Skip to main content

This project presents the SDM-RDFizer, an interpreter of mapping rules that allows the transformation of (un)structured data into RDF knowledge graphs. The current version of the SDM-RDFizer assumes mapping rules are defined in the RDF Mapping Language (RML) by Dimou et al.

Project description

SDM-RDFizer

This project presents the SDM-RDFizer, an interpreter of mapping rules that allows the transformation of (un)structured data into RDF knowledge graphs. The current version of the SDM-RDFizer assumes mapping rules are defined in the RDF Mapping Language (RML) by Dimou et al. The SDM-RDFizer implements optimized data structures and relational algebra operators that enable an efficient execution of RML triple maps even in the presence of Big data. SDM-RDFizer is able to process data from Heterogeneous data sources (CSV, JSON, RDB, XML).

SDM-RDFizer workflow

The results of the execution of SDM-RDFizer has been described in the following research reports:

  • Enrique Iglesias, Samaneh Jozashoori, David Chaves-Fraga, Diego Collarana, and Maria-Esther Vidal. 2020. SDM-RDFizer: An RML Interpreter for the Efficient Creation of RDF Knowledge Graphs. The 29th ACM International Conference on Information and Knowledge Management (CIKM ’20).

  • Samaneh Jozashoori, David Chaves-Fraga, Enrique Iglesias, Oscar Corcho, and Maria-Esther Vidal. 2020. FunMap: Efficient Execution of Functional Mappings for Knowledge Graph Creation. The 19th International Semantic Web Conference - Research Track (ISWC 2020).

  • Samaneh Jozashoori and Maria-Esther Vidal. MapSDI: A Scaled-up Semantic Data Integrationframework for Knowledge Graph Creation. The 27th International Conference on Cooperative Information Systems (CoopIS 2019).

  • David Chaves-Fraga, Kemele M. Endris, Enrique Iglesias, Oscar Corcho, and Maria-Esther Vidal. What are the Parameters that Affect the Construction of a Knowledge Graph?. The 18th International Conference on Ontologies, DataBases, and Applications of Semantics (ODBASE 2019).

  • David Chaves-Fraga, Antón Adolfo, Jhon Toledo, and Oscar Corcho. ONETT: Systematic Knowledge Graph Generation for National Access Points. The 1st International Workshop on Semantics for Transport co-located with SEMANTiCS 2019.

  • David Chaves-Fraga, Freddy Priyatna, Andrea Cimmino, Jhon Toledo, Edna Ruckhaus, and Oscar Corcho. GTFS-Madrid-Bench: A benchmark for virtual knowledge graph access in the transport domain. Journal of Web Semantics, 2020.

Additional References:

  • Dimou et al. 2014. Dimou, A., Sande, M.V., Colpaert, P., Verborgh, R., Mannens, E., de Walle, R.V.:RML: A generic language for integrated RDF mappings of heterogeneous data. In:Proceedings of the Workshop on Linked Data on the Web co-located with the 23rdInternational World Wide Web Conference (WWW 2014)

Projects where the SDM-RDFizer has been used

The SDM-RDFizer is used in the creation of the knowledge graphs of EU H2020 projects and national projects where the Scientific Data Management group participates. These projects include:

The SDM-RDFizer is also used in EU H2020, EIT-Digital and Spanish national projects where the Ontology Engineering Group (Technical University of Madrid) participates. These projects, mainly focused on the transportation and smart cities domain, include:

  • H2020 - SPRINT (http://sprint-transport.eu/): performance and scalability to test a semantic architecture for the Interoperability Framework on Transport across Europe.
  • EIT-SNAP (https://www.snap-project.eu/): innovation project on the application of semantic technologies for national access points.
  • Open Cities (https://ciudades-abiertas.es/): national project on creating common and shared vocabularies for Spanish Cities
  • Drugs4Covid (https://drugs4covid.oeg.fi.upm.es/): NLP annotations and metadata from more than 60,000 scientific papers about COVID viruses are integrated in a KG with almost 44M of facts (triples). SDM-RDFizer was used for creating this KG.

Installing and Running the SDM-RDFizer

From PyPI (https://pypi.org/project/rdfizer/):

python3 -m pip install rdfizer
python3 -m rdfizer -c /path/to/config/file

From Github/Docker: Visit the wiki of the repository to learn how to install and run the SDM-RDFizer. You can also take a look to our demo at: https://www.youtube.com/watch?v=DpH_57M1uOE

Version

3.5.2.2

RML-Test Cases

See the results of the SDM-RDFizer over the RML test-cases at the RML Implementation Report. Last test date: 08/06/2020

Experimental Evaluations

See the results of the experimental evaluations of SDM-RDFizer at SDM-RDFizer-Experiments repository

License

This work is licensed under Apache 2.0

Authors

The SDM-RDFizer has been developed by members of the Scientific Data Management Group at TIB, as an ongoing research effort. The development is coordinated and supervised by Maria-Esther Vidal (maria.vidal@tib.eu). We strongly encourage you to please report any issues you have with the SDM-RDFizer. You can do that over our contact email or creating a new issue here on Github. The SDM-RDFizer has been implemented by Enrique Iglesias (current version, s6enigle@uni-bonn.de) and Guillermo Betancourt (version 0.1, guillermojbetancourt@gmail.com) under the supervision of David Chaves-Fraga (dchaves@fi.upm.es), Samaneh Jozashoori (samaneh.jozashoori@tib.eu), and Kemele Endris (kemele.endris@tib.eu)

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

rdfizer-3.5.2.2.dev1620918060.tar.gz (46.9 kB view details)

Uploaded Source

Built Distribution

rdfizer-3.5.2.2.dev1620918060-py3-none-any.whl (45.6 kB view details)

Uploaded Python 3

File details

Details for the file rdfizer-3.5.2.2.dev1620918060.tar.gz.

File metadata

  • Download URL: rdfizer-3.5.2.2.dev1620918060.tar.gz
  • Upload date:
  • Size: 46.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.9.5

File hashes

Hashes for rdfizer-3.5.2.2.dev1620918060.tar.gz
Algorithm Hash digest
SHA256 71904cfeae9206145595f683357fe54f9e1c7877a763515f31fd1786b9460e08
MD5 d7a30b80095d1afb3f4daa9f734f9a34
BLAKE2b-256 8d20853aab9a616e2831af1a01e7bf6bc4a0124b5f8a838e70aec0991ff9c253

See more details on using hashes here.

File details

Details for the file rdfizer-3.5.2.2.dev1620918060-py3-none-any.whl.

File metadata

  • Download URL: rdfizer-3.5.2.2.dev1620918060-py3-none-any.whl
  • Upload date:
  • Size: 45.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.9.5

File hashes

Hashes for rdfizer-3.5.2.2.dev1620918060-py3-none-any.whl
Algorithm Hash digest
SHA256 7fddef0c36cf42d89d83c31a06ad535d3da7464e0c5ffaa79f343ce7830e269c
MD5 16bb0021cd2aafcff8207ccc2f6c297c
BLAKE2b-256 af71d486fcad9803b3c38d9412a17b9c4daebe6f9657a4a22eb6a7fd706de33d

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page