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Data Analysis Provenance: Use Case for Exoplanet Search in CoRoT Database

机译:数据分析来源:在Corot数据库中使用Exoplanet搜索的用例

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CoRoT (COnvection Rotation and Planetary Transits) is a mission led by the French national space agency CNES, in collaboration with Austria, Spain, Germany, Belgium and Brazil. The mission priority is dedicated to exoplanet search and stellar seismology. CoRoT light curves database became public after one year of their delivery to the CoRoT Co-Is, following the CoRoT data policy. The CoRoT archive contains thousands of light curves in FITS format. Several exoplanet search algorithms require detrend algorithms to remove both stellar and instrumental signal, improving the chance to detect a transit. Different detrend and transit detection algorithms can be applied to the same database. Tracking the origin of the information and how the data was derived in each level in the data analysis process is essential to allow sharing, reuse, reprocessing and further analysis. This work aims at applying a formalized and codified knowledge model by means of domain ontology. It allows to enrich the data analysis with semantic and standardization. It holds the provenance information in the database for a posteriori recovers by humans or software agents.
机译:COROT(对流旋转和行星途转)是法国国家空间机构CNE领导的任务,与奥地利,西班牙,德国,比利时和巴西合作。使命优先级致力于外产搜索和恒星地震学。 Corot Light Curves Database在循环数据策略之后向CoroT Co-IS交付一年后成为公众。 COROT存档包含成千上万的光线格式。几个ExoproAlet搜索算法需要DEVREND算法来消除恒星和仪器信号,从而改善检测过境的机会。不同的DELEND和TRANSIT检测算法可以应用于同一数据库。跟踪信息的原点以及数据分析过程中每个级别的数据如何导出是必不可少的,以允许共享,重用,再处理和进一步分析。这项工作旨在通过域本体进行正式和编纂的知识模型。它允许通过语义和标准化来丰富数据分析。它在数据库中占据了人类或软件代理的后验恢复。

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