El acceso a la información pública tiene un rol fundamental en la exigibilidad de otros derechos y es una de las herramientas principales que la sociedad civil requiere para controlar e influir en los gobiernos.

Como periodistas trabajando con documentos y bases de datos, nos encontramos con que la información más interesante se oculta en aquellos documentos que son largos, no estructurados o incompletos.

La Nacion, CLIP, Ojo Público, and MuckRock collaborated together to explore how machine learning could help fuel more effective ways for journalists, researchers, and the public to keep an eye on large government document sets. Here’s what we learned and how you can build on that work.

As journalists dealing with data and document sets, we find that the most interesting information is usually hidden in large, unstructured, and incomplete sets of documents. Especially information in public contracts: what the government is buying, how much money is being spent, and who are the suppliers. To answer these questions, four media organizations joined forces under the JournalismAI Collab and experimented with different machine learning tools and techniques in order to build a platform that helps investigative reporters understand and process unstructured documents to get useful insights. This platform ended up being “Dockins”.