  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.
