[Presentation] LATINNO (Innovations for Democracy in Latin America) is the first and so far the most comprehensive and systematic source of data on new forms of citizen participation that have evolved in Latin America - the so-called democratic innovations. The LATINNO database gathers data on democratic innovations developed in 18 Latin American countries between 1990 and 2020. The data is coded for 43 variables related to the context, institutional design, and impact of each innovation. Along with the quantitative data, qualitative information on each case has also been gathered and assessed. The countries covered by LATINNO are: Argentina, Brazil, Bolivia, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Uruguay, and Venezuela. Additionally, the database also registers transnational cases with similar institutional design that take place in more than one country. LATINNO sought to emphasize that democracy in Latin America encompasses more than elections, and that new forms of citizen participation go beyond protests and demonstrations. The evidence collected by the LATINNO database shows that the growing volume and scope of participatory innovations should not be ignored by assessments of democracy in Latin America. The project and database were designed to fill the gap on comparative knowledge about democratic innovations. More than providing information on individual cases, LATINNO sought to underscore the diversity of new democratic institutional designs and experimentations with citizen participation in Latin America. The data we have gathered and processed enables cross-country comparison over thousands of different institutional designs in 18 countries. In this codebook, we present the conceptual elements that allow for the identification of democratic innovations and offer the detailed instructions that were used to collect and assess data on each individual case according to their context, institutional design and impact. This codebook has served as basis for the project's endeavor to collect, assess, and generate valid and reliable data between 2015 and 2020.