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Micronutrient Action Policy Support (MAPS) - A decision support tool for investigating the scale and geographic distribution of micronutrient availability in sub-Saharan Africa

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Micronutrient Action Policy Support (MAPS) - A decision support tool for investigating the scale and geographic distribution of micronutrient availability in sub-Saharan Africa
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Micronutrient deficiencies (MNDs), so-called ‘hidden-hunger’, can have serious ramifications for the health of individuals affected and the economy of the country in which they live. MNDs are a global problem but disproportionately affect populations in low-income countries. Work to alleviate these deficiencies aligns with the UN’s Sustainable Development Goals (SDG), especially SDG2 – access to adequate safe and nutritious food. Data which can support the understanding of the scale and location of these deficiencies can be fragmented in their availability and accessibility, creating a barrier to their use in planning interventions by stakeholders in the very nations where the impacts of MNDs are most severe. The Micronutrient Action Policy Support (MAPS) tool is a web-hosted open access platform providing a unique enabling environment for the wider agriculture-nutrition community and beyond which allows users to view and explore MND risks at various spatial and temporal scales. The tool can provide users with dietary micronutrient supply estimates of all nations in sub Saharan Africa using national-scale and subnational-scale data. Preprocessing steps to clean these data in R language are made available through the open github repository, so that any user can replicate the data used in the tool. Priorities for the data and functionality have been co-designed with key users from project proposal stage. Stakeholder feedback is used in continued iteration as richer content, supporting material, and functionality is planned, developed and released. The platform is built on open-source technologies utilising Postgres and PostGIS to store, combine and interrogate a range of heterogeneous datasets to calculate micronutrient supply estimates, node.js for data APIs and web map services using Geoserver. Further data processing is conducted using R, with the front-end interface utilising Angular, leaflet.js and chart.js. Metadata is managed and served via Geonetwork. The code for the platform, as well as data processing scripts, methods and processes are all open source at https://github.com/micronutrientsupport. This talk will provide an overview of the platform along with the datasets and open-source technologies that underpin its functionality, and the UX approaches taken to ensure that this tool meets the currently unmet needs of priority users. (micronutrient.support)
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Transcript: English(auto-generated)
Hi, I'm Andrew Bean from the British Geological Survey, and I'm going to talk to you a little bit about our work in the Micronutrient Action Policy Support, or MAPS project, developing a decision support tool for investigating the scale and geographic distribution of micronutrient availability in sub-Saharan Africa. So micronutrient deficiencies, so-called hidden hunger, can have serious ramifications
for the individuals affected, as well as the economies of the countries in which they live. They're a global problem, but they're of significant concern in sub-Saharan Africa, and work to alleviate these deficiencies aligned particularly with SDGs 2 and 3, particularly
SG2 access to safe and nutritious food. So micronutrient availability in populations can vary for a number of reasons, and can vary spatially, for example, in relation to soil geochemistry, so that can have an increase in nutrients that are taken up by plants that subsequently become foodstuffs.
The data available for evaluating and understanding the scale and location of these deficiencies can be quite fragmented in its availability, and can create a barrier for its use to plan interventions, particularly by stakeholders in the very nations where the impacts of
these micronutrient deficiencies are the most severe. And this is where the MAPS project comes in. So we integrate a range of heterogeneous data sets, ranging from diet data relating to food that's consumed, as well as the nutrient content of those foodstuffs.
Biomarker measurements, so direct measurements of micronutrient biomarkers from blood and urine samples, projections of micronutrient availability into the future based on various social and climate projections, along with a range of auxiliary data sets that are used
as part of the analyses. So the common factor between all these data sets is that they all relate to some specific geographic location, be that either point data or a wider polygonal area. So we're all here to talk about software, so what do we use to wrangle and process and visualize this data?
So our core data store is spatially enabled Postgres, and then the data is served by a REST API, OGC web services through GeoServer, and the metadata is cataloged in GeoNetwork. We also make use of OpenCPU to provide a REST API on top of more complicated geostatistical
processes using R. In the front end, it's a web application using Angular, and then Leaflet and ChartJS for visualizing and presenting the data. We also draw upon a number of other open source projects, for example FIDR for collating user feedback, Unleash for feature flags, and Plausible for analytics.
And of course all of our code, our methods, our processes are all open source as well on our GitHub repository, so on our GitHub organization, so invite you to look there. In terms of the outputs, I won't dwell too long on this, just due to the length of the talk, but I'll provide just a few screenshot examples of the decision support tool and
the kind of data dashboard that we've produced, and just highlight that it is available in Open Beta. We've just recently released this, so please feel free to check it out. On top of that, I should just say that although the web application is the primary output for our key stakeholders, the API web services, metadata catalog, are all again
first-class outputs and available for integration by other teams and other projects into existing workflows, new tools, etc. And with that, I'm just going to say thank you for listening.
If you're interested in finding out more, please check out our various kind of web and GitHub presence, or feel free to chat to me in any of the coffee breaks, I'd be very happy to talk further. Thank you very much. Thank you very much.