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; with talks from Philemon Mjwara, Mary Glackin, Muki Haklay, Christopher Tucker, and Mae Jemison. [I’ll revise the blog with notes later]

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.