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DDI-RDF

DDI-RDF. Leveraging the DDI Model for the Linked Data Web. Why RDF for DDI ?. To increase visibility of data holdings using mainstream Web technologies (RDF) Based on a proven metadata model – DDI! Using an approach in line with best practice in the Linked Data community

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DDI-RDF

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  1. DDI-RDF Leveraging the DDI Model for the Linked Data Web

  2. Why RDF for DDI? • To increase visibility of data holdings using mainstream Web technologies (RDF) • Based on a proven metadata model – DDI! • Using an approach in line with best practice in the Linked Data community • To increase the connection between research data sets and other resources • Users can provide layers of additional linking • Similar to some methods used in qualitative research • To better identify opportunities for merging datasets and other emerging functionality such as inferencing • To improve the quality of approaches to research data within the Linked Data community • Based on a single coherent set of standards • Leveraging the experience and knowledge of the DDI community

  3. The Goal • To have a single, proven, standard way of describing microdata within the Web of Linked Data using RDF • To leverage existing metadata holdings within archives, data libraries, and data producers • DDI in all versions • Process of producing RDF should be automated • To fit coherently into a broader RDF ”data” context • Microdata description and metadata • Aggregate data and metadata/tables • Classifications, concepts, and ”foundational” metadata holdings • To increase the absolute number of RDF tribbles triples on the Web!

  4. discovery use case • Which studies are connected with a specific universe consisting of the 3 dimensions: time, country, and population? • What questions with a specific question text are contained in the study questionnaire? • What questions are connected with a concept with a specific label? • What questions are combined with a variable with an associated universe consisting of the 3 dimensionstime, country, and population? • What concepts are linked to particular variables or questions? • What representation does a specific variable have? • What codes and what categories are part of this representation? • What variable label does a variable with a particular variable name have? • What‘s the maximum value of a certain variable? • What are the absolute and relative frequencies of a specific code? • What data files contain the entire dataset?

  5. The DDI Ontology • Made for the discovering use-case • Higlevelmodelof DDI-Codebook and DDI-Lifecycle • Exposingcomplex metadata in a simple format • Usesestablishedvocabularies

  6. study | coverage

  7. instrument | question | concept

  8. values | value labels

  9. variable | descriptive statistics

  10. logical dataset | dataset | data file

  11. conceptual model

  12. Resources • The DDI Discovery Vocabulary, an RDF vocabulary for data description and discovery based on DDI • https://github.com/linked-statistics/disco-spec • Tools and examples to support the RDF expression of the DDI (Data Documentation Initiative) standard • https://github.com/linked-statistics/DDI-RDF-tools • SKOS extension for statistical classifications • https://github.com/linked-statistics/xkos

  13. Contributors and links • Slides by • Thomas Bosch, GESIS - LeibnizInstitute for the Social Sciences, Thomas.Bosch@gesis.org • Arofan Gregory, ODaF - Open Data Foundation, Arofan.Gregory@earthlink.net • Olof Olsson, Swedish National Data Service, Olof.Olsson@snd.gu.se Presentation IASSIST 2012 http://snd.gu.se/sites/snd.gu.se/files/IASSIST_2012-DDI-RDF-Trouble_with_Triples.pdf

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