Statistical Data and Metadata Exchange (SDMX) in Academic Libraries

A Conceptual Review of Applications and Service Implications in the Context of Information Retrieval Scenario

Abstract

Statistical Data and Metadata Exchange (SDMX) is a standard developed to ease the exchange of data and metadata among international statisticians. It develops, maintains and upholds standards and guidelines that are accepted across nations, accompanied by implementation tools to ease the exchange of statistical data and metadata with the help of advanced information technology. The study focuses on analysing current literature instead of conducting experimental or empirical analysis by adopting a conceptual and narrative review approach. The study uses two major scholarly databases- Google Scholar and Scopus. Precise search phrases were used to find high-quality data through a systematic methodology using Scopus on ‘SDMX’.  This allows for focused analysis of SDMX in academic libraries and research contexts and aligns with the study objectives. Google Scholar was considered the initial step for checking the depth, relevance and validity of the research, but refinement beyond these initial steps is mandatory. This article aims to highlight the technology behind SDMX and review the literature on how it can be used in academic libraries in the context of research and the scientific community. Additionally, the study highlights the SDMX mechanisms in comparison with DDI, DCAT and Dublin Core. It finds out how various uses of SDMX in libraries and outlines the quality improvements that can be achieved through its implementation. The study has made efforts to understand interoperability and data standards in libraries in the context of use and applications of SDMX.