Matches in Ruben’s data for { ?s ?p "A large part of scientific output entails computational experiments, e.g., processing data to generate new data. However, this generation process is only documented in human-readable form or as a software repository. This inhibits reproducibility and comparability, as current documentation solutions do not provide detailed metadata and rely on the availability of specific software environments. This paper proposes an automatic capturing mechanism for interchangeable and implementation independent metadata and provenance that includes data processing. Using declarative mapping documents to describe the computational experiment, term-level provenance can be automatically captured, for both schema and data transformations, and storing both the used software tools as the input-output pairs of the data processing executions. This approach is applied to mapping documents described using RML and FnO, and implemented in the RMLMapper. The captured metadata can be used to more easily share, reproduce, and compare the dataset generation process, across software environments."@en }
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- publication abstract "A large part of scientific output entails computational experiments, e.g., processing data to generate new data. However, this generation process is only documented in human-readable form or as a software repository. This inhibits reproducibility and comparability, as current documentation solutions do not provide detailed metadata and rely on the availability of specific software environments. This paper proposes an automatic capturing mechanism for interchangeable and implementation independent metadata and provenance that includes data processing. Using declarative mapping documents to describe the computational experiment, term-level provenance can be automatically captured, for both schema and data transformations, and storing both the used software tools as the input-output pairs of the data processing executions. This approach is applied to mapping documents described using RML and FnO, and implemented in the RMLMapper. The captured metadata can be used to more easily share, reproduce, and compare the dataset generation process, across software environments.".