Best practices on climate resources quality documenting using QualityML

Autor: López, Javiera Crisóstomo, Torres, Alaitz Zabala, Òscar González-Guerrero
Rok vydání: 2022
DOI: 10.5281/zenodo.7852299
Popis: This document corresponds to deliverable 4.3 entitled "Best practices on climate resources quality documenting using “QualityML" and is based on the outcomes of the Task 4.3 "Data quality assessment and feedback mechanism for GEOSS datasets". The work starts from the results of the Data Quality Co-design Workshop (DQ Cd W, which completion correspond to MS7), since it was the starting point to know the use cases of each Pilot, with the purpose of advising on the correct documentation of the quality of their data. The main objective of this work is to generate a set of best practices and recommendations for data quality documentation. This objective is achieved through the information extracted from different meetings designed to: • Collect information on the level of experience in using and producing metadata records (with especial emphasis on quality metadata indicators) of the different partners involved in the Pilot cases, as well as their knowledge on Geospatial User Feedback systems. • Collect information on the processes involved in the different data product generation and validation in order to detect possible quality indicators to be recorded on metadata files.
Databáze: OpenAIRE