Peter Fox, Prof & Tetherless World Constellation, Chair, Earth

Peter Fox, Prof & Tetherless World Constellation, Chair, Earth

The U.S. Global Change Research Program (USGCRP) coordinated the production of the 3rd U.S. national climate assessment (NCA3) that presents the best understanding of the nature and impacts of global changes in Earth's climate. Such an undertaking relies on a diverse collection of scientific research, researchers and data sources. Inherent in science undertakings are the cognitive biases introduced by people. Different people introduce difference biases in different stages of their research. The process for assessment reports, that are mostly based on previously published work (not just the NCA3),  to reduce bias is chapters to be authored by multiple reseachers, and edited by different researchers. To date there is no systematic approach to representing bias and bias mitigation for such reports. However, it is common for agencies and organizations releasing climate change information to receive requests for all supporting materials resulting in a particular finding or data underpinning a key figure in the assessment. Unfortunately, the provision of such information rarely can be assemlbed to assess the influence of bias, let alone engender a level of trust in the findings and recommendations in the report. The current approach toward the ideal solution consists of capturing and presenting global change provenance, i.e. a model of relations to the research papers, data sets, models, analyses, observations, satellites, etc., that support the key research findings in this domain can increase understanding and aid in the verifiability of results and conclusions. In fact while the encoded model is an ontology, the model begins at the concept level with the goal of minimizing cognitive bias in terms of the inter-relations. The modeling and cognition aspect will be discussed in the context of version 1 of the Global Change Information System (GCIS; together with colleagues at the USGCRP, the University Corporation for Atmospheric Research and a commercial web desginer) that presents the content of the NCA3 report and its provenance, including the scientific support for the findings of the assessment. GCIS presents this information both through a human accessible Web site as well as a machine-readable interface for automated mining of the provenance graph. This talk describes the process of developing the NCA and how the provenance trail of the report and each of the technical inputs are captured and represented using W3C PROV. The overall intent of these traceable accounts is to increase transparency into the assessment process, increase verifiability, and possibility of reproducibility, and ultimately increase the credibility and trust of the resulting report.



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