Open Science Graphs (OSGs) are scientific knowledge graphs representing different entities of the research lifecycle (e.g. projects, people, research outcomes, institutions) and the relationships among them. They present a contextualized view of current research that supports discovery, re-use, reproducibility, monitoring, transparency and omni-comprehensive assessment. A Data Management Plan (DMP) contains information concerning both the research processes and the data collected, generated and/or re-used during a project’s lifetime. Automated solutions and workflows that connect DMPs with the actual data and other contextual information (e.g., publications, fundings) are missing from the landscape. DMPs being submitted as deliverables also limit their findability. In an open and FAIR-enabling research ecosystem information linking between research processes and research outputs is essential. ARGOS tool for FAIR data management contributes to the OpenAIRE Research Graph (RG) and utilises its underlying services and trusted sources to progressively automate validation and automations of Research Data Management (RDM) practices. A comparative analysis was conducted between the data models of ARGOS and OpenAIRE Research Graph against the DMP Common Standard. Following this, we extended ARGOS with export format converters and semantic tagging, and the OpenAIRE RG with a DMP entity and semantics between existing entities and relationships. This enabled the integration of ARGOS machine actionable DMPs (ma-DMPs) to the OpenAIRE OSG, enriching and exposing DMPs as FAIR outputs. This paper, to our knowledge, is the first to introduce exposing ma-DMPs in OSGs and making the link between OSGs and DMPs, introducing the latter as entities in the research lifecycle. Further, it provides insight to ARGOS DMP service interoperability practices and integrations to populate the OpenAIRE Research Graph with DMP entities and relationships and strengthen both FAIRness of outputs as well as information exchange in a standard way.

中文翻译：

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作为链接的开放数据的数据管理计划：利用 ARGOS FAIR 和 OpenAIRE 研究图中的机器可操作输出

开放科学图（OSG）是代表研究生命周期的不同实体（例如项目、人员、研究成果、机构）以及它们之间的关系的科学知识图。他们提出了当前研究的情境化观点，支持发现、重复使用、可重复性、监控、透明度和全方位综合评估。数据管理计划 (DMP) 包含有关研究过程以及项目生命周期内收集、生成和/或重复使用的数据的信息。目前缺少将 DMP 与实际数据和其他上下文信息（例如出版物、资金）连接起来的自动化解决方案和工作流程。作为可交付成果提交的 DMP 也限制了其可查找性。在开放且支持公平的研究生态系统中，研究过程和研究成果之间的信息链接至关重要。用于 FAIR 数据管理的 ARGOS 工具为 OpenAIRE Research Graph (RG) 做出了贡献，并利用其底层服务和可信来源逐步实现研究数据管理 (RDM) 实践的验证和自动化。将ARGOS和OpenAIRE Research Graph的数据模型与DMP通用标准进行比较分析。随后，我们通过导出格式转换器和语义标记扩展了 ARGOS，并通过 DMP 实体和现有实体与关系之间的语义扩展了 OpenAIRE RG。这使得 ARGOS 机器可操作 DMP (ma-DMP) 能够集成到 OpenAIRE OSG，丰富并公开 DMP 作为 FAIR 输出。据我们所知，本文首次介绍了在 OSG 中暴露 ma-DMP，并在 OSG 和 DMP 之间建立联系，将后者作为研究生命周期中的实体引入。此外，它还提供了对 ARGOS DMP 服务互操作性实践和集成的见解，以便用 DMP 实体和关系填充 OpenAIRE 研究图，并以标准方式加强输出的公平性和信息交换。