The following are the outputs of the captioning taken during an IGF virtual intervention. Although it is largely accurate, in some cases it may be incomplete or inaccurate due to inaudible passages or transcription errors. It is posted as an aid, but should not be treated as an authoritative record.
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>> GONG KE: I think it is time to start.
>> JING MA: Okay. Thanks for opening meeting for our workshop. Okay. I think it is time to start our workshop. Dear speakers and participants, welcome to our workshop, big data for environmental sustainability. And which is organized by the Chin Association of Science and Technology Committee on Communication and Telecom.
So very pleased to have, we will have the chair for this workshop, Dr. Zhou together with me as moderator. I think we have six speaker. And open discussion followed by the presentation.
Firstly, please let me briefly introduce our workshop. As we know, human social and economic activity greatly affects the earth's system, environmental pollution and is massive consumption of energy and water resource have both significant impact on the sustainability of the earth's environment.
Many countries and cities around the world are now facing increasingly severe ecologic and environmental problems. Utilizing new technology to investigate the change and the interaction of system to seek effective measure with our environmental programs in order to achieve sustainable development as a key issue that needs to be resolved.
So I think it is also common interest in all of the stakeholder. And so this workshop will focus on the potential of big data and artificial intelligence to provide effective solutions to address environmental programs.
As we know, emerging technologies such as big data and AI can provide strong support for tackling existing environmental issue and further integration and open sharing of data, the benefit of big data on environmental sustainability will be maximized.
We will also discuss the challenge of open sharing of environmental data as well as policy framework and cooperation for environmental data sharing among the different stakeholders and the different groups.
So I think this is a brief introduction about our workshop. Actually, we have six speakers from different regions. So at the beginning, I would like to invite professor from the federation of engineering organization and also he is chair of the consulting committee on information technology CCIT and acceleration of science technology to give us an opening remark.
>> GONG KE: Thank you very much. Could you hear me?
>> Thank you very much, Dr. Zhou, it is my great pleasure to join this very important workshop at the IGF 21. Good day, ladies and gentlemen.
All of us know in the recently released IPCC assessment report, the sixth assessment report of IPCC in which it is indicated despite many efforts have been made the climate emergency is still being exacerbated.
This report pointed out recent changes in the climate are widespread, rapid and intensifying and unprecedented in thousands of years.
This report also shows that it is indisputable that human activities are causing climate change, making extreme climate events including heat waves, heavy rainfall, and droughts more frequent and severe.
In fact, all of us have witnessed and experienced these mentioned extreme climate events no matter where we live on the earth.
Therefore, the report gives the code red alarm as described by the United Nations Secretary General Gutierrez. Unless immediate rapid and large scale reduction in greenhouse gas emission limiting the warming to 1.5 Celsius degree, we will be beyond reach.
So facing to this severe climate change and other environmental challenges, we should make strong rapid and sustained actions to reduce the carbon dioxide methane and other greenhouse gases to limit the global warming by especially by energy decarbonization.
As called by the carbon 36. As mentioned by Dr. Zhou, big data is a powerful tool to empower us in these actions. However, how to fully explore great potential big data is itself a big challenge to us. How to effectively and widely collect the data, how to ensure the quality of data, how to safeguard the privacy and security of data while access them openly.
How to effectively process and use data and how to narrow rather than expand the digital divide, the data divide. How to coordinate data loss, policies, and technical standards globally to meet global challenges especially the challenger of eco environmental sustainability.
This requires a series of innovations in big data science technology, engineering, and governance.
So today's workshop with speak a variety of speakers and participants is going to address these problems. I do hope this workshop will be a brainstorming exchange of experience and ideas and be a milestone for the first collaboration among us. Thank you. I stop here. Hello? Hello? I think the floor is back to Dr. Zhou and Horst.
>> HORST KREMERS: There seems to be no good connection at the moment in Beijing.
So to use the time, maybe I will take the chance to introduce the next speaker. That is Chuang Liu so that would be nice if she is able to reconnect maybe.
>> GONG KE: Perhaps we go to the next one?
>> HORST KREMERS: Ricardo, would you mind starting your presentation in the meantime? Ricardo is available. He is professor in Mexico and his presentation is on implementation of big data and the use of clean energy. Please.
>> RICARDO ISRAEL ROBLES PELAYO: Thank you very much. Well, thank you for the invitation to this important forum. As we all know, the preservation of sustainable environment is an important goal of the agenda of governments and the private sector.
The production and consumption of energy are necessary for human subsistence. Alternatively, the consequence is inevitable environmental impact. There are modalities, however, on this occasion, and to comply with the time established for this intervention I will only talk about electric power and the measures that Mexico has incorporated based on international treaties signed with the United States and Canada.
These countries entered into the North American Free Trade Agreement, NAFTA, to promote the improvements of the environment through economic and efficient measures. The three countries have read to include from the policies and practices to prevent pollution and approve the observance and application of environmental loss and regulations.
Finally, committed to supplying environmental information at the request of the corresponding authorities.
They subsequently signed the United States-Mexico-Canada agreement and came in 4 of July last year.
Chapter 45, 44 establishes regulations related to the environment. The parties are committed to expanding the cooperating relationships on environmental matters, recognizing that this will help them to achieve their common environmental goals and objectives including the development and improvement of environmental protection practice and technologies.
In the case of Mexico, it legislated electrical reform where the different energy laws according to the objectives of the USMCA leaving open the possibility of implementing the technological means necessary for the protection and sustainability of the environment.
In Mexico, electricity generation is carried out by the public sector and with the participation of the private sector. In both fields, different actors are trying to implement state of the art technology. However, the use and exploitation of big data analytics are not enough to achieve the goal set in the treaties. The Mexican government established a goal that by 2024 the generation of electricity to clean energy will be 35% and incorporated at the technological infrastructure.
That integrates new methodologies such as big data analytics to guarantee the supply, access and integration of renewable energy.
According to the Mexican government, currently this big data infrastructure is implemented in the national training centers of the Federal Electricity Commission and used for the analysis and monitoring of the photovoltaic systems. The benefits to achieve a sustainable environment are in obtaining the information of the process of generating electricity and renewable energy.
Historical, this is in real time and there is renewable energies in the electricity grid. As a result, better decisions can be made for better use of energy that translates into less environmental impact.
In conclusion, we suggest implementation of specific legal instruments to implement big data analytics in the generation of clean energies to environmental sustainability. So thank you very much.
>> HORST KREMERS: Thank you, Ricardo, for sharing with us this very good presentation.
Should we allow one or two immediate questions? We have discussion afterwards but maybe one or two if it is directly to the content of the presentation. Anyone like the floor? If not, then I'm -- are our friends from Beijing -- our friends from Beijing didn't arrive yet.
So the next presentation will be also from oh, there you are.
>> Thank you. Maybe we can start from Chuang Liu presentation.
>> HORST KREMERS: Very good. We didn't see you. Please, you do the moderation,.
>> Thank you. So let's -- yeah. Okay. Okay. Good. So delighted to have my topic here about the ECADA action on environmental protection and high quality geographical products and sustainability.
This one is we are open data and knowledge driven for SDGs. So sustainable development equals environment protection plus development. So for now we have challenges. Mostly in China and many of the developing countries have the same challenges. So good environment, less development.
High quality products, low price in markets. People wants to get high quality products with good pay, but very hard to find where they are.
And the trusted data information are not available to be accessed. All these challenges. So this is for us to think about it. So then we have joint organizations, joint actions from the WFEO and CODATS, PASTD task group. We are going to have a new task group, working group to work on this.
And also the World Data Center of Global Change Research data publishing and repository and Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences and Big Data Working Committee of Geographical Society of China. And there are so many organizations that pay more attention, but if only one or two couldn't solve this problem.
So we agree to have the joint action. So we use open science but open science mostly important that things is open data and open knowledge.
So we have open data, partition the data. The boundary so we have the cases are open working data we have. Boundary data of the research area and the physical geography data including soil, water, climate, grassland and so on.
And also have the characteristics of the geography from products and socioeconomic civilization culture and management. And the data format and the size of the data. And all of this can free download for everyone.
This kind of sheep, this is the sheep in the grassland area, and this is physical geography data and also some kind of socioeconomic data also. So there are all of the things come together to understand how the special area can protect the environment and also keep this environment sustainability.
So then we partnership, published data in the Journal of Climate Change Data and Discovery and published in the paper and this we have the segment of the management, the foundation and how to download the data.
And then we also give this registration. We have three registrations. One is for data center registration for the data center. And then the CSTR in China in the science and technology, community of science and technology there the registration. And also the DOI for the geodc.
And then at the end we have certificate to them and then we give to local people to understand what this is.
And then this is only one case. Cases of methodology. So this is -- this already approved. There are five cases, and we also have another several photos.
So on the -- as Ricardo sited in Mexico, there is agreement and U.S. Mexico and Canada agreement. Focus on the high quality product treaty.
So that is China. We have this international fair for trade in services this year in Beijing and then we have the joint forum in the geographical and environmental sustainability.
And then we realized that the international trade is increased year by year, especially in China, the people look at the more rich and more money. They want to buy something and really want to, but now China now there is so face to face. So this is my presentation about what we wanted to discuss in this forum so we could work together. Okay. So this is my presentation. So we are coming to have discussions and other questions. Next.
>> HORST KREMERS: Can I have a question at the moment? Just could you repeat or indicate how participants in our audience could contact you and what is the procedure of interest of being colleagues being able to contact you to that big data repository that you set up.
>> XIANG ZHOU: Okay. I think that this is -- it will be agreed that we will follow up with the multiple detail in the presentation and how to and the procedures.
So this time we can get the comment and the data and dataset and the geo and so on. Okay. Any other questions?
>> HORST KREMERS: No, no other questions here in the chat or else I don't see.
>> Okay. Horst, will you just go ahead and moderator.
>> HORST KREMERS: Thank you. Of course, I'm pleased to introduce you to the audience. Sorry for the short delay.
Our next speaker is a professor in Beijing and co-chair of the task group of information for developing countries and is professor of Aerospace Institute of Chinese Academy of Sciences in Beijing. And this is on big data analysis on ecology and environment and green development.
>> XIANG ZHOU: Thank you for the introduction. Hello, everyone. As my presentation title shows, environment is the foundation for the development of our planet earth.
So today I would like to speak a bit more on this issue from technology aspect. The next big technological efforts is approaching.
So a brief background about the issue I'm going to address. As we know, the SDG is high priority for the government under the cooperative mechanism.
So quite a lot SDG goals of SDG related to the environment like the clean water and sanitation and also seven clean energy. And, of course, 11, sustainable cities and communities. We also have very strong emphasis on the climate change.
So also it is listed as one of the goals in SDG13. And so I think all of the implementation of these SDG goals requires long-term monitoring of the region, also evaluation using the different scientific and reasonable index to monitor the progress and information degree of each goals.
So big data, that will bring more implication scenario for the ecosystem and the environmental monitoring which also allow emerging ICT technology as I mentioned to integrated various results, datasets and also the new advancing technology means. And accelerates the sharing and circulation of big data.
So from the picture you can see we have a lot of issue to tackle with support of the information technology which will give us the data information about when, where, what object and what changed about the environmental parameters. So if we try to define big environmental data.
We will find there are a lot of issues for factors need to be considered. For example, we need long-term and, of course, integrated observation which focus on the change of environment and also we have to rely on the capability of artificial intelligence and also cloud computing specifically which can help us have a deeper knowledges and understanding about our environment that form the basis for the analysis and simulation of systems.
So environmental internet of things, cloud computing, big data and also data management and, of course, open data access by trusted service to bring us the deep knowledge and discovery these various information and also we also have a lot of consideration approach to have -- to help us well understood the global change and also the phenomena which happened, of course, by the environmental change.
So if you notice the right picture on the slide you will find the more than 200 indicators extracted from the features of the SDG goals so all of computing of this indicator requires high quality data side from the environmental monitoring and also observation.
So that's why we need concept or framework of big environmental data. So I think the big data plus artificial intelligence require AI for way for data to information and, of course, supporting the decision-making.
Big data not only find the big knowledge but also improve the capability and realize the potential of information technology promoting -- of course, it is to support the implementation of SDG.
So I will take an example by a big space data which help us better understand. So you will find a lot of observation data were shared on the internet by the different stakeholder. So the typical example is the LANDSAT that provides 40 years achieve of global data provided freely on the internet.
So you have deep technology and command information about vegetation and about the land use change. So it will help us to know our planet.
So also some challenges for the environmental sustainability. Forecasting. So we need scientists committee to build platforms of predicting the earth system. Observing. So we need to know what social and environmental system need to be observed and what scale observation is used is for the purpose of monitor the global change. And confirming so how to improve scientific technology about global change.
And how the policy maker and citizen is the most effective way to do global change. Of course, for responding we need to determine what institution, what kind of activity and change can affect the global sustainable development.
And the most important I think is innovating. Encourage the innovation in technology and policy development so it is challenges we need to consider for further research and discuss.
For action plan. So we need, of course, the group power from the public civil society and research community, technology sector and discuss the policy and open data and innovation and how to empower the technology and integration.
So we need to build a massive spectrum environmentally friendly community, facility and also which is very crucial we need to consider the application scenario, it is very important for us to promote environmental application model.
I think with this is our brief thinking about the big data for environmental sustainability from the technical aspect. Thank you.
>> HORST KREMERS: Very good. Thank you, Xiang Zhou, for this good overview and highlighting important aspects. We have 10 minutes time until the procedure in the next part of our session for 10 minutes for open discussion.
Please, there was a remark in the chat on linking our sessions to other sessions in IGF. Yes, of course. We didn't mention that yet, but in the course maybe at least I wanted to touch that in my presentation also there are several activities in IGF.
And there are several activities or joint activities in World Science and Information Society. Many colleagues of us here in that presentation and also probably the audience are active in United Nations global level science and technology and administration fields.
So and this gives that cross-sections where in our session we only have the six minutes for each presentation which is rather short for such big topics, but we want to raise interest and give opportunity to stay connected. Thank you for that remark.
Other questions, please. You may raise your hand in the reactions button of Zoom.
When I can have a question, please, that in the last presentation you had a -- you said about policy networks and my question would be you said about when, where, what and what change.
The question of change is something that can be slow change and that can be rapid change and that can be streaming complexity change.
You know, I'm working in disaster management and when disaster and the environment comes together there sometimes the complexity is really rapidly streaming.
Is there -- is there special aspects to recommend for such situations?
>> XIANG ZHOU: Thank you. I think if you want to get total information I mean just digitalized first by the timely information especially about environment still have a lot of challenges.
First we need to build a lot of platform. Maybe one or two for global one or regional one to try to plot small data source. As I mentioned maybe if we take earth as the -- I mean one research object we need long datasets from the space so it will give us about data the understanding about carbon cycling and also the water resource.
So I think this kind of information cannot be totally complete environment or a single means, but we try to use the big data from different source to get accurate results which can help us to get -- and also as you mentioned try to give a better solution to further environmental problem which has offered and also with the technology solution.
>> HORST KREMERS: Yeah, thank you very much. There was another question on what is -- is there some special aspects on carbon footprint of digitalization. All of the computations we do, and all of the big data shifted around and analyzed and so on has a car your group is not so specially working on this, am I right or are any of the speakers involved in the carbon footprint?
There are other activities, I know ITU International Trade Organization for the union of United Nations has a special activity in that direction.
And we could share information afterwards maybe. But does one of the speakers want to touch this? Not at the moment. Please, Mark Urban, and others, please contact us after the session and we will happily get you in contact with the colleagues that also cover this holistic, that's right the holistic aspect.
Yes, you have also to see what is the carbon footprint of the data. It is nice to have the data, but the computers are energy consumption sometimes very heavy and so on and all of the digitalization is a big problem, and we don't touch that at the moment in our presentations here about it is linked to other activities left and right. And this is shared nationally.
So we have possibility of another remark or question? If that is not the case, then maybe I get another minute more for my presentation. Xiang Zhou, could you take over the moderation for me to start my presentation.
>> XIANG ZHOU: Okay. So okay. So I think okay, we are seeing the screen. Horst, go ahead.
>> HORST KREMERS: Okay. My presentation today is on challenges, risks and gaps in environmental data management.
When I made the proposal of abstract for the session, I didn't know that in the end I would have only six minutes to do this.
Usually the topic is much larger and, of course, we are working since years in the field, and everyone can be referenced for our work we did already. Today so let me in the few minutes let me stick to certain aspect.
I want just to mention more the aspects of governance needed in a big environmental data sustainability. We already heard we are doing about monitoring, assessing, accounting, valuing, pricing, define/generate tradeable values.
And believe it or not, if you have heard, you will be astonished if you not have heard you will be even more astonished that now people are getting nature to the stock exchange and make money out of it.
So just that our aspects I want to touch very shortly. And there are follow up things also. Let's start with monitoring. Just a single slide where you see what a typical overview of first order metadata catalog is that is from the -- from a European part of European Environmental Information System. And this is just an example of datasets indicated which are for the whole region of the Baltic Sea in northern Europe.
And just to show and remind that monitoring is already complex.
Then after monitoring we do assessing but is it a good state, not that is typical in evaluating. It is nice that I can mention that in one of the previous presentations today already was mentioned the trade agreements and the various assessment there is not just user trade agreements but also to assess the impact of trade agreements on biodiversity and ecosystems.
You will receive the download for the presentation in the end so you can read that in quiet on your desk.
For accounting. Now, this is something which is in the recent years. So in the European Union at least there is some activities on the report for pilot for an integrated system ecosystem. The reference document as far as if you are interested in environmental systems accounting then you have it detailed in that European report. So that makes for the accounting.
The ecosystem extent accounts. Ecosystem accounts and services accounts. And so that is especially the services account I want to mention record the supply of various ecosystem services such as providing recreational opportunities in nature or protection of human property in floods by ecosystems to the society and how the society benefits from their use. You now see that is benefits for the use in video of the overview I gave of my presentation here you see benefit that sounds like money.
Actually, we had this before, but nowadays we are in the final slide we go to the stock market. Just take care about the notations used.
Now we are getting into value and pricing. Valuing of ecosystem service accounts. Evaluating the actual floor of nature based recreation from ecosystems to people.
And there is a link here and doing certain methods of pricing captures the consumer's willingness to pay for what they perceive of environmental differences that add or detract from the intrinsic value of a set of property.
If there is money behind it, you know that there is something positive, very positive about it. If there is money in disaster management, we call that losses. In disaster we don't talk too much of gains.
But here in the environmental and the environmental improvements there may be gains and there may be other losses if there are disasters in the environment. I always see the complex space and you heard about the big disaster in the Amazonian basin. That is a multibasin and not just Brazil.
And here we have to deal with losses and the moment you can put dollars or Euro or whatever currency into the losses of environment then politicians maybe have pick up their ears and have a more stronger aspect of support needed there.
Actually there are numbers in the European Union, there are types of economic units defined and nature-based recreation for instance. There is one of tables in the larger compilation and for nature based in the European Union that will be -- that you see the countries. Austria, BE, Belgium and so on GE, Germany and other countries. And the last line do compute the nature based recreation economy.
Now that has of the pricing there is necessary or a possible to define/generate tradeable values. The opportunities that some people say that is a traditional economy has set values of 512 trillion. Nature's economy, they compile to 4,000 trillions.
This is what you have stockbrokers read such statistics and they get really interested to see what go from 500 trillion values to 4,000 trillion where is my hedge under getting into these things?
You see if there is gain of money then we want to have solution. And in that reference you see there will be possible to read details about that.
And then finally, get nature to the stock market and make money. This is not my favorite. You see, actually, but I want to see to tell you what is the situation right now.
There is any id to have natural asset companies that are sustainable enterprises that hold the right to ecosystem services produced by natural working or high braid hands and enables owners to convert natures if value in financial capital providing additional resource necessary to power a sustainable future. This sounds nice and would be positive if everything runs positive. Now, nevertheless you have to read in care and observe in care what is going on there. And not everyone is happy what big money globally does with environment.
So I just say I don't want to make a valuation of the whole thing. I just want to raise your interest and raise your observation and make up your own mind in what is going on there. This is real activities.
Finally, my summary is to put it in elements of sustainability information. Governance. That is about economic and business management issues. Financing. Economic instruments. Sustainability in finance. Recording and valuation of ecosystem services. That is the service of what makes money and what is of value. Environmental-economic accounting and dialog with companies and business associations.
So maybe I hope that in IGF or in World Summit on Information Society we find possibility or may already made proposal to collect a working group or something like that and exchange ideas about observing these things and making up our minds.
The other more technical operational things of governance would be to develop mowed this, techniques, operations, control, accountability ethics, issues and there is risk management or compliance, administration. All of society participative governance.
How does Civil Society make its mind of what is going on in the stock market of environmental efficiency pricing and values kind of done up in certain instruments of the stock market. I want to stop here. For me it is not everything is very positive in the future.
I would be happy if it is, but I think it would be necessary to observe. All this, of course, is a circular vision also that participative governance needs to go in all of the previous mentioned topics.
Thank you for your attention today. And for further contact, please contact me and the presentation is for download. And I will send that link also to the chat right now. Thank you very much for your attention. And if there are questions, I'm happen to touch them. Thank you.
>> JING MA: Very good. Horst, I have a question for you. So you have the new services or not new services, but about the new services.
Online services.
>> HORST KREMERS: This is there is a list of nature services from which I only picked as an example that recreation service that nature can do.
Now, you see the -- just for instance as part of breaking down in bits and pieces, part of nature recreation services would be how many people and pricing would be along parameters for instance, how many people go in that nature preserve every year?
>> JING MA: Mm-hmm.
>> HORST KREMERS: You see, we are fighting for a lot of bio reserves where no one please should go. Now is the price low of these areas because no one ask going there or what. And if we have in Switzerland, here in Europe people go for skiing, people go for holidays. And devastating environment in certain regions quite a lot. Everyone is concerned.
And then they make parameters of that. The value is better when people go there. So you see, I just want to raise to talk about solutions I have in my -- I don't want to talk about solutions I have in my head, but it is just the type of bits and pieces that is really astonishing.
But it is a future which we also have to deal. Not only the basic. My first slide of the tradition of having meta information systems and repositories of basic data and nowadays we have to go in different arms into pricing and going to the stock market with big data.
>> JING MA: Okay. Great. Thank you. So I will discuss with you later. I want to know more.
>> XIANG ZHOU: Okay. Thank you, Horst. I think if there are no more questions right now we move to the next presentation which are from Dr. Daisy Selematsela from South Africa.
Daisy Selematsela is at the studies at the University of South Africa and Professor of ecology and management. Daisy will be presenting about the management in university levels. Okay. Daisy, you have the floor.
>> DAISY SELEMATSELA: Can I please for Horst to activate. I need to put the screen up so I can share. Okay. Thank you colleagues and participants at this meeting.
I just want from my side to share with you how the issues around big data for environmental sustainability and actually data in general with regards to open data or when you talk about open science how it impacts and how us as the persons who are in the forefront in higher education or universities and especially then where we are in a position to ensure the standing of the processes -- the understanding of the sciences with open science and open data. I will highlight more in this regard.
There are a number of challenges in the positioning of data management. And these challenges especially in the global south is alignment with national priorities. Funding and sustainability, technical feasibility and standards, quality assurance and management, governance which the other presenters have spoken about.
Policies with regard to open source open data and the government policies that we have and the views from society, civil society including the scientists with regard to open data and data sharing and accessibility to data.
And in Africa as a region, participation and contribution of data.
So what we have seen is that the global change actually impact drivers. For 2020 we have a world rapidly changed and countries are grappling with how to use scientific challenges to deal with challenges. So the potential that lies in the collaborative opportunities offered by a changing and increasingly connected and globalized environment like what we are doing today.
And those aspects that impact are the following. Social change. Scientific and technological imperatives. Economic imperatives and Horst has highlighted a number of this in his discussion also.
Environmental impacts and geopolitical, for example, and especially for us in the south they impact us when it comes to issues of whether it is big data, how you look at it or open data or open science.
And these are the global drivers that I just wanted to share. And social change, for example, it is for us it is the issues around population growth. The aging population. The African youth bulge. Urbanization.
The global north. 84% of the population urbanized and in Africa 62%. The increasing uncontrolled migration to developed countries leading to social instability and the other aspect under social change would be international mobility.
The other aspect with regards to scientific and technological science and proliferation and science breakthroughs that are quicker and translated faster.
And we have seen that with the pandemic. And the 34IR and measured lines between physical and digital spheres which we look at legal, ethical and socioeconomic consequences.
When we look at the other global driver on the economy for example. Like Horst indicated before me, the emerging economies. And here looking at the growing middle class and increasing consumerism which is the demand for goods and services.
And we have lots about technological change which promote social inclusion and economic growth but causes loss of traditional jobs and high proportion of unskilled workers and disruptive effects of globalization.
And here we picked up that analysts do not foresee the large-scale retreat of globalization even though there are protective policies especially in the global north.
And when we look at the fourth one of the environment, the climate change challenges. For example, the degradation of the natural environment, biodiversity loss that will shape policies and also the new policies that require new technologies, processes and services and build business models.
And the last one will be on the geopolitical which is the shift of world's economic and political power from west and north to east and south. And also the international landscape that is increasingly multipolar.
So what are the implications of the drive of global change in when we -- and what we are doing as we try to make our communities especially our research communities in the global south as in the forefront to ensure that we have data repositories or institutional repositories.
The impediments are that the current innovative thinking does not adequately seem to respond to a world in rapid transition. The shift from thinking about systems which are in isolation. It is also impacting on considering the entire socio technical systems and values underlying them.
Here an example is how we look at transport systems to systems of mobility. Instead of just looking for issues around how do you build as part of cities and science in your respective cities for transport.
And how then does the knowledge development component comes in there from our creation or support of knowledge networks where scientists organize scientific exchanges and educational programs and other opportunities to build capacity and encourage innovation and knowledge production to improve diplomacy.
And when we look at open science and open innovation, it is quite important that when we talk about big data, this also forms part of that because access to public science provides potential for research ecosystem to be participative and productive.
And here looking at reducing duplication and the costs of create transferring and reusing data. The other aspect would be fostering the digitally enabled open and collaborative innovation which is a key component. And we know that in a networked -- in a networked world, where we live in, we no longer -- it is no longer possible to ring fence what we know or have invented and to create new value that you internal means alone.
It is a collaborative space. And just quick that I this collaborative info expectations involves greater use of internet, and that is why we are sitting here today.
Digital technologies and social networks to foster learning, enable the co-creation of codified knowledge and provide wide access to tools, data and resources.
And how can we then strengthen these processes especially in Africa we need to look at strategy and coalitions. And under this looking at how can we build developing regions strategies, declarations and operations that would support open access or open data policies. How do we then seek, national regional and international support to strengthen scholarly led access to open data. And how do we look at the open data policies and initiatives.
The institutional repositories. National repositories and regional. And also how do we deal with the issues around encouraging our researchers and also data producers to look at self-deposit in national repositories of institutions with less research outputs. And that's the end of my talk and thank you very much.
>> XIANG ZHOU: Thank you, Daisy. Very impressive talk. And technology management. Do we have any questions here? From others?
>> HORST KREMERS: If I can have a question or remark. Daisy, this is so good compilation you did because that is rather on this level, you see that is not on the bookshelf level but is at the governance level and this is so important to get such overviews.
The question for me is how to go on with this, how to make that effective in terms of governance oriented communities and so on.
How to make recommendations not only in science because you are touching society aspects and you are touching organizational aspects. What is your proposal how to go on from your presentation?
>> DAISY SELEMATSELA: Yeah, the issues around in especially coming from my background also with being involved in the international science council the core data committee for data issues it is around -- it is first driven by policy.
For us, it is around policy and also because if policy is not driving this process then there is no movement because whatever it is done is based on public funding for public good.
And our community, research community they look at that value add to say if governments are not saying this to us, then we won't be moving towards that direction.
So that is why I have seen that happening across in all of the 20 year -- 16 years that I have been involved in the data issues when we started in from Senegal Pact and so forth up to where we are now it is the same issues that we have.
And if I talk for South Africa is totally different with the uptake and the understanding but you still have the naysayers in understanding this process. And especially that where we see some pushbacks when it comes to, for example, open publishing. It is those fears and not understanding the value of having your data available and data repurposing and so forth, yes.
>> HORST KREMERS: Thank you.
>> XIANG ZHOU: I think there is comments from mark Urban. He mentioned there is a need for research and education network that are dedicated and trying to provide the digital tools for the purpose as mentioned, as Daisy mentioned like GEANT in Europe. RedCLARA in Latin America. Any response, Daisy on this?
>> DAISY SELEMATSELA: I can't hear, I have been trying to listen. I can't hear. Horst, is that a question to me or a comment on chat. I cannot hear what has been questioned there.
>> XIANG ZHOU: Okay.
>> HORST KREMERS: I think it is just a --
>> XIANG ZHOU: It is just comments from Mark. You can check the chat window and we may have time to respond later. So maybe we need to move ahead.
Our last speaker from University of Japan and has done a lot of research in ecosystem and environmental protection and renewable energy.
And I think she will give us a presentation on the AI oriented monitoring. You have floor, please.
>> TOMOKO DOKO: I ask Horst to direct the sharing of the presentation.
>> XIANG ZHOU: Yes, you can share the screen.
>> TOMOKO DOKO: Okay. Can you see that? The okay, great. My name is Tomoko Doko. I'm CEO of nature and science consulting in Japan. Today I would like to have a talk about my monitoring system using AI oriented systems as a case study.
Today's topic is about big data and AI and how I applied those techniques to the ecosystem science.
So first let me introduce what is big data. Big data refers to the large diverse sect of information that grow at ever increasing rates and encompasses the volume of information and speed of way change is created and collect and variety and scope of data points being covered.
Big data often comes from the data mining, okay. And probably everybody heard of the artificial intelligence. I tried to talk a little bit about the definition of what is AI.
AI is computer or computer controlled robot to perform tasks commonly associated with intelligence being to the project of development systems and with interaction processes characteristic of humans such as ability to reason, discover meaning, and generalize or learn from past experience.
And since the development of the computer in the 1940's it has been the thought that computers can be programmed to carry out complex tasks as, for example, discovering proofs of mathematics theorums or playing chess with great efficiency.
And today my topic is national case study. In fact, I am a specialist of ecology. I am a specialist of the geographic science but also an ecologist. And how can big data and AI be applied to science, especially environmental sustainability is today is my question.
And I would like to introduce one example of monitoring animals in Japan. By the way, here on the right side. It could be the biggest animal in Japan and the black Asiatic bear also inhabited in China and yeah, and some eastern Asia plus Japan. We have a name in Japanese there but black bear.
The distributions you have the area here where there is a brown bear and the main island area we have the black bear.
So we have species in Japan. Today I want to introduce some perspective like how to monitor because I installed traps to check the bear. In this picture is my trap. This is the trap. And bears maybe, you know from some book, but they really love honey. So I set up honey and how shall we know that the bear is actually captured and what kind of animals come to visit the trap is my question.
But sometimes the animals are not too cute, right, we can -- right to bears we can't touch directly, it's too dangerous.
So we want to set up some safe material for human being so that we can know the system is done remotely so we monitor system. So humans don't need to go to check the site.
And we can know if something happens remotely through the internet. So we have used the technology of the camera traps, too. Camera trap has been increasingly used to estimate the relative abundance and distribution of wildlife and it is a powerful tool. We cannot know the photographs at the near time or real time.
So I wanted to set up the system which can transfer the data automatically through the internet.
>> HORST KREMERS: If you go in presentation mode.
>> XIANG ZHOU: You are not moving your slides, I think.
>> Slide has problem?
>> XIANG ZHOU: You are still on the first page.
>> Really?
>> JING MA: Yeah.
>> I am sorry. Maybe
>> It is still the title page. Maybe like this you can see.
>> XIANG ZHOU: Yes, yes.
>> Sorry. There I go to show the slide show. Yeah, I sorry, I came to around here. Okay. This page maybe.
And okay. So I set up the system to -- sorry, maybe I can show you some picture. Like this was the Asiatic black bear I introduced.
And here is the geographic distribution of this species. And here you can see this is the trap to capture the bear. And this is the study area. Here is Japan and my study area is inside of main island around the Tokyo area.
And I used the mobile phone system to set up the traps and also I used the satellite system what is called alert system to monitor the trap. And the methods like we set up the camera traps to take a picture of the traps and transfer all of the data remotely so that I can see the result through the internet like this.
And so the trap together with the -- there is a sensor in the camera here. So if they take pictures they can send the photograph to the server and transferred to mobile phone users or computer. And then I can see the website the condition of the result accessing. And the system was like that, and it can give me message like this.
And this is system. This is, for example, what kind of animal I can take. This is the Japanese Marten. And this is an animal in Japan, the Japanese Serow that was a national monument in Japan. And I can see them close to my trap.
And this -- these kind of pictures can be archived on the website directory. And this is Asiatic black bear actually came to visit my trap. This is a mother bear and one bear together to come.
And this was a video I prepared but maybe it would not work without the slide show so that is all from my side. Thank you.
>> XIANG ZHOU: Thank you, Tomoko. Very interesting talk. I think from your presentation I feel that animals, the real animals are not so far from us. So very, very good information you can get from these AI data equipment and also help the protection of those animals. Thank you. Any questions from our audience?
>> JING MA: So Tomoko, very good and I'm interested, very interesting your job, you know. I remember several years ago your data about this present research is published in the Global Change Data Repository already. I think several people use your data analysis.
Do you have some idea to publish your research, this research? So if you are interested, please come to my journal to publish this, your data. Very good. So you know, we will publish it and whose data is and we use the research. So that is good. I invite you to publish your paper to my journal.
>> TOMOKO: Thank you very much, I will.
>> HORST KREMERS: I would like to have a question, Tomoko. There is, as you said, one possibility is to observe animal species and to --
>> XIANG ZHOU: Horst, we are not -- we are not seeing it.
>> HORST KREMERS: Sorry.
(Laughter)
>> HORST KREMERS: One possibility is to observe species and met them, met the distribution. The other thing is that along with this there may be a possibility to elaborate on the habitat parameters of these animals.
Did you try or do colleagues of you try to specify or derive habitat parameters from observations?
>> TOMOKO DOKO: That is a good question, and I'm in fact a geographical science so if we have the present data and some cases it will have access data and we can model the habitat geographically.
I published several paper of the Asiatic black bears from the field data and the existing data.
>> HORST KREMERS: If that is not in Japanese language, which I am sorry I cannot read it, if that is --
>> TOMOQKO: It is English paper. International paper. If you like, I can give you the link.
>> XIANG ZHOU: Okay.
>> HORST KREMERS: Here is a little bit of -- I don't know if I take the responsibility of closing the session if there are no other immediate urgent questions.
We send you in the presentations I think we will make them available somehow on the internet. We have that space of the infonet where we in the blog we share such information.
And so if you keep in contact with us you are very welcome to share experience after this presentation, too. Greetings to the colleagues in Beijing.
At the moment, I'm very delighted of this big discussion we had today and that will be something that we certainly have to work on and share in future. Thank you very much for your attendance and all speakers for the contributions.
And especially trying for doing all that proposals and doing every bits and pieces and colleagues, of course, in Beijing we are happy to continue this for many of us long years acquaintance in science activities and international council of science and we are happy to continue that work. Thank you very much. And have a good day. Thank you.