"溯源信息—证据"视角下的科学数据信任决策模型研究OACHSSCD

[Purpose/Significance]The deepening of the open science paradigm is driving a transition in scientific data from closed retention to open reuse;scientific data has become a key strategic resource within the global research system.Trust in scientific data refers to a comprehensive state of trust formed by researchers in an open science environment during the evaluation and utilisation of target scientific data,with a view to supporting further scientific innovation.Addressing the challenges of data quality and credibility in the management and application of scientific data,this study adopts a data provenance perspective and further introduces evidence as an intermediary to explore decision-making regarding trust in scientific data from the"provenance information-evidence"perspective,with the aim of enhancing the ability to assess the credibility of scientific data.[Method/Process]The study explained the logical compatibility between evidence and prove-nance in data trust decisions:evidence provides an effective path for trust judgment,while provenance information serves as the prerequisite for generating evidence.Based on this alignment,the paper proposed a scientific data trust decision-making model.In this model,provenance information described by the"W7+R3"framework served as the decision input;provenance evidence constituted the decision process and was categorized by function into entity,activity,and ethical data evidence;and the final trust determination represented the decision output.During evaluation,individual evidence units were assessed across four dimensions—structure,source,logic,and ethics,to calculate a comprehensive credibility score.For evidence chains,the evaluation method accounted for ethical prerequisites and temporal coherence.An empiri-cal case study was conducted using the ImageNet dataset,following a structured pathway that included identifying the data-set,acquiring provenance information,generating evidence units,evaluating the evidence chain,and making the final trust decision.[Result/Conclusion]The scientific data trust decision model effectively traces data provenance,evaluates the credibility of evidence concerning key operational events.It and outputs trust decisions such as accept/adopt or reject/avoid,thereby providing a reference for the trustworthiness assessment of scientific data.However,the model's applica-bility has not yet been fully validated.Future research would explore automated collaborative evidence judgment mechanisms in multi-source heterogeneous data fusion scenarios,refine the quality assessment criteria for evidence transformation,and enhance the model's generalizability and precision.