Since 2022, MapAction, the United Nations Office for the Coordination of Humanitarian Affairs (UN OCHA) and the University of Georgia, Information Technology Outreach Services (ITOS) have been working on strengthening data quality for what are referred to as Common Operational Datasets (COD): ‘best available’ shared datasets that ensure consistency and simplify the discovery and exchange of key data among humanitarian organisations.
Bad data equals more human suffering. Each time a disaster or a health epidemic strikes, data is at the heart of the first response. Yet public data is often full of gaps. If a population census is old, inaccurate or non-existent, people fall off the map. If a certain area is contested and the admin boundaries are disputed, people pay the price. Data is crucial to estimate people’s vulnerability and wellbeing in an emergency.
Why data quality is important
People overlooked due to data gaps will struggle to gain access to emergency services such as food, water, housing, health or parachute financial aid packages. Emergency service providers need good data and data management tools to make the best decisions under extreme pressure.
People overlooked due to data gaps will struggle to gain access to emergency services such as food, water, housing, health or parachute financial aid packages.
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Poor data quality can undermine the effectiveness of evidence-based decision-making in the humanitarian sector. The path to improvement starts with identifying the challenges.
Humanitarian data highway stakeholders convene
In April 2024, MapAction hosted a panel with other organisations working to build ‘the humanitarian data highway’ to address the challenges on data quality. The panel was hosted at Humanitarian Networks and Partnerships Week (HNPW) in Geneva, Switzerland, and featured panellists from OCHA’s Centre for Humanitarian Data, Flowminder, ACAPS, Impact, CartONG, Heidelberg Institute for Geoinformation Technology (HeiGIT) and Start Network.
The panel, titled ‘Data quality challenges and their impact on the humanitarian response cycle‘, explored data quality for emergency response, preparedness and anticipatory action. All phases of a data project were covered, from data collection to visualisation and accessibility but also the specifics of working with open data and quality frameworks. The panellists also noted that limited resources for COD-related maintenance projects make it hard to fill this gap.
Data analytics ecosystem
More data is needed; although not all data is good data. If we don’t compile and process data by age or gender we’ll fail to understand the specific needs of women and mothers; miscalculating the trajectory of a storm or its geographic boundaries could mean communities remain displaced, stranded and exposed. If we can’t automate the proximity of communities to vital services and support mechanisms our partners cannot maximise the impact of emergency aid delivery. These are just some of many considerations that affect the quality of data, and ultimately, the quality of disaster response reduction efforts.
If we don’t compile and process data by age or gender we’ll fail to understand the specific needs of women and mothers; miscalculating the trajectory of a storm or its geographic boundaries could mean communities remain displaced, stranded and exposed. If we can’t automate the proximity of communities to vital services and support mechanisms our partners cannot maximise the impact of emergency aid delivery.
READ ALSO: Why we must address the gender gap in humanitarian data
Where are the borders?
Within this context, MapAction has been working together with OCHA and the University of Georgia Information Technology Outreach Services (ITOS) on data quality analysis for the Common Operational Datasets (COD) for Administrative Boundaries (COD-AB).
Common Operational Datasets, or COD, are authoritative reference datasets needed to support operations and decision-making for all actors in a humanitarian response. COD are ‘best available’ datasets that ensure consistency and simplify the discovery and exchange of key data. The data is typically geo-spatially linked using a coordinate system (especially administrative boundaries) and has unique geographic identification codes (P-codes).
These data sets are often derived from data collected by local authorities and international partners to ensure quality, but most vitally, local ownership. COD can be collected on administrative boundaries, population and more.
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After a first discussion with OCHA and ITOS partners in 2022, a preliminary methodology proposal has been developed by MapAction to assess the geospatial quality for Common Operational Data-Administrative Boundaries (COD-AB). COD-AB sets can become outdated or less effective if they are not regularly updated. A country’s administrative boundaries can be redrawn more than a dozen times in a tumultuous year; an outdated data set becomes a means of exclusion.
COD-AB sets can become outdated or less effective if they are not regularly updated. A country’s administrative boundaries can be redrawn more than a dozen times a tumultuous year; an outdated data set becomes a means of exclusion.
With this partnership with OCHA and ITOS we aim to create a quantitative assessment mechanism that enables the prioritisation of work to update or enhance existing COD-AB data sets. The expected output is a quality index for each COD-AB data set based on tests for features (geographical, metadata, etc). A diverse team of MapAction volunteers has been formed to tackle this project, with GIS, data engineering, data science and software volunteers.
How does this partnership work?
ITOS analyses and enhances the quality of COD-AB countries proposed by OCHA. The recent discussions have raised, in particular, the need for support on a prioritisation queue. This queue would combine a geospatial quality index and risk index per country in order to help OCHA to select priority countries and ITOS to focus their high level analysis on the most important countries.
Blossoming InnovationHub
As a fledgling branch of any organisation, our InnovationHub is growing wings and beginning to expand its focus areas. The number of partnerships with other organisations working on similar goals is growing.
As climate scientists continue to predict that natural disasters will increase in severity in the coming years, our goal is to make sure no one is left behind and falls off the map. “Any sufficiently advanced technology is indistinguishable from magic,” wrote Arthur C. Clarke. Only by pushing the boundaries and committing resources can we come up with ‘magic’ models and frameworks to combat the climate emergency and mitigate seasonal hazards and conflicts. Our InnovationHub marks our sustainable commitment to that cause.
This work is funded by USAID’s Bureau for Humanitarian Assistance (BHA).
MapAction would like to acknowledge the generous contribution that Max Malynowsky is making to the COD Quality project. Max has dedicated years to contributing to administrative boundaries in the humanitarian sector. His multiple projects, hosted at fieldmaps.io, include significant work towards making it easier to access global boundary data sets, including COD-AB.
Background: About MapAction and building the ‘humanitarian data highway’
There are dozens of agencies and organisations working in what is known as the ‘humanitarian data analytics’ sector: essentially the delivery of data sets, information management systems and in MapAction’s case, geospatial data and expertise, as well as anticipatory action risk models, applied to disaster reduction. They range from large UN agencies to small local civil society organisations. The International Organization for Migration Displacement Tracking Matrix alone brings together 7,000 data collectors and over 600 technical experts serving in over 80 countries.
Since MapAction’s inception in 2002, the organisation has mapped for people in crises in more than 150 emergencies. We have created 1000s of maps used by emergency service providers.
In 2022, MapAction launched an InnovationHub: to tackle some of the biggest challenges confronting data scientists, data analysts and humanitarian responders working with data in emergency relief. We still don’t have all the answers, but we believe that the InnovationHub will find solutions by posing the right questions. Our work is increasingly in anticipatory action: supporting countries to co-build risk models, with the right data, to help mitigate future hazards.
LEARN MORE: MapAction and anticipatory action