Rubric-Q: Adding Quality-Related Elements to the GEOSS Clearinghouse Datasets

Geospatial data have become a crucial input for the scientific community for understanding the environment and developing environmental management policies. The Global Earth Observation System of Systems (GEOSS) Clearinghouse is a catalogue and search engine that provides access to the Earth Observa...

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Bibliographic Details
Published inIEEE journal of selected topics in applied earth observations and remote sensing Vol. 6; no. 3; pp. 1676 - 1687
Main Authors Zabala, Alaitz, Riverola, Anna, Serral, Ivette, Diaz, Paula, Lush, Victoria, Maso, Joan, Pons, Xavier, Habermann, Ted
Format Journal Article
LanguageEnglish
Published IEEE 01.06.2013
Subjects
Data visualization
Geospatial analysis
GEOSS Clearinghouse
Global Earth Observation System of Systems
ISO standards
lineage
metadata visualization
quality
Sociology
Spatial databases
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Summary:Geospatial data have become a crucial input for the scientific community for understanding the environment and developing environmental management policies. The Global Earth Observation System of Systems (GEOSS) Clearinghouse is a catalogue and search engine that provides access to the Earth Observation metadata. However, metadata are often not easily understood by users, especially when presented in ISO XML encoding. Data quality included in the metadata is basic for users to select datasets suitable for them. This work aims to help users to understand the quality information held in metadata records and to provide the results to geospatial users in an understandable and comparable way. Thus, we have developed an enhanced tool (Rubric-Q) for visually assessing the metadata quality information and quantifying the degree of metadata population. Rubric-Q is an extension of a previous NOAA Rubric tool used as a metadata training and improvement instrument. The paper also presents a thorough assessment of the quality information by applying the Rubric-Q to all dataset metadata records available in the GEOSS Clearinghouse. The results reveal that just 8.7% of the datasets have some quality element described in the metadata, 63.4% have some lineage element documented, and merely 1.2% has some usage element described.
ISSN:1939-1404
2151-1535
DOI:10.1109/JSTARS.2013.2259580