发表机构
University of California, San Diego; University of Toronto; Dunlap Institute for Astronomy & Astrophysics, University of Toronto; University of Illinois Urbana-Champaign; FAIR Data Innovations Hub, California Medical Innovations Institute; National Center for Supercomputing Applications, University of Illinois Urbana-Champaign; SciOS; University of California Berkeley; Center for Astrophysics | Harvard & Smithsonian; Astrophysics Source Code Library | University of Maryland College Park; Universität Heidelberg, Zentrum für Astronomie (ZAH), Institut für Theoretische Astrophysik; Institute for Cyber-Enabled Research, Michigan State University; The US Research Software Engineer Association; San Diego Supercomputer Center, University of California, San Diego; Center for Computational Astrophysics, Flatiron Institute（加州大学圣地亚哥分校; 多伦多大学; 多伦多大学邓普尔天文与天体物理研究所; 伊利诺伊大学厄巴纳-香槟分校; 公平数据创新中心，加州医疗创新研究所; 美国国家超级计算应用中心，伊利诺伊大学厄巴纳-香槟分校; SciOS; 加州大学伯克利分校; 哈佛&史密森尼天体物理中心; 天体物理学源代码库，马里兰大学帕克分校; 海德堡大学，天文学中心（ZAH），理论天体物理研究所; 密歇根州立大学网络使能研究所; 美国研究软件工程师协会; 加州大学圣地亚哥分校圣地亚哥超级计算中心; 平顿研究所计算天体物理中心）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究基于NASA资助的研讨会，分析软件引用的文化、规范、技术和AI挑战，提出干预措施，强调编辑和出版商是推动变革的关键，使正确引用成为最省力路径。
AI 中文摘要
软件既是现代计算研究的基础工具，也是其首要产出，然而软件的引用实践仍然不一致、不完整，且很少能实现机器可操作。为论文和数据引用设计的现有基础设施无法充分满足软件引用的独特需求，留下的空白阻碍了可复现性，错误归属了学术贡献，并掩盖了研究流程中嵌入的劳动。基于2026年4月由NASA资助的社区研讨会，我们分析了四个相互关联的主题：（I）一致引用实践的文化障碍；（II）对更清晰的社区规范和惯例的需求；（III）现有技术基础设施和工作流程中的空白；（IV）AI辅助研究带来的新兴挑战。针对每个主题，我们确定了有针对性的干预措施，并在利益相关者群体之间分配责任。我们得出结论，有意义的进展需要在技术和文化两条战线上同时采取行动。期刊编辑和出版商是加速这一变革的最高杠杆点，而正确的引用必须成为研究人员现有工作流程中最省力的路径。
英文摘要
Software is both a foundational tool and a primary output of modern computational research, yet citation practices for software remain inconsistent, incomplete, and rarely machine-actionable. Existing infrastructure designed for paper and data citation does not adequately serve the distinct needs of software citation, leaving a gap that impedes reproducibility, misattributes scholarly credit, and obscures the labor embedded in research pipelines. Drawing on a NASA-funded community workshop held in April 2026, we present an analysis of four interconnected themes: (I)~the cultural barriers to consistent citation practice; (II)~the need for clearer community norms and conventions; (III)~gaps in existing technical infrastructure and workflow; and (IV)~the emerging challenges posed by AI-assisted research. For each theme we identify targeted interventions and assign responsibility across stakeholder groups. We conclude that meaningful progress requires simultaneous action on technical and cultural fronts. Journal editors and publishers represent the single highest-leverage point for accelerating this change, and correct citation must become the path of least resistance within researchers' existing workflows.
Comments17 pages, 1 figure (including appendices)
