标题： IoD研究：通过数据互联网对私有异构数据的深度研究 显示英文标题

标题： IoDResearch: Deep Research on Private Heterogeneous Data via the Internet of Data

摘要： 多源、异构和多模态科学数据的快速增长日益暴露了传统数据管理的局限性。 大多数现有的深度研究（DR）工作主要集中在网络搜索上，而忽略了本地私有数据。 因此，这些框架对于私有数据的检索效率较低，并且无法符合FAIR原则，最终导致效率低下和可重用性有限。 为此，我们提出了IoDResearch（数据研究互联网），一种以私有数据为中心的深度研究框架，实现了数据互联网范式。 IoDResearch将异构资源封装为符合FAIR原则的数字对象，并进一步将其细化为原子知识单元和知识图谱，形成异构图索引，用于多粒度检索。 在此表示基础上，一个多智能体系统支持可靠的问答和结构化科学报告生成。 此外，我们建立了IoD深度研究基准，以系统评估IoD场景下的数据表示和深度研究能力。 在检索、问答和报告写作任务上的实验结果表明，IoDResearch始终超越了代表性的RAG和深度研究基线。 总体而言，IoDResearch展示了在数据互联网范式下以私有数据为中心的深度研究的可行性，为更可信、可重用和自动化的科学发现铺平了道路。 显示英文摘要

摘要： The rapid growth of multi-source, heterogeneous, and multimodal scientific data has increasingly exposed the limitations of traditional data management. Most existing DeepResearch (DR) efforts focus primarily on web search while overlooking local private data. Consequently, these frameworks exhibit low retrieval efficiency for private data and fail to comply with the FAIR principles, ultimately resulting in inefficiency and limited reusability. To this end, we propose IoDResearch (Internet of Data Research), a private data-centric Deep Research framework that operationalizes the Internet of Data paradigm. IoDResearch encapsulates heterogeneous resources as FAIR-compliant digital objects, and further refines them into atomic knowledge units and knowledge graphs, forming a heterogeneous graph index for multi-granularity retrieval. On top of this representation, a multi-agent system supports both reliable question answering and structured scientific report generation. Furthermore, we establish the IoD DeepResearch Benchmark to systematically evaluate both data representation and Deep Research capabilities in IoD scenarios. Experimental results on retrieval, QA, and report-writing tasks show that IoDResearch consistently surpasses representative RAG and Deep Research baselines. Overall, IoDResearch demonstrates the feasibility of private-data-centric Deep Research under the IoD paradigm, paving the way toward more trustworthy, reusable, and automated scientific discovery.