Presentations

This paper describes the efforts to marry LOD techniques to the needs of the international statistical community during two workshops on Semantic Statistics held at Schloß Dagstuhl, Leibniz Center for Informatics with the support of the GESIS Leibniz Institute for Social Sciences and the Data Documentation Initiative (DDI). Specifically, the authors address the extension of the Simple Knowledge Organization System (SKOS), an RDF vocabulary, to satisfy the requirements of classification systems and concept management for the statistical community.

This paper was part of METIS, Work Session on Statistical Metadata, Geneva, Switzerland, May 2013. It focuses on the extension to SKOS called xKOS, developed by the DDI community.

This paper was part of the Pproceedings of the 6th Linked Data on the Web (LDOW) Workshop at the World Wide Web Conference (WWW), Rio de Janeiro, Brazil, May 2013. It focuses on the DDI-RDF Discovery Vocabulary – based on a subset of the DDI - which supports the discovery of statistical data as well as metadata.

This presentation was part of the Proceedings of the 1st International Workshop on Semantic Statistics, 12th International Semantic Web Conference, CEUR Workshop Proceedings, Aachen (2013).  It focuses on on the description of how other vocabularies are reused and on the description of use cases associated with the usage of the DDI-RDF Discovery Vocabulary.

There is a clear interaction between this project and the “Framework and Standards for statistical Modernisations” recently discussed by the High-Level Group for the modernisation of statistical production and services (HLG), in particular with the work tasks dealing with GSIM and its mapping to DDI and SDMX. A DDI-SDMX integrated production flow implies transitions from one standard to the other. For example, a typical case is DDI-documented statistical micro-data sets which can be

This paper, delivered at a UNECE METIS meeting in Geneva in 2013, outlines the strategic directions that the DDI Alliance is undertaking in order to support open access to data and advance effective data-driven science and policy-making.