In this paper we propose an innovative architecture, called Mo.Re.Farming, for handling agricultural data in an integrated fashion and supporting decision making in the precision agriculture domain. This architecture is oriented to data analysis and is inspired by Business Intelligence 2.0 approaches. It is hybrid in that it couples traditional and big data technologies to integrate heterogeneous data, at different levels of detail, from several owned and open data sources; its goal is to demonstrate that such integration is feasible and beneficial in supporting situ-specific and large-scale analyses. The proposed architecture has been developed in the context of the Mo.Re.Farming project, aimed at providing a Decision Support System for agricultural technicians in the Emilia-Romagna region and to enable analyses related to the use of water and chemical resources. The architecture is fully deployed and serves as a hub for agricultural data in Emilia-Romagna; the integrated data are made available in open access mode and can be accessed through web interfaces and through a set of web services. The paper describes the architecture from the technological and functional points of view and discusses the Mo.Re.Farming project outcomes and lessons learnt.

在本文中，我们提出了一种创新的架构，称为Mo.Re.Farming，用于以集成方式处理农业数据并支持精确农业领域的决策。该体系结构面向数据分析，并受到商业智能2.0方法的启发。它是混合的，因为它结合了传统数据技术和大数据技术，以集成来自多个自有和开放数据源的不同细节级别的异构数据；它的目标是证明这种整合在支持特定于现场的大规模分析中是可行且有益的。拟议的体系结构是在Mo.Re.Farming项目的背景下开发的，旨在为Emilia-Romagna地区的农业技术人员提供决策支持系统，并进行与水和化学资源使用相关的分析。该架构已完全部署，可作为Emilia-Romagna农业数据的枢纽。集成的数据以开放访问模式提供，并且可以通过Web界面和一组Web服务进行访问。本文从技术和功能的角度描述了体系结构，并讨论了Mo.Re.Farming项目的成果和经验教训。