Quality Assurance Framework Development Based on Six New ECV Data Products to Enhance User Confidence for Climate Applications

Nightingale, Joanne; Boersma, K. Folkert; Müller, Jan-Peter; Compernolle, Steven; Lambert, Jean-Christopher; Blessing, Simon; Giering, Ralf; Gobron, Nadine; Smedt, Isabelle De; Coheur, Pierre‐François; George, Maya Madhavan Dr. A.P.; Schulz, Jörg B.; Wood, Alex J.

doi:10.20944/preprints201806.0155.v1

Cited by 10 publications

(1 citation statement)

References 26 publications

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“…Feedback on the operational utility of the prototype QA4ECV QA system was sourced from the following: the QA4ECV product producers [53]; the independent QA office auditors (NPL and IASB-BIRA) [53]; and a selected number of product "champion" users that were identified during the project [54]. The QA4ECV product producers agreed that the QA system is streamlined and relatively easy to use, and likewise, champion users were positive concerning the product QA report content, traceability chains, and accessibility of this standardised information.…”

Section: Discussionmentioning

confidence: 99%

Quality Assurance Framework Development Based on Six New ECV Data Products to Enhance User Confidence for Climate Applications

et al. 2018

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Data from Earth observation (EO) satellites are increasingly used to monitor the environment, understand variability and change, inform evaluations of climate model forecasts, and manage natural resources. Policymakers are progressively relying on the information derived from these datasets to make decisions on mitigating and adapting to climate change. These decisions should be evidence based, which requires confidence in derived products, as well as the reference measurements used to calibrate, validate, or inform product development. In support of the European Union's Earth Observation Programmes Copernicus Climate Change Service (C3S), the Quality Assurance for Essential Climate Variables (QA4ECV) project fulfilled a gap in the delivery of climate quality satellite-derived datasets, by prototyping a generic system for the implementation and evaluation of quality assurance (QA) measures for satellite-derived ECV climate data record products. The project demonstrated the QA system on six new long-term, climate quality ECV data records for surface albedo, leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FAPAR), nitrogen dioxide (NO 2 ), formaldehyde (HCHO), and carbon monoxide (CO). The provision of standardised QA information provides data users with evidence-based confidence in the products and enables judgement on the fitness-for-purpose of various ECV data products and their specific applications.

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Section: Discussionmentioning

confidence: 99%

Quality Assurance Framework Development Based on Six New ECV Data Products to Enhance User Confidence for Climate Applications

et al. 2018

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Quality Assurance for Spatial Research Data

Wagner

Henzen

2022

IJGI

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In Earth System Sciences (ESS), spatial data are increasingly used for impact research and decision-making. To support the stakeholders’ decision, the quality of the spatial data and its assurance play a major role. We present concepts and a workflow to assure the quality of ESS data. Our concepts and workflow are designed along the research data life cycle and include criteria for openness, FAIRness of data (findable, accessible, interoperable, reusable), data maturity, and data quality. Existing data maturity concepts describe (community-specific) maturity matrices, e.g., for meteorological data. These concepts assign a variety of maturity metrics to discrete levels to facilitate evaluation of the data. Moreover, the use of easy-to-understand level numbers enables quick recognition of highly mature data, and hence fosters easier reusability. Here, we propose a revised maturity matrix for ESS data including a comprehensive list of FAIR criteria. To foster the compatibility with the developed maturity matrix approach, we developed a spatial data quality matrix that relates the data maturity levels to quality metrics. The maturity and quality levels are then assigned to the phases of the data life cycle. With implementing openness criteria and matrices for data maturity and quality, we build a quality assurance (QA) workflow that comprises various activities and roles. To support researchers in applying this workflow, we implement an interactive questionnaire in the tool RDMO (research data management organizer) to collaboratively manage and monitor all QA activities. This can serve as a blueprint for use-case-specific QA for other datasets. As a proof of concept, we successfully applied our criteria for openness, data maturity, and data quality to the publicly available SPAM2010 (crop distribution) dataset series.

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Evaluating Geospatial Data Adequacy for Integrated Risk Assessments: A Malaria Risk Use Case

Petutschnig,

Clemen,

Klaußner

et al. 2024

IJGI

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International policy and humanitarian guidance emphasize the need for precise, subnational malaria risk assessments with cross-regional comparability. Spatially explicit indicator-based assessments can support humanitarian aid organizations in identifying and localizing vulnerable populations for scaling resources and prioritizing aid delivery. However, the reliability of these assessments is often uncertain due to data quality issues. This article introduces a data evaluation framework to assist risk modelers in evaluating data adequacy. We operationalize the concept of “data adequacy” by considering “quality by design” (suitability) and “quality of conformance” (reliability). Based on a use case we developed in collaboration with Médecins Sans Frontières, we assessed data sources popular in spatial malaria risk assessments and related domains, including data from the Malaria Atlas Project, a healthcare facility database, WorldPop population counts, Climate Hazards group Infrared Precipitation with Stations (CHIRPS) precipitation estimates, European Centre for Medium-Range Weather Forecasts (ECMWF) precipitation forecast, and Armed Conflict Location and Event Data Project (ACLED) conflict events data. Our findings indicate that data availability is generally not a bottleneck, and data producers effectively communicate contextual information pertaining to sources, methodology, limitations and uncertainties. However, determining such data’s adequacy definitively for supporting humanitarian intervention planning remains challenging due to potential inaccuracies, incompleteness or outdatedness that are difficult to quantify. Nevertheless, the data hold value for awareness raising, advocacy and recognizing trends and patterns valuable for humanitarian contexts. We contribute a domain-agnostic, systematic approach to geodata adequacy evaluation, with the aim of enhancing geospatial risk assessments, facilitating evidence-based decisions.

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Quality Assurance Framework Development Based on Six New ECV Data Products to Enhance User Confidence for Climate Applications

Cited by 10 publications

References 26 publications

Quality Assurance Framework Development Based on Six New ECV Data Products to Enhance User Confidence for Climate Applications

Quality Assurance Framework Development Based on Six New ECV Data Products to Enhance User Confidence for Climate Applications

Quality Assurance for Spatial Research Data

Evaluating Geospatial Data Adequacy for Integrated Risk Assessments: A Malaria Risk Use Case

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