improving Reproducibility In SciencE (iRISE)

结构化地理解不可再现性的驱动因素，并提出具体的工具和干预措施解决方案，将有助于提高科学证据的质量、可靠性和可重复使用性。为此，iRISE建议为具体干预措施的有效性提供理论和经验证据，并为旨在提高可重复性的干预措施的制定、评估和实施提供一个强有力的循证路线图框架。iRISE汇集了来自学术界和中小企业的定性和定量专业知识，包括元科学，统计学，经济学，人工智能，研究道德和诚信，质量保证和项目管理。iRISE建议开发一个通用框架，用于使用分析和计算建模、模拟和元研究诊断和解决再现性问题。将系统地整理和评估现有干预措施的数据，并与利益攸关方协商，以共同确定应优先实施的做法和工具。iRISE建议对基于技术和实践的解决方案进行实证研究，以提高可重复性。在所有iRISE活动中，将调查研究文化的影响，重点是将公平，多样性和包容性做法的系统整合纳入主流。一个全面的利益相关者论坛将提供建议，iRISE将致力于开放和可复制的做法。所产生的不同类型的证据将被整合到一个开放的知识库中，以支持社区决策，以确定，测试和实施有效和可行的可重复性解决方案。iRISE的成员过去在稳健性，严谨性和可重复性方面做出了关键的科学和政策贡献，并拥有成功完成这一雄心勃勃的项目的技能和工具，该项目在欧洲及其他地区具有潜在的科学，经济和社会收益。

Structured understanding of the drivers of irreproducibility and presenting concrete solutions of tools and interventions will help to increase the quality, reliability and re-usability of scientific evidence. To this end, iRISE proposes to provide theoretical and empirical evidence of the effectiveness of specific interventions, and a framework for a robust, evidence-based road map for the development, assessment and implementation of interventions intended to improve reproducibility. iRISE brings together qualitative and quantitative expertise, from academia and SMEs, including meta-science, statistics, economics, artificial intelligence, research ethics and integrity, quality assurance, and project management. iRISE proposes the development of a general framework for diagnosing and addressing reproducibility problems using analytical and computational modelling, simulations and meta-studies. Data on existing interventions will be systematically curated and evaluated, and stakeholders will be consulted to collaboratively identify practices and tools that should be prioritised for implementation. iRISE proposes to conduct empirical studies of both technical and practice-based solutions to increase reproducibility. Across all iRISE activities, the influences of research culture will be investigated, with a focus on mainstreaming systematic integration of equity, diversity and inclusion practices. A comprehensive Stakeholder Forum will be engaged to provide advice, and iRISE will commit to open and reproducible practices. The different types of evidence generated will be integrated into an open knowledge base to support the community in decision-making to identify, test, and implement effective and feasible solutions for reproducibility. The members of iRISE have made pivotal scientific and policy contributions relating to robustness, rigour and reproducibility in the past and have the skills and tools to succeed in this ambitious project that has potential scientific, economic and societal gains both in Europe and beyond.