks like an important poverty reduction strategy and achieving SDG 2: Zero Hunger helps achieving SDG 1: No Poverty having SDG 10: Reduced Inequalities as intermediary. Layer after layer, we arrive at a densely packed map revealing the most essential mutual influences among the Moldovan SDGs targets and related policies. From this comprehensive exercise, we narrowed down the common vision for Moldova in 2030 to three main poles: People with a good quality of life, with decreased emigration and progressive values, have to be put at the centre of the development vision – i.e. development should be for the people rather than by the people. Effective, accountable and inclusive institutions able to put an end to corruption are essential for unleashing the potential existing in the wider society. Sustainable production and sustainable industrialization is the most promising economic model enabling a decisive and lasting reduction in poverty and in providing equal opportunities for all to achieve high standards of living. We found some answers and have more questions Overall, systems analysis proved to be a great method for looking at the big picture. It helped identify the most connected elements which served as a basis for defining the development vision for the National Development Strategy Moldova 2030 and for prioritizing key areas of intervention. As such, we made the first step towards understanding the causal links between SDG targets. However, what we couldn’t see is how these links reproduce over time. The next step in this analysis would be to check how these links change over time, allowing us to understand the dynamics of the system. Similarly, we would want to see the strength of the links to understand the magnitude of influence. This would represent a highly ambitious exercise, requiring a different time-frame and more solid data. Are you trying using a similar approach to untangle the Sustainable Development Goals? Share with us!

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TONSE – From Zambia to the Google Play Store

BY Matts Weurlander | October 24, 2018

This is the story of a creative and ambitious collaboration, led by the UN in Zambia, that brought together a non-conventional Finnish software company, a Lusaka-based coding school, an up-and-coming Zambian media company, and young minds from all over Zambia to come up with an application to engage young people in the promotion of the Global Goals. Tonse is a mobile application, which allows anyone to easily create and join community projects and become active participants in sustainable development. We can proudly say that Tonse was born and made in Zambia and is now ready for worldwide testing on the Google Play Store. When brainstorming spins in empty circles, let  go and let the young people design it We started this project with the idea of using a digital scorecard to track progress on SDG  indicators related to youth (for example, education, employment and income). The team quickly realized that while this seemed like a fine idea on paper, it would be problematic to implement, partly due to the slow pace by which SDG indicator data is generated in Zambia, and partly due to the technical and rather boring nature of indicators. A mobile application needs new data by the minute to stay interesting.  Not every year, or every four years, like data for national SDG indicators.  Could we develop an application that would serve our overall objective of giving young people a voice in sustainable development, but at the same time be fun, simple and interactive? What would it be? What would it look like? What would it do? Our internal brainstorming sessions were taking us nowhere. Our discussions, though well-intentioned and lit up by occasional buzz words, spun in empty circles. We were like square-shaped objects aspiring to become something round and fluid-like, but not knowing how. It was, to be honest, frustrating. Our team decided to leave the content part to the intended users: we would invite networks of young people to workshops and they would tell us what to do. Meanwhile, we turned our attention to the “how” part of things. None of us in the UN team working on young people’s rights and development knew how to code. On top of that, software developers are a rare breed in Lusaka and the few quotations that we received from commercial companies far exceeded our budget. We were in a double bind: we didn’t know what to do, and we didn’t know who could do it. Pro bono partnerships to the rescue Things started to look brighter after we contacted Vincit Ltd., a Finnish software company. We had been in touch with the company a year ago to discuss pro bono opportunities and this project seemed to be the perfect match! Vincit brands itself as “not another software company”, which was exactly the kind of spirit we wanted to embrace. We were both surprised and excited when, towards mid-October, Vincit confirmed that an experienced full-stack software developer would collaborate with us for two months, the first month in Lusaka to get the project rolling. We had found our project manager, and he was both world class and affordable. Amidst our excitement, we discovered that the developer from Vincit was not enough. We would also need local partners to ensure that the look and feel of the application would appeal to the Zambian market and to ensure sustainability. This is how we found Hackers Guild and Oemph Media, who quickly grasped what we wanted to do (although we had yet no clue about this ourselves) and were ready to jump on board. Hackers Guild is a technology organization that provides training on software development to young people, as well as product development and consultancy services. They put together a team of young developers who implemented the application in collaboration with the Vincit developer. For the look and feel, we discovered Oemph Media, a small media and marketing company founded by Zambian young talent Catherine Fundafunda. Oemph Media’s role in the partnership was to be provide the visual concept and user experience/user interface design and development of the marketing strategy. From ‘Tinder for Good’ to…. Tonse The software developer from Helsinki arrived in Lusaka in the beginning of November. After a round of introductory meetings with our UN team, we threw the happy Finnish developer straight into a series of workshops with young people. Through the UN Youth Partnership Platform, which brings together 23 young people from all over Zambia, we convened a diverse mix of young women and men to brainstorm about possible application concepts. Organised at the youth hub Global Platform, the half-day workshops aimed to bring out ideas, thoughts and suggestions – the crazier, the better – on how a mobile application could increase young people’s participation in sustainable development. Through group exercises and discussions, a total of 51 participants helped us to identify the obstacles that hinder young people’s participation and how these could be overcome with the help of a mobile application. We encouraged the young people to design applications that they would like to use, without consideration as to what is possible. While the emerging list of ideas was long, the common message was clear: the new application should inspire action, strengthen social accountability, and be rooted in real-life experiences. The focus should not be on learning the SDGs (i.e. reciting the goals from 1 to 17), but on living the SDGs. In short, the app should be practice, not theory; action, not words. Workshop participants are all smiles after brainstorming around application concepts. After the brainstorming workshops, the core team, led by Vincit software developer Sten Karlson, analysed all the ideas and suggestions and distilled these to three separate application concepts, called “SDG Dinner Challenge”, “Self-improvement app” and “Tinder for Good”. They presented these concepts to the project steering group in the form of simple, but working applications simulated on a mobile phone and wireframes. The aim was to let the audience grasp the concepts intuitively, without lengthy explanations. The steering group agreed to pursue with the “Tinder for Good” concept, which eventually acquired the Zambian name “Tonse”. Tonse means “all of us” or “everyone” in Nyanja. The name was born at the first workshops, and it stood the test of time, receiving strong positive feedback from test users. Sten Karlson, Vincit, and Catherine Fundafunda, Oemph Media, design wireframes for presentation to steering group. Tonse is about inspiring people to take action on issues that matter to them and to get others involved in improving local communities. Thus, the core concept is a direct enabler for Agenda 2030 and the SDGs. The basic idea is simple: Tonse provides a platform where anyone can effortlessly launch, browse and join community initiatives. As in the popular dating application “Tinder”, the user sets his or her preferred radius and the application then shows only initiatives that fall within that radius. If you are, for example, keen to see initiatives within walking distance from your house, you can set the radius at, say, 5km. As in Tinder, the initiatives appear as cards, with a picture and a brief description, and the user then swipes right if interested and left if not interested. The beauty of the concept lies in the interplay between local and global: while facilitating local action, the application itself can work anywhere in the world. Coke Zero, Skype and Fast Food to make it happen Once the concept was chosen, it was implementation at full throttle. At this stage, the Vincit developer was wrapping up his one-month stay in Lusaka. We used that time to set up practices and systems that would allow Vincit, Hackers Guild and Oemph Media to work as a team despite the roughly 14,000km distance between Helsinki and Lusaka. During the next couple of months, we were constantly having  Skype meetings, long WhatsApp calls, and new cards on the ever-expanding Trello board. In March of this year, the developer from Vincit returned to Lusaka for a two-week polish sprint. We pushed code for long hours and worked together solving problems with the Hackers Guild team, fuelled by Coke Zero and fast food, the preferred diet of any software developer, Zambian and Finnish alike. At the end of the two weeks, we shared the first working demo of Tonse with a diverse test group consisting primarily of young people of different affiliations, but also of UN colleagues across agencies. We received overwhelmingly positive feedback and this encouraged us to continue with the development of the application and implementation of further features. Check us out on the Google Play Store The Tonse application is now available on Google Play Store, for users with Android phones. The UN Youth Group continues the collaboration with Hackers Guild, with the aim to launch the application in Lusaka through social media campaigns on 5 December 2018. Vincit remains involved as part of the project advisory board. Before the launch, the UN country team is planning outreach activities to existing organisations. While it has taken a long time to reach this stage, the team is conscious that much work still lies ahead – a thousand technical bugs await to be fixed and tens of strategic decisions to be taken. The Tonse story is just starting – download the app, send us your feedback and stay tuned for more updates.

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Natural Language Processing to align national plans in Serbia with Global Goals

BY Karla Robin Hershey, Dennis Schleppi, Vuk Batanović | October 17, 2018

The Republic of Serbia is on a mission to map the work that is underway to implement the 17 Sustainable Development Goals (SDGs). As a first step, the UN Country Team in Serbia reviewed the compliance of the country’s policy framework with the 169 targets and 230 indicators of the 17 SDGs and assessed the country’s readiness to proceed with their implementation. The fact that Serbia is a candidate country for the accession to the EU, the Republic of Serbia called for a special review of the compliance and complementarities between 35 EU accession negotiation chapters that are implemented through a series of ongoing reform processes and linkages to Agenda 2030. We conducted a real time comprehensive analysis in late 2017 to early 2018 using UNDP’s developed methodology called RIA – Rapid Integrated Assessment (RIA). The objective of the assessment tool is to support countries in mainstreaming the SDGs into national and subnational planning, by helping assess their readiness for SDG implementation. We engaged a dozen of national experts who successfully reviewed over 100 of national policy documents, including those setting the targets relevant for the EU accession. Most of the documents were in Serbian, with a few available in English. The exercise outlined those areas that are well covered with the existing policy instruments, identifies areas where more attention is needed by policy makers, detects bottlenecks and accelerators and reviews institutional capacities in place to implement the SDGs. Scaling up and gaining efficiency with artificial intelligence We know it is important work, so we were on the lookout for innovative ways to make this process and other similar policy mapping exercises easier and more efficient. In January 2018, we heard about a pilot initiative between UNDP and IBM research which demonstrated that an artificial intelligence (AI) approach could be time saving and provide accurate mapping information. Using AI based on natural language processing (NLP) techniques could be successful in automating the rapid integrated assessment process that provides a baseline to measure future progress. The assessment, which looks at defining a roadmap for a country to implement the SDGs, was our starting point. They piloted the assessment in five countries where policy documents were available in English. We got satisfactory results from the pilot. We teamed up with local policy experts from the SeConS Development Initiative Group, an independent organization which aims at contributing to the long-term socio-economic development and improving the living conditions of individuals and social groups in Serbia and the region. Our team at the UN also met with natural language processing experts from the School of Electrical Engineering at the University of Belgrade to take this initial pilot to the next level – and research how the assessments could be translated from English into another language, thus for the first time facilitating an automated mapping of policy documents in Serbian. The development of the methodology and testing of the automated policy mapping exercise in Serbia is being implemented between August and November 2018. Talking to a computer in Serbian is not as easy as Siri makes it look Thanks to an abundance of language tools, resources, and algorithmic NLP models available in English, the initial pilot allowed for an automation in countries where English is the predominant language for official documents. In the attempt to translate the automated text processing to Serbian, our team noticed several linguistic traits that make this work particularly challenging: Unlike English, Serbian changes in form according to grammatical functions such as tense, mood, number and gender. Serbian is a fully digraph language, meaning that it can be written using two different alphabets (Serbian Latin and Serbian Cyrillic script). Latin characters often appear in Cyrillic texts, especially where foreign terms (usually from one of the European languages) are presented verbatim. Although Serbian grammar often uses the same default Subject-Verb-Object word order as English, the very nature of the language makes word ordering more flexible. In addition to the language-related challenges mentioned above, we also identified the following specific context related advantages: The automated policy mapping will focus on specific sectors – social protection, health, education. In this area we have adequate data both in quality and in quantity. Given the specific focus of the automated analysis, we will be able not only to compare automated versus manual policy mapping results, but also to get a more specific idea of the data gaps in the social, health and education sectors, which is very important for localizing Agenda 2030 in Serbia. By closing sectoral data gaps for nationalization process for the global goals, the pilot project in Serbia will also create a baseline to support the country’s SDG reporting obligations. This is particularly relevant given that Serbia will provide its first voluntary national review at the High-Level Political Forum in New York in 2019 on its SDG progress to date. The voluntary national reviews aim to facilitate the sharing of experiences, including successes, challenges and lessons learned, with a view to accelerating the implementation of the 2030 Agenda. These reviews also seek to strengthen policies and institutions of governments and to mobilize multi-stakeholder support and partnerships for the implementation of the SDGs. The Republic of Serbia will present the results produced by the automated mapping on achievements in the area of reducing inequalities in the country. Getting started, getting technical Our first step was to choose a sample of the 17 SDGs to be analyzed, limiting the dataset. Taking into consideration the quality and format of data available, and keeping in mind that next year’s voluntary national review discussion will focus on inequality, the team selected five SDGs that are clustered under the heading People, including: SDG 1: No Poverty: end poverty in all its forms everywhere SDG 2: Zero Hunger SDG 3: Good Health and Well Being: ensure healthy lives and promote well-being for all at all ages SDG 4: Quality Education SDG 5: Gender Equality: achieve gender equality and empower all women and girls. The second step was to consolidate the document database previously used in the manual assessment process to ensure that documents were available in a machine-readable format. This presented our team with a significant technical problem, since most documents were available in PDF format, which is not great for precise text extraction. Initial tests indicate that a combination of Adobe Acrobat Pro’s text extraction mechanism and a replacement procedure through which particularly problematic PDF files would be replaced with an easier to read alternative (e.g. Word files) could prove to be successful in tackling this problem. The months ahead We expect a number of technical innovations to surface from the process of adapting the proposed AI approach to texts in Serbian. The complexity of texts in Serbian will be decreased through the use of stemmers, tools that reduce each word to its stem (a stem is similar to a word’s root form). Such tools have been found to increase natural language processing model performance on several semantic tasks in Serbian, so there is good reason to believe these tools may be effective with the similar, albeit more complex, rapid integrated assessment exercise. Our initial efforts show that flexible word ordering is not likely to be a major issue in terms of transferring the (English-centric) automated pilot exercise to Serbian, since the AI method focuses on sentence or paragraph-level semantics, where the exact word ordering becomes less important. Finally, we will work around the lack of available data from the manually-conducted rapid integrated assessment in Serbian by setting up a simulation, dividing the available Serbian document collection into two groups: a training set and test set. By conducting a manual rapid integrated assessment for the training set, a foundation will be established for the automated assessment for the test set in Serbian. After these technical and algorithmic adaptations have been completed, the School of Electrical Engineering at the University of Belgrade and SeConS will measure the effectiveness of the AI method using the data from the manual exercise conducted in Serbia earlier this year and will submit a report showing the comparison between the two report, more importantly we be looking to see if the accuracy of the AI driven report the same or superior to the manually produced rapid integrated assessment report.   Despite all of the linguistic and technical challenges, this project could prove to be beneficial for data collection and analysis processes not only in Serbia, but also for neighboring countries, due to close linguistic ties within the sub-region. We will discuss the results of this pilot exercise extensively with data holders, producers and users, including the Government and civil society partners, to obtain their valuable input to inform the way forward. The UN Country Team will use the additional feedback to see if and how this automated policy data search could be used to save time and improve the accuracy of data analysis. Lessons learned will be applied to other activities in Serbia aimed at supporting Government efforts toward fulfilling their priorities towards Agenda 2030 in Serbia. The questions that we hope to answer  in the follow up consultations include: Can we use automated policy mapping for other processes beyond the initial SDG data mapping? How can we use it to map the progress towards SDG achievement and its linkages to the EU Acquis? Whatever the answers to these questions may be, we will keep you updated. Watch this space and follow our progress on social media.     Photo by: Nathaniel Shuman

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Innovation scaling: It’s not replication. It’s seeing in 3D

BY Gina Lucarelli | September 12, 2018

My brother is a mathematician and on family vacations, he talks about data in multi-dimensions. (Commence eyes-glazing over). But as the family genius, he’s probably on to something. Lately, in my own world where I try to scale innovation in the UN to advance sustainable development, I am also thinking in 3D, or, if properly caffeinated,  multi-dimensionally. As new methods, instruments, actors, mutants and data are starting to transform how the UN advances sustainable development, the engaged manager asks: when and how will this scale?  To scale, we need to know what we are aiming for.  This blog explores the idea that innovation scaling is more about connecting experiments than the pursuit of homogeneous replications. Moving on from industrial models of scaling innovation In the social sector, the scaling question makes us nervous because the image of scaling is often a one dimensional, industrial one: let’s replicate the use of this technology, tool or method in a different place and that means we’ve scaled. This gives us social development people pause not only because we can’t ever fully replicate [anything] across multiple moving  elements across economic, social and culture. Even if we could replicate, it would dooms us to measuring scaling by counting the repeated application of one innovation in many places.   Thankfully, people like Gord Tulloch have given us a thoughtful scaling series that questions the idea that scaling social innovation is about replicating single big ideas many times over. [Hint: he says scaling innovation in the public sector is less about copy-pasting big ideas and more about legitimizing and cultivating many “small” solutions and focusing on transforming cultures.]  Apolitical’s spotlight series on scaling social impact includes a related insightful conclusion: when looking at Bangladesh’s Graduation Approach as one of the few proven ways out of poverty, they suggest that while the personalized solutions work best, they might be replicable, but too bespoke to scale. So if scaling ≠ only replication, how do we strategize for scale? I’ve got a proposal:  what if we frame the innovation scaling question more about doing deep than broad? The scaling question becomes: How will we move from distinct prototypes managed by different teams at the frontier of our work to a coherent, connected use of emergent  experiments in programme operations? Scaling also means moving from fringe to core Scaling innovation in a large organization like the UN has a glorious serendipity to it. Did you hear that we are looking into impact bonds in Armenia? What about the food security predictor in Indonesia? Nice collective intelligence approach in Lesotho. Blockchain is being used for cash transfers in Pakistan and Jordan. Check out the foresight in Mauritius. UNICEF is using Machine learning to track rights enshrined in constitutions. UNHCR is using it to predict migration in Somalia. UNDP is testing out social impact bonds for road safety in Montenegro. These organic innovations are beautiful and varied and keep us learning, but we as a UN system are not yet scaling in 3D. These days, I’ve been talking to people (my brother’s eyes glaze over at this point) about how to see various methods of innovations not as distinct categories of experiments, but rather as connected elements of an emergent way of doing development. Towards a connected kind of 3D.  Yes innovation is more of an evolving set of disruptions than a fixed taxonomy of new methods, but if we narrow our scope for a moment to the subset of innovations which have passed the proof of concept stage, can we start thinking seriously about how they connect? [As an important side note, thinking in terms of taxonomies of innovations is not a panacea. Check out @gquagiotto’s slides for a more thorough story on how classification is trouble for public sector innovation because it means we limit our vision and don’t see unexpected futures where they are already among us.] Projectizing innovation without keeping an eye on the links among the new stuff won’t get us far, and might even be counter-productive.  Instead, what would it be like if innovations were deployed in an integrated way? A bit like Armenia’s SDG innovation lab where behavioral insights, innovative finance, crowd-sourced solutions and predictive analytics [among others] are seen as a package deal.  I am looking for collaborators to learn more about how are all these methods and tools related. Do they help or hinder each other? Are there lessons that can be learned from one area and applied to others? Should some new tech and methods not be combined with others? 9 elements of next practices in development work A few of us UN experimenters came together in Beirut in July to pool what we know on this.  We had a pretty awesome team of mentors and UN innovators from 22 countries. We framed our reflections around the 9 elements of innovation which I see as approaching critical mass in the field. This is by no means exhaustive, but it’s a start to moving these methods from fringe tests led by various teams to core, connected operations. Here are the “nine elements of next practice UN” we are working with: Tapping into ethnography, citizen science and amped up participation for collective intelligence to increase the accuracy, creativity, responsiveness and accountability of investments for sustainable development. Using art, data, technology, science fiction and participatory foresight methods to overcome short-termism and make sustainable futures tangible. Complementing household survey methods with real time data and predictive analytics to see emerging risks and opportunities and design programmes and policies based on preparedness and prevention. Building on the utility of “superman dashboards”  for decision makers to helping real people use their own data for empowerment, entrepreneurship and accountability. Leveraging finance beyond ODA and public budgets by finding ways to attract private capital to sustainable development. Evolving the way we do things and even what services we offer by managing operations through new technologies Applying psychology and neuroscience for behavioral insights to question assumptions, design better campaigns and programmes and to generate evidence of impact when it comes to people’s behavior. Carving out space for science and technology partnerships within the UN’s sustainable development work Improving how we support our national partners in managing privacy and ethical risks Moving from “that’s cool” to “aha it’s all connected” We need to start thinking of these 9 elements as connected. It might be that they reinforce each other - whereby focusing on data empowerment gives meaning, context and legitimacy to the use of big data to understand behaviors and online activity. Or that they undermine each other - in the way that citizen science can undermine innovative finance pay-outs, or behavioral insights are helping companies get around privacy regulations. Looking for the practical connections, here’s what we’ve got so far: Collective intelligence methods that listen to people organically can help determine whether your behavioral campaigns are resonating.  Because people’s intell is often more granular than statistics, they could also be used to test whether new forms of finance are making an impact on health, education and other development issues. Small scale and/or internal experiments in the UN to manage operations with new technology help us know what the next generation privacy and ethics risks are. Experiments in gray zones can then inform future-oriented regulatory frameworks. Keeping a focus on helping people use data for empowerment is a good northstar when using new data and predictive analytics to ensure that cultivating realtime sources of data isn’t deepening the digital or data privacy divide. Using foresight methods or predictive analytics can point to signals of where to invest with innovative finance instruments [Follow Ramya from IFRC innovations for more on this. Hence some early connections form a budding conspiracy theory! If you are thinking multi-dimensionally too, or using a few of these methods and see where this line of thinking can be improved, help me draw more lines on the innovation conspiracy board! [Or tell me why this is the wrong tree to be barking towards… That’s always helpful too.]   We’re working on a playbook to codify what we know so far in terms of principles and methods for each of these 9 elements. Stay tuned for that... and please do get in touch to throw your own knowledge in!

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Promise to data: What the SDGs mean for persons with disability in China

BY Marielza Oliveira, Elin Bergman | August 29, 2018

China has strong and capable statistical systems, no surprises there. After all, China is known for its ambitious Five-Year Plans, which have shifted focus from economic growth to policy planning, environmental protection, and social programmes for its population of 1.4 billion. What's different and unique about its 13th Five-Year Plan is that it's very much aligned with the 2030 Agenda for Sustainable Development. Even so, China faces a daunting challenge to implement Agenda 2030. For starters, it only has official data for less than 30 percent of the Sustainable Development Goals (SDGs) indicators, and much less when considering data that covers vulnerable groups, such as persons with disabilities. With more than 85 million, China has the largest population with disabilities in the world. The good news is that China keeps a record of people with disability, so the official data sources are up-to-date. To support the Chinese government’s efforts to improve monitoring of the SDGs addressing people with disabilities, we at UNFPA, UNESCO, UNRCO, UN Women and WHO came together to test innovative approaches to collect focused and disaggregated data. Starting in Qinghai We selected the Qinghai Province in Northwest China as the pilot location to test new ways of collecting data. In Qinghai, the estimated number of persons with disability is five percent of the total population, of which about 70 percent live in rural areas. There are about 150,000 people registered in Qinghai Disabled Persons’ Federation, the local chapter of China Disabled Persons’ Federation. Therefore, it was important for us to look at their administrative data, which are key for crosslinking data from various sectors, including public services data. To demonstrate how data collection in underdeveloped regions can be operationalized in a smart way, we collected, analyzed and crosslinked all the administrative data of people with a disability ID with the following big data sources: Data from the national survey of basic services and needs for people with disabilities which is developed and updated by China Disabled Persons’ Federation, the National Bureau of Statistics and local Disabled Persons’ Federations; Data from the public services and various sectors including health, education, employment, social security, poverty alleviation and community services. This type of data is gathered from crosslinking disability ID data with public services data. Data from internet-based platforms. It's possible to use big data to integrate and crosslink all data from the disability ID system, administrative data of disability services from China Disabled Persons’ Federation and the administrative data of public services. By expanding the existing official data with information from other sources, China has the potential to not only monitor the additional SDG indicators, but it can also compile additional disaggregated views of SDG progress to monitor specific groups and locations in need of support while strengthening “real-time” monitoring and analytics. During this process, we engaged the vulnerable groups in the analysis and interpretation of data. For us, knowing what people living with disabilities think and need is key. We carefully examined their views to highlight the SDGs indicators that could directly benefit their well-being. The hindrances of data collection We experienced a few setbacks throughout the process, but, we adopted coping mechanisms to address the issue of data collection and analysis: Quality control of data. The disability data available from different sectors uses very different standards and follows different collection approaches. Moving forward, we propose to check and purify the data using standard disability datasets and a data crosslink approach. We also optimized the timeliness and the mechanisms to update the data. Sharing data among sectors. The key index of disability and people with disabilities was determined using the disability ID. The data across sectors was crosslinked with key index such as disability ID and others. What we discovered The administrative data platform of people with disability was recently updated with the results from the annual survey of unmet needs and services for people with disabilities nationwide. This platform provides timely data for monitoring SDGs that address people with disabilities. Other sectors have developed big data platforms using citizens’ ID. To continue enhancing the administrative data records, it's important to collaborate with other stakeholders, such as health care and educational departments to extend the existing data sources. Household surveys can also be used to fill in the gaps of official disability statistics. We shared our discoveries with an expert panel, which included representatives from the Chinese government, the National Bureau of Statistics, China Disabled Persons' Federation and its Qinghai branch, Qinghai Department of Commerce, Institute of Rehabilitation Information/WHO Family International Classifications Collaborating Center China, China Disability Data Research Institute, Soochow University, Nanjing Special Education Teachers College, UN agencies, as well as Chinese IT giants What's next The methodology implemented in Qinghai province can easily be extended to other vulnerable groups since they also face similar challenges. Stakeholders can also adopt similar tactics to develop specific SDG indicators, data collection and analysis to evaluate their progress. As for next steps, the UN country team will continue to research protocols and methods to monitor disability-inclusive SDGs. We will also develop a knowledge platform in Chinese to promote capacity building for the implementation of Agenda 2030 and conduct an international comparative study of technical approaches of data collection and analysis. Data and internet-based surveys will also be developed to learn more about the needs of people with disabilities and improve services for them, while at the same time using those statistics to make sure that we leave no one behind. What methods are you disaggregate the SDGs to ensure data for action with people living with disabilities? If you have some tips, do tell! Photography: Jonathan Kos-Read. License by Creative Commons

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What Can Ship Identification Systems Tell Us About Development Policy?

BY Pulse Lab Jakarta | August 9, 2018

Maritime transportation is the life force of the world’s economy. Between 1990 and 2013 worldwide maritime trade more than doubled, with total volumes in 2013 reaching nearly 9.6 billion tons. The UN Country Team in Indonesia and Universitas Gadjah Mada have teamed up to analyze port network evolution across Indonesia. The dataset is global so if a similar analysis is of interest to other UN Country Teams please get in touch. Automatic Identification System (AIS) Data The global marine vessel identification system, called AIS, is an automatic tracking system used on ships and by vessel traffic services to improve safety at sea. The International Maritime Organization requires AIS to be fitted aboard international voyaging ships with 300 or more gross tonnage, and all passenger ships regardless of size. Alongside its practical application to maritime safety, AIS is useful for research on a variety of topics, from studying rescue patterns of migrants and refugees to understanding risk factors to marine ecosystems from shipping. Based on a request from the Ministry of Development Planning in Indonesia and an initial analysis of port network connectivity using AIS data, conducted by a team of inter-disciplinary researchers at a Research Dive hosted by UN Global Pulse Lab Jakarta, we plan to conduct further analysis using the dataset with a view to informing maritime development policy. Indonesia Port Network Analysis As an archipelagic state, the Government of Indonesia envisions a greater role for the country as a global maritime axis and is working to achieve this through several maritime development plans, including Tol Laut. To understand better the opportunities and challenges connected to this ambition, over the coming months we will: Model and analyze the maritime network based on AIS data; Create summary statistics of ports in Indonesia, including the number of ships processed by ports, average waiting times at ports and shipping times between ports; and Predict how the maritime network in Indonesia will evolve given specific scenarios, including with and without Tol Laut. Beyond this, we have a few ideas to look at network resilience to storms and cyber attacks (with MIT) and risk factors to marine ecosystems from shipping. If any of the above is of interest to other UN Country Teams, please get in touch as the AIS dataset is global so the analysis can be expanded relatively easily.

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Powering up data collection systems in Palestine

BY Subhra Bhattacharjee | July 11, 2018

In 2016 we prepared a Common Country Analysis (CCA) for Palestine. A CCA is UN speak for a detailed analysis of a country in preparation for a multi-year action plan of the UN. It identifies key development challenges and where the UN needs to focus its development investments. For our analysis this time, we decided to look at people. In hindsight it appears to be the obvious thing to do, but we were not the first to think of this. The Nepal UN Country Team did it before us. For our CCA we asked ourselves two questions: Who are the most vulnerable groups in Palestine? What are the structural drivers of their vulnerability? We thought if we could identify the most vulnerable groups and analyze the structural drivers of their chronic vulnerability, we will have a good sense of what it will take to ensure that our sustainable development investments leave no one behind. The first call for ideas brought out 61 proposed groups, each backed by passionate arguments as to why they are the most vulnerable. We merged some groups, reduced duplications, clarified categories, tinkered with definitions, and after extensive discussions, honed our focus to 20 vulnerable groups. This gave us a window to the factors that keep some groups in Palestine systematically at a disadvantage. Next, we did a deep-dive to understand why development was leaving some groups behind. For some groups, including out-of-school children and children in the labour market, the lack of adequate data makes it difficult for government to formulate specific policies and programmes for these groups. Alternative data collection methods for groups that are small compared to the population After a comprehensive exercise to account for the data, especially looking at Sustainable Development Goals indicators, we noted that relevant data on smaller groups couldn’t be collected only through existing surveys. The Palestinian Central Bureau of Statistics (PCBS) uses representative samples for each geographical area of the occupied Palestinian territory (oPt), and even though it produces high quality data consistent with international standards, there is a lack of up-to-date and periodic disaggregated data on several smaller groups. Take for example, the fishermen of Gaza. There are some 4,000 registered fishermen in Gaza, accounting for 0.2 percent of Gaza’s population of two million. If PCBS samples 1,000 people from Gaza for one of its quarterly labour force surveys, it will have at most two fishermen in its sample. We cannot draw any reliable conclusions about the socio-economic conditions of fishermen in Gaza from a sample of two people. And if PCBS included more fishermen in their sample, the percentage of fishermen in the sample will be larger than the percentage of fishermen in Gaza’s population. To create a large enough sub-sample for fisherfolk, PCBS will need to do a new level of sub-sampling by profession or sector on top of the two layers it is already subsampling. This would significantly increase its cost of surveys. Are you still tracking with us? Keep reading.   Flash surveys to the rescue So, for the smaller groups, we at the UN looked for an approach to gather data that would not cost too much, would not create too much additional work and most importantly, that is able to produce good quality data. The first thing we tried is a series of flash surveys – with small samples, and short questionnaires. These flash surveys had several benefits over the more traditional surveys with bigger samples and longer questionnaires: They allowed us to test our systems for collecting primary data and iterate quickly and cheaply if necessary to work out the flaws in the system. They enabled our enumerators to get hands-on training at a relatively low cost to us. They are also particularly suitable for understanding the smaller groups that don’t get adequately represented in the bigger surveys. We chose four vulnerable groups: adolescent girls, children in labour, the elderly and persons with disabilities as pilot cases. UNFPA took the lead in this. They engaged the Sharek Youth Forum, a non-profit, and one of UNFPA’s implementing partners to conduct the surveys. OHCHR, FAO, UNRWA, helped with the quality control. 37 university students (28 from the West Bank and 9 from Gaza) were recruited from Sharek’s network and trained as enumerators by an expert. The survey questionnaires in Arabic were uploaded on KoBoToolbox, a free and open source suite of tools for collecting data. Many of the young enumerators owned smartphones so they downloaded the app on their phones and entered the data for each person they surveyed into their smartphones. Sharek provided the others with tablets. A village, a town and a refugee camp were selected in each governorate. Sharek’s enumerators visited schools to survey adolescent girls, reached out to the elderly in their local communities, and found persons with disabilities through support groups. ILO provided information on the areas with high concentration of child labour. The enumerators collected the data over a period of two weeks, and, in some cases, they used paper forms to collect the data and documented problems as they arose. The enumerators collected data on a small number of key demographic variables for each group. For the data on the four groups produced by Viz for Social Good, click here, here, here, and here. Before even looking at the data, we noted a few things. First, we now have 37 trained enumerators who can be deployed again at short notice to conduct other flash surveys. The investment in training and the hands-on experience they got has started the process of creating systems to collect data on vulnerable groups. Second, we need to finesse our sample selection if we want to use the surveys to provide baseline indicators and monitor progress. Third, we need to think through how to combine the data from smartphones and paper surveys. Fourth, we need to figure out how to identify our target groups based on more rigorous definitions. For instance, not all work done by children should be classified as child labour. According to ILO, child labour refers to work that “deprives children of their childhood, their potential and their dignity, and that is harmful to physical and mental development”. Fifth, flash surveys need more quality control if they are to serve the same purpose as traditional surveys. This is because with smaller samples of flash surveys, the choice of location will need extra attention to ensure that the sample is indeed representative. This year, we will work through these wrinkles. Engaging people in their own data analysis In data circles, we often hear the idea of engaging communities to collect and use their own data. But the instances of it being done in a meaningful, low cost, sustainable way to generate usable data are few and far between. Could we pull it off? We decided to experiment with combining data collection and empowerment for one of the most vulnerable groups in the oPt, namely, Area C communities. Area C accounts for 60 percent of the West Bank. It has some of the most fertile agricultural land and almost the entirety of Palestine’s natural resources. An estimated 300,000 Palestinians live in Area C and a greater number depend on its resources for their livelihoods. Area C is controlled by the Israeli military,  which has exclusive control over land, planning and construction. Significant portions of Area C land are allocated for Israeli settlements and declared as Israeli state land. Only about 30 percent of Area C is available for Palestinian construction, but so far Palestinians have been issued permits to build on less than one percent of the land. Since construction permits in Area C are closely tied to Israeli spatial plans, spatial plans driven by Palestinian communities have been used in recent times to empower communities, and to rally the Israeli Civil Administration to issue permits to Palestinians for construction. In addition to Israeli military orders, land ownership in Area C is governed by a complex legal framework resulting in insecurity of land tenure and confusion about ownership and user rights of private land. Consequently, land registration has been a long-time priority of local and international development actors in the oPt. As the next activity of our project, we integrated a community-driven process to map land ownership and user rights. UN-Habitat took the lead in developing a system called the Social Tenure Domain Model. This participatory tool is a pro-poor, gender responsive system based on free and open source software, which means that all the data collected and stored is available to the communities and owned by the users. The system is based on information and evidence shared by local communities making them a part of the decision-making process. The system records and analyzes the social tenure relationship of people and land, and the social services/amenities that available to the inhabitants of a location. It fits the oPt’s highly complex tenure system, because it supports a continuum of land rights ranging from formal to informal. An Arabic interface was created for the system so it can easily be deployed in other Arabic-speaking countries. UN-Habitat also provided training for the Palestinian Land and Water Settlement Commission staff. This system for community mapping of land rights with a special focus on women and youth will help us empower the community, build social cohesion, and generate data on land rights. The resulting database will serve as a shadow land register, support land valuation, raise awareness about land governance in Area C, and inform advocacy efforts to defend land rights of Palestinian communities. These efforts are supported by the ‘Road Map for Reforming Palestinian Land Sector’ of 2017. Right now, the background work is still ongoing. The model will be piloted in 2019. Will this actually work? We don’t know. For now, we know that we now have the systems in place to replicate or update the data collection of smaller groups through flash surveys, we can engage communities participate in collecting and analysing their own data and integrate a community-driven process to identify land ownership and user rights, at a lower cost than in the first run. And we will use whatever we learn from these initiatives to finesse our methods in our next set of data collection initiatives in 2018.

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Making money move: New financing to achieve the SDGs

BY Richard Bailey | July 3, 2018

“Money doesn’t grow on trees.” Regardless of where you grew up, we all learn about the importance of securing every penny, rand, real, euro, yen, ruble, or rupee. And the saying is particularly relevant today since development organizations like the United Nations (UN) must mobilize more than US$3.0 trillion every year if we hope to achieve the ambitious goals laid out in the 2030 Agenda for Sustainable Development. Official development assistance (ODA) is still an important finance mechanism but only $140 billion are secured each year. If we, the UN, intend to accelerate progress so no one is left behind, ODA needs to be used more strategically, and other sources of finance must be secured. There also needs to be an organizational shift from strictly funding programmes and initiatives to an approach that involves “funding and financing” to tap into international, national, private and public financial flows. Perspective shift: from funding to financing A growing number of blended finance sources have helped advance development aims in recent years.[1] Private sector guarantees, syndicated loans, and shares in collective investment vehicles mobilized $36.4 billion,[2] while socially responsible investing exceeded $6 trillion between 2012 and 2014. Impact investors and development finance institutions created a new investing asset class that is projected to grow to $400 billion by 2025. When it comes to financing, the rules are changing, and the UN is looking at new ways of aligning financial flows and attracting new investors. UN Country Teams (UNCTs) in Kenya, Indonesia and Armenia explored ways of helping national governments and local partners secure broad, non-traditional funds for development purposes. They mapped out challenges, unlocked new types of financing and used resources in a timely and innovative manner. The three most successful tools adopted were impact investing, Islamic financing, and sector-specific fund modalities. Impact investing in Armenia In the last few years, Armenia has turned into a thriving tech start-up hub and financing initiatives have followed two major trends: venture philanthropy and impact investing. To capitalize on these new forms of funding, the UNCT set up a country platform for SDG implementation that is aligned with national reform and SDG efforts. The collaborative space allows the UN, development partners and civil society to strengthen relationships and develop new ones with international financial institutions, donors and philanthropists. Other innovations: SDG Innovation Lab, the Kolba Social Innovation Lab, ImpactAim Venture Accelerator. Islamic financing in Indonesia Home to the world’s largest Muslim population and the tenth largest economy, the Government of Indonesia recently turned to inclusive and ‘green’ financing to accelerate the SDGs. The UNCT saw the potential and embraced new forms of finance to support sustainable development initiatives. Good practices include employing blended finance instruments and Islamic financing (Baznas).[3] In 2017, UNDP channelled zakat (charitable funds) for a micro-hydro energy project to improve access to water, renewable energy and livelihoods in some of the most remote parts of Indonesia. Other innovations: Financing Lab, “Bring Water for Life” and #TimeforTigers crowdfunding campaigns. Primary health care financing in Kenya One million people in Kenya fall into poverty every year because of a fractured health care system,[4] which is why the national government prioritized rolling out Universal Health Care in the “Big 4 Action Plan.” The UNCT supports the government by working with private sector partners on the Private Sector Health Partnership Kenya initiative and SDG Philanthropy Platform. Bringing together the private and public sectors together has opened doors to new cross-sectoral opportunities in the health, tech, early childhood development, nutrition, and technical and vocational training sectors. Make it rain: harnessing the potential of innovative financing The cost of solving the world’s most critical problems currently runs into the trillions, forcing development financing into a new era. There are no other options if traditional development aid no longer makes the grade. The UN has to pivot and embrace the changes taking place or risk becoming redundant and irrelevant. Luckily there are many opportunities to seize, and the UN has plenty of comparative advantages to bring to the table. The organization has a long, successful history of bringing together partners, training and recruiting experts, scaling up projects, and imparting technical knowledge. UN staff are skilled in advising, brokering knowledge, innovating, analysing data, and measuring impact. As we have seen in Kenya, Armenia and Indonesia, capital can be mobilized through impact investing, attracting early investors, or securing funds for larger investments in sectors identified by the central government. Embracing the latest tech innovations (e.g. e-health or mobile diagnostics) can turn unattractive investment areas into “bankable propositions.” Perhaps the most important takeaway is to not “let perfection be the enemy of the good.” Change may take time but UNCTs can’t wait for everything to be in place before embarking on new initiatives or adopting innovative types of financing. Steps to secure the right kind of capital have to be taken because time is running and “business as usual” no longer works—the numbers tell the whole story. Societal progress involves taking calculated risks, and achieving the SDGs is no exception. Unlocking new sources of funding is one way the UN can make sustainable gains and help governments make returns on the 2030 Agenda. ---- [1] Discussed in detail in “Financing the UN Development System. Pathways to Reposition for Agenda 2030” (September 2017), Dag Hammarskjöld Foundation in collaboration with the MPTF Office, http://www.daghammarskjold.se/wp-content/uploads/2017/09/Financing-Report-2017_Interactive.pdf. [2] Amounts Mobilised from the Private Sector by Official Development Finance Interventions: Guarantees, syndicated loans and shares in collective investment vehicles’, OECD working paper, 2016. [3] Baznas was established by the government based on Presidential Decree 8/2011. The agency is responsible for collecting and distributing zakat at the national level. [4] Thomson Reuters Foundation, February 2018, http://news.trust.org/item/20180209112650-s1njv/.

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Caring is Sharing: Towards Gender Equality Care Services in FYR Macedonia

BY Louisa Vinton | June 22, 2018

Sustainable Development Goal number 5 recognizes the need to achieve gender equality and the empowerment of all women and girls by 2030. As the UN Country Team in the former Yugoslav Republic of Macedonia, we have been wrestling with this topic and are working tirelessly to help national partners achieve the Global Goals, which have come with a series of challenges. Care or Construction to drive the economy? Our UN team in the former Yugoslav Republic of Macedonia has been advocating for two potential solutions to the existing inequalities regarding the burden of unpaid care work. The first proposed solution is to promote an expansion in state-funded social care services, such as care for preschool children, the elderly, and people living with disabilities. An increase in care services should be seen as an investment that stimulates growth and creates new and better jobs primarily taken by women. For us at the UN, this is a very attractive equation, because doing the right thing is also the economically sound thing to do. It also provides a refreshing contrast to an entrenched belief in the former Yugoslav Republic of Macedonia that investing in construction work is the best way to use public funds to create jobs. Debunking myths about the care economy To prove this point, we did some data digging. Research conducted by UNDP and UN Women in Turkey helped us build a case on the importance of investing in social care infrastructure versus construction infrastructure. According to their research, social care investments could generate 2.5 times more jobs than investments in construction. So, imagine this: instead of a mere 290,000 jobs in construction, the same amount of government spending could yield 719,000 jobs in care services. And 73 percent of these new caregiving jobs would go to women, against just 6 percent of those in construction. Alongside this first powerful idea, we are trying to combat the stereotype that house chores are handled only by women. This conviction runs deep in the former Yugoslav Republic of Macedonia, and men are let off the hook when in fact they could proactively step it up and share the burden of house work. To gain traction for these arguments, we made the idea of “care economy” the centerpiece of a high-profile UN-sponsored conference in June 2017. At the event, the new Prime Minister, Zoran Zaev gave a speech where he emphasized the importance of greater inclusion of women in the labor market and encouraged men to share more responsibilities at home. This high-level affirmation put wind in our sails, and the new Government has engaged with us energetically! Beyond the grandparent model of childcare Despite some research, our work has still been hampered by a lack of up-to-date data. The country has not conducted a census since 2002, and there are only a few areas in which gender-disaggregated data is collected systematically. For example, on workforce participation, there is minimal gender-sensitive analysis to explain the behaviors behind the numbers. This creates uncertainty as to why women are not more active in the labor market and why men are not doing more at home. We have assumptions, but we still need to test them to prove their validity or not. UN Women undertook a recent study on labor force participation. More than 3,600 women from 2,500 households participated. As expected, more than a third of those surveyed were not working because of care responsibilities in the home. There was no surprise here, but what did intrigue us was that conservative beliefs about appropriate roles for women seemed as big a deterrent to working outside the home. On one hand, women overwhelmingly saw employment as the key to an independent life. On the other hand, women seemed to feel that they were better at caregiving than men. This experience helped us to make sense of one of the findings of UN Women’s research. The secret, we concluded, was to offer care services outside the home that provided something more than a safe and secure kind of ‘human storage.’ This was clear, for example, in conversations with the mayor of a rural ethnic Albanian municipality with 25,000 inhabitants where UNDP helped to establish the first public preschool facility in 2015. The Mayor underlined the need to get beyond the “grandparent model” of childcare to ensure that preschool children enjoyed the benefits of socialization and early childhood education and can compete in the modern world. These findings also reinforced a new initiative by UNICEF to expand the reach of early childhood education programs. Since poorer families currently don't (or can't) access early childhood education opportunities, this expansion would overcome the current bias of daycare offerings towards well-off families and help to fight the intergenerational transmission of poverty. But here, too, demand would need to be stimulated, since so many families still believe in the idea of “grandparent care.” How we undertake these tasks will depend on the results of our quest for further data. We are pursuing three new lines of inquiry that should bring us closer to solutions:  Is there a compelling economic argument for the “care economy” in the former Yugoslav Republic of Macedonia? Our initial analysis looked at supply and demand trends for both childcare and eldercare. There are 96 institutions (public and private) with 4,655 staff providing early childhood care services to 34,386 children. However, 4,158 children were refused in 2016 due to lack of capacity. This suggests that the country is failing to satisfy childcare needs. The outlook is similar for care for the elderly, where social care options are even less developed. Currently only 20 institutions with 365 staff provide care for 1,050 elderly people nationwide. Is there a nationwide centralized registry that encompasses the full spectrum of preschools and kindergartens, elder care institutions and daycare services for persons with disabilities? The answer is no. We are wrapping up the first-ever national inventory of social care services covering all three different sectors: public, private and civil society providers. The results are still being analyzed, but it is clear that core populations are underserved. This is especially the case in rural areas and areas dominated by ethnic minority populations (Albanians, Roma and Turks). For example, under 4 percent of Roma children are in childcare. Why are men reluctant caregivers? UNDP conducted a survey to identify the main obstacles that hinder men from getting involved in care work with the hopes finding ways to initiate behavioral change among the male population. Next steps Once the results are analyzed and digested, our next step is to hold design-thinking workshops to discover what might encourage men to undertake a larger share of “women’s work” at home. We hope that these workshops will help us find volunteers willing to serve as caregiver champions or at least as positive deviants. UNFPA and UN Women have already built modest advocacy campaigns around these themes (see poster), and the UN team as a whole looks forward to campaigning in 2018 to break down the barriers women face to employment, and those that men face to caregiving. “Men can do it too” – UNFPA’s tongue-in-cheek campaign on gender roles and housework

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Silo Fighters Blog

Busting silos in statistical capacity in Guatemala

BY Carmen Aida Gonzalez, Claudia Lopez Robles | May 16, 2018

When the Guatemalan government realized that it had failed to achieve 63 percent of the  targets of the Millennium Development Goals (MDGs), it was a wake up call. Guatemala has struggled for years to connect, coordinate, and analyze its national statistics, making it difficult for decision makers to understand what investments the country needs to move forward. When the time came to adopt the 2030 Agenda for Sustainable Development in 2015, the Government committed to taking action and help improve the lives of the Guatemalan people. We knew we needed to up the game on data analysis from different public institutions. Currently, only 15 percent of the indicators of the Sustainable Development Goals can be fully produced by the National Statistical System in Guatemala. In Guatemala, obtaining disaggregated data is not an easy task since most institutions aren’t yet aware of the importance of such data. For example, obtaining disaggregated data on indigenous peoples and people of African descent is a struggle for national administrative records, despite their best efforts. Fortunately, Guatemala will carry out a population and housing census this year, and with these results, we at the UN hope to obtain disaggregated data about ethnic groups, people living with disabilities, migratory origin and other relevant information. Need a Data Strategy? We’ve got 70 of them To address the immediate challenge of limited data, we at the UN in Guatemala formed an inter-agency team of statisticians last year, spearheaded by UNFPA and bringing together UNDP, UN Women, IOM, OHCHR, FAO, IFAD, PAHO/WHO and the World Bank, with the support of the Resident Coordinator’s Office. This team came together to identify the resources that each agency had and what type of data we needed to achieve the Global Goals in the country. We wanted to do three things: 1) strengthen the National Institute of Statistics by developing strategies according to each statistical office in the country; 2) systematize good practices at the national level regarding health-related statistics; and 3) work with public institutions on participatory statistics management and SDG indicators to mainstream the 2030 Agenda for Sustainable Development.   For us at the UN, one “aha” moment was discovering that public institutions have very diverse statistical capacities. Through this exercise, we were able to see the level of disparity and the gaps that we as the UN can help fill in order to collect data better. Out of 70 statistical strategies that we identified with the National Institute of Statistics, we helped fine-tune the six that we considered to be essential for producing relevant data for the SDGs in Guatemala. The institutions we are working with are: The Ministry of Agriculture, Livestock, and Food The Ministry of Public Health and Social Assistance The Ministry of Environment and Natural Resources The National Telephone Fund The National Coordinator for Disaster Reduction; and The Ministry of Security These public institutions are contributing to various SDGs, including: SDG 2 Zero Hunger; SDG 3 Good Health and Well-Being; SDG 6 Clean Water and Sanitation; SDG 11 Sustainable Cities and Communities; SDG 12; Responsible Consumption and Production; SDG 13 Climate Action; SDG 15 Life on Land; and SDG 16 Peace, Justice and Strong Institutions, to name a few. Currently, the National Institute of Statistics is doing an in-depth analysis of these six key statistical strategies to develop an overarching plan for the production and management of national statistics, with an emphasis on baseline development, including SDGs indicators. The goal is for  Guatemala to increase the percentage of monitored indicators for the 2030 Agenda from 15 percent to nearly 40 percent. The data that we obtain from these strategies will help us to disaggregate data related to gender, age and geographical location represented in the rates of population. Helping improve health stats Another important area of work is the collaboration between PAHO/WHO, the National Institute of Statistics, the Ministry of Public Health and Social Assistance and the National Registry of Persons to systematize vital statistics, such as the number of births, marriages, and deaths. In the coming months, the National Institute of Statistics will publish a report that we developed collectively as an example of best practices for collecting statistical data. The report highlights the challenges that the public institutions face, because until now, Guatemala had limited resources to generate and produce quality data, hindering institutions from taking evidence-based decisions.  Taking the field experience to a virtual class Together with UNDP Colombia and the National Institute of Statistics, we  developed an e-course, aimed at national officers working in public institutions that are part of the National Statistical System. This e-course will run from May to June 2018 and will be delivered through webinars and a virtual panel to a group of 40 people. The added value of this online course is that it’s being adapted to the Guatemalan national context and each participant will receive personalized feedback from the instructor. We also want to reach national officers that live outside the capital city. The National Institute of Statistics will be responsible for following up with the liaison officers and we hope that this tool be used widely across all public institutions to continue empowering national officers. If you are interested in using this Spanish language course for your context, let us know. As for us at the inter-agency statistics team at the UN in Guatemala, the silo-busting has only begun...

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