Skip to main content

RAMP Shapes: Declarative RDF \(\leftrightarrow \) ADT Mapping

  • Conference paper
  • First Online:
Metadata and Semantic Research (MTSR 2019)

Abstract

With the broad availability of Linked Data efficient and convenient programmatic access to semantic graph data within programming languages is important for using the data in applications. To this end, we present RAMP (RDF Algebraic Data Type Mapping), a type construction language, specification and an implementation of mapping operations between RDF graphs and structured data types. RAMP is based on algebraic data types, and aims to overcome limitations of existing approaches for example regarding the set of supported language constructs, or the ability to generalize over a different programming languages. At the same time, RAMP focuses on providing computationally efficient mapping operations.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    https://www.w3.org/TR/shacl-af/#union.

  2. 2.

    http://rdf.js.org/data-model-spec/.

  3. 3.

    https://github.com/ramp-shapes/ramp-shapes.

  4. 4.

    https://github.com/digitalbazaar/jsonld.js/.

  5. 5.

    https://github.com/ProjectMirador/mirador-website.

  6. 6.

    https://iiif.io/api/presentation/2.0/#linked-data-context-and-extensions.

  7. 7.

    http://digi.vatlib.it/iiif/MSS_Vat.lat.3225/manifest.json.

  8. 8.

    https://github.com/AlexeyMz/ramp-shapes-perf.

References

  1. Akhtar, W., Kopecký, J., Krennwallner, T., Polleres, A.: XSPARQL: traveling between the XML and RDF worlds – and avoiding the XSLT pilgrimage. In: Bechhofer, S., Hauswirth, M., Hoffmann, J., Koubarakis, M. (eds.) ESWC 2008. LNCS, vol. 5021, pp. 432–447. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-68234-9_33

    Chapter  Google Scholar 

  2. Boag, S., et al.: XQuery 1.0: an XML query language (2002)

    Google Scholar 

  3. Cohen, A., Herrmann, C.: Towards a high-productivity and high-performance marshaling library for compound data. In: 2nd MetaOCaml Workshop (2005)

    Google Scholar 

  4. Corby, O., Faron-Zucker, C., Gandon, F.: A generic RDF transformation software and its application to an online translation service for common languages of linked data. In: Arenas, M., et al. (eds.) ISWC 2015. LNCS, vol. 9367, pp. 150–165. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-25010-6_9

    Chapter  Google Scholar 

  5. Johnson, S.C., et al.: YACC: Yet Another Compiler-Compiler, vol. 32. Bell Laboratories, Murray Hill (1975)

    Google Scholar 

  6. Knublauch, H., Kontokostas, D.: Shapes constraint language (SHACL). W3C Candidate Recommendation, vol. 11, no. 8 (2017)

    Google Scholar 

  7. Lisena, P., Troncy, R.: Transforming the JSON output of SPARQL queries for linked data clients. In: Companion of the The Web Conference 2018 on The Web Conference 2018, pp. 775–780. International WWW Conferences Steering Committee (2018)

    Google Scholar 

  8. Longley, D., Kellogg, G., Lanthaler, M., Sporny, M.: JSON-LD 1.0 processing algorithms and API, vol. 18. WWW Consortium (2015). www.w3.org/TR/json-ld-api/

  9. Prud’hommeaux, E., Labra Gayo, J.E., Solbrig, H.: Shape expressions: an RDF validation and transformation language. In: Proceedings of the 10th International Conference on Semantic Systems, pp. 32–40. ACM (2014)

    Google Scholar 

  10. Snydman, S., Sanderson, R., Cramer, T.: The international image interoperability framework (IIIF): a community & technology approach for web-based images. In: Archiving Conference, pp. 16–21. no. 1. Society for Imaging Science and Technology (2015)

    Google Scholar 

  11. Sporny, M., Longley, D., Kellogg, G., Lanthaler, M., Lindström, N.: JSON-LD 1.0, vol. 16, p. 41. W3C Recommendation (2014)

    Google Scholar 

Download references

Acknowledgements

This work was supported by the Government of the Russian Federation (Grant 074-U01) through the ITMO Fellowship and Professorship Program. Furthermore, the work is supported by Sputniq GmbH.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alexey Morozov .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Morozov, A., Wohlgenannt, G., Mouromtsev, D., Pavlov, D., Emelyanov, Y. (2019). RAMP Shapes: Declarative RDF \(\leftrightarrow \) ADT Mapping. In: Garoufallou, E., Fallucchi, F., William De Luca, E. (eds) Metadata and Semantic Research. MTSR 2019. Communications in Computer and Information Science, vol 1057. Springer, Cham. https://doi.org/10.1007/978-3-030-36599-8_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-36599-8_4

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-36598-1

  • Online ISBN: 978-3-030-36599-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics