Rubric-Q: Adding quality-related elements to the GEOSS clearinghouse datasets

Alaitz Zabala; Anna Riverola; Ivette Serral; Paula Diaz; Victoria Lush; Joan Maso; Xavier Pons; Ted Habermann

doi:10.1109/JSTARS.2013.2259580

Rubric-Q: Adding quality-related elements to the GEOSS clearinghouse datasets

Alaitz Zabala, Anna Riverola, Ivette Serral, Paula Diaz, Victoria Lush, Joan Maso, Xavier Pons, Ted Habermann

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

8 Citations (Scopus)

Abstract

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. © 2013 IEEE.

Original language	English
Article number	6514679
Pages (from-to)	1676-1687
Journal	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Volume	6
Issue number	3
DOIs	https://doi.org/10.1109/JSTARS.2013.2259580
Publication status	Published - 2013

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to <a href="mailto:[email protected]">[email protected]</a>.

Funding

This work was supported in part by the European Commission through the FP7-265178-GeoViQua project (ENV.2010.4.1.2-2) and in part by a grant to the Consolidated Research Groups given by the Catalan Government (2009 SGR 1511). The work of X. Pons was supported in part by an ICREA Acadèmia Excellence in Research grant (2011-2015).

Research Keywords

GEOSS Clearinghouse
lineage
metadata visualization
quality
usage

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abstract = "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. {\textcopyright} 2013 IEEE.",

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Rubric-Q: Adding quality-related elements to the GEOSS clearinghouse datasets. / Zabala, Alaitz; Riverola, Anna; Serral, Ivette et al.
In: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 6, No. 3, 6514679, 2013, p. 1676-1687.

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

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AU - Riverola, Anna

AU - Serral, Ivette

AU - Diaz, Paula

AU - Lush, Victoria

AU - Maso, Joan

AU - Pons, Xavier

AU - Habermann, Ted

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Rubric-Q: Adding quality-related elements to the GEOSS clearinghouse datasets

Abstract

Bibliographical note

Funding

Research Keywords

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