Eye on Earth (Day 2 – Morning) – moving to data supply

Eye on Earth (Day 2 – Morning) – moving to data supply The second day of Eye on Earth moved from data demand to supply . You can find my posts from day one, with the morning and the afternoon sessions. I have only partial notes on the plenary Data Revolution-data supply side, although I’ve posted separately the slides from my talk. The description of the session stated: The purpose of the the session is to set the tone and direction for the “data supply” theme of the 2nd day of the Summit. The speakers focused on the revolution in data – the logarithmic explosion both in terms of data volume and of data sources. Most importantly, the keynote addresses will highlight the undiscovered potential of these new resources and providers to contribute to informed decision-making about environmental, social and economic challenges faced by politicians, businesses, governments, scientists and ordinary citizens.

The session was moderated by Barbara J. Ryan (GEO) the volume of data that was download in Landsat demonstrate the information revolution. From 53 scene/day to 5700 scene/day once it became open data – demonstrate the power of open. Now there are well over 25 million downloads a year. There is a similar experience in Canada, and there are also new and innovative ways to make the data accessible and useful.

The first talk was from Philemon Mjwara (GEO), the amount of data is growing and there is an increasing demand for Earth Observations, but even in the distilled form of academic publications there is an explosion and it’s impossible to read everything about your field. Therefore we need to use different tools – search engines, article recommendation systems. This is also true for EO data – users need the ability to search, then process and only then they can use the information. This is where GEO come in. It’s about comprehensive, effective and useful information. GEO works with 87 participating organisations. They promote Open Data policies across their membership, as this facilitate creation of a global system of systems (GEOSS). GEOSS is about supply, and through the GEO infrastructure it can be share with many users. We need to remember that the range of sources is varied: from satellite, to aerial imagery, to under-sea rovers. GEO works across the value chain – the producers, value added organisation and the users. An example of this working is in analysis that helps to link information about crops to information about potential vulnerability in food price.

Mary Glackin (the Weather Corporation), reviewed how weather data is making people safer and business smarter. The Weather Company is about the expression of climate in the patterns of weather. Extreme events make people notice. Weather is about what happen in the 100 km above the Earth surface, but also the 3.6 km average depth of the oceans, which we don’t properly observe yet and have an impact on weather. There are 3 Challenges: keep people safe, helping businesses by forecasting, and engage with decision makers. Measuring the atmosphere and the oceans is done by many bodies which go beyond official bodies – now it includes universities, companies, but also citizens observations which is done across the world (through Weather Underground). The participants, in return, receive a localised forecast for their area and details of nearby observations. It’s a very large citizen science project, and engagement with citizen scientists is part of their work. Forecasting require complex computer modelling – and they produce 11 Billion forecasts a day. Engaging decision makers can be individual fisherman who need to decide if to go out to sea or not. There is a need for authoritative voice that create trust when there are critical issues such as response to extreme events. Another example is the use of information about turbulence from airplanes which are then used to improve modelling and provide up to date information to airlines to decide on routes and operations. Technology is changing – for example, smartphones now produce air pressure data and other sensing abilities that can be used for better modelling. There are policies that are required to enable data sharing. While partnerships between government and private sector companies. A good example is NOAA agreeing to share all their data with cloud providers (Microsoft, Amazon, Google) on the condition that the raw data will be available to anyone to download free of charge, but the providers are free to create value added services on top of the data.

Next was my talk, for which a summary and slide are available in a separate post.

Chris Tucker (MapStory) suggested that it is possible to empower policy makers with open data. MapStory is an atlas of changes that anyone can edit, as can be seen in the development of a city, or the way enumeration district evolved over time. The system is about maps, although the motivation to overlay information and collect it can be genealogy – for example to be able to identify historical district names. History is a good driver to understand the world, for example maps that show the colonisation of Africa. The information can be administrative boundaries, imagery or environmental information. He sees MapStory as a community. Why should policy makers care? they should because ‘change is the only constant’, and history help us in understanding how we got here, and think about directions for the future. Policy need to rely on data that is coming from multiple sources – governmental sources, NGOs, or citizens’ data. There is a need for a place to hold such information and weave stories from it. Stories are a good way to work out the decisions that we need to make, and also allow ordinary citizens to give their interpretation on information. In a way, we are empowering people to tell story.

The final talk was from Mae Jemison (MD and former astronaut). She grow up during a period of radical innovations, both socially and scientifically – civil rights, new forms or dance, visions of a promising future in Start Trek, and the Apollo missions. These have led her to get to space in a Shuttle mission in 1992, during which she was most of the time busy with experiments, but from time to time looked out of the window, to see the tiny sliver of atmosphere around the Earth, within which whole life exist. Importantly, the planet doesn’t need protection – the question is: will humans be in the future of the planet? Every generation got a mission, and ours is to see us linked to the totality of Earth – life, plants and even minerals. Even if we create a way to travel through space, the vast majority of us will not get off this planet. So the question is: how do we get to the extraordinary? This lead us to look at data, and we need to be aware that while there is a lot of it, it doesn’t necessarily mean information, and information doesn’t mean wisdom. She note that in medical studies data (from test with patients) have characteristics of specificity (relevant to the issue at hand) and sensitivity (can it measure what we want to measure?). We tend to value and act upon what we can measure, but we need to consider if we are doing it right. Compelling data cause us to pay attention, and can lead to action. Data connect us across time and understanding a universe grater that ourselves, as the pictures from Hubble telescope that show the formation of stars do. These issues are coming together in her current initiative “100 years starship” – if we aim to have an interstellar ship built within the next 100 years, we will have to think about sustainability, life support and ecosystems in a way that will help us solve problems here on Earth. It is about how to have an inclusive journey to make transformation on Earth. She completed her talk by linking art, music and visualisation with the work of Bella Gaia

After the plenary, the session Data for Sustainable Development was building on the themes from the plenary. Some of the talks in the session were:

Louis Liebenberg presented cybertracker – showing how it evolved from early staged in the mid 1990s to a use across the world. The business model of cybertracker is such that people can download it for free, but it mostly used off-line in many places, with majority of the users that use it as local tool. This raise issues of data sharing – data doesn’t go beyond that the people who manage the project. Cybertracker address the need to to extend citizen science activities to a whole range of participants beyond the affluent population that usually participate in nature observations.

Gary Lawrence – discussed how with Big Data we can engage the public in deciding which problem need to be resolved – not only the technical or the scientific community. Ideas will emerge within Big Data that might be coincident or causality. Many cases are coincidental. The framing should be: who are we today? what are we trying to become? What has to be different two, five, ten years from now if we’re going to achieve it? most organisations don’t even know where they are today. There is also an issue – Big Data: is it driven by a future that people want. There are good examples of using big data in cities context that take into account the need of all groups – government, business and citizens in Helsinki and other places.

B – the Big Data in ESPA experience www.espa.ac.uk – data don’t have value until they are used. International interdisciplinary science for ecosystems services for poverty alleviation programme. Look at opportunities, then the challenges. Opportunities: SDGs are articulation of a demand to deliver benefits to societal need for new data led solution for sustainable development, with new technologies: remote sensing / UAVs, existing data sets, citizen science and mobile telephony, combined with open access to data and web-based applications. Citizen Science is also about empowering communities with access to data. We need to take commitments to take data and use it to transforming life.

Discussion: lots of people are sitting on a lots of valuable data that are considered as private and are not shared. Commitment to open data should be to help in how to solve problems in making data accessible and ensure that it is shared. We need to make projects aware that the data will be archived and have procedures in place, and also need staff and repositories. Issue is how to engage private sector actors in data sharing. In work with indigenous communities, Louis noted that the most valuable thing is that the data can be used to transfer information to future generations and explain how things are done.

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mukih

Professor of GIScience, University College London

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