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Semantically Assisted XBRL-Taxonomy Alignment Across Languages

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Abstract

The eXtensible Business Reporting Language (XBRL) has standardized the generation of and the access to financial statements like balance sheets, but language and XBRL-taxonomy diversity makes financial data integration across national borders and jurisdictions problematic. Integrating financial data in these circumstances requires that different multilingual jurisdictional taxonomies be aligned by finding correspondences between concepts. In this chapter, we outline a logic-based approach to this important alignment problem. The approach centers around the construction of an Accounting Ontology which, acting as a common denominator, is first used to enrich the semantics of ontologized XBRL taxonomies before reasoning is applied for alignment. Initial alignment experiments conducted on the French and Spanish balance sheets yielded 73.9 % recall and 36.6 % precision, but 100 % precision, if redundant mappings are ignored.

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Notes

  1. 1.

    See http://www.sec.gov/.

  2. 2.

    See http://www.hmrc.gov.uk/.

  3. 3.

    See http://www.eba.europa.eu/Supervisory-Reporting/FINER.aspx.

  4. 4.

    See http://www.ebr.org/.

  5. 5.

    See http://www.xbrl.org/knowledge_centre/projects/list.

  6. 6.

    See http://www.wired.com/techbiz/it/magazine/17-03/wp_reboot?currentPage=all.

  7. 7.

    See http://www.xbrl.org/comparability-task-force.

  8. 8.

    See http://www.w3.org/TR/owl-features/.

  9. 9.

    See http://oaei.ontologymatching.org/2012/.

  10. 10.

    See http://fadyart.com/en/.

  11. 11.

    See http://xbrl.squarespace.com/financial-report-ontology/.

  12. 12.

    See http://www.w3.org/TR/swbp-specified-values/.

  13. 13.

    See http://www.monnet-project.eu/.

  14. 14.

    See http://www.w3.org/TR/rdf-sparql-query/.

  15. 15.

    See http://www.co-ode.org/resources/reference/manchester_syntax/.

  16. 16.

    See http://www.w3.org/TR/REC-xml-names/.

  17. 17.

    See http://www.w3.org/TR/skos-reference/.

  18. 18.

    The YAM++ of year 2012 does not require training.

  19. 19.

    See http://www.xbrleurope.org/working-groups/xebr-wg.

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Acknowledgments

The work presented in this chapter has been funded in part by the EU FP7 Activity ICT-4-2.2 under Grant Agreement No. 248458, Multilingual Ontologies for Networked Knowledge (MONNET) project, and by the DFG Research Unit FOR 1513, project B1. We would especially like to thank the xEBR Working GroupFootnote 19 for their help.

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Authors and Affiliations

  1. SAP AG, Karlsruhe, Germany

    Susan Marie Thomas & Xichuan Wu

  2. Institute of Theoretical Computer Science, Technische Universität Dresden, Dresden, Germany

    Yue Ma

  3. Digital Enterprise Research Institute (DERI), NUI, Galway, Ireland

    Sean O’Riain

Authors
  1. Susan Marie Thomas
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  2. Xichuan Wu
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  4. Sean O’Riain
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Correspondence to Susan Marie Thomas .

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Editors and Affiliations

  1. National University of Ireland, Galway, Ireland

    Paul Buitelaar

  2. Universität Bielefeld, Bielefeld, Germany

    Philipp Cimiano

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Thomas, S.M., Wu, X., Ma, Y., O’Riain, S. (2014). Semantically Assisted XBRL-Taxonomy Alignment Across Languages. In: Buitelaar, P., Cimiano, P. (eds) Towards the Multilingual Semantic Web. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43585-4_17

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  • DOI: https://doi.org/10.1007/978-3-662-43585-4_17

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