Publication Date

2013-02-28

Abstract

Academic libraries have a critical role to play as data quality hubs on campus. There is an increased need to ensure data quality within ‘e-science’. Given academic libraries’ curation and preservation expertise, libraries are well suited to support the data quality process. Data quality measurements are discussed, including the fundamental elements of trust, authenticity, understandability, usability and integrity, and are applied to the Digital Curation Lifecycle model to demonstrate how these measures can be used to understand and evaluate data quality within the curatorial process. Opportunities for improvement and challenges are identified as areas that are fruitful for future research and exploration.

Rights


This work is licensed under a Creative Commons Attribution 3.0 License.

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