Leveraging the DDI model for linked statistical data in the social, behavioural, and economic sciences
作者： Richard Cyganiak , Joachim Wackerow , Benjamin Zapilko , Thomas Bosch
DOI:
关键词: Computer science 、 Metadata 、 Ontology (information science) 、 Data science 、 Conceptual model (computer science) 、 RDF 、 Linked data 、 Data Documentation Initiative 、 Documentation 、 Ontology-based data integration
摘要: Experts from the statistical domain worked in close collaboration with ontology engineers to develop an of a subset Data Documentation Initiative, established international standard for documentation and management data social, behavioral, economic sciences. statistics formulated use cases which are seen as most significant solve frequent problems. Various benefits Linked community well connected RDF representation developed ontology. In main part paper, DDI conceptual model implementations explained detail.
dublincore.org参考文章(6)
Data-Intensive Science Chapman & Hall/CRC. ,(2013) , 10.1201/B14935
Thomas Bosch, Brigitte Mathiak, XSLT transformation generating OWL ontologies automatically based on XML Schemas international conference for internet technology and secured transactions. pp. 660- 667 ,(2011)
James A. Jacobs, Charles Humphrey, Preserving research data Communications of the ACM. ,vol. 47, pp. 27- 29 ,(2004) , 10.1145/1015864.1015881
Wolfgang Halb, Jeni Tennison, Simon Field, Arofan Gregory, Richard Cyganiak, Semantic Statistics: Bringing Together SDMX and SCOVO LDOW. ,(2010)
Thomas Bosch, Brigitte Mathiak, Evaluation of a Generic Approach for Designing Domain Ontologies Based on XML Schemas 2013/08. pp. 42- ,(2013)
Tomi Kauppinen, Alkyoni Baglatzi, Carsten Keßler, Linked Science : Interconnecting Scientific Assets Chapman and Hall/CRC. pp. 298- 319 ,(2013) , 10.1201/B14935-15