Metadata quality : implications for library and information science professionals

Purpose - In contrast with recent studies noting the necessity of library and information science (LIS) skills in digital library and repository projects, this study aims to examine the impact of metadata quality requirements on how LIS professionals apply their skills outside a library setting. Design/methodology/approach - The paper reviews the concept of metadata quality and examines the implications of this for LIS professionals by reviewing the differences between the context of the library community and other relevant communities of practice. Findings - The paper argues that, although much needed, LIS skills require contextualisation before application outside library settings. Research limitations/implications - Many of the new opportunities for and settings of LIS skills are immature - consequently this analysis may date as the context of these settings mature. Current trends, however, suggest that it will not. Practical implications - Training in LIS skills should take account of how they might apply differently outside libraries. Librarians co-operating with colleagues outside the library should appreciate the potential metadata 'compromises' they might have to make and why they are necessary. Originality/value - The paper provides food for thought on the increasing number of LIS professionals working outside library settings

Metadata Quality for Digital Libraries

The quality of metadata in a digital library is an important factor in ensuring access for end-users. Several studies have tried to define quality frameworks and assess metadata but there is little user feedback about these in the literature. As collections grow in size maintaining quality through manual methods becomes increasingly difficult for repository managers. This research presents the design and implementation of a web-based metadata analysis tool for digital repositories. The tool is built as an extension to the Greenstone3 digital library software. We present examples of the tool in use on real-world data and provide feedback from repository managers. The evidence from our studies shows that automated quality analysis tools are useful and valued service for digital libraries

A tool for metadata analysis

We describe a Web-based metadata quality tool that provides statistical descriptions and visualisations of Dublin Core metadata harvested via the OAI protocol. The lightweight nature of development allows it to be used to gather contextualized requirements and some initial user feedback is discussed

A novel framework for assessing metadata quality in epidemiological and public health research settings

Metadata are critical in epidemiological and public health research. However, a lack of biomedical metadata quality frameworks and limited awareness of the implications of poor quality metadata renders data analyses problematic. In this study, we created and evaluated a novel framework to assess metadata quality of epidemiological and public health research datasets. We performed a literature review and surveyed stakeholders to enhance our understanding of biomedical metadata quality assessment. The review identified 11 studies and nine quality dimensions; none of which were specifically aimed at biomedical metadata. 96 individuals completed the survey; of those who submitted data, most only assessed metadata quality sometimes, and eight did not at all. Our framework has four sections: a) general information; b) tools and technologies; c) usability; and d) management and curation. We evaluated the framework using three test cases and sought expert feedback. The framework can assess biomedical metadata quality systematically and robustly

Metadata quality issues in learning repositories

Metadata lies at the heart of every digital repository project in the sense that it defines and drives the description of digital content stored in the repositories. Metadata allows content to be successfully stored, managed and retrieved but also preserved in the long-term. Despite the enormous importance of metadata in digital repositories, one that is widely recognized, studies indicate that what is defined as metadata quality, is relatively low in most cases of digital repositories. Metadata quality is loosely defined as "fitness for purpose" meaning that low quality of metadata means that metadata cannot fulfill its purpose which is to allow for the successful storage, management and retrieval of resources. In practice, low metadata quality leads to ineffective searches for content, ones that recall the wrong resources or even worse, no resources which makes them invisible to the intended user, that is the "client" of each digital repository. The present dissertation approaches this problem by proposing a comprehensive metadata quality assurance method, namely the Metadata Quality Assurance Certification Process (MQACP). The basic idea of this dissertation is to propose a set of methods that can be deployed throughout the lifecycle of a repository to ensure that metadata generated from content providers are of high quality. These methods have to be straightforward, simple to apply with measurable results. They also have to be adaptable with minimum effort so that they can be used in different contexts easily. This set of methods was described analytically, taking into account the actors needed to apply them, describing the tools needed and defining the anticipated outcomes. In order to test our proposal, we applied it on a Learning Federation of repositories, from day 1 of its existence until it reached its maturity and regular operation. We supported the metadata creation process throughout the different phases of the repositories involved by setting up specific experiments using the methods and tools of the MQACP. Throughout each phase, we measured the resulting metadata quality to certify that the anticipated improvement in metadata quality actually took place. Lastly, through these different phases, the cost of the MQACP application was measured to provide a comparison basis for future applications. Based on the success of this first application, we decided to validate the MQACP approach by applying it on another two cases of a Cultural and a Research Federation of repositories. This would allow us to prove the transferability of the approach to other cases the present some similarities with the initial one but mainly significant differences. The results showed that the MQACP was successfully adapted to the new contexts, with minimum adaptations needed, with similar results produced and also with comparable costs. In addition, looking closer at the common experiments carried out in each phase of each use case, we were able to identify interesting patterns in the behavior of content providers that can be further researched. The dissertation is completed with a set of future research directions that came out of the cases examined. These research directions can be explored in order to support the next version of the MQACP in terms of the methods deployed, the tools used to assess metadata quality as well as the cost analysis of the MQACP methods

Metadata quality issues in learning repositories

Metadata lies at the heart of every digital repository project in the sense that it defines and drives the description of digital content stored in the repositories. Metadata allows content to be successfully stored, managed and retrieved but also preserved in the long-term. Despite the enormous importance of metadata in digital repositories, one that is widely recognized, studies indicate that what is defined as metadata quality, is relatively low in most cases of digital repositories. Metadata quality is loosely defined as "fitness for purpose" meaning that low quality of metadata means that metadata cannot fulfill its purpose which is to allow for the successful storage, management and retrieval of resources. In practice, low metadata quality leads to ineffective searches for content, ones that recall the wrong resources or even worse, no resources which makes them invisible to the intended user, that is the "client" of each digital repository. The present dissertation approaches this problem by proposing a comprehensive metadata quality assurance method, namely the Metadata Quality Assurance Certification Process (MQACP). The basic idea of this dissertation is to propose a set of methods that can be deployed throughout the lifecycle of a repository to ensure that metadata generated from content providers are of high quality. These methods have to be straightforward, simple to apply with measurable results. They also have to be adaptable with minimum effort so that they can be used in different contexts easily. This set of methods was described analytically, taking into account the actors needed to apply them, describing the tools needed and defining the anticipated outcomes. In order to test our proposal, we applied it on a Learning Federation of repositories, from day 1 of its existence until it reached its maturity and regular operation. We supported the metadata creation process throughout the different phases of the repositories involved by setting up specific experiments using the methods and tools of the MQACP. Throughout each phase, we measured the resulting metadata quality to certify that the anticipated improvement in metadata quality actually took place. Lastly, through these different phases, the cost of the MQACP application was measured to provide a comparison basis for future applications. Based on the success of this first application, we decided to validate the MQACP approach by applying it on another two cases of a Cultural and a Research Federation of repositories. This would allow us to prove the transferability of the approach to other cases the present some similarities with the initial one but mainly significant differences. The results showed that the MQACP was successfully adapted to the new contexts, with minimum adaptations needed, with similar results produced and also with comparable costs. In addition, looking closer at the common experiments carried out in each phase of each use case, we were able to identify interesting patterns in the behavior of content providers that can be further researched. The dissertation is completed with a set of future research directions that came out of the cases examined. These research directions can be explored in order to support the next version of the MQACP in terms of the methods deployed, the tools used to assess metadata quality as well as the cost analysis of the MQACP methods

Metadata quality matters in Open Government Data (OGD) evaluation! An empirical investigation of OGD portals of the GCC constituents:An empirical investigation of OGD portals of the GCC constituents

Purpose: The study seeks to investigate the quality of metadata associated with the Open Government Data (OGD) portals of the six Gulf Cooperation Council (GCC) constituentsBahrain, Kuwait, Oman, Qatar, Kingdom of Saudi Arabia (KSA), and United Arab Emirates (UAE). Design/methodology/approach: A quantitative framework, supported by extant literature, is adopted to assess the metadata quality of the six OGD portals of the GCC constituents. Findings: Among the six GCC countries, Qatar has the most advanced OGD metadata quality followed by KSA, UAE, Oman, Bahrain and Kuwait. Furthermore, the OGD metadata quality of UAE and Oman stand at the same pedestal whereas Bahrain and Kuwait OGD portals are lagging behind. Originality: Whereas the OGD quality has been investigated in extant literature, the metadata quality of the OGD portals for the GCC countries has not been investigated so far- the present study seeks to plug this ga

Experiences in deploying metadata analysis tools for institutional repositories

Current institutional repository software provides few tools to help metadata librarians understand and analyze their collections. In this article, we compare and contrast metadata analysis tools that were developed simultaneously, but independently, at two New Zealand institutions during a period of national investment in research repositories: the Metadata Analysis Tool (MAT) at The University of Waikato, and the Kiwi Research Information Service (KRIS) at the National Library of New Zealand. The tools have many similarities: they are convenient, online, on-demand services that harvest metadata using OAI-PMH; they were developed in response to feedback from repository administrators; and they both help pinpoint specific metadata errors as well as generating summary statistics. They also have significant differences: one is a dedicated tool wheres the other is part of a wider access tool; one gives a holistic view of the metadata whereas the other looks for specific problems; one seeks patterns in the data values whereas the other checks that those values conform to metadata standards. Both tools work in a complementary manner to existing Web-based administration tools. We have observed that discovery and correction of metadata errors can be quickly achieved by switching Web browser views from the analysis tool to the repository interface, and back. We summarize the findings from both tools' deployment into a checklist of requirements for metadata analysis tools

Experiences in deploying metadata analysis tools for institutional repositories

Current institutional repository software provides few tools to help metadata librarians understand and analyze their collections. In this article, we compare and contrast metadata analysis tools that were developed simultaneously, but independently, at two New Zealand institutions during a period of national investment in research repositories: the Metadata Analysis Tool (MAT) at The University of Waikato, and the Kiwi Research Information Service (KRIS) at the National Library of New Zealand. The tools have many similarities: they are convenient, online, on-demand services that harvest metadata using OAI-PMH; they were developed in response to feedback from repository administrators; and they both help pinpoint specific metadata errors as well as generating summary statistics. They also have significant differences: one is a dedicated tool wheres the other is part of a wider access tool; one gives a holistic view of the metadata whereas the other looks for specific problems; one seeks patterns in the data values whereas the other checks that those values conform to metadata standards. Both tools work in a complementary manner to existing Web-based administration tools. We have observed that discovery and correction of metadata errors can be quickly achieved by switching Web browser views from the analysis tool to the repository interface, and back. We summarize the findings from both tools' deployment into a checklist of requirements for metadata analysis tools