Quantifying and measuring metadata completeness

Abstract

Completeness of metadata is one of the most essential characteristics of their quality. An incomplete metadata record is a record of degraded quality. Existing approaches to measure metadata completeness limit their scope in counting the existence of values in fields, regardless of the metadata hierarchy as defined in international standards. Such a traditional approach overlooks several issues that need to be taken into account. This paper presents a fine‐grained metrics system for measuring metadata completeness, based on field completeness. A metadata field is considered to be a container of multiple pieces of information. In this regard, the proposed system is capable of following the hierarchy of metadata as it is set by the metadata schema and admeasuring the effect of multiple values of multivalued fields. An application of the proposed metrics system, after being configured according to specific user requirements, to measure completeness of a real‐world set of metadata is demonstrated. The results prove its ability to assess the sufficiency of metadata to describe a resource and provide targeted measures of completeness throughout the metadata hierarchy.

Recovering uncaptured citations in a scholarly network: A two‐step citation analysis to estimate publication importance

“…Bruce and Hillmann (2004) enhanced and modified these six indicators for the library community. Margaritopoulos, Margaritopoulos, Mavridis, and Manitsaris (2012) found that completeness of metadata is one of the most essential characteristics of their quality; the authors presented a fine-grained metrics system for measuring metadata completeness, based on field completeness. Margaritopoulos, Margaritopoulos, Mavridis, and Manitsaris (2012) found that completeness of metadata is one of the most essential characteristics of their quality; the authors presented a fine-grained metrics system for measuring metadata completeness, based on field completeness.…”

“…The enhanced criteria include completeness, accuracy, provenance, conformance to expectation, logical consistency, coherence, timeliness, and accessibility. Margaritopoulos, Margaritopoulos, Mavridis, and Manitsaris () found that completeness of metadata is one of the most essential characteristics of their quality; the authors presented a fine‐grained metrics system for measuring metadata completeness, based on field completeness. Citation quality and its correlation with retrieval/recommendation ranking performance in this framework, unfortunately, have rarely been investigated.…”

Metadata quality in learning object repositories: a case study

“…Typical indicators and dimensions of quality of metadata records in LORs include the ones presented in Table I, as they have been the basis for a number of studies focusing on the metadata quality assessment of LORs (Yen and Park, 2006;Ma et al, 2010;Ochoa et al, 2011;Westbrook et al, 2012;Margaritopoulos et al, 2012).…”

“…More specifically, the data used to describe the learning objects (i.e. its metadata) -a key enabler for the deployment of efficient search mechanisms and services on top of LORs -seems to be incomplete, as several studies indicate (Najjar et al, 2003;Hughes, 2004;Shreeves et al, 2005;Yen and Park, 2006;Ma et al, 2010;Manouselis et al, 2010;Ochoa et al, 2011;Westbrook et al, 2012;Margaritopoulos et al, 2012). Actually, the time span of these studies indicates that the problem has been around for almost a decade and some of these authors point out even more serious quality problems than the completeness of the records, with issues related to the content of the completed metadata records in terms of validity and correctness.…”

Semiotic Principles for Metadata Auditing and Evaluation

“…In an effort to improve metadata in an information system, reviewing the types of data and ways that they are being used for particular elements in records can be a way of isolating particular issues involved with the metadata creation process. 3 Hopefully this would lead to an improvement in the overall consistency of records.…”