@article {stvilia_metadata_2004,
	title = {Metadata Quality for Federated Collections},
	year = {2004},
	note = {00059},
	month = {nov},
	abstract = {he aim of the essay is to showcase an "approach to conceptualizing, measuring, and assessing metadata quality" by presenting the results from an empirical study on the quality of metadata across large corpuses. The methodology of this empirical study involved creating a framework of quality dimensions used to then assess the quality of the data. These dimensions were intrinsic information quality, relational information quality, and reputational information quality. Stvilia et al. concluded in their study that poor quality metadata is equal to a value loss, that quality is equal to the amount of interaction with an object, and that quality is also equal to the effectiveness (and efficiency) of the metadata. In a random sample of 150 OAI Simple DC records (taken from a total corpus of 154,782 records) the research team determined six major quality issues: "(1) lack of completeness, (2) redundant metadata; (3) lack of clarity; (4) incorrect use of DC schema elements or semantic inconsistency; (5) structural inconsistency and (6) inaccurate representation." In conclusion, Stvilia et al. state that their future research will "focus on user valuations of metadata quality." },
	url = {https://www.ideals.illinois.edu/handle/2142/721},
	author = {Stvilia, Besiki and Gasser, Les and Twidale, Michael B. and Shreeves, Sarah L. and Cole, Timothy W.}
}