Linked Open Statistical Metadata

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Author(s): Franck Cotton (National Institute of Statistics and Economic Studies (INSEE), France)and Daniel Gillman (U.S. Bureau of Labor Statistics (BLS), USA)
Copyright: 2017
Pages: 24
Source title: Data Visualization and Statistical Literacy for Open and Big Data
Source Author(s)/Editor(s): Theodosia Prodromou (University of New England, Australia)
DOI: 10.4018/978-1-5225-2512-7.ch012

Keywords: Data Analysis & Statistics / Information Retrieval / Information Science Reference / Library & Information Science

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Abstract

Linked Open Statistical Metadata (LOSM) is Linked Open Data (LOD) applied to statistical metadata. LOD is a model for identifying, structuring, interlinking, and querying data published directly on the web. It builds on the standards of the semantic web defined by the W3C. LOD uses the Resource Description Framework (RDF), a simple data model expressing content as predicates linking resources between them or with literal properties. The simplicity of the model makes it able to represent any data, including metadata. We define statistical data as data produced through some statistical process or intended for statistical analyses, and statistical metadata as metadata describing statistical data. LOSM promotes discovery and the meaning and structure of statistical data in an automated way. Consequently, it helps with understanding and interpreting data and preventing inadequate or flawed visualizations for statistical data. This enhances statistical literacy and efforts at visualizing statistics.

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