Digital democracy and new forms for direct digital participation in policy making gain unprecedented momentum. This is particularly the case for preferential voting methods and decision-support systems designed to promote fairer, more inclusive and legitimate collective decision-making processes in citizens assemblies, participatory budgeting and elections. However, a systematic human experimentation with different voting methods is cumbersome and costly. This paper introduces VoteLab, an open-source and thoroughly-documented platform for modular and adaptive design of voting experiments. It supports to visually and interactively build reusable campaigns with a choice of different voting methods, while voters can easily respond to subscribed voting questions on a smartphone. A proof-of-concept with four voting methods and questions on COVID-19 in an online lab experiment have been used to study the consistency of voting outcomes. It demonstrates the capability of VoteLab to support rigorous experimentation of complex voting scenarios.

翻译：数字民主及政策制定中直接数字参与的新形式正获得前所未有的发展势头。在公民大会、参与式预算及选举中，旨在促进更公平、更具包容性和更合法的集体决策过程的优先投票方法与决策支持系统尤其如此。然而，对不同投票方法进行系统人类实验既繁琐又昂贵。本文介绍了VoteLab——一个开源且文档详尽、支持投票实验模块化与自适应设计的平台。它能够以可视化与交互方式构建可复用的活动，并选择多种投票方法，同时投票者可轻松通过智能手机对订阅的投票问题作出响应。通过在线实验室实验，以四种投票方法及关于COVID-19的问题进行概念验证，研究了投票结果的一致性。这证明了VoteLab支持对复杂投票场景进行严谨实验的能力。