Transcript: Opening Remarks at Archiving Kenya's Past and Futures

Transcript of Opening Remarks at "Archiving Kenya’s Past and Futures: Stewardship and Care of Research Data"

November 12, 2019

Venue: McMillan Library

Speakers:

Angela Okune

Leonida Mutuku

Initial transcript done by https://otter.ai and cleaned and edited by Trevas Matathia.

Angela Okune  0:00 
Maybe just also an acknowledgement of the various sponsors. First and foremost Book Bunk. We're so grateful to have been selected to actually have our event here. This is an amazing space. I think it's quite different from anywhere else. We could have held this event and so we're really appreciative for all of their support, including support with photography. So Moses from global audio is there helping us with even the sound system. We have circle and square productions are helping with video and photos Spez who will be feeding us during tea and and lunch. And we have other sponsors listed here at the bottom. So a big thanks to everyone who helped to make this event possible.

So in many conferences in Canada and increasingly in the US, acknowledging the lands on which the event is taking place is becoming kind of a new norm if you will, and a way to insert awareness about indigenous presence, and recognize the history of colonialism and the need for change in settler colonial societies. And so as we were planning this events, sorry, let me just get this going. As you're planning our events, we started discussing what it would mean to do at land acknowledgement. Because I don't know about you all, but I've never heard a land acknowledgement done in Kenya. But especially given the space that we're in, we thought that it was really important to think about what it means to be in this particular location. So while I hope that being in this space, you know, I mean, it's impressive chandelier that it's high ceilings, and all of these very old book leaves the kind of physical impression on us. I also want us not to just be nostalgic about the past, and not just romanticize which sometimes happens when we're in these kinds of old spaces because, contrary to many of The lore about how Nairobi was just wilderness and a no man's land, before the British. This place didn't start to exist. When the British arrived by and began to develop their base, there are other people, other uses, and other stewards for this land. So as much as we must remember McMillan, in whose memory this library was erected, there are others who are on this land long before the library was ever standing that we should also remember when we are all sitting here and when we acknowledge this land, so I tasked and I asked Syokau and Trevas Matathia, who you've probably seen running around, he's been a huge help and putting this event together. If we could find out a little bit more about who exactly we could acknowledge in a land acknowledgement, who in fact managed this land before McMillan's wife decided to build this library in his memory in the early 1900s. Unfortunately, we couldn't dig up direct records describing what was here pre 1900. But we did find out the Kenyan National Archives some brief mention of nomadic Maasai. But again, these records were written by the British themselves. So as much as today, we might end up focusing on the records, documents and archives that are sitting in this space with us. I also want us to remember the records that are not here, the oral histories about the place of the cold water, the uses and stories about this land that we might never know, we don't have a photo of what was here before the library, because who owned cameras, and what photos were they interested in taking. So let's pay attention not only to what is not, let's see attention to what is not documented and captured, as we also think about what we want to archive and save for the future. Next slide, please.

So just briefly, and the times are a bit off now everything is pushed by about 30 minutes. But this is the kind of setup for the day. So we really wanted this to be very interactive. And so we actually asked the panelists to not necessarily present Long, long presentations because we want to keep it very Question and Answer. So I hope all of you in the audience also feel very, a lot of agencies also speak up. As Syokau was mentioning bathrooms, just housekeeping, you go outside and they're outside located in the back here. And tea and lunch will be in this kid's corner in the in the side. And we also have a gallery exhibit that we put up there. So you can view some of the different spaces that house research data in Nairobi. For those of you I hope most have gotten their lunch, say their name badges, you may or may not have a star on your name badge. If you have a star, then you're in the first lunch group. So we're splitting the lunch into two. So the first lunch will begin at 12. And the people with the star will be the ones who will go for lunch first, and then the others will go for the tour of the library. So the rest of you will be able to go we're going to go show you up in the reading room and a lot of the other collections here and then we'll switch so then the other group will begin at 1230 and and go for the tour those who have eaten and then the rest will come down for lunch. Just to know at registration, you made a completed a consent form. So we are recording. Thank you, Daisy. We're recording this because many people wanted to attend and they're not able to attend. And so for those who are wearing a red name badge, they requested that their image not be captured. So also those of you who are doing maybe some social media posts, if you end up taking a picture with someone with a red name badge, please crop them out. And you're welcome to share everyone who has a blue name badge. This is one way to think about consents and in person identities. And so if you also don't want to be captured on video, but you have a question or remark, you can just write it down and and hand it to some of the ushers. I think we have ushers who will be coming in and helping us during q&a sessions. So you can just have them read it. For social media folks, we're using the Twitter #researchKE and finally everyone has I believe a one pager that you should have received that registration. So we We invite you to kind of jot down your thoughts throughout the day based on the conversation, the tour all your interactions, because we see this as a way for you to actually help us analyze what's going on, and to feed your thoughts into and back into next steps as well. So we'll be collecting these as you leave and digitizing them and uploading them as part of the notes. And so if you don't want yours to be shared, just right at the top, and we won't digitize it, but otherwise, we really would invite you to help help keep this going beyond this. All right. Next slide, please.

So before we jump into the first panel, we really Leo and I want to set the stage in terms of why we felt this event was important and what we're hoping to achieve today. And I'll just start by some background on the political economy of academic publishing, to really make the case for why we today need to be concerned and turn our attention to research infrastructure, especially on the place that I would call heavily saturated with research. But stakes are high in Nairobi, for us to take Care of our research at different levels. So I'll talk a little bit more about the work I've been doing on research data. And then I'll turn it over to Leo, to close us out and talk more about open data specifically in Kenya, and what we're hoping to achieve today. Next slide. When you participate in so many researches, and you don't know what is happening as a result, and it's not changing the environment that we're in, you feel wasted. You keep on asking questions, but this data will go where the one who takes data will never come back to us like, okay, we took this and this are the results, so you feel wasted, like a Kibera resident explain to me, despite decades of research aiming to solve Africa's problems and billions of dollars in funding. Many of those who are studied see little change in their everyday lives, particularly communities, including the Nairobi tech sector where I worked for five years and Kibera in its infamous neighboring informal settlements appear to be increasingly over researched, demonstrating survey fatigue, falsified responses and even feelings of exploitation. Next slide. During four years of managing research as part of the Ihub Nairobi, the community increasingly felt burdened by the gaze of researchers and journalists, everyone asked similar questions. And we grew tired of giving the same responses, because an economist has a different perspective and set of questions than a political scientist, I was told, when I questioned why a researcher couldn't just use the same outputs that someone else had already produced about us. As an academic I understand that logic. But as a research participant, the questions they asked didn't feel different to me. And after taking more than two hours of my day with a masters student from Europe, I specifically asked him to please share the transcript from this interview, so that I could send it along to future research requests, that I knew I would get I never received the transcripts. And I never heard back about any findings or any research outputs at all. And this was not a one-off case. This happened many times. So at the research Ihub research team and I increasingly began to articulate these feelings of being over-researched, we also became hyper aware about our own research practices. How are we engaging with those we studied? Did we also go back and build community with them? Or were we just one and done researchers. So through such self reflections, I began to recognize this is much more complex than just a matter of being a foreign or local researcher. Because we are based in Kilimani and we're just here and we were Nairobi based. And I was the only mzungu. I became interested in how funding incentives and timelines of research structured the work that we were able to do and the types of engagements we were able to have with research participants. Next slide. So this gives some of the background in terms of how I became interested in studying research itself, and also how we might make research more accountable to those who are studied. Since I know we come from different backgrounds, I just want to briefly cover some of the terms that I think will come up today. So for those who have not heard about it, open access is a mechanism by which research outputs are distributed online free of costs and other access barriers. Open Data In a similar vein is a term to describe the idea that some data should be freely available to everyone to use and republish as they wish, without restrictions from copyright and other mechanisms of control. So what do you think of when I say data?
 

[audience murmers]

Metrics, ones and zeros, numbers, statistics, I think often this is our perception when we when we talk about data. But as a qualitative researcher, I defined data much more broadly. to also include textual data like transcripts, written documents, multimedia, like photos, and video and material artifacts like found physical objects. So the open data movement in Kenya that Leo will tell us a bit more about has often focused on government data set and numerical statistical data sets. But today, we brought together those working in research very broadly, not just computer scientists, not just statisticians, because we believe that we also need to be thinking about the unique considerations of open research data Especially qualitative data, which is often missing from these kind of open data discussions. The term open plan just to put that out there, describe this broader umbrella under which open data and open access all fit under. Next slide. So since our time at Ihub research, Leo and I became involved in different open movements. Leo is part of studying the open data movement since the early 2010. And I have been involved with open science discussions. And through that work came across this map, which illustrates the high imbalance in regional representation and published academic work. And this is public published work in the Web of Science. So it's an imperfect map. It doesn't cover every all knowledge is and all works produced. But it does give us a sense of how certain existing academic publisher publishing processes, really privileged certain regions and types of knowledge. Clearly, isn't it? So good, open science that is methods, tools, technologies, To kind of increase public access and participation in science, address some of these inequalities, about whose knowledge is valued or conversely, might actually exacerbate these already existing inequalities and gaps. Next slide. So the map seems to echo what Benin philosopher Pauline Hontogi has written about for decades that too often research on the continent, investigate subjects which are of interest, first and foremost, to a Western audience. Many of the articles are published in journals located outside of the African continent, which are therefore meant for non-African readers. He turned this extroverted scientific activity designed to meet the theoretical needs and questions of the Western Academy and not the society within which the science is being conducted. And I think this echoes a lot with what the opening statements were kind of indicating. Luckily, on our first panel, we actually have someone from Strathmore University Press. And I think it's very important to think about local publishers who are local publishers, and how is it worth that We're creating here actually circulating locally. I've also put in Ngugi seminal work here and Linda to devise miss work on the colonizing methodologies, because I think these are also important work that speak to what it means to decolonize knowledge practices. And this work continues to be relevant. It's from the 1990s. In recent given recent current events in scholarly publishing, next slide. Over the last few years, big Academic Publishers, corporate publishers, like Elsevier, have been acquiring various companies across the research lifecycle. As publishers move towards open access, they've been kind of trying to continue to figure out how they can continue to to maintain their profits, and redirecting business strategy towards the acquisition of not just publishing but actually the whole infrastructure. When I say infrastructure, I mean the tools and services that underpin kind of our end to end research lifecycle. This image here in the gray I think you can see the grey shows the traditional publisher’s role. So usually it comes in about submission, once you've finished your project, maybe write something up and you submit it to a journal. And then it goes through peer review. And and eventually, you know, will go out and be distributed. And let me say most, most especially corporate publishers make a huge profit, because a lot of the labor involved here, like peer review is done for free by other researchers. So in fact, they've they've estimated I think, Elsevier's profits are above Apple's above Google's at some point. It really is a big money making machine. Next slide.

So this second diagram by my colleague, shows the vertical integration, resulting from Elsevier's recent acquisitions over the last five, five years or so. So all of these, these are logos of companies, and also new services that Elsevier has recently acquired, and it shows that from end to end now. Basically, they're extending their influence and ownership throughout the whole process. So this includes right funding. It includes many, many of you maybe have used Mendelli It includes using, you know, software management systems that includes the networking systems, it really covers everything now, and many of us don't realize that actually, these are all owned by the same company. So the fact that these big publishers are strategically taking over this infrastructure needs to be something that concerns us because it really can further exclude originally already marginalized researchers and groups. So we not only need to look at who's doing the research work, but we have to also look at these structures, and how academic knowledge is circulating, who owns and makes decisions about these structures, who's making a profit off of our knowledge, and I think this is the best way to answer the question of whether Open Science really can address structural knowledge and equality it needs to start with us looking at the way that the knowledge is circulating. Next slide. So again, this commercialization of scholarly infrastructure, it really is time I think, to discuss what we need to do to protect, catalyze and further strengthen community-based knowledge repository systems. We wanted to bring it all together here. Because we can't do it alone. I don't know the answer. So I really hope that we can all think about exactly how the underlying systems that run Nairobi research needs to interface and how we might better coordinate amongst our different sectors our different disciplines our different interests in order to supplement and reinvest in a robust public research infrastructure. So again, when I say infrastructure, I'm not just talking about the technical side, but as well as the physical but also the social connections and the the social layers that facilitate how research is conducted. So I really hope the conversation today allows us to think more about what regenerative research processes might look like. So these are processes that don't extract processes that restore renew, revitalize communities, own knowledges and energy and materials. Next slide.

So this is kind of the big context. I know you're talking about this big level of why we ended up focusing on research data today. The notion of data can be viewed from multiple perspectives. And I think you'll see from the way that we've divided divided the panels that all of them actually have some research data at the core there but are coming from different, different lenses. So I've been conducting fieldwork in Nairobi since Jan, this year, especially focused on commercial and nonprofit and academic research organizations. I've been sitting with three different groups throughout the city, doing a multi sided ethnography. And one of the first things I quickly learned was that it was early to be talking and fostering conversation about sharing data across organizations. Initially, I was going to bring everyone together and we're going to start immediately talking about sharing data. But I realized that these organizations were not necessarily sharing data even within the organization with their team members. And this is surprisingly true both of well-resourced multinational company as well as the small side up so it wasn't just a problem that one one group was facing. So I began to seek out where existing public qualitative research data already existed. Where would a student go to begin their research project? Instead of setting up new infrastructure for such resources? What is it that prevents new data sets from feeding into existing public infrastructure. So this is what led me to start paying more attention to Nairobi's archives and libraries, and also what their current and potential role as data managers might be. Next slide. So as part of the fieldwork, I ended up doing a landscape analysis of libraries and archives in Nairobi, including accessibility and the content that they have. For example, I was surprised to find that in one library, there was transcripts and Field Notes typed up from 1992. And so you can find more about there was some really interesting stuff that ended up coming out. And this is a QR code, you can use your phone and snap a shot, that Trevas and Syokau and I worked on. And so this is a digital exhibit, but the physical exhibits which are in that gallery space, also reflect some of them of the things that you can find that online. Next slide. So Trevas and I have also developed an ongoing crowd map, through Ushahidi software that pinpoints various research resources in the city. So our target audience is Kenyan university students just starting out on a research project, who might not know where to go to begin. And so this map really isn't comprehensive. But the beauty of having a participatory mapping software is that anyone can suggest a pin. So I'm sure everyone in this audience has other sites that they would want to add. So if you go to the site there, you can just add it in. And as soon as the admin approves it, it's there. So please go ahead and suggest we'd really invite you to collaborate on that.

So finally, we conceptualize today's events - Next slide - as being at the intersection of decolonial knowledge practices, open data and digital archiving, but the decolonial part is key. Because we talk of open as as if open is always the best. But as opening comments indicated, we need to also ask open to who and open for what? I haven't given up on open. Obviously, I'm still a believer in that concept of openness. But I also recognize that the community and individuals right to refuse to be researched or to be open should also be respected. And so we need to build in infrastructures and systems that also respect the right to be closed sometimes and that openness all the time is not always the best. So different people on the panel will be speaking to the challenges of putting the colonial into practice. But I also invite you to be thinking throughout the day about how we can ensure that Kenya's research infrastructure closes the loop. So that meaningful research gets back to those who are actually studied. We have an open task together to think about how to make scientific research less extroverted, and instead supplement and regenerate what matters to the everyday life that Kenyans. Thank you very much.

And we'll be holding questions. Thank you. Please write them down on your one pager because I think we hope that this will lead us into the first panel and the next panels. But I hope this has generated some discussion points in your head, but please write them down. And then we'll, we'll use them into the panel.

Leonida Mutuku  21:12
Hello. Hi. You know, I realized Angela jumped right into her presentation and we didn't introduce ourselves. So, or maybe you all know her, but you might not know me. Um, I am Leonida Mutuku, a researcher been studying data in its various forms over the past 10 years. Angela alluded to the fact that since the early days of actually, I mean, almost nine years ago. I've studied Open Data specifically in Kenya. And now my research interests have diversified and looking now at new technologies, looking at Big Data looking at artificial intelligence and, in my presentation, bring it all back to her work on research data archiving. So, Angela gave a definition of what open data is. But I just wanted to situate it in our context here in Kenya specifically. And so of course, as she mentioned, open data is freely accessible, used, modified and shared by anyone for any purpose. And usually the only thing, The only caveat that's put is that you attribute the person who first put out that data. And so as you can see, there is a legal openness in that even if you were to find open data and use it for whatever you want to do, make money out of it. Or just you know, for your own personal hobbies, there's no legal restriction there. By the same time, open data as specific, it also looks at technical openness, which means that any machine can basically read that data. So we are talking about your CSV, your Excel, briefs, PDFs. So basically, data that a machine can read. And also, you know, analyze. So open data was coined first in 2003. So in the science field, it's relatively new. And the global movement itself really took off from 2008. So we are basically around 11 years into open data as a global movement. And the whole idea of thinking about open data stemmed from governments opening up government data. And the idea was that if you open up government data Then your government is more transparent and accountable to you, you can really question decisions they're making. And at the same time, that data can be reused by different ministries or different individuals in the private sector as well, for innovation. So those early examples were, for instance, when the Transport for London, which operates the buses and the trains in London opened up their data. And all of a sudden, we had all these like fantastic apps where you could, you know, see we're going to get late or you're going to miss your bus and people made money from that. But at the same time, we also had, you know, weather data being opened up, and that's what a lot of people in agricultural are using, but next slide, so that's a global level. When we bring it back to Africa and Kenya, Kenya was actually a pioneer in this space. So if you think about we've had the Kenya Bureau of Statistics for the longest time. We've had the Minister of planning, we've had Treasury, and a lot of the ministries deal with data. And so data is not a new concept when you think about government and government data, then has been in existence for quite a while. But in the 2000s, Kenya embarked on the digital government digitizing its government processes.

And I'm sure many of you interacted with the e-government initiatives at that point, even just having a government website was fantastic, you know, at that point that you could find up, you know, like where a ministry's office is. And so bringing it back to open data. Kenya was quite a pioneer in this space, led by the efforts of Professor Ndemo and other early actors. So we launched our open data portal, which hosts a wide variety of government data that again, based on the same definitions I had earlier mentioned in 2011. And this was launched by Kibaki, and some of us in the room here were present at that launch. And so Kenya was the second country in Africa after Morocco to set up an open data portal. And at that point, you could find budget data, education data, health data, agriculture data, and a lot of that data is still on the portal right now.

Next slide, please.

However, we have to realize that transparency didn't come naturally to Kenya or to African governments, for that matter. So we are coming from a situation where a lot of government information was held in secrecy. There was an infamous, The Secret Act, which a lot of especially former British colonies had, where government data was a secret from the public. And so governments are very close to public scrutiny and not accountable to anyone but themselves. And so now you're here telling them open up data, you know, let people keep it to account, you know, it will promote innovation. It's a hard sale. And so open data was actually seen a lot as a donor agenda goes, a lot of those early efforts were funded by the likes of the World Bank, etc. So they're like, okay, fine, if you're giving us a grant, or giving us money, we might consider, you know, putting up this portal and putting up some data. And when you start thinking about it, you start wondering what then are the quality, what's the level of efforts in maintaining that initiative, what's the value of the data sets that actually go up against those datasets you just pulled from your desktop and put on your portal? Or is there a systematic way of opening up government data? And so a lot of maps are built by Mapps and Msomething other based on open data, so you could find an app that helps you find your dispensaries. The question is, if you have lived somewhere for a long time, you probably know where your dispensaries are. So that data, that app may not necessarily be helpful to you. And so there's not a lot of scale or impact from these innovations from this opening up data. And government says, so why should we continue opening up data we can see any impact from it. In fact, there's a story I wanted to say and they forgot earlier on so in the open data circles, we know of a group of civil society actors in Uganda who went to the Ministry of Finance and asked for budget data to be opened up. And the minister was like, wait, but we are very open you we always have our budget data opened up. In fact, if you look at the newspaper from June, we published our budget there. So but you remember from my definitions of open data that is not necessarily open data, because you I mean, unless you scan the newspaper, or scan that report, you can't do much with that data when it there. So the lack of scale of open data initiatives in Africa really been attributed to lack of championship and political will from governments. And so maybe that transparency agenda was not the right narrative, to push for open data in our context. And then comes 2015 when the new SDGs or rather the SDGs were availed and became the global development agenda. And one of the big things that were agreed upon by Member States was what is called the data revolution, or basically harnessing both traditional data, so statistics etc. and new sources of data, for instance, how Angela is crowdsourcing from new data on where libraries are, think about mobile phone data, satellite imagery, etc. To help achieve development goals, a lot of times we've mainly relied on censuses which happen every 10 years or those some statistically sample what's what's the word? representative sampling here. surveys to basically understand who you know, our communities resource and location and where the gaps are But when you start thinking about harnessing data and really putting it at the core of the development agenda, then then we start shifting our mindsets around what can be done towards addressing SDGs. Next slide.

So Kenya specifically has tried over the past few years to align, you know, its development agenda from their medium term plans to build long term plans to vision 2030, to SDGs. And we of course, we all know about the big 4 agenda. And so both private sector and public sector actors have been asking themselves how can we use data to really achieve our development goals? How can we harness it? How can we apply it in our different contexts to accelerate how Kenya develops and so of course, here's an opportunity for these open data to achieve development goals and know that has  a stronger sell than say to be transparent. And let's keep you accountable. Because now you can show that if you use data, you can allocate your resources more efficiently. You can save money. And I know I'm talking in the context of quite a tough economy. But the hope is that, yes, data is being used for current policy planning. And so, as I mentioned earlier, as part of the data revolution, we have, started looking at different types of open data. So we're not just relying on government ministries to open up data. These are screenshots from an analysis done on the what is called the African regional data cube, which is actually a satellite data for the past 20 years has been made open and has data on about five African countries and Kenya is one of them. So before that like for you to for a country like Kenya to access satellite data on its country, they had to spend a close to $1 million a year. So now 19 years of this data is already free and available for reuse, you know, again, the Open Data definition. And so in this example, you see, you can start monitoring mining activities in Ghana. This is a project that's been done by the by the Ghanaian government. And there's also activities around studying deforestation in Kenya in the Mau region, but have also been done using this data cube which would have probably taken a lot of site visits to understand that phenomena. So there's, and of course, there is different use cases for instance of using mobile cell phone data To understand how diseases are spreading, so big data is becoming more open. And again, becoming accessible and being used for beyond just, for instance, what the original company that's generating the data intended to do with it. For instance, this data from IRDC is actually NASA data is data from a couple of satellites, and Modi's. And it's usually proposed in a way that you don't have to really know how to deal with satellite data. But you can, if you can analyze data, you can use it. Next slide, please. So now, bringing back the conversation to I mean, this space we are in a library and open data, how to do that to come together. So this last week, there's been quite a big storm on Twitter around and this is dealing with Americans and then I'll bring back to the Kenyan context regarding the Apple's new credit card. So based on Apple's algorithms, people who have the same credit score, have been finding that, especially the women are being scored lower for this credit card. And one of one of the folks on Twitter was complaining that he and his wife have the same credit score in other banks. And they have, you know, they pay their bills on time have not defaulted on anything, but she only qualified for a $50. That's about 5000 shillings credit card limit, while he got 20 times more than her. So you wonder what data was used to score the wife for that. And then a lot of people jumped on and said, it's exactly the same thing. So what Apple realized or what came out from this Twitter storm was that women were being discriminated against By this algorithm. And so you set wondering how would I mean we are using machines are trying to scale, how we analyze our context? Maybe this is where there is still room for qualitative data. How do you explain causality how to explain phenomena? And here's where research data, qualitative data plays in this space. And so then if we are trying not to leave anyone behind, but not everyone is in the big data sets. Then if you analyze that and use that to understand a whole population, you're missing out on critical people in society. So then, but then again, there's another issue and Angela touched on it. I do want access to the services, but I also do want to my data to be private to me, I just don't want anyone swooping in and swapping out and using me to market goods. So in this era of big data, analytics and AI, there is a big issue of privacy. Kenya just passed Data Protection Law was it last week on Friday? But it was signed into law. And it spells out how companies will treat people's personal data. So now, going back to the example of the credit scoring, you want to get a loan from the bank, but the bank is obliged to share your data with the credit reference Bureau. But the law says you have the right to be forgotten. So if you defaulted on the loan, can you use the law and say, Actually, I don't want my records out there, that I defaulted on alone. So there's all these different tensions coming in. You want service provision, but you want control of your data. And companies need to share your data to offer you services. What is the middle ground? And then now when we start talking about qualitative research data, when you think about transcripts, if any of you have done research, if you read through a transcript of subjects you interviewed, you completely remember who that subject was, without writing without even the name being there. You'd be like this yeah yeah, because the information and the way they responded to those questions is very identifying to them. But at the same time, we are complaining that we are being over researched, because we have all these people coming into the country, or different researchers asking us questions. Why don't they share the data that was produced from a previous research? So again, the same tensions are playing when you start opening up more qualitative data, which is very important to understand causality. So that really is the conversation we are trying to set today. We want to preserve our knowledge, a lot of knowledge being produced now is on digital formats. Maybe some of you have as many books as this library in your laptop or on the cloud. But And so that has to be considered differently than, you know, physical storage of books. And so in this era, where we are new artifacts that regard our culture, our heritage, are on digital platforms, but need to be opened up, how do we start thinking about the infrastructure?

Will they be stored in these libraries? Will they be stored in the archives? in the cloud, but then whose cloud is it? Who owns that space? Who owns that infrastructure? And so those are the questions that we've been asking ourselves, like coming from a more quantitative view of data and opening that up versus more qualitative view of data and opening that up. And so we are hoping that conversations might bring us closer to understanding how to start dealing with these new artifacts in this space. For instance, the National Archives are supposed to hold records of all government records, for instance, but then, do they have a snapshot of a Ministry's website from 2010? Because it will look very different from today. And if it if they have that snapshot, how do you access it? And what would you be looking for in that snapshot of that website? So I think really, those are the conversations we hope to have today and through the various panels with touch on different aspects of infrastructure and privacy governance. And we do believe that it's not just limited to open data and research data, but more broadly, and knowledge preservation. There's one slide, the last slide, really, so sorry. So the next one. So, um, there's been an ongoing series of conferences for the past 10 years called the International Open Data conference, which ideally, this is where these conversations take place. And most of them have been in the global north. So for the past, I think, until last year, they were held bi-annually in Washington DC, in Toronto, in Madrid. And then last year, it went to Buenos Aires, it was the first time it was coming to the global south, and then Kenya won the bid to host this open data conference next year. And so Why we're very excited about hosting open data in Kenya. I mean, the International open data conferences in Kenya is typically, I mean, many of you might have been invited to travel abroad for conferences. And if it's not sponsored, you can't attend it. And so we hope that it's being locally will have more representation from not just the global south, but from African participants, and talking about an African agenda. And the theme of the IODC, next slide. 2020 is actually bridging data communities for sustainable development. So we are trying to figure out like, Okay, again, dealing with open data, and so, not just government data, its private data that's being opened up. We are trying to create this new partnership called collaborative. What, what governs those relationships between us researchers and Safaricom and the government of Kenya, without infringing on, you know, your rights. So, a lot of those conversations will be taking place in IODC, and in the run up to IODC these events such as ours, that some set the agenda setting and a lot of their conversations from here could inform as well like back final program towards IODC. So, look out for it, probably it will be in KICC and it probably will be as disruptive as the current conference that's going on right now, because it's quite a big deal in the data community. And it will be a combination of major events because next year is SDG plus five, next year is the Beijing conference plus 25. So there's a lot of big activities that are now and big, different data communities that will be coming together to talk about how data is affecting the different practices and I hope, the research data community here and whatever other communities of practices you're dealing with, will also join us at IODC. And if we have time later, maybe I'll invite one of the convenors to talk about it.

Thank you.

Angela Okune  44:15 
Thank you so much, Leo.