Academic journal article Information Technology and Libraries

Evaluation of Semi-Automatic Metadata Generation Tools: A Survey of the Current State of the Art

Academic journal article Information Technology and Libraries

Evaluation of Semi-Automatic Metadata Generation Tools: A Survey of the Current State of the Art

Article excerpt


With the rapid increase in all types of information resources managed by libraries over the last few decades, the ability of the cataloging and metadata community to describe those resources has been severely strained. Furthermore, the reality of stagnant and decreasing library budgets has prevented the library community from addressing this issue with concomitant staffing increases. Nevertheless, the ability of libraries to make information resources accessible to their communities of users remains a central concern. Thus there is a critical need to devise efficient and cost effective ways of creating bibliographic records so that users are able to find, identify, and obtain the information resources they need.

One promising approach to managing the ever-increasing amount of information is with semiautomatic metadata generation tools. Semi-automatic metadata generation tools concern the use of software to create metadata records with varying degrees of supervision from a human specialist. (1) In its ideal form, semi-automatic metadata generation tools are capable of extracting information from structured and unstructured information resources of all types and creating quality metadata that not only facilitate bibliographic record creation but also semantic interoperability, a critical factor for resource sharing and discovery in the networked environment. Through the use of semi-automatic metadata generation tools, the library community has the potential to address many issues related to the increase of information resources, the strain on library budget, the need to create high-quality, interoperable metadata records, and, ultimately, the effective provision of information resources to users.

There are many potential benefits to semi-automatic metadata generation. The first is scalability. Because of the quantity of information resources and the costly and time-consuming nature of manual metadata generation, (2) it is increasingly apparent that there simply are not enough information professionals available for satisfying the metadata-generation needs of the library community. Semi-automatic metadata generation, on the other hand, offers the promise of using high levels of computing power to manage large amounts of information resources. In addition to scalability, semi-automatic metadata generation also offers potential cost savings through a decrease in the time required to create effective records. Furthermore, the time savings would allow information professionals to focus on tasks that are more conceptually demanding and thus not suitable for automatic generation. Finally, because computers can perform repetitive tasks with relative consistency when compared to their human counterparts, automatic metadata generation promises the ability to create more consistent records. A potential increase in consistency of quality metadata records would, in turn, increase the potential for interoperability and thereby the accessibility of information resources in general. Thus semi-automatic metadata generation offers the potential to not only ease resource description demands on the library community but also to improve resource discovery for its users.


Assessment of the current landscape of semi-automatic metadata generation tools is particularly important considering the fast development of digital repositories and the recent explosion of data and information. Utilization of semi-automatic metadata generation is critical to address such environmental changes and may be unavoidable in the future considering the costly and complex operation of manual metadata creation. Even though there are promising experimental studies that exploit various methods and sources for semi-automatic metadata generation, (3) a lack of studies assessing and evaluating the range of tools have been developed, implemented, or improved. To address such needs, this study aims to examine the current landscape of semiautomatic metadata generation tools while providing an evaluative analysis of their techniques, features, and functions. …

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