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A Model-Based Chatbot Generation Approach to Converse with Open Data Sources

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Web Engineering (ICWE 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12706))

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Abstract

The Open Data movement promotes the free distribution of data. More and more companies and governmental organizations are making their data available online following the Open Data philosophy, resulting in a growing market of technologies and services to help publish and consume data. One of the emergent ways to publish such data is via Web APIs, which offer a powerful means to reuse this data and integrate it with other services. Socrata, CKAN or OData are examples of popular specifications for publishing data via Web APIs. Nevertheless, querying and integrating these Web APIs is time-consuming and requires technical skills that limit the benefits of Open Data movement for the regular citizen. In other contexts, chatbot applications are being increasingly adopted as a direct communication channel between companies and end-users. We believe the same could be true for Open Data as a way to bridge the gap between citizens and Open Data sources. This paper describes an approach to automatically derive full-fledged chatbots from API-based Open Data sources. Our process relies on a model-based intermediate representation (via UML class diagrams and profiles) to facilitate the customization of the chatbot to be generated.

Work supported by the Spanish government (TIN2016-75944-R project).

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Notes

  1. 1.

    https://dev.socrata.com/.

  2. 2.

    https://ckan.org/.

  3. 3.

    https://www.odata.org/.

  4. 4.

    https://www.openapis.org/.

  5. 5.

    https://data.cityofchicago.org.

  6. 6.

    http://governobert.gencat.cat/en/dades_obertes/index.html.

  7. 7.

    https://developer.deutschebahn.com/store.

  8. 8.

    Full model available at http://hdl.handle.net/20.500.12004/1/C/ICWE/2021/232.

  9. 9.

    http://hdl.handle.net/20.500.12004/1/C/ICWE/2021/411.

  10. 10.

    https://analisi.transparenciacatalunya.cat/api/views/metadata/v1/tasf-thgu.json.

  11. 11.

    https://analisi.transparenciacatalunya.cat/api/views.json?id=tasf-thgu.

  12. 12.

    Note that this scales well as we do not actually create completely separate intents for each possible combination but use intent templates that can be instantiated at run-time over the list of elements in the model.

  13. 13.

    https://github.com/opendata-for-all/open-data-chatbot-generator.

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Authors and Affiliations

  1. UOC., Barcelona, Spain

    Hamza Ed-douibi, Javier Luis Cánovas Izquierdo, Gwendal Daniel & Jordi Cabot

  2. ICREA., Barcelona, Spain

    Jordi Cabot

Authors
  1. Hamza Ed-douibi
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  2. Javier Luis Cánovas Izquierdo
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  3. Gwendal Daniel
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  4. Jordi Cabot
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Corresponding author

Correspondence to Javier Luis Cánovas Izquierdo .

Editor information

Editors and Affiliations

  1. Dipartimento di Elettronica, Politecnico di Milano, Milan, Italy

    Marco Brambilla

  2. E2S UPPA, LIUPPA, Université de Pau et des Pays de l’Adour, Anglet, France

    Richard Chbeir

  3. Econometric Institute, Erasmus University Rotterdam, Rotterdam, The Netherlands

    Flavius Frasincar

  4. Inria Saclay-Île-de-France, Institut Polytechnique de Paris, Palaiseau, France

    Ioana Manolescu

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Ed-douibi, H., Cánovas Izquierdo, J.L., Daniel, G., Cabot, J. (2021). A Model-Based Chatbot Generation Approach to Converse with Open Data Sources. In: Brambilla, M., Chbeir, R., Frasincar, F., Manolescu, I. (eds) Web Engineering. ICWE 2021. Lecture Notes in Computer Science(), vol 12706. Springer, Cham. https://doi.org/10.1007/978-3-030-74296-6_33

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  • DOI: https://doi.org/10.1007/978-3-030-74296-6_33

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