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+The Premise Validation Project introduces the Python package dopo (short for Detecting Outliers in Premise Operations). This package provides an outlier detection framework specifically designed for premise-based prospective Life Cycle Assessment (LCA) databases.
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+dopo visualizes premise databases by sector and defined characterization methods. It can also quickly compare LCA scores between a premise database and an ecoinvent database. It currently generates three types of plots that present data at varying levels of granularity, along with tables containing detailed information. The visualizations are outputted in an Excel workbook, making it easier for users to analyze and interpret the results.
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+The goal of dopo is to streamline the outlier detection process, allowing users to quickly identify anomalies in premise data and better understand their implications on LCA results.
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+Besides, dopo can also be used adaptively for visualizing a whole database not filtered by sector and to assess any other database used in brightway.