Linking application and semantic data with RDF Lens
- Author
- Arthur Vercruysse (UGent) , Julian Andres Rojas Melendez (UGent) and Pieter Colpaert (UGent)
- Organization
- Abstract
- Linked Data is commonly regarded as an unfriendly data structure to be directly used by application developers. The (often unknown) triple-based structure of RDF graphs causes developers to struggle to extract the triples of interest and translate them into the object-like structure needed for their application. A generic, composable and reusable way to look into RDF graphs as plain objects would remove an important barrier for integrating Linked Data in all facets of application logic. We propose RDF Lens, a library based on ideas from the Haskell lens library that allows for composable and reusable data extraction units, called lenses. Value is shown by implementing a lens that generates a new lens based on a SHACL shape that extracts the semantic data into the desired plain object. Abstracting data extraction at the lens level allows for mixed extraction: using both custom extraction and declarative extraction, which could increase ease of use and reusability. The current implementation is a proof of concept that defines how to extract data from an RDF graph in JavaScript applications but does not allow (yet) writing or altering linked data with the same lenses. Future work would allow for creating and updating Linked Data in the same elegant way
Downloads
-
publisher version.pdf
- full text (Published version)
- |
- open access
- |
- |
- 673.67 KB
Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01J84WVHSJGYJPWQWRHYYJJ107
- MLA
- Vercruysse, Arthur, et al. “Linking Application and Semantic Data with RDF Lens.” POSTERS, DEMOS, WORKSHOPS, AND TUTORIALS OF THE 20TH INTERNATIONAL CONFERENCE ON SEMANTIC SYSTEMS, SEMANTICS 2024, edited by D. Garijo et al., vol. 3759, CEUR, 2024.
- APA
- Vercruysse, A., Rojas Melendez, J. A., & Colpaert, P. (2024). Linking application and semantic data with RDF Lens. In D. Garijo, A. L. Gentile, A. Kurteva, A. Mannocci, F. Osborne, & S. Vahdati (Eds.), POSTERS, DEMOS, WORKSHOPS, AND TUTORIALS OF THE 20TH INTERNATIONAL CONFERENCE ON SEMANTIC SYSTEMS, SEMANTICS 2024 (Vol. 3759). CEUR.
- Chicago author-date
- Vercruysse, Arthur, Julian Andres Rojas Melendez, and Pieter Colpaert. 2024. “Linking Application and Semantic Data with RDF Lens.” In POSTERS, DEMOS, WORKSHOPS, AND TUTORIALS OF THE 20TH INTERNATIONAL CONFERENCE ON SEMANTIC SYSTEMS, SEMANTICS 2024, edited by D. Garijo, A. L. Gentile, A. Kurteva, A. Mannocci, F. Osborne, and S. Vahdati. Vol. 3759. CEUR.
- Chicago author-date (all authors)
- Vercruysse, Arthur, Julian Andres Rojas Melendez, and Pieter Colpaert. 2024. “Linking Application and Semantic Data with RDF Lens.” In POSTERS, DEMOS, WORKSHOPS, AND TUTORIALS OF THE 20TH INTERNATIONAL CONFERENCE ON SEMANTIC SYSTEMS, SEMANTICS 2024, ed by. D. Garijo, A. L. Gentile, A. Kurteva, A. Mannocci, F. Osborne, and S. Vahdati. Vol. 3759. CEUR.
- Vancouver
- 1.Vercruysse A, Rojas Melendez JA, Colpaert P. Linking application and semantic data with RDF Lens. In: Garijo D, Gentile AL, Kurteva A, Mannocci A, Osborne F, Vahdati S, editors. POSTERS, DEMOS, WORKSHOPS, AND TUTORIALS OF THE 20TH INTERNATIONAL CONFERENCE ON SEMANTIC SYSTEMS, SEMANTICS 2024. CEUR; 2024.
- IEEE
- [1]A. Vercruysse, J. A. Rojas Melendez, and P. Colpaert, “Linking application and semantic data with RDF Lens,” in POSTERS, DEMOS, WORKSHOPS, AND TUTORIALS OF THE 20TH INTERNATIONAL CONFERENCE ON SEMANTIC SYSTEMS, SEMANTICS 2024, Amsterdam, the Netherlands, 2024, vol. 3759.
@inproceedings{01J84WVHSJGYJPWQWRHYYJJ107,
abstract = {{Linked Data is commonly regarded as an unfriendly data structure to be directly used by
application developers. The (often unknown) triple-based structure of RDF graphs causes
developers to struggle to extract the triples of interest and translate them into the object-like
structure needed for their application. A generic, composable and reusable way to look into
RDF graphs as plain objects would remove an important barrier for integrating Linked Data in
all facets of application logic. We propose RDF Lens, a library based on ideas from the Haskell
lens library that allows for composable and reusable data extraction units, called lenses. Value
is shown by implementing a lens that generates a new lens based on a SHACL shape that
extracts the semantic data into the desired plain object. Abstracting data extraction at the
lens level allows for mixed extraction: using both custom extraction and declarative extraction,
which could increase ease of use and reusability. The current implementation is a proof of
concept that defines how to extract data from an RDF graph in JavaScript applications but
does not allow (yet) writing or altering linked data with the same lenses. Future work would
allow for creating and updating Linked Data in the same elegant way}},
author = {{Vercruysse, Arthur and Rojas Melendez, Julian Andres and Colpaert, Pieter}},
booktitle = {{POSTERS, DEMOS, WORKSHOPS, AND TUTORIALS OF THE 20TH INTERNATIONAL CONFERENCE ON SEMANTIC SYSTEMS, SEMANTICS 2024}},
editor = {{Garijo, D. and Gentile, A. L. and Kurteva, A. and Mannocci, A. and Osborne, F. and Vahdati, S.}},
issn = {{1613-0073}},
language = {{eng}},
location = {{Amsterdam, the Netherlands}},
pages = {{5}},
publisher = {{CEUR}},
title = {{Linking application and semantic data with RDF Lens}},
url = {{https://ceur-ws.org/Vol-3759/}},
volume = {{3759}},
year = {{2024}},
}