In this paper, we propose a novel data valuation method for a Dataset Retrieval (DR) use case in Ireland's National mapping agency. To the best of our knowledge, data valuation has not yet been applied to Dataset Retrieval. By leveraging metadata and a user's preferences, we estimate the personal value of each dataset to facilitate dataset retrieval and filtering. We then validated the data value-based ranking against the stakeholders' ranking of the datasets. The proposed data valuation method and use case demonstrated that data valuation is promising for dataset retrieval. For instance, the outperforming dataset retrieval based on our approach obtained 0.8207 in terms of NDCG@5 (the truncated Normalized Discounted Cumulative Gain at 5). This study is unique in its exploration of a data valuation-based approach to dataset retrieval and stands out because, unlike most existing methods, our approach is validated using the stakeholders ranking of the datasets.

翻译：本文针对爱尔兰国家测绘机构的数据集检索应用场景，提出了一种新颖的数据估值方法。据我们所知，数据估值技术尚未应用于数据集检索领域。通过利用元数据与用户偏好，我们评估每个数据集的个性化价值以优化数据集检索与筛选流程。随后，我们基于数据价值的排序结果与利益相关方对数据集的排序进行了对比验证。所提出的数据估值方法及应用案例表明，数据估值在数据集检索中具有显著潜力。例如，采用本方法的优化数据集检索在NDCG@5（截断归一化折损累计增益@5）指标上达到了0.8207。本研究开创性地探索了基于数据估值的数据集检索方法，其突出贡献在于：与现有大多数方法不同，我们的方法通过利益相关方对数据集的排序进行了实证验证。