>> MARILYN CADE:  Welcome.  My name is Marilyn Cade.  I'm acting as the mistress of ceremonies for the first segment, and my colleague and chief organizer and planner of the architect of this session, Wisdom, will replace me so that I can move to the audience in just a few minutes. 

So I'm just going to make very brief opening comments, and I want to welcome all of you and try to set the stage for what we're going to do today, and then we are going to hear from our host country ambassador, Thomas Schneider.  Very, very quickly, this is a working session.  We are faced with the kind of challenge in measuring and planning and analyzing that the world faced when E‑commerce was first conceptualised back in the '80s and '90s. 

Up until that time, the way we measured what was going on in the high‑tech world was to count households, businesses, the number of mainframes and terminals, and land lines.  We didn't have local phones, we didn't have online applications.  So all of the agencies responsible for statistical reporting had to completely rethink how they were going to gather information and what they were going to count and how they were going to report it. 

Today, we're accustomed to having really in‑depth statistical analysis from the UN organisations, UNCTAG, WTO, ITU, and more, health from WHO, and about labour from ILO, and we're accustomed having reports from think tanks like Gardner and others that tell us how technology is growing and how it is being used. 

But in order to adopt that particular measurement and analysis environment, to help us measure the SDGs, we have to go far beyond that, and our data gathering has to change.  The people we gather it from, the institutions we gather it from, and the companies we gather it from and the individuals we gather it from have to change. 

So this is a working session, to learn from many who are working in this space and to think about what our recommendations are to them and to ourselves, including to the private sector, not just to government agencies and think tanks about what we need to do differently so that we know what to measure, how to measure, how to analyze, to help to inform planning so that we will make progress in achieving the SDGs. 

I would like to turn this over to our host country speaker, ambassador Schneider, and then we will move forward with the rest of the programme. 

>> Schneider:  Thank you, Marilyn.  My name is Thomas.  We hope that some more people will make it through the security impasse at the UN here, because I personally think that this is one of the most important sessions, because this is fundamental.  It has become, I think we all agree, fundamental to achieving the SDGs.  The thing is, not just everybody is really thinking about this in a strategic way. 

Maybe just to give you a quick experience on how we deal with this on a national level.  We have the SDGs, development corporation ‑‑ not corporations, agencies as part of the government.  Plus, another federal office that deals normally with landscape and space planning and space allocation.  And they have started what they call an agenda 2030 baseline assessment, where they go through all the 17 SDGs and 169 or whatever they are sub goals of the SDGs, and look at what does this mean for our country, where are we standing on national level, where are we standing with our development activities to support other countries, and they haven't by themselves taken into account digital transformation or anything like that in a systematic way. 

So when we were invited, that was an open process, a multi‑stakeholder process in the Civil Society businesses on national level, but it was us as the Office of Communication, at the same time as the IT department of the public administration that both were told to listen, you're forgetting something very important.  If you look at the SDGs, digital transformation of economy and society applications, this has an impact on basically all of the SDGs, and actually most of the ‑‑ a lot of the sub goals, and what we provided them with is basically a simple chart with an invitation to what extent we think that every particular line is impacted that can be positive or negative by digitisation, just by adding one D, two Ds to every SDG. 

We had a session with them, and actually they can (?) on the national level of where we are achieving the SDGs without looking ahead just a few years and thinking about the effect of the digital transformation on each of the SDGs. 

And so now this has become a full part of the national SDGs strategy and we are having regular meetings, and we've also brought in other stakeholders that did not work on the development issues properly or concretely, but actually come from the different fields of digitisation, and now there's a cooperation that is going on that is very useful. 

But they themselves wouldn't have thought of this in the beginning.  Now it is fundamental that you have a development strategy for the national level that is aligned with the digital strategy no matter what you call it, because if this is not aligned, and you use knowledge or awarenesses that it would be (?) to benefit, because it is all there.  Our colleagues from the development agency, they use ICTs in all their approaches, from micro funding issues to systems where they support the sharing of market data for whatever agricultural products are produced. 

But they haven't looked at these things with a systematic focus on what is the effect, what are the opportunities, but also what are the challenges that people face when using these ICTs, and they are now basically trying to develop a more systematic approach, having internal exchanges about experiences with these things, and so we really think that this has helped us using these ‑‑ is helping us in the making of all of this. 

But just to give you that message that also we have to learn and people in our administration had to learn that they need to collect in order to understand what is going on in order to be able to support projects with other partners in an efficient way and knowing what they may be facing in terms of challenges when they undertake a project with ICT components and how to deal with this in a more systematic and strategic way. 

So this is just a national experience that I wanted to share with you.  I have to prepare for another session that we're having at 10:00, but I really think that this is a fundamental issue, so I wish you a very good and fruitful and hopefully enlightening and mutually inspiring discussion.  Thank you very much. 

[ Applause ]

>> MARILYN CADE:  Thank you.  Thomas, I thank you so much also because we know we ‑‑ you have a very busy schedule, both in your role as host, but also this important session that is coming up.  And one thing I want to commend to anyone who is a newcomer to IGF is that we are very, very fortunate that all of our sessions are transcribed and recorded as well, so that if you missed a session that you're particularly interested in, you will be able to catch up on it. 

So we're going to miss the great session that the host country has organised that you're going to, I'm sure many of us will be looking to see what's going on there and we'll be able to then know that you can look back to us as well. 

So, thank you again, and thank you to Switzerland for being our host for the IGF for 2018 ‑‑ for 2017.  Okay, I'm going ahead. 

I'm going to turn over to, as I said, the chief architect of this.  I just want to recognise Zeina, who is sitting with us and will be with us for at least the first hour, who is also one of the co‑organizers, and thank her as well for being part of the organising team. 

Now, fortunately, my job is over.  I get to hand off to Wisdom and I get to come be part of the audience. 

>> WISDOM DONKOR:  Thank you, Marilyn, and thanks for all the support.  As we continue the first part of the session, we have the executive (?) of global technology for (?) data.  In relation to (?) in the developing countries.  They've been to Ghana a couple of times and other parts of Africa.  So she will always be giving us a statement.  After her, we will have (?). 

So, Dr. Claire, are you on the line?  Can you please respond? 

>> Claire:  Thank you.  Just to confirm that you're able to hear, wave if you can hear me.  Hello?  I'm not sure that we're getting any sound there. 

>> WISDOM DONKOR:  I think we have to move on.  We'll turn to Mr. Andre to give us his statement.  Andre, you can introduce yourself and let the audience know who you are. 

>> Thank you very much, Wisdom.  As you have heard on the ‑‑ I think it's working now.  I'm the executive director of the global open data initiative for (?).  We believe that one of the best ways to achieve global food security, global nutrition for everyone, and at the end of the day the improvement of the quality of life for everyone, especially on the horizon of 2015 based on demographics and climate change among other problems that we have to overcome, is through the exchange of knowledge and the exchange of data, which is the underlying source of knowledge. 

During my lifetime, and yours I guess, we went through three quiet revolutions.  The first one was the Internet, because that connected the world in a way that never happened before. 

Second was intelligent phones.  That allowed and allows many countries to leapfrog steps in their development.  Now, you can go to most remote parts of Africa and Asia and other continents and you find people with mobile phones.  There may not be phone lines, but there's mobile phones.  There is therefore mobile banking, and there's a lot of interactions that just weren't possible a few years ago. 

And the third revolution is data, because that's bringing the Internet and all the knowledge that it carries to your fingertips. 

A lot of smart applications are being developed to maximize the use of that and bring big data to the common people, to the farmers, to the regular guy down the street, to you and me.  I'm thinking through just the one or two ‑‑ and it's really important.  I need to think of a couple of examples, but just to illustrate why this is important, in 2025, the world is going to generate about 180 zettabytes of data.  180 zettabytes of data is 180 plus 21 zeros after that.  That's the number of bytes of data that the world will be generating. 

So there's no shortage of data.  The issue is how do we make use of it and how can we bring data, the Internet and the data it carries, to the reach of everyone.  That's why these applications are very important, because they make it in a very transparent and easy way. 

Just one or two as an example.  There's one application ‑‑ see we have about 600 partners, for those who don't know, I would invite you to go to our website.  We have 618 partners as of yesterday. 

Among the applications, I'm thinking of one by Plant Wise and the other one called Weed Scout.  The most remote farmer, when he or she sees its maize dying, all he or she needs to do is take a picture of that, and then artificial intelligence, it goes through a central database to big data and in a fraction of a second, it comes back to you and tells you what the problem is and what is the best way to address it. 

So that's one of the ways to bring big data to everyone thanks to modern technology and the availability of this mass of information there is. 

Other approaches also ‑‑ I'm thinking of geodata, which is also another way to leapfrog technology in terms of managing agriculture and managing environment and respective countries.  The problem with geodata is that its positive side now censors and satellite so accurate, it generates so much information that it becomes massive.  So unless you have huge computing capacity, it's very difficult to absorb all of that. 

But thanks to new search engines, what you can do now is two things.  Either just to download the part of the information that you need, or to leave the information where it is and do your processing within the cloud so that you only deal with the answers, with the results of the research that you are doing.  But to make that happen, of course, there's a number of obstacles to overcome.  Technological, training, capacity building, and that's part of the discussion today. 

Thank you very much. 

[ Applause ]

>> WISDOM DONKOR:  Thank you.  We will now move to Mr. Gamme.  (Phonetic)

>> Good morning, everyone.  My name is (?).  I'm the Chairman of the commission and decision support center at Egyptian cabinet.  Fortunately, I used to be a member for three years, so I'm quite familiar with the IGF.  For this session, data and the SDGs, it seems to me like it is exactly what worked for the information (?).  I need to explain this in a brief. 

This has been in place for the last 30 years, and with the aim of gathering the information related to all projects, plans, and relations of citizens in the hub, and then making the analysis, and providing the support with that regards. 

With the movement and improvement of the digitisation, this has been used to the purpose. 

So when an industry has two organisations, one is (?) which is the statistical organisation responsible for making statistics.  We have IGAC that is responsible of making the MNE, that is responsible for connecting between citizens and the government, it is responsible for analyzing the information that is gathered and making proper suggestions to the decision maker before taking corrective action. 

When (?) took place and we have our vision in Egypt for 2030, it became a mandate for IGST using its monitoring mechanics and analyzing mechanism to provide the corrective monitoring and improvement directions. 

What we do is we do ‑‑ one of the them is digital development maps.  We are connected to the government authority.  We get through a data management system, updated information about the execution of the plans, and the large project development undertaking, and this is gathered on a daily basis from the data management system, and using this, we are building geo maps, layers, different layers that gather information from all sectors all together, so we have the information layer, we have the agriculture layer, we have industrial and economic layer, we have the (?) layer, we have the social protection layer, et cetera, and with this, we are able to visualise the gaps and opportunities that exist and put accordingly supporting suggestions for the decisions of the Prime Minister and the cabinet. 

Just an example of how data can be once connected properly and analyzed and visualised, helps making a difference in the decision process.  On top of this layer, we have teams that are working on M&I, monitoring and improvement, which completes the next step of the chain by analyzing the plans of the government and the information that is coming regarding execution of the different projects.  And then, there is ‑‑ we are using DSS systems that analyze one degree of activities of different sectors are complementing each other, or are not, so we can put better synergy among them. 

Another aspect is the government aspect.  One of the rules that IGSE is doing is improving governments.  Reporting the cabinet to the Prime Minister.  We are to monitor all activities of the government and the relation between the citizens and the government.  And once again, to do this, we have our digital tools.  We have the (?) system for the government, where on a daily basis, we have receiving thousands of complaints from all over the country digitally through the website (?) and is the receiving ‑‑ it's a complete GRM system that receives complaints from citizens related to any government need.  And this is gathered again in our data center in order to do two things.  One, to follow up with different government authorities, the response and the execution of the complaint would find limits that is allowed to each different type of complaint. 

And also, to analyze this for two things.  One is to what degree different authority is responding as required, and if there is any potential corruption.  Wherever there is many complaints coming from certain areas and certain sector, this would give an indication there is a possibility of a corruption there. 

And then we take another action, another authority in order to be able to see how to take a corrective action with that regards. 

We have also an application called EGEDE (phonetic).  This application role is to make a connection between the citizen of smart phones and the government.  One of them is new information providing the citizens on regular basis with the information for the activities of the government in different projects, as well as different information about how to handle what are the new rules that apply, but there is a module for observation.  So a citizen can simply pass by a rule and find that there is a problem there, there is something happening, and he can just take a picture with the geo, send it to us, and then we guide the right authority to take action upon this in order to have a swift corrective action. 

We have many other things, so I don't want to say too much more.  What I'm saying is there is a model that can be aligned.  It is a model of how in a digital world, in a developing country, we can optimize the use of information gathered from the citizen side and from the government side, and help supporting taking proper decisions by the government.  Thank you. 

[ Applause ]

>> WISDOM DONKOR:  Thank you very much.  We'll turn to Dr. Claire.  Again, I think we have to use our headphones. 

So, Dr. Claire, if you can hear me, can you please proceed? 

>> Claire:  I can hear you.  Can you confirm please, that you can hear me? 

>> WISDOM DONKOR:  Hello? 

>> Claire:  Hello.  I'm speaking now.  Can you hear me? 

>> WISDOM DONKOR:  Hello.  Doctor, can you hear me? 

>> Claire:  Yes, I can hear you.  Are you able to hear me?  Yes, I can hear you. 

>> WISDOM DONKOR:  Dr. Claire, can you please speak up? 

>> Claire:  Hello, are you able to hear me now? 

>> WISDOM DONKOR:  Yes, I can hear you, but very far. 

>> Claire:  Okay.  Let me just try to adjust my audio.  Hello, are you able to hear me still? 

>> WISDOM DONKOR:  Yes, we can hear you.  (?) (audio echo)

>> Claire:  Thank you very much.  My apologies that I'm not able to be with you today.  My name is Claire, the director of the global partnership for sustainable development data.  It's great to be there with a number of our partner organisations.  I know on the panel.  Greetings, Andre, and also I'm sure in the room. 

The Global Partnership for Sustainable Development Data is an organisation that was born from the sustainable development goals, and its mission is to harness all of the amazing technologies and the possibilities that now exist in the world of data, to harness those towards the achievement of the sustainable development goals. 

We've already heard, I've been listening as your discussions have proceeded, we've already heard some very inspiring stories from other speakers about how those things are already happening in different sectors and in different countries and some of the new possibilities that now exist in the world of data. 

I think as the sustainable development goals were being agreed, it really catalyzed and crystalized a vision for many countries of the way that they will be able to take advantage of the new sources of technology, some of the new possibilities that exist in the world that did not exist at the time of the millennium development goals, the way that they would be able to harness those and use them to help them achieve the sustainable development goals.  And, of course, in signing up to such a broad and ambitious agenda, it was very important to use all the tools that were at their disposal. 

So, my organisation, the global partnership, came out of that UN process. 

Our mission is very broad.  We're interested in all of the sustainable development goals.  And because of that breadth, we very deliberately take a very broad cross‑cutting whole of government approach.  So we've already heard from the ambassador about the importance of linking a development strategy with a digital strategy.  Let me add a third D onto that, which is the data strategy, and we really ‑‑ our work is working with governments and with many of our several hundred partners around the world to bring them together to understand where the needs exist and where the organisations exist that can meet those needs and how we can work together to create those data strategies and data systems that can help governments, that can help the private sector, that can help Civil Society organisations to achieve the sustainable development goals. 

So, I know the topic of this meeting is the data road maps, and this is something that we ‑‑ where we are working very closely with a number of governments, including the government of Ghana, and it's great to see Wisdom.  I know that other colleagues are in the room or online, so greetings to all of you. 

And we work very closely with governments to develop priorities, and then to look into our network at where are we able to make the connections that will help ‑‑ that will allow governments to work towards those priorities and to achieve their objectives. 

And I think in this regard, it's really important to think about data as a whole system, and I hope that this will be helpful in guiding the discussions that follow.  Sometimes we think about data simply as a single data point or as a single application, and these things are absolutely critical as we put data to use in very specific ways.  But if we're going to have the infrastructure and the infrastructure and in a sense the engineering that will allow us to ‑‑ that will allow us to have that opportunity to put data to use, we need to think about the whole data system.  So we need to think about all of the methods of collecting data that, of course, relies on a very strong and well‑resourced national statistical system within a country.  But it also relies on other systems that connect to other data from around the world.  We've already mentioned data from satellites, observation data that can provide an incredibly rich and nuanced source of data that didn't exist years before. 

And of course, also, data from mobile phones, the data that we're all creating every day as we walk around with phones in our pockets.  And many other sources of data that come from citizens and from the things, the Internet of things that are producing data every day of the week. 

So we need to think about an entire data collection system, one that takes advantage of all of the different sources of data that we have in the world, and of course that covers all citizens and doesn't leave anybody out in order to meet the sustainable development goals promised to leave no one behind. 

So we think about that.  That involves partly the complicated arrangements that are necessary to have access to the data with due regard to privacy and to the legislation that will allow that data to be shared or transmitted safely and freely. 

And then, of course, it involves ‑‑ once we have the data, then we need to think about moving on to the second part of the system and the capacity to analyze and to process that data.  That's not something which is easily done.  We're thinking about a whole range of new skills, in not just statistics, but also data science, computer programming, and of course the very deep technological and infrastructural requirements of connectivity, which I know is a subject that will be coming up again and again in your discussions over the next few days. 

And also there, not just the technical requirements, but the institutional requirements, sharing data across government departments has not always been straightforward, and allowing data to move freely requires not just the technology, not just the data systems and the interoperability, but also the legal and the institutional frameworks and willingness to share data across governments to really make sure that this data is going to be used to its best effect. 

And then, of course, the third part and the most critical part of the data system, which is the use.  We need to make sure that this data, which is being so painstakingly collected and processed and shared and combined, is actually being used by decision makers to allocate resources in the best way, to ensure that programmes are having their desired effect, to ensure that the most critical problems in any given country or region or the world are the ones which, in fact, are being addressed, and to make sure that policy and politics is based on evidence. 

So these are the three constituent parts of the data system.  Data collection, data analysis, and data use.  And in this world of data, what we call the data revolution, it's impossible to conceive of any of this being done effectively without combining a great number of very different kinds of organisation without combining governments critically at the center of this, but also with the private sector companies who are actually generating the majority of the data that we see in the world.  The software engineers, the Civil Society organisations that can ensure that the conversation with the general public is one where everyone understands the progress that is being made and the constraints around it.  And, of course, the day‑to‑day conversations with policymakers at very different levels to make sure that this data is actually answering their questions and meeting their needs. 

So it's a very broad ‑‑ it's a very big problem that requires a very broad approach, one with many, many different stakeholders, and in the global partnership, we're very proud to be working with many hundreds of stakeholders across many countries, across regions, and at the global level to try to bring these conversations together, to share experiences, to develop collaborations, and I hope in the end to build stronger data systems through developing data road maps at the national level, at the regional level, and ultimately globally that will help us to achieve the sustainable development goals. 

So I thank you all for your attention this morning.  I will look forward to listening in to the conversation for part of this morning, and I wish you very good deliberations in the meetings to come.  Thank you. 

>> WISDOM DONKOR:  Thank you, Claire.  Before you go, I think there is one question for you about data. 

>> PARTICIPANT:  Good morning, everyone.  I do have a question.  Does your organisation work with Civil Society organisations, or only governments?  Thank you. 

>> Claire:  Thank you.  We absolutely do work with Civil Society organisations.  We have Civil Society organisations represented on our board, and we are very ‑‑ we're very clear that our approach within any country is a multi‑stakeholder approach, so we work closely with governments clearly as some of the main implementers of the broader data system, but we are very ‑‑ we are very keen to work closely with Civil Society.  We have a working group on citizen generated data where we're particularly keen in that group to understand Civil Society as a collector of data and how that data can be made useful to all stakeholders in achieving the sustainable development goals. 

And we also see that Civil Society has a very, very critical role in acting to ensure that the way that the data systems are developed within countries are a way that meets the interest of all citizens, and particularly, of course, those most vulnerable citizens and ensure that data helps to, as we say, with the SDGs, to leave no one behind. 

So, absolutely, we work closely with Civil Society organisations and see part of our role as brokering a conversation between those organisations and governments and the private sector to improve data systems.  

>> WISDOM DONKOR:  Thank you very much.  We hope you will still be with us for the second part of the presentation. 

We will now move on to the presentation.  I'm going to invite Mr. (?) to come onstage, the chief executive for (?) mobile phones, and we are going to present on ‑‑ we are going to present on the challenges of the (?) a case of developing countries. 

(Audio echoing)

So (?) after this presentation. 

>> Good morning, everyone.  Thanks for having me here.  I am the CEO co‑founder of mobile phones.  It's a company we started last year.  Trying to solve a huge problem in Africa.  But I'll come back to that. 

So for a long time, Africa is the next frontier.  That explains why every year, NGOs, businesses, donors trying to (?) on different points.  However, we have huge problems.  It still looks ‑‑

It still looks like a black box.  It's almost entirely possible to get reliable data in Africa, and when we're able to do that, it takes months to get it out and takes another month to try to clean up the data and present it.  It is almost impossible.  And we know what the issues are. 

Next slide, please. 

First, the fact that the information is very poor with communication almost nonexistent.  A big chunk of the population is still (?) so you cannot (?).  A laptop or a desk top becomes an issue, and (?).  For a long time, we've been trying to use (?) or trying to do routine data collection, which is a huge problem on its own. 

And the fact that a lot of the details is all offline.  Almost entirely offline.  They are probably not kept properly, or they must get to the ‑‑ over time, the quality reduces.  So we are excited to give something else a try to see what we can do to solve the problem.  Next slide, please. 

So what can we do to (?) this infrastructure?  (?) to get things done.  Africa has been known to leapfrog technology for a very long time.  For example, I didn't grow up with a land line in our house.  So we need to keep looking for ways to leapfrog these technologies.  More granular, smaller, and then we can collaborate. 

People with mobile devices (?) who are willing to give extra time on behalf of the international community.  And in this case, they can do it consistently.  They can do it periodically.  And they're doing it with mobile devices.  By doing that, they're ‑‑ oh, I'm sorry. 

How do we analyze the data (?) and as fast as possible.  Next slide, please. 

So we started out this model in Nigeria, and (?) in Ghana.  I'll talk about Ghana in a bit.  Today we have access to over 100,000 (?) in Nigeria, individuals with smart phone devices, and they are willing to (?) in their spare time.  Proud of people who come together to work on one goal. 

Next slide, please. 

Data works.  So we want organisations to find data requirements, the structure into a digitised form, the dynamic digital form, and then we should push it across all the (?).  So everyone across the country and community will get notifications and carry out these tasks in realtime.  Maybe it is one hour away from them.  Some of them move around gathering the data.  They are able to capture that offline, and when they get back to the committee where they leave ‑‑ where there's Internet, to the cloud.  All the data is time stamped. 

And so what that means is we're able to gather reliable data way faster than anyone else can get it. 

Next slide, please. 

So remember that what we've done is we've tried to ‑‑ that means that we're working with people to use infrastructure and see how it can help them.  So one of the areas we are able to help address is special data.  We are able to help across the data, for example occupations.  For a long time, we didn't know where (?) were.  We didn't know what services they offered and we didn't know how they looked like.  And there were some that were not registered or functioning. 

What we're able to do, in the course of five days, we are able to (?) with those facilities and along with that, pictures and services we offer.  So what that means is, it's interesting because we can cover the entire country in the same amount of time.  We can get all of the data across the country in a very short period of time. 

Next slide, please. 

Another area we're helping the statistics to (?) across the country.  The way that we determine is by (?).  Before now, it took months to get that data, before you analyze it.  It's just amazing, right?  So now we can do that in three days.  Process (?) all across the country.  And who is doing this?  The mothers and wives who normally go to the market and buy things.  They don't mind pulling out their phones and do a lot more (?).  And it also exposes ‑‑ they also have this belonging, the fact that they are contributing to a greater purpose, because all of the data collected from the area, in the end, it still goes back to (?) in their community. 

Next slide, please. 

And which I just mentioned, the fact that they are able to supplement their income.  Second, they feel like they are part of a greater good.  They're contributing way more.  And whatever improvements they see around them is as a result of the data that they are providing. 

So we try to tell that story as much as we can.  And this kind of tells the stories of people who (?) across the community, or people who have to go to a extreme to get to a community, but they're happy to do it.  They take a picture and they smile.  It also helps them understand their surroundings more.  The global initiative, they're happy to volunteer for it because they've seen exactly where the problem is. 

Next slide, please. 

So like I said, it's an infrastructure, and we've seen it across different industries.  For governments, written applications, they are working with the Ghana (?) service.  They are trying to do something very innovative, which is the fact that getting every Ministry to use the same system so that all that data goes into one data server, and I think it's amazing.  So one institution holds everything together.  So what that means is that whatever Ministry (?) collected from whatever community, whatever it is, everything is going to one place.  No more transcribing.  No more trying to put into another place.  It just makes the whole process way faster.  Now we can start to build models on top of that data, and I think the beauty of this is being able to do particular analysis when you're able to get data (?). 

So I commend what we're doing with the Ghana commission, looking forward to amazing things to come up there. 

We're also helping businesses, like FNCGs, we're trying to better understand their supply chain.  Trying to (?) understanding that products are getting to the right spot.  So (?) across the country with pictures, aware of whether the product exists or not. 

And of course, non‑profit and international community.  We're working with them to help them do location, mapping, (?) and routine data collections, confirming if an infrastructure is (?) things like that.  It's been an exciting journey so far. 

Next slide. 

The next steps, we've built a model we believe can work.  We can scale across Africa.  We have an obligation toward targets and the first thing we need to do is (?).  So we're looking at visions to build national trackers across the country.  Where the communities are the ones giving the feedback into the system in almost realtime. 

So we're looking for (?) to join us in this journey.  We have an exhibition put up there.  If you would like to join us or contribute to us in any way possible, we need partners who will work with us for every country now.  I mean, we know Africa ‑‑ it's one Africa.  We need partners in every country, and we've been getting tremendous support from the (?). 

So the more we work with them, the more we (?) and then get it done.  Policy also from the government should be ‑‑ government needs to be willing to collect data freely and openly in the community. 

And finally, is funding.  We are doing routine data collections.  We're going to take it a step further by doing more complex surveys and we're going to need viewed capacity.  Once we've viewed the capacity once, all we need to do is constant capacity data, which is not going to be like initial investment.  And to try and improve the capacity to do more complex surveys on a routine basis.  We look forward to speaking with everyone. 

Next slide should be the end.  Thanks for having me. 

[ Applause ]

>> PARTICIPANT:  Hello.  So we do have one comment and a question.  It is from (?).  Besides data regeneration, there is need for user education on how to seek out information from data and application.  And he's asking how accessible is the data being generated?  Thank you. 

>> Panelist:  Thanks for that.  I agree with his comment.  Right now, we are working with (?) all the data that we collect for them.  Their privacy policies.  What we really want to do ‑‑ and, I mean, we put in for grants.  We want to do like (?) and we want it all entirely open.  So a lot of that will be determined by the funder on how to use the data, and we will also start to sponsor projects.  So we have open data.  We probably call it open data (?).  Simple projects like (?) across the country.  And the more we can get permission to make more data open, the more we will do.  Thank you. 

>> WISDOM DONKOR:  Thank you.  Omar is online, he is ready to do his presentation.  Omar, if you're online, can you speak up? 

>> OMAR SEIDU:  Thank you very much.  I can hear you.  Can you hear me? 

>> WISDOM DONKOR:  Yes.  We can hear you.  Are you going to use a presentation or just talk? 

>> OMAR SEIDU:  I have it with me, so I can just talk. 

My name is Omar Seidu.  I'm the head of grammar statistics, and I coordinate the SDG data for monitoring, and currently working with all the national stakeholders, including Wisdom, to ensure that Ghana is positioned to report on the SDGs. 

Since the adoption of the Sustainable Development Goals, Ghana realized that there was a need to avoid the implementation and reported challenges associated with the different frameworks that we have signed onto, so we adopted a position to align, adopt, and adapt the SDGs to our national report development framework. 

So, with that, three institutions were put in place to oversee the implementation and monitoring of the SDGs in the country.  The first is the high level Ministry chaired by Ministry for planning and chaired by the office of the President.  With SDG monitoring responsibility.  And they would have the SDG implementation committee, which is a multi‑stakeholder committee that has government, Civil Society, the private sector, philanthropy, academia, the media, being part of to oversee the implementation and monitoring. 

And then the National Technical Committee that has membership across the various government departments that have the responsibility to implement the SDGs. 

So with that, we instructed all government agencies and departments to streamline the SDGs into their sector plans so that we will not have separate implementation programmes for the SDGs and then for other sector plans.  So these have been done. 

Once these were done, the National Statistical System now has to think how do we produce the monitoring progress against SDGs and these other frameworks.  So we constituted a team to look at how to link the different needs of the SDGs through the Africa union and our own national development framework. 

And doing so, we tried to assess the capacity of the country in monitoring the SDGs.  So we looked at data availability.  We focused on the tier one and tier two indicators.  You realized SDG are being classified under (?).  Tier one and tier two were where data is available.  The concept is (?) and agreed methodology for monitoring. 

So we focused on the tier one and the tier two indicators.  So we looked at which data sources do we have as a country for monitoring the SDGs, which institutions within the country produce this data, how often do these institutions produce those particular data, and what is the most recent year for these indicators, and then important for leave no one behind is disaggregation, so we look at the existing structure or culture of data disaggregation and, of course, we also look at (?) do not currently have data, what are the potential sources that we could have data. 

And this helps us to identify the capacity of the country in monitoring, so we classify all the tier one and tier two indicators into three categories.  One category is those indicators that we currently are already using.  And then the next category was the set of indicators that we have (?) across different government agencies that need to be brought together, in some cases with minimal (?) that need to be addressed.  And the third category is those that we do not even have data at all for monitoring. 

So this brought us to the challenge of ‑‑ the key challenges for (?) which is one of the keys on disaggregation, by location, by socioeconomic groupings, the timeliness of the production, then data (?).  As a country, we have not really explored.  And the fact that we have been working in silos, and there was a need to make sure data feed into policy. 

So with these things, we started engaging all of these activities happened within 2016, so we started engaging and said, how do we strategize to meet the different needs of the country.  So we started talking to the Global Partnership for Sustainable Partnership Data.  Happy Claire was one of the speakers earlier. 

We started engaging with global partnership, and by December 2016, we realized that that was the way to go, because that way, we were able to have a national framework for addressing the data gaps for the country.  So we joined the global partnership, and during the first UN data forum in Capetown in January 2017, we had bilateral meeting with Claire and her team on the way forward and we agreed to host a national data road map forward in April. 

So we started working towards that. 

One of the key success stories that we have is the constitution of an advisory committee for data road map in Ghana, and this committee is a multi‑stakeholder committee that is co‑chaired by the national (?) office and the national development planning commission and has membership across different government agencies, the private sector, the Civil Society, and so this team came together to ‑‑ two things.  To first implement the road map forward, and take forward the issues that arise from the forum.  So this group has been working to ensure that the issues are identified from the road map forum streamlined into our daily activity, and we are able to meet the needs of the SDGs. 

As we speak, three key areas were identified from the road map forum held in April 2017.  The first one is filling the data gaps.  That is strengthening surveys, building an effective administrative system, and exploring new sources on types of data. 

The second is encouraging (?).  Of course, it does not make sense to produce so much data if it is not going to feed into policy.  So encouraging data use.  (?) data more open and reusable, better communication and visibility of data, and meeting user needs, and ensuring it is interoperable and organised. 

And the third area was tied to ecosystem, engaging with all the stakeholders in the production cycle to ensure that we effectively coordinate and work together to achieve the goals we have for ourselves. 

So with this, we agree that there was a need to (?).  I must say, at this point, the streams have been working and have been unable to get projects running towards filling the different gaps and all the areas that we have identified, and we agree that the coming years, we need to map and understand with all the actors in the ecosystem to have clear rules and responsibility in the area of data production. 

And we need to also enhance the existing capacity and build new capacities.  We also need to take advantage of existing infrastructure and also build new ones where we think they are for meeting the SDG data needs for Ghana. 

And I am happy and proud to say His Excellency the President of Ghana has endorsed the key priority areas as something he and his government are committed to ensuring that Ghana is able to implement for achieving the SDGs.  Of course, there is a video to that, which I have sent as part of the presentation.  Listeners can look at it to later on see what His Excellency says. 

Now, a quick one.  Since the forum in April, (?) as a country in trying to address the key priority areas.  One, we realize that it was very important to have ‑‑ to build a political and sustained political commitment to the data agenda. 

Secondly, we realize that there was a need for us to continue and deepen the multi‑stakeholder engagement that we have started for data production for sustainable development in the country.  So we joined the global partnership and the governments of Kenya ‑‑

>> WISDOM DONKOR:  Hello, Omar? 

>> OMAR SEIDU:  Hello? 

>> WISDOM DONKOR:  Hello? 

>> OMAR SEIDU:  Can you hear me? 

>> WISDOM DONKOR:  Yes, I can hear you.  I think time is up.  Can you please wrap up? 

>> OMAR SEIDU:  Okay.  So (?) activities have since been implemented towards that, and one of the key things is at the moment, we have been able to get a partnership with the private sector entity in the country to use private sector data for SDG monitoring in Ghana.  For the first ever such an endeavor has been taken. 

We have the Vice President of the Republic of Ghana also, something to be (?) which shows the kind of political commitment that we have, and this could not have been actually (?) if we had not been part of the data movement if we had not started this process. 

So to wind up, three key things that we have achieved with this is (?) in Ghana, and building political support for the data agenda.  And the third is deepening multi‑stakeholder engagement towards data forces of development.  Thank you. 

>> WISDOM DONKOR:  Thank you very much, Omar.  We have two other presentations, and I think if you can help me so that we ‑‑ and we'll move on to the next part.  We'll get to the next part, and (?).  So if that's fine, we will move to Tanya, which should be a brief one. 

>> Panelist:  I'm going to be as brief as possible. 

>> WISDOM DONKOR:  Will you please introduce yourself?  The country you are coming from. 

>> TANIA ZAROUBI:  I'm Tania Zaroubi at the Office of Reform in Lebanon. 

The Lebanese government in 2014 embarked on devising a strategy for the process of business registration in the country, and this started the initiative for data protection, data sharing, interoperability, and all the ones listed here in front of you.  The first was the Lebanese government interoperability framework with all its components.  The governments, the principles, the interoperability levels, which are organizational, legal, technical, semantics, and of course, we need to have the agreements between all the stakeholders that we will be working on. 

Plus, the servers model.  So the most important ‑‑ one of the most important components of the government interoperability framework is the (?) service model, which I will explain very briefly.  It's going to be through, one, a national interoperability ‑‑ it's a single point of context, where we are going to have a portal, and it will be the one‑stop shop for all different transactions for the government. 

Now, the first initiative will be about a project that is called the commercial registration of companies, and it will be through the interoperability framework, and the way it's going to be, the domain ‑‑ each sector will have its own domain interoperability basic service with all the institutions working together and interchanging the data. 

Another sector would have, of course, another domain to work on.  I'm trying to be as quick as possible.  Please next slide. 

Our basis for this is going to be the data, where we have established data dictionary, and the standard form for this project, which is ‑‑ which has already started.  The data will make sure to put all the elements of data needed among the three stakeholders, which I will explain very briefly who they are, and it will most importantly say who is the owner of this data, and who is the one who is going to push the data to the others.  It always has to be a single point for (?) of data.  We don't want to replicate and enter the data in many cases, as I currently do right now in all our databases in the government. 

The project is called (?) the interoperability ‑‑ interoperable platform.  It is a one‑stop shop for commercial registration, for business registration services.  It's going to develop a commercial register that will be a single point of interaction of all the business community with the public and private sectors. 

It's going to be improving the business environment in Lebanon, introduce a national legal entity identifier for the companies, because right now, we don't have a single entity that is unique for a company.  In every database, the company identifier is slightly different than another database.  For example, in one of the stakeholders, it has a commercial registration number, and another one, it has parts of it and not all of it. 

This project, one of the things we are going to do is to clean up the data in those three stakeholder databases, so that we can create a clean one database that (?) by the three stakeholders. 

Of course, eventually, we are hoping to improve the investment in Lebanon.  The stakeholders are going to be the Ministry of Finance, the Ministry of Justice, and the Ministry of Labour.  The Ministry of Finance is where the tax authority is.  Ministry of Justice is where the commercial registry resides.  And in the Ministry of Labour, we have the national Social Security fund. 

The three stakeholders, those are the main ones to interact together for the data of the companies.  The first instance is to register at the commercial register, but also, of course, to carry onward the transaction and to make sure that the ‑‑ this company is legal and it has to pay its taxes, and of course, it's going to have employees where they have to be registered in the national Social Security fund. 

The data is shared among those three stakeholders just to make sure that all the data is correct.  The enablers also are the ones you see around this, which is the Ministry of Economy and Trade, where all the foreign companies are registered.  Of course, we have the (?) center bank for other data.  The civil registry, status registry is where the civil status data is registered, so anybody who owns a company and is a partner must have the digital ID ‑‑ the unique identifier, which also exists in the civil status registry, and we also have to communicate and authenticate ‑‑ to authenticate the shareholders and all the people who are related into the company. 

Of course, we have also the general security forces where they have a unique ID number for foreigners, and (?) association, because all our companies to be registered, you need to have a lawyer to register the company. 

Now, to start on the data, which we found in those three main databases, the tax and the Ministry of Finance in the commercial register, and in the National Social Security Fund, we wanted to do an analysis of the data.  The linking of the three databases was very difficult.  There is also variances in the name of what we call the legal entities.  Legal entities are companies or are sole merchants that have their own trading. 

And, we also found significant differences in the data, because whenever you are updating data in one database, sometimes the data is not being updated in the other database. 

So, what are the core problems?  It's the inability to link the three identifiers, and the significant variances in the data that is being captured in the three databases. 

When we looked at the number of (?) even the number of (?) in the databases.  In front of you, you will see in the commercial register, we have 362,582 companies, whereas in the Ministry of Finance, we have only 164,306.  And the Ministry of Labour, we have around 128,762.  Now, those three ‑‑ oh, it's not showing.  I'm sorry.  Okay.  The numbers probably are listed in the top. 

Those three could be companies that are dormant in the commercial register.  Companies that they should be closed and they are not because they have to pay a lot of taxes or a lot of fees to close their companies.  So they are not doing anything.  So that's why you'll find discrepancies. 

Also between the National Social Security and the tax, you will find that not all companies are actually letting it be known that you have ‑‑ that they have employees that benefit from the national Social Security. 

This is a quick slide to show the kind of ‑‑ next one ‑‑ the kind of matching.  The databases, of course ‑‑ the Ministry of Justice, the commercial register is an open data.  Everybody can look at it.  It's partly digitized.  The Ministry of Finance, we have confidential data.  It's not open.  It's definitely protected and secure and it's digitized.  And the Minister of Labour, it is, of course, confidential data and it's digitized. 

Next. 

The data conversion process.  Of course, we're going to have special forms.  We're going to introduce the legal, the unique legal entities, and one important message is each stakeholder knows his or her own data, and there is going to be a team from those stakeholders who are going to work on the data. 

The status of the project is already expressing of interest launched on 13 December, and the strategy of the data has started, and anybody who would like to look at the terms of (?) they will see it on the website on (?). 

Finally, I'd like to invite you all at 3:00 to Room 12A where we have our digital transformation (?) sector.  Thank you very much. 

>> WISDOM DONKOR:  Thank you, Ms. Tanya. 

So we have the last presentation.  It is very brief for us to have more time to go into discussion. 

>> Panelist:  Good morning, everybody.  I am going to present on (?).  My name is (?) I am a university professor of computer science in Kosovo, and I have worked for the government for several years in the field of open data. 

So the Kosovo Open Data Initiative began three years ago, and as we say, a big journey begins with a small step.  It began with an open data strategy action plan, which involved public‑private institutions and NGOs, and the overall objective in the beginning, it was to improve transparency, and then further on, it was to stimulate the business environment and to create demand and supply for the open data. 

Moreover, the objective of the national plan was to harness the ICTs and to foster innovation using the open data. 

Next slide, please. 

So, open data for development is an objective that was from the beginning streamlined in Kosovo, and what we're doing is we are leveraging the open data for evidence‑based policies.  We started with public procurement open data, and with census open data.  Also with financial open data, which seemed to be the most important in the beginning of the process of making open data available in Kosovo. 

Further on, after we have opened the financial data and the public procurement data, there was a need to open up the environment data, and especially the field of air quality, land, and water quality.  Moreover, there's a strong focus now in the consumption or consumers open data, where we want to track the different consumer behaviors, and where we want to strengthen the businesses. 

The overall goal of open data now is to (?) the economy. 

On top of that, we have started with open data for agriculture and nutrition, and with the help and the support of the global open data coalition, which is the GLOD, we have started for (?) nutrition, and this has proved to be very important for strengthening reformers, and for economic development in Kosovo. 

Next slide, please. 

So which are the tools and instruments for collecting open data?  Open data collection is one of the most difficult process in the open data initiative, and we're using two approaches.  The first approach is via surveys, which are online and on‑site. 

And the second approach is via administrative data.  However, there's a big challenge in the need for qualitative data, because the data which are being collected, either via surveys or administrative data, often lack the quality.  In the case of surveys, these are mostly based like ‑‑ subject‑based data, which could be sometimes inaccurate, and it is very difficult to measure and to verify the accuracy of those data.  In terms of administrative data, the challenge is that most of the time these administrative data are outdated and we need more up‑to‑date administrative data. 

Also, there is a strong need to gather and fully harness the potential of ICTs for open data collection extraction and (?).  And if we harness the pools that we have at hand today, the ICT tools, that we would have better data collection and better qualitative data. 

Next slide, please. 

So what are the challenges for Kosovo and data initiative?  First of all, there's still three years later a limited available open data.  There's open data, of course, over the government data sets, but there's a lack of resources for data collection and for measurements.  Kosovo has high productivity and very strong infrastructure for ICTs.  There is an 80% Internet penetration in Kosovo.  There is widely available ICTs and computers and servers and data centers. 

However, the use of centricity is lacking, because we lack on the (?) data and the users are still not using as much as they should the open data. 

So we need to tackle this.  We need to work on user centricity and we need to work on the ways to harness the potential of open data for usage.  And we need to increase the open data usage in Kosovo. 

Next slide, please. 

So, streamlining open data is the most important thing based on our experience, and we have to look ‑‑ which are the ways forward for streamlined open data.  This is an ongoing process.  And based on our experience, streamlining open data is made possible via the following global mechanisms. 

First of all, with United Nations through the Sustainable Development Goals.  This is a very good mechanism which is now fostering the increase of usage of open data and collection of open data. 

Second of all, we are streamlining open data via (?) and this is also very important because World Bank is helping us through the PFSCB mechanism, which is the trust fund for statistical stability, and they've been an amazing global player in opening up the data, including in Kosovo.  So based on our experience, they are also one of the ways to streamline open data, and we're looking forward to collaborating. 

Another streamlining mechanism is the Global Coalition For Sustainable Development Goals and this again comes from the UN and the World Bank initiative.  It is a cross‑cutting initiative, and we are working with them.  We are streamlining open data with them as well. 

And finally, I would like to emphasize the Global Open Data For Agriculture and Nutrition.  I am very happy to see here next to the CEO of GODAN, who is working on this and who has helped a lot in opening up the data for agriculture and nutrition in Kosovo. 

Next slide, please. 

So which are the short and medium‑term objectives for open data as we move towards this process?  First of all, data gaps and financing.  There is a lack of resources in Kosovo and there is a lack of budget for opening up the data, so we need to find out new financing instruments in order to foster this process. 

Encouraging data use.  There is a lack of user centricity and a lack of users, so we need to find ways of increasing usage by means of ICTs, by means of creation of businesses. 

Third, strengthening the open data echo system, by creating new businesses based on open data, and this is a huge opportunity, because when you open up data, businesses have another levy to create new businesses.  For example, if we open up transfer data, we could create private businesses that make it possible to buy tickets via those businesses, who provide the better interface, and who are using the open data for transportation from the public institutions.  So that would be a huge opportunity. 

And also, other opportunities in the economic environment. 

Fourth of all, improving open data systems.  In order to improve the open data systems, the open data collection mechanisms, we need to work more on harnessing the ICTs.  And as we advance in the technology field, we are having new tools, we're having new ways, new instruments, and we have to be sure that we are using those tools most of the time, those tools are free and available to be used.  We have to make sure that we keep up with the updates to technology and to make the most of them. 

And finally, the fifth short and medium term is the policy on enabling environment for open data.  This I would say is one of the most important aspects in going on with the process.  We have to keep up the momentum.  And we have to keep up with a new and updated policies, with the new and updated strategies and action plan for opening up the data. 

Next slide, please. 

So what is the way forward with open data?  First, foster global cooperation, with UN, World Bank, UN development goals, GODAN.  We have to further foster this collaboration and we have to find new ways to collaborate. 

Second, increase the demand and supply, opening up the data, it all depends on how much is the demand and how much is the supply.  So we have to find new ways in increasing the demand, and also increasing supply.  The more we have supply, we will have higher demand.  And vice versa.  More demand will have higher supply.  So this is a triple helix between institutions, public institutions, private institutions and academia that we have to work in increasing the demand and supply for opening data. 

Also, use of ICTs.  We have to find new ways of increasing the ICTs.  And finally, innovate with open date.  As I said, there are new businesses being created as we speak, and opening of the data increases enormously the innovation in the business sector, because businesses could collect those data and link those data between the different data sets, between the different open data sources, and create new alternatives in solving problems and issues in the society. 

With that, I would like to thank the CEO of GODAN, Mr. Wisdom Donkor, the head of Africa Open Data Initiative, very glad to meet him and work with him, and also all of the families and stakeholders in the open data movement.  Thank you so much. 

[ Applause ]

>> WISDOM DONKOR:  Thank you very much.  We will take a few questions, and then we move straight to the next part of the session.  So if you have a question for them, raise your hand.  Okay, so the first ‑‑ one minute. 

>> Thank you very much.  What incentive do you give to the people who work with you on gathering the data?  For example, I know that the local guides programme that is available, you probably have to do that to get people onboard. 

Secondly, how do you get those people on your platform? 

>> I promise to be brief.  First is sometimes (?).  Second is through cash disbursement.  We talk about how we get there. 

So it turns out that there were already pockets of networks all across the country.  So what we did is ‑‑ I hope you can hear me.  What we did was approached those networks and kind of created (?) other agents, and bought them on that same day and put them in a group where we can constantly share educational materials to get them better. 

>> Audience:  A Geneva‑based NGO.  We participated in the 2030 agenda and with (?) from the start, and having listened to the very interesting presentations of the panelists, I was just wondering, for countries ‑‑ for instance, I'm making reference to the presentation on Lebanon, the struggle there is that you have formal and informal societal structures, which can be more difficult to get a meaningful monitoring in terms of the SDGs than if you almost had no multiplicity of formal or informal structures. 

So the leapfrogging that our colleague was suggesting for Africa, wouldn't it be best to find a way to use ground truth methodology, meaning mobile phones, to leave the complexity of informality and formality, as is the case, for instance, in Lebanon, as well as in many other countries, and to go into mobile phone based direct data collection from the ground as was exemplified by what Tommy is doing in Africa. 

>> WISDOM DONKOR:  Is this for Lebanon? 

>> Panelist:  Okay.  The data we will be collecting actually already exists in the databases of the institutions, the government institutions.  It's official data, and we will be later using mobile ways of ‑‑ not gathering the data, but actually displaying the data. 

Now, I can't see how we're going to get official data ‑‑ well, I can see (?). 

>> WISDOM DONKOR:  Mr. Andre. 

>> Panelist:  This is a very interesting question.  I don't pretend to have the absolute wisdom on this, but I see different parts of the world four approaches to this issue of collecting data, whether it's informal or in formal systems, with various levels of success. 

One is some places they rely very much, whether it's NGOs, on champions to get people to provide data.  And that works to some extent and for a certain time. 

Second approach, some have tried to pay people to provide data.  The downside with that is that it sometimes works for a little while, but then the reliable of the data becomes questionable.  At times, people will tell you whatever data you want just so that they get paid for it.  So it doesn't quite work. 

Third one is ‑‑ I think it's really a sustainable one, it has to do with the business model of system kind.  So giving of data, or whether it is in the context of a survey or any other form of data collection is about as exciting as filling an income tax report.  I mean, nobody really likes that.  You're busy doing other things and then these guys, they come and they start asking questions and you don't have time for this reading, and even if you do, then you don't really see the return coming out of that. 

So the best way is if you can find a way to get the return, some kind of a benefit out of it.  That's what governments are trying to do, but by providing service ‑‑ in fact, the former director of the World Bank was picturing it like that.  He said, you know, governments and their research centers, they have a lot of information, which, in fact, citizens pay through their taxes.  In fact, said they own it in some way. 

But by making it available to all we make it available among others to private sector that can then develop applications, ways to simplify the data to make it more accessible to people to provide services. 

Somebody mentioned transport as an example.  My field is agriculture, but I use other ones also.  In the city of London, when they decided to open their data about transport, they had a problem, the congestion problem.  Basically, some metro lines or train lines were overcrowded while some others were unused, so there were peak times when it was just jammed, and other times, not so much. 

So, they would just tell them the way it is.  So that was the original idea.  But then it had the surprising very good effect for them, because people found ‑‑ and right now, I can't tell you where my bus is right now at this very moment.  And if I see that I would have missed it, then probably I would walk, or I would take the train or I would take the subway.  I'll take another way. 

So the unforeseen impact is that it regulated the flow of traffic, which was very good for the consumers because this way, they don't wait for a bus that's already gone.  They take the fastest way to get there.  But the interesting part for the city of London, because that's often the problem in business cases, who pays for making the data available and keeping it up to date. 

Well, for the city of London, the return on their investment, what it did cost them to make data available, and now the influx they get and the better use of their traffic system is 70‑to‑1.  If you want a good business case, that's one right there. 

But the last one, and now I'm back to agriculture is, at the end of the day, it's human nature to do any kind of effort or action, especially if it comes out of the ordinary, out of what you normally do.  There has to be a benefit for it.  And I'm just thinking of one life example I think from Thailand.  It may not apply everywhere, but that's an example.  There, they have the cooperatives where they say, okay, we're going to provide data to farmers, whether data ‑‑ market data, data that will help them grow their stuff better. 

The way they used to work, farmers would go to their cooperative to buy their seeds for the year or whatever they need, and they would say, okay, I'd like this here to plant this rice, and maybe they get advice, maybe not.  They try to build up the capacity of these cooperatives, and now not only do they provide rice to the farmers and which type of rice this year is going to be best or when is the best time to plant and think that that can help or harm their crop this year, but they computerise it, so that each of the cooperatives, they get an iPad. 

So when you come there, their advantage is that the plots are pretty well‑defined, which is not the case everywhere, but over there it is.  So I can come there and I can say, okay, I have plot number 35B, and I intend to plant rice this year, but I'm not really sure if I should plant this one or this one.  Well, they're going to put that in and tell me that this year, based on current conditions, this one would give you better results than that one.  So it's very helpful for the farmer, but it's also helpful for the cooperative because at the end of the day, now they know everything that's growing in their neighborhood so that they can plan, okay, we need more seeds this year, or we need more fertilizer or less of something because the demand is going this way or that way. 

So it's an example of a win/win situation, which some may say leads also to privacy issues, but that's another discussion we can have. 

>> WISDOM DONKOR:  Thank you, Andre.  We will take one more question.  Okay.  So two more questions and then we move into the next session. 

>> PARTICIPANT:  Hi, I work for the Pacific community.  We work for the governments of the Pacific island countries in the area of health, et cetera. 

There are quite a few challenges in relation to data.  But one of the key challenges that we have is the issue of data sharing policies and agreements.  It has been quite difficult for us to enforce this because people are reluctant to share data.  That's one. 

Two is the other (?) is having a sustainability plan or exit strategy.  Projects come and go.  People create data systems.  It gets ‑‑ when the project ends, it becomes (?) and then you leave all that data.  So the two things that ‑‑ I mean, the one thing that I would like to ask is that if there are any strategies that can overcome these challenges that we have, because it's a growing concern for us, and we are constantly looking to (?) and also opportunities to sort of collaborate and find partnership in doing this work in the Pacific region. 

We have a fixed data hub and we collect a lot of the data across the Pacific in a lot of areas, climate change, climate data, resilience, agriculture health, et cetera, so these are some of the issues that we are currently facing and it would be nice to get some strategies on that. 

>> WISDOM DONKOR:  Thank you very much.  I think we should take the last question. 

>> PARTICIPANT:  Good morning.  My name is (?) I am from Brazil, and I am here by the IGS province, the Youth Programme. 

I think my question is close to hers.  I would like to know more about how can we share quality of data.  You talk in the presentation a lot about the challenge through collective data.  But how do you assure the quality of the data?  Thank you. 

>> WISDOM DONKOR:  Thank you.  Okay.  One last question.  You have 30 seconds. 

>> PARTICIPANT:  Thank you.  I am from Pakistan.  Open data (?) and the open data packaging.  In developing countries, digitisation process is challenging.  And the developing countries are still working on the (?) in terms of agriculture, in terms of help, in terms of citizen experience automation. 

So the first step is basically the digitisation.  In the developing countries and the concept like the open data will be accessible.  So my request to the panel, what are your recommendations that you know it is a long‑term process.  So how developing countries should make a strategy to progress on open data in terms of maybe (?).  Thank you. 

>> WISDOM DONKOR:  Thank you. 

>> Andre:  Okay, I'm going to try to answer three of you.  So first of all, regarding data quality, so there are many mechanisms to ensure the data quality and to verify the accuracy of data, and starting from data collection, data curation and verification.  But what is the most important in this aspect is that once you open up the data, once the data is available, then the public can challenge those data.  And the public can ensure that those data are accurate. 

If we do not open up the data, then nothing has to be challenged, and this data will be taken as a fact.  So this is one of the more reasons why we have to open up the data. 

In terms of data sharing, as the lady said, as you said, you're very right.  People are reluctant to share data, and sometimes no matter what kind of strategy, no matter what kind of public body for data exchange, like a data exchange agency, things will be very difficult because as you've said, people are reluctant to share and to collect. 

But on the other hand, people are not reluctant to share, let's say, for example, private data, which is being shared on the social network.  So we have to work on this.  We have to make sure that open data is well understood by the public and it is being embraced by the public.  Open data is not about personal data.  It is data that can be freely shared, used and modified without any obligation. 

But, if it's being ‑‑ it doesn't have any, like, personal context. 

So if we open up ‑‑ if we share our information, prior information on social networks, why we shouldn't share the data that is collected by the different organisations, public and private organisations, because open data is not just about public institutions.  Remember, it's also about private institutions. 

So we have to work on this and sharing new ways of open data. 

And finally, the question regarding the digitalisation.  I fully agree.  If there is no connectivity in some country, then opening up data is very difficult.  You have no way to use them.  But the good news is that connectivity is improving.  In some areas, of course we are still far from that.  But it is a ‑‑ it is a prior condition.  So we have to have connectivity in order to have open data. 

And I would say we could go in parallel with increasing connectivity, increasing the availability of open data, because as I've said, this will improve the economic environment.  You can just imagine if you have open data available for any kind of sector, how much businesses and what kind of businesses you would be able to create.  And those businesses would have not just web interfaces, but also mobile interfaces, and sometimes an interface is sufficient to create a new business, or to innovate with a new business. 

And so I think we have to keep up with this momentum, and to leverage all of the strong reasons why we need open data and to work more towards this field so that public and private institutions open up the data and we move with this very important process. 

>> WISDOM DONKOR:  Thank you, Doug. 

So we are going to move to the next session, but before we do that...

(?) to go to the next session.  Okay. 

>> MARILYN CADE:  Marilyn Cade.  I just want to resume my mistress of ceremonies role for a moment and introduce ‑‑ we're going to have the opportunity to hear from Torben Frederickson, the chief of one of the very important parts of UNCTAD that is engaged in helping to measure, analyze, and publish all of the present approach of the data gathering and analysis that UNCTAD does.  I've asked him to join us.  He has competing opportunities, so he graciously changed his schedule and is joining us.  He'll be explaining to you a little bit about his job here, his role, and then I'm going to hand out a short flier and he will also say a little bit more about his commerce week. 

>> THORBIN Frederickson:  Thank you, mistress. 

[ Laughter ]

I understand that you were discussing throughout this morning the link between data collection and the sustainable development goals, and from UNCTAD's perspective, it's very much focused on how ICT can be used in enterprises, how it can strengthen the digital and ICT sector, but increasingly, there's a strong focus on E‑commerce.  How do we measure that?  The sad thing is, if we go to developing countries, we have hardly any statistics in this area, and that makes it very, very difficult for governments to actually prepare and implement effective policies in this area. 

So when UNCTAD had its ‑‑ you know, UNCTAD is the UN Conference on Trade and Development, we have our office in this build, a global body within the UN, and at our last ministerial conference we held in Nairobi in 2016, Member States decided to set up a new intergovernmental group of experts on E‑commerce and the digital economy. 

The first session of that group was held in October this year, only two months ago.  One of the concrete outcomes was a decision by Member States to establish a new working group under the intergovernmental group of experts dedicated to measuring E‑commerce and the digital economy.  We see that among OTB countries, there is some data available, but even there, it's very limited, especially if you want to look at how trade in the digital sphere is evolving. 

We have group data on trading goods, in trading services, but it's very difficult to distinguish how much of the trade that is a result of electronic commerce. 

At the same time, we have, for instance, Sustainable Development Goals number 17, and there is a target that is aimed at improving the share of developing countries, and especially the least developed countries in global trade. 

Now, as more and more trade goes digital, if more and more trade involves E‑commerce, we need to ensure that developing countries also go digital, otherwise, they will simply not have a chance to participate in the growth of trade online.  So that's why it very important to have this gathering of data in the relevant areas.  So we will send other bodies that can be involved in collecting data. 

And then they will come here to Geneva and we will talk about how one can foster the data collection and data analysis in this area.  But given the way that digitalisation works, we will also have to have close collaboration with the private sector, because a lot of the data that is relevant to measuring what's going on will come from E‑commerce platforms, payment platforms, so on and so forth. 

And the question of data and development has featured in all the E‑commerce weeks that we have held so far.  It is a week that discusses anything related to E‑commerce, digital economy, and development, and I will ‑‑ it's a very multi‑stakeholder approach.  We have a lot of participants from the government, from the national organisation, from Civil Society, and the private sector.  Also academia. 

So I would just encourage you, whatever you discuss in this conference, especially to the extent that it also touches upon the E‑commerce or the economic dimension of development, keep the E‑commerce week in mind and see if we can also contribute to further the dialogue that you are starting here today many this conference. 

I will not take up more of your time.  I am in the round this way, so if you need to get hold of me, I would suggest you go through the mistress and she will know where to find me.  Thank you very much. 

>> WISDOM DONKOR:  Thank you very much. 

[ Applause ]

>> WISDOM DONKOR:  Andre, I will hand it over to you to continue with the next session. 

>> Andre:  Thank you very much.  I think we've gradually slid into the final session, which is I think what I was discussing with Wisdom is that instead of breaking up in groups, I don't know about you, but I like very much this kind of exchange and dialogue that we are having, so I think we should maybe continue that way, if that's okay. 

So, first I would like to just have a few words on the questions that were asked before this intervention and maybe introduce you the five points, some of which we have partially addressed, but that we should maybe discuss a little bit more. 

First, it's hard to come after him because what he said was ‑‑ you read my mind, I was just about to say it.  I think what he said was perfect, especially in relation to the quality of data.  If you think of Wikipedia, for instance, it's an example I like to quote, because when it first came out, it was full of mistakes, as we know.  But in a fairly short period of time, it improved quite a bit.  Now it may not be perfect, because it's quite good.  Because it's exposed, it was open.  The minute there was a mistake, somebody around the world would point it out and got it prevented.  So that's one advantage of opening data. 

The second one, which is really a fundamental point that we're hammering a lot, and it has to do with breaking the silos or link to open data, as it's called nowadays.  There was a nice workshop in Berlin.  In fact, recently on this issue, because when you combine data from different sources, it allows for many different things.  It allows for one thing, to cross‑check the data that you have. 

In one of the countries where we work, when we started comparing trade data with production, agriculture production data, we found that according to statistics, they exported more than what they produced.  So obviously, there was a mistake there.  Other places, according to statistics, they would have consumed incredible quantities of sugar, which would have made everybody diabetics.  So obviously there was another mistake there.  By comparing, you do nice things.  Then you can become much more efficient.  Another country, they're saying because it's very costly and that country has to be very big, they can only afford to do ag surveys once every ten years, and even then they don't go everywhere because some parts of the country are very difficult to reach. 

So that means most of the time they navigate in the dark a little bit in trying to find what's going on in their country.  This is what geodata comes up, because the most recent (?) are extremely accurate, not only in telling me where things are growing or not growing, but how they are doing.  So you can use this, among other things, for predictive analytics.  You know much better what surface is being cultivated, but also how your crops are evolving throughout the season and being in a better position to predict what's going to happen. 

So that's linked open data. 

And then we spoke about digitisation of data.  Statistic for you.  In 1987, less than 1.5% of the world's data was in a digital format.  In 2005, it was 97%.  So the issue is not so much to get digital format.  The problem is that it's very fragmented, as my colleague said earlier.  People tend to keep data on their computer, and the sharing of this data is inefficient at this point in time, which leads to another problem beyond the fact that it leads to duplications and the fact that it's not shared, but the data person who retires, for instance, oftentimes somebody takes over the computer, reformats it or whatever, and that data is lost.  So that's one of the ways people ‑‑ one of the things people are trying to address by having these repositories where reserves data in particular can be stored and kept for posterity. 

Now, I hear ‑‑ I am going to interrupt for a second, because I hear the chief ISD in the African Union is here and has a contribution to make, so I would like to give Mr. Moktar (phonetic) a chance to speak.  I don't know where he is.  Please, you're welcome. 

>> PANELIST:  Thank you very much for this opportunity.  The good thing about speaking last most of the time is everybody has said what you have to say, and then you don't have to say anything more.  I will have to be very short and sweet and stick to the point by saying something that hasn't been said.  So to make it a little bit spicy. 

Now, first of all, most of the time when people speak about the SDGs, it is thought it is some kind of programme for developing countries, which is actually not the case, because the climate change issue has made it also universal in general. 

Number two, the concept of developing or implementing those programmes are always kind of linked with the programmes, because most of the countries should and must invest by putting their domestic fundings.  The African Union specifically decided that they will be using 1% of the stock of all countries to use it to form government programmes, with the hope that one day we'll be actually independent from aid and international support. 

The statistics that are actually ‑‑ or data that should be generated to address many, many of the indicators that we do have, probably when you look at the number of indicators we do have, 230 indicators for 190 countries, a huge model of data.  But the good thing is technology is capable of helping us to do all of the things. 

We have so much of data, so much of personal data, and the data that somehow we can say that it is the end of (?) and the rise of functions, if we speak in terms of mathematics.  So we go exactly to ‑‑ we are not able to ‑‑ capable to exactly transfer probabilities into exact science.  But we ‑‑ this form of technology doesn't really help us at the same time to get to those data, because most of the time data will be very, very poor, and therefore cannot be meeting the requirements to have the ‑‑ to have a very informal decisions about what's happening. 

Coming back to SDGs, from a Africa point of view, we have a vision.  We have the same indicator, and to do what is mainly in a very coordinated manner, actually in line with these SDGs. 

The problem we are facing is the poor quality of the data collected most of the time.  Although we have the system to connect them, because we have started one of the biggest programmes that could address most of the MDGs for (?) and it has been actually on for since 2010, and the programme governs the ICT sector, the energy sector, the transport sector, and the (?) sector.  The development will unload to address most of the (?) goal, specifically with regard to the energy sector. 

We have what we call the African renewable energy initiatives, which countries have (?) on the programme.  Billions of dollars have been pledged for.  Goals and aspirations we do have in our agenda 2063. 

Again, the (?) has been a programme for effective development in Africa has been on since 2010.  Some of it has been implemented, specifically with regards to the ICT sector.  Two of the priority programmes out of 300 implemented within the country, actually has input a lot.  The InterConnectivity, specifically in (?) systems, says that $65 million could be used for ‑‑ out of the continent to be uses for other programmes that are going to happen. 

We face this issue of connecting data and the quality that is required.  We are improving.  Technology is improving.  Next year, we will have it better than we had.  (?) so this is all I wanted to share with you swiftly, nicely, and I will be happy to answer any questions.

Thank you very much. 

>> PANELIST:  So the floor is open to questions. 

>> PARTICIPANT:  Thank you for enlightening us on the progress of PIDA and other projects that are close to our heart.  Now, is Africa a data desert?  I have just come from another session on artificial intelligence and policymaking.  One of the risks that was pointed out at that area was that a lot of these robots and technologies that learn from data are learning from biased data sets, where data sets from certain regions and certain populations are mixing.  And I'd like his comment about whether a lot of that missing data is from the African continent, which everyone is now looking up as a very good market for their product. 

But the products have not learned on African data. 

So, do we have a data culture, or do we have more of an opinion culture where we listen to people who are authoritative, but were not really looking for the data and trying to build modern (?) ourselves.  So those are my two questions. 

>> PANELIST:  Wonderful questions.  Let me first answer the first one with regard to missing data.  Now, there is a principle, if you let people (?) meaning if somebody is generating outside data and applies to you, then (?).  We start collecting data, our specific data.  I don't know why you have to do that, because for instance, IT has them.  But IT has collective data, for instance.  And need their own analysis dated on their own environments.  And this is where it is important for me to have my own data and do my own analysis and do my own definitions to defend myself.  It is very important for you. 

In fact, we as the specificities of the developing world has really being missed because we have the tendency to standardise everyone, to say that every criteria applies to everyone.  I will give you one example.  It happened to me during my first year as an engineer. 

When I start doing my first ‑‑ this was 20 years ago.  I had been told that the (?) for you to define the number of (?) for a telephone is to assume that you have a number of teachers, a number of doctors, a number of whatever professionals, and supposed to have a phone.  So therefore, will extrapolate the number of (?) required.  Base it on what you call economic (?). 

Now, if you go back in most of the African countries, the data cannot (?) on the phone.  The teacher could not afford himself a phone.  So therefore, I cannot assume that the income of the doctor or a teacher in Africa is equal to the income of a doctor somewhere else.  And therefore, my (?) is biased. 

So this is the same thing.  Today, we continue comparing an apple in Africa or in Asia and the same criteria.  I don't think that's the approach that will be at least as objective as it needs to be.  Specificity has to be taken into consideration.  And therefore, the analogies need to be appropriate to the culture, because the perception of democracy are not in the same ‑‑ there is no (?) values to define a lot of what may happen in the sector. 

Place, culture, and individual need to be taken into consideration. 

Second question.  No, we don't have so far in Africa data counter.  We don't have this so far.  And we hope we will be thinking of something like that.  (?)

>> MARILYN CADE:  Marilyn Cade speaking.  Thank you.  I must say that ‑‑ and I really want to compliment all of you on how interesting and informative this has been, and how much I feel that we're all learning from each other, and how important it's going to be now to kind of take the step of, so what, right? 

But I want to just make a couple of quick ‑‑ throw out a couple of quick ideas.  I've heard statements from some of the speakers about the interest in finding partners and finding other data sources, so I'm going to make a comment about that in a minute in an idea I had. 

But I want to go back to the comment you made about are we an opinion‑based culture or are we a databases or information based culture.  I organised the session yesterday on fake news, disinformation and misinformation.  One of the things we talked about was the problem about artificial intelligence learning from inaccurate information or biased information because of the way the marketing programmes are established, and the way the data is gathered.  There are other problems in creation of false information, where false websites are set up to sort of ‑‑ as a marketing ploy that make it look like there's things going on that perhaps aren't.  And I do think this idea, as we continue to work together, this idea about how do we get past opinion, or misinformation is really something that's going to need a lot more discussion.  Particularly as ‑‑ because there is so much data, there's always going to be an interest in trying to automate, automate, automate, use artificial intelligence, et cetera. 

So that's one point. 

The point I wanted to make is there are now 101 national and regional IGFs.  So 101 countries have a national IGF.  That's not true.  There are ten regionals, and as a matter of fact, Moktar is the major champion of the African IGF. 

But one thing I was thinking about, and Wisdom is the coordinator and champion of the IGF in Ghana.  One thing I was thinking about is perhaps we should be thinking about how we broaden our inclusiveness of invitation to representative spectators yourself and other speakers to come and speak at the national and regional IGF as an objective, so that we are beginning to bring together these communities and these issues. 

The national and regional IGFs are very focused on achieving the SDG.  Just to throw that idea out, because I have two experts I see, one from Ghana and from the African continent who are very familiar with the national and regional IGFs and the opportunities we might have to have a day zero event, which would also help to strengthen the work that needs to go on, but help to enhance the participation in the ‑‑ in our eyes. 

>> PANELIST:  By the way, my answer to you was not really accurate in the matter of do we have data counters.  In fact, and this is just because we just triggered the IGFs.  We are starting generally in 2018 a huge programme, a platform to coordinate among all African stakeholders.  The Member States and the national IGF forums would be contributing. 

It is also in parallel capacity, and we'll be setting up all national forums, and even (?) each and every country.  Moving up and having that platform where everybody can contribute to the data and therefore probably somehow create the data the (?) but we will have now our own statistics and our own (?) of the data. 

But, again, this is specifically related to ICT matters.  It should be comprehensive.  We should not limit ourselves to (?) only to ICT, national IGF, whatever et cetera, but (?) climate change, all of those issues, all of those aspirations, so we do have ‑‑ we need to make sure that (?) now. 

Now, do we have that luxury to go beyond our mandate, because we have to (?) has to be taken into account, but what should be the contribution of ICT in general.  So at least we'll do that hoping that one day we'll be having some mechanism that will allow everybody to have a real approach that will define the impact of the SDGs in general. 

>> PANELIST:  I want to follow up on your point regarding artificial intelligence and fake news and how could data be used with fake news, and how could official intelligence algorithms use those data. 

Well, first of all, it is true that the fake news phenomenon and ‑‑ is becoming wide and we have seen this in the social networks.  And on the other hand, I would say that if we make data available, if we bring more data, this would enhance the verification systems and the reputation algorithms.  We already have ‑‑ I think that we already have algorithms and artificial intelligence algorithms to verify sources, to verify fact, and the more we have, the AI, the artificial intelligence algorithms would be. 

Artificial intelligence systems are improving, and I will give you an example for that.  In the past, we had the possibility to upload, for example, (?) videos on YouTube, Facebook, et cetera, and that video would not be taken down because it wouldn't be detected as copied.  However, nowadays, we have artificial intelligence systems algorithms who can track those videos and can automatically see that they are copied and they will be taken down. 

On the other hand, what the users did, they stripped the video in the beginning and at the end of the video and they uploaded only some portions of the video, and then artificial intelligence algorithms were improved, and now data can even do that.  You cannot even upload a video without the rights into YouTube or Facebook or other systems. 

So, artificial intelligence is not something that will actually threaten the societies.  In terms of to actually make better societies.  And all of that is data is used properly.  Bear in mind that even with TV, Internet, radio, all of these media mechanisms, they can be used for good and for bad.  And so it is up to the users to determine how these will be used, and Internet also has the ‑‑ that kind of potential of being used for bad purposes. 

So artificial intelligence as well, it will have the good dimension and the bad dimension.  But it is up to us to make regulations maybe or to educate and to use mechanisms so that we can ensure that artificial intelligence is used for the good of societies, and for the advancement of human kind. 

And there are many examples of where artificial intelligence can improve the user experience and can improve the human life.  So we have to make sure to follow up on those examples and we have to make sure that we do not create bad usages of the new systems such as artificial intelligence.  Thanks. 

>> Andre:  Thank you, we have to keep track of time.  We have two questions, this gentleman has been waiting a long time, one here, and one here, and after that, we'll start wrapping up. 

>> PARTICIPANT:  Thank you for sharing the (?) of Africa.  Of course, you adopted sufficient strategies for moving forward on these projects. 

Any question is that if the developing countries and other (?) want to adopt your projects as a case study, how they will follow?  Thank you. 

>> Andre:  I think we should take the three questions, so it will be easier.  Your turn, please. 

>> PARTICIPANT:  Thank you so much.  My name is (?) from Austria.  I happen to be a coordinator for the SDGs in my Ministry, which is the Ministry of (?) Innovation and Technology.  I am also in ITF now for ten years, and I observe that (?) are system‑focused, but this would not lose track of (?) emphasize that SDGs are on a much larger scale to be debated.  So we have to take into account climate change and all of those issues. 

And also, my (?) has set up (?) where we are dealing with data provided at the national statistical institute, which is entirely independent institution, working together with SDG, IPUs, and (?).  So these data (?) transparent, so everybody can look at the home page and make up ‑‑

(no audio)

>> PANELIST:  There was exactly that debate on CNN, so there may be phenomenons that are not that universal.  But there are some regional realities that are different for sure, and I'm sorry this person left on the sustainability of models that we elaborated to manage data. 

In Colombia, there's a movement called (?) where farmers decided to establish their own platforms so that they can trade, deal with markets and so on, and so they subscribed ‑‑ I think it's $35 a year or something.  Some people may say in some places in Africa, $35 is a lot of money.  Some other models, one that I'm pleased to have a nice clip on YouTube, another partner of ‑‑ called (?).  They're from Ghana originally.  They started with a donor‑funded project where they would provide on cell phones weather data for farmers, so they did that for a number of years, but as the funding was about to dry out, they thought, what do we do?  We can't charge people for something that used to be free before, because they're not just not going to go for it.  Unless we bona fide the system. 

So we thought, let's add in there things like market information, so instead of selling it to my regular market, I know that the other market will pay me more today, so I'll go there, and same in buying stuff. 

As we speak now, five years later, (?) covers 350,000 farmers in 16 countries in Africa.  And they all pay a little bit for it.  But average income NSOCO numbers pay anywhere between 10% and 30%.  So it's much easier to ask people to pay from additional income they get than from some possible income they may get.  So that's maybe one thing to think about. 

So anyway, I conclude with that.  Once again, I thank everybody, and this has been an extremely rich discussion.  Thank you, Moktar.  Thank you, the panelists, everybody, it was a fantastic session.  Thank you to all of you. 

[ Applause ]