DOI: 10.5281/zenodo.3964116
title: Database populated with European diversification experiences

description: The EU Horizon 2020 project DiverIMPACTS aims to promote the realisation of the full potential of crop diversification through rotation, multicropping and intercropping by demonstrating technical, economic and environmental benefits for famers, along the value chain and for society at large, and by providing innovations that can remove existing barriers and lock-ins of practical diffusion. DiverIMPACTS does so by combining findings from several participatory case studies with a set of field experiments across Europe, and translating these into strategies, recommendations and fit-for-purpose tools developed with and for farmers, advisors and other actors along the value chain. To first gain a good overview of the current situation, i.e. the existing success stories and challenges of crop diversification in Europe, Work Package 1 (WP 1) identified and analysed factors of success and failure associated with a variety of crop diversification experiences (CDEs) outside those already represented in the consortium (see Deliverable 1.1). WP 1 thus makes sure that the rich experience with crop diversification initiatives across Europe (e.g. from other Horizon 2020 projects) is taken into account for developing strategies, recommendations and tools. Deliverable 1.1 provided i) a list of key drivers (ex ante occurrence of market opportunities, environmental constraints, availability of enabling advisory services, land and workforce availability etc.) to be further considered in WP3, and WP5; and ii) a comprehensive and exhaustive description of the links between key factors and CDE types. This analysis is the basis for consolidating or updating the tentative typology of crop diversification situations used for setting up DiverIMPACTS (case studies), and was used for selecting experiences for more detailed investigations in T1.2. It also complements the identification and characterisation of lock-ins and barriers to crop diversification, and serves their overcoming. During the process of collecting, cleaning and analysing the survey data, a Database of European diversification experiences was created. All together 128 valid responses from 15 European countries – mainly from the project countries Belgium, France, Germany, Hungary, Italy, the Netherlands, Poland, Romania, Sweden, Switzerland, and UK, but also from Denmark, Finland, Luxemburg and Spain were received in T1.1, and were included in the database. The database is stored in original and back-up form in a tabular ='.csv'= format that can be opened in Excel on the Sharepoint system of the project and now on Zenodo, under restricted WP1 area. A further ='.csv'= file was created to store the metadata of the database. This file helps to have a better overview of the questions and sub-questions that were asked in the survey and the type of answer that could be provided to each of them (e.g. factor, Yes-No selection or character). Using the meta data and the database, a selection of personal data fields has been made (e.g. email addresses and names of people) that cannot be published with open access, and needs special attention and data handling. These variables were removed from the original database, and a public version of the database was created that can be shared with third parties. Links to the data files will be shared here after. Developing a Shiny(c) application in R was chosen as a solution to visualize the public data, and make it possible for Partners and all interested parties to interactively view the survey results. The Shiny application is shared as an R-package and are freely accessible on the internet. The users have the possibility to download application and public data in order to visualize them on their own computer. A remote solution, facilitating the consultation of the data, will be installed in CRA-W, where the open data analyses module will be hosted. A short user guide and tutorial is part of this deliverable for helping interested parties to use the Shiny interface. The chosen approach, linking R scripts, R packages and data files, will be useful in the future in order to continiously complete the data base and to update the application (new graphs, new functions regarding the demand of the main users). The release of the application will be shared using modern technologies of information and communication : project website, newsletter, blogs, twitter and other social networks. The main deliverable (D1.2) which is public, is added in this repository for giving more details on the approach and the results