PRECIsE seeks to contribute to debates on the impacts of the use of Big Data on Climate Research addressing the SDGs.
The quality, originality and credibility of PRECIsE derives from the search to unearth fresh evidence of the multidisciplinary dimensions of climate change on society addressing cutting-edge approaches on Climate Modelling, Big Data and Analytics, Statistics and Policy Making. The team will address as a central problem how best to make a (causal) connection between the many and varied local activities and more macro longer-term global outcomes through the application of cutting-edge approaches in agriculture, environment and climate in dryland areas (Case Study: Cape Verde). We will be focused on combining Modelling Tools and Big Data and Analytics, Statistics with Evidence-Based Policy Making to spur greater action on Climate Change capturing potential causal pathways and accounting for the effects of major discontinuities in climatic, social and ecological conditions in order to provide stakeholders and governments with information about the connections between global change and local impacts, and how local actions influence global changes integrating gender dimension in the research content effectively. Our strategy is to tell people about their interaction with the environment locally in ways they can understand, and the only way to do that is with big data analysis. PRECIsE also aims to advance research and foster innovation and scientific knowledge to improve and advance life, society and the economy in Europe, Africa, and worldwide through training-through-research. As expected innovative results, PRECIsE will contribute to debates on the impacts of the use of Big Data and Analytics on Climate Change Research addressing the 2030 Agenda of Sustainable Development aimed at demonstrating new ways of understanding its impacts on society, agriculture and in the environment, in order to drive innovation to help us reduce our impacts on the climate and adapt to a changing world.
What actions do you propose?
Climate change is projected to have substantial adverse impacts on future development pathways, in developing and developed countries alike2 . It will lead the World to fundamental socioeconomic and environmental transitions3 . Although, it remains difficult to move beyond this broad concept and begin to answer specific questions, like how much climate change can be tolerated before complex socioeconomic, agricultural and environmental systems start to shift4.At the local and global levels, social-ecological systems (SES) theory, sustainability evaluation frameworks, and assessment methods are still limited by the inability of current tools and models to account for major pathways of potential effects of environmental, political and socioeconomic damage on society5,6,7,8,9,10. In this regard, as the world embarks on an ambitious project to meet new Sustainable Development Goals11 (SDGs), there is an urgent need to mobilise the data revolution12 for all people and the whole planet in order to monitor progress, hold governments accountable and foster sustainable development as new technologies are leading to an exponential increase in the volume and types of data available, creating unprecedented possibilities for informing and transforming society and protecting the environment13. Thence, Data needs improving. Despite considerable progress in recent years, whole groups of people are not being counted and important aspects of people’s lives and environmental conditions are still not measured14. Data are the lifeblood of decision-making and the raw material for accountability15. Without high-quality data16 providing the right information on the right things at the right time; designing, monitoring and evaluating effective policies becomes almost impossible as the total impact of climate change on the society is unclear, although resulting in negative impacts17. PRECIsE, then, is expected to be of a fundamental value to a proper validity, reliability and measurement of the data used in research.
PRECIsE aims to support detailed predictions about the effects of climate change on society in dryland areas (Case Study: Cape Verde), and to make those predictions available to the general public by the development of an analytical framework of systematic analysis addressing the 2030 Agenda of Sustainable Development integrating comprehensive environmental and socioeconomic analysis. The objectives will follow these parameters: Parameter 1 - WP1: The Development of Innovative Models, Tools, New Methodologies and Research Strategies. Parameter 2 - WP2: Foster the Use of Big Data on Climate Change Research. Parameter 3 - WP3: To Reach European Policy objectives concerning Sustainable Development and Climate Change.
The type of research is comparative, case-study and evidence-based. Methodologically, it will employ mixed methods such as multi-criteria analyses and process-tracing methods to develop innovative models, tools, new methodologies and research strategies. PRECIsE will take into account complex interactions and cross-cutting themes between climate and social and ecological systems in dryland areas to estimate the effect of climate change on society. The team will build PRECIsE upon the SACRED framework to incorporate distributions of climate outcomes allowing evaluation of robust adaptation strategies. Focusing on distributions of socioeconomic outcomes, which represents an inherent step into big data. This framework traces the implications of changes in selected outcomes through a series of important impact channels. These impacts will serve as inputs into a political and economy-wide model in order to consider economic impacts and policy options. The innovation activities proposed in PRECIsE will be implemented across borders, applying methods from various disciplines, opened to research outside traditional approaches. Although it will be built on the previous United Nations and Universities Data and experience it will involve training of the team and local actors in the areas of expertise and subjects of study - WP1 - to generate innovative outcome specific simulation models and trade-off analysis to estimate future climate change-attributable sustainable development effects based on a future annual rate of global change in dryland areas (Case Study: Cape Verde) following the methods, standards and procedures of current available models and tools such as the Dehesa Model (UPM - Patented software: Dehesa Model (agroforestry systems simulated model) version 1.0, Nº reference: 16/2009/6250, Property: Universidad Politécnica de Madrid). WP5 – Training in the use of this software will follow the guidelines in a customized Activities Development Plan. The cutting-edge approach is based - WP2 - on the leverage of big data from available databases, using United Nations Methodology (FAO, UNDP Data, etc) to identify revolutionary new approaches to climate mitigation and adaptation based on datasets available in open data from countries and industries in dryland areas (Case Study: Cape Verde). We will analyse anonymised and aggregated data from digital data sources such as mobile network data, financial data, social media data, retail data or energy usage data, etc, to provide valuable insights on human behaviour and climate risk. Followed up by participatory consultations and expert assessments in the host team in Cape Verde, using a variety of inter- multidisciplinary methods and evaluate their effects on selected outcomes. We will contextualize Data in synergy with the Universidad Politécnica de Madrid - UPM (integrating many different research groups and projects) as well as in the proposed field activities in Cape Verde, using satellite images, GIS technology (Geographic Information Systems), socioeconomic data, censuses, surveys, vulnerability, modelling tools, etc. The aim is to - WP3 – generate and improve indicators to support decision-making mechanisms and action plans, addressing the 2030 Agenda of Sustainable Development, to move towards more sustainable and resilient societies based on multi -stakeholder partnerships (academic and non-academic sectors) to integrate knowledge, influence and required data as a tool for social and technical innovation fostering the use of Evidence-Based Policy-Making to spur greater action on Climate Change according to European standards (ETC/CCA methods and standards). This proposal will follow the UPM Data Management Plan – PA GO DA – and the Guidelines on European Research Guidelines (Data Management in Horizon 2020). We intend to use a systems perspective to support the SACRED framework to support evaluation capacity, enhancing evaluation quality and ultimately advance the understanding of system dynamics theory, with focus on horizontal and environmental policy integration and processes as well as questions of legitimacy, accountability and sustainability including evidence-based practice and translational research to improve the use of modelling tools and Big Data on climate change research.
Firstly, PRECIsE will demonstrate its originality and innovative aspects by combining inter multidisciplinary cutting-edge approaches on Climate Modelling*, Big Data and Analytics** with Evidence-Based Policy Making *** to spur greater action on Climate Change. Its motivation is Data Revolution, aimed at the responsible use of Big Data in interaction with society towards the SDGs full implementation as the need for new methods to deal with big data is a common theme in most scientific fields. Secondly, PRECIsE is likely to address specific challenges to sustainable development implementation that will rely on a global partnership and active engagement of governments, as well as civil society, the private sector, and the United Nations system to succeed. The originality and innovative aspects of this proposal also rely on the fact that there is still a large gap between the availability of knowledge and its effective application in decision making. We will address this gap. At the same time we believe that PRECIsE will be of great value for the understanding of the theme making it feasible to develop practical and applicable solutions, based in a intersectoral approaches between academic and non-academic sectors as the proposed research is of very high quality utilising cutting-edge approaches. In this regard, the contribution that the action is expected to make to advancements within the action field will be shown by encouraging preliminary results.
PRECIsE assumes a strong inter- multidisciplinary aspect and a cutting-edge approach as one of its key components are related to policy development as well. It aims to Reach European Policy objectives concerning Sustainable Development and Climate Change by the Unearthing of Fresh Evidence of the Multidisciplinary Dimensions of Climate Change in dryland areas Using Climate Modelling, Big Data and Analytics and Statistics.
WP7 - Several outreach activities will be implemented during the evolution of PRECIsE, aiming to reach a wide variety of people. The activities proposed are the following: Taking part in “Semana de la Ciencia en Madrid” as well as in Local outreach activities in Cape Verde, and in United Nations meeting and events. The team will present their work, explaining in a general way to specialists and lay person audiences what Big Data on Climate Change Research and its applications are and how to use the results to advance science, life and society. They will stress the importance of Climate Actions for Europe and Africa. It will be planned collaboration with popular science blogs and newsletters as an outreach activity. The team will seek to collaborate with the National Climate Justice blog, the itdUPM Blog, the Climate Reality Project, the Medact blog, KDnuggets, weADAPT® and the Klimalog to spread the importance of this project, along with publications in the itdUPM, Ceigram and UPM newsletters. Participation in European Researchers’ Meetings organized by the UPM, and participation in The UN Big Data Climate Challenge, in the IDB Group Conferences, in the ETC CCA Events and Workshops as well as EURAXESS activities in order to spread scientific knowledge to the general public. The team will follow the guideline Communicating EU research and innovation guidance for project participants as well as to the "communication" section of the H2020 Online Manual.
Pilot Program Cape Verde, West Africa and the European Union, Madrid, Spain.
Duration: 24 months. (Possible extension: 12 months). Total: 36 months.
Who will take these actions?
Universidad Politécnica de Madrid - itdUPM
United Nations Joint Office of UNDP, UNFPA and UNICEF in Cape Verde, Africa. United Nations Development Programme (UNDP/UNV)
Local Universities in Cape Verde
Where will these actions be taken?
In the European Union, Madrid, Spain
In Developing Countries, Cape Verde, Africa
What are other key benefits?
The PRECIsE’s proof of excellence and the scientific challenge of the project as well as the relevance of the topic to science rely on the analysis and development of effective process designs that will take into account Industry and stakeholders’ actual needs and problems by the use of cross-sectoral approaches to model, interpret and illustrate predicted effects of climate change on society. PRECIsE will be built around the principle of predictive modeling, based on real, observed data, then by adjusting variables we expect to be able to see how it might be possible to halt or even, in some cases, reverse the effects of major discontinuities and the damage that is being done. After all, the whole point of big data analysis, in climate science or otherwise, is to generate actionable insights that can drive growth or change (or, in the case of the climate, prevent too much change).
What are the proposal’s costs?
Team (Values per Individual in Euros (€)/Number of Months: 12):
One (1) Team Leader.
Annual Living Allowance: 120000,00€
Mobility Allowance, Travels, Relocation: 15000,00€
Annual Research, training and networking costs: 20000,00€
Material, Management and Overheads: 15000,00€
Total Anual Investment: 170000,00€
Four (4) seasoned researchers (PhD and/or Postdocs).
Annual Living Allowance: 60000,00€
Mobility Allowance, Travels, Relocation: 10000,00€
Annual Research, training and networking costs: 10000,00€
Material, Management and Overheads: 10000,00€
Total Investment (4): 360000,00€
Three (3) Masters and/or Doctoral students.
Annual Living Allowance: 40000,00€
Mobility Allowance, Travels, Relocation: 6000,00€
Annual Research, training and networking costs: 5000,00€
Material, Management and Overheads: 5000,00€
Total Investment (3): 168000,00€
Team Total Annual Investment: 170000,00 + 360000,00 + 168000,00 = 698000,00€
Three (3) years Pilot Program Total Investment: 2094000,00€
The proposed actions will be phased in over the short term (3 years). Posterior development following the 2030 Sustainable Development Agenda (3-13 years).
Pilot Program: Cape Verde, West Africa.
European Union: Madrid, Spain.
Duration - Pilot Program: 24 months. (Possible extension: 12 months). Total: 36 months.
I am not sure. I am not totally familiarized with the Climate CoLab.
1 Causal pathways, related to proximal and distal (upstream) risk factors in agriculture, environment and the climate are not easily modelled using currently available methods.
2 IPCC 2014.http://ar5-syr.ipcc.ch/topic_futurechanges.php
3 Global trends and challenges to sustainable development post-2015.http://www.un.org/en/development/desa/policy/wess/wess_current/wess2013/Chapter1.pdf
4 Brown, Alastair. 2014. Ecological transitions: Simulating Ecosystem Shifts. Nature Climate Change. doi:10.1038/nclimate2126
5 Institutions and adaptation processes: A social-ecological system approach for the study of adaptation to climate change. https://dlc.dlib.indiana.edu/dlc/bitstream/handle/10535/9374/WG5_Epstein%20et%20al.pdf?sequence=1
6 The Resilience, Adaptation and Transformation Assessment Framework: From theory to application.http://www.stapgef.org/stap/wp-content/uploads/2015/03/CSIRO-STAP-Resilience-Adaptation-TransformationAssessment-Framework-Report.pdf
7 Allen, T. & Prosperi, P. 2016. Modeling Sustainable Food Systems. Environmental Management. 57: 956. doi:10.1007/s00267-016-0664-8
8 Leslie, H. M. et al., 2015. Operationalizing the social-ecological systems framework to assess sustainability. Proceedings of the National Academy of Sciences of the United States of America.http://doi.org/10.1073/pnas.1414640112
9 Schlüter, M., et al., 2014. Application of the SES framework for model-based analysis of the dynamics of social-ecological systems. Ecology and Society.http://dx.doi.org/10.5751/ES-05782-190136
10 Binder, C. R., et al., 2013. Comparison of frameworks for analyzing social-ecological systems. Ecology and Society.http://dx.doi.org/10.5751/ES-05551-180426
11 The 17 SDGs of the 2030 Agenda for Sustainable Development.http://www.un.org/sustainabledevelopment
12 UN Data Revolution. Report: A World That Counts.http://www.undatarevolution.org/wp-content/uploads/2014/11/A-World-That-Counts.pdf
13 Data Revolution for Sustainable Development. 2014.http://www.undatarevolution.org/wp-content/uploads/2014/12/A-World-That-Counts2.pdf
14 Jerven, Morten. Development by Numbers. A summary. Associate Professor in Global Change and International Relations, International Environment and Development Studies, Norwegian University of Life Sciences
15 Be Data Driven Guides.http://digitalprinciples.org/be-data-driven-guides
16 Jerven, Morten, 2014. The problem with the data revolution in four Venn diagrams. The Guardian. Global Development Professionals Network. Development 2030.https://www.theguardian.com/global-developmentprofessionals-network/2014/dec/17/data-revolution-limitations-in-images
17 Tarp, Finn, et al. 2014. Development under Climate Change: An Application to South Africa. Big Data Climate Challenge – Climate Summit 2014. https://www3.wider.unu.edu/sites/default/files/News/Documents/Big-Data-Climate-Challenge-UNU-WIDER-submission-5633.pdf