In our data-centric society, the imperative to determine the value of data has risen. Therefore, this paper presents a taxonomy for a data valuation business capability. Utilizing an initial taxonomy version, which originated from a systematic literature review, this paper validates and extends the taxonomy, culminating in four layers, twelve dimensions, and 59 characteristics. The taxonomy validation was accomplished by conducting semi-structured expert interviews with eleven subject matter experts, followed by a cluster analysis of the interviews, leading to a taxonomy heatmap including practical extensions. This paper's implications are manifold. Firstly, the taxonomy promotes a common understanding of data valuation within an enterprise. Secondly, the taxonomy aids in categorizing, assessing, and optimizing data valuation endeavors. Thirdly, it lays the groundwork for potential data valuation standards and toolkits. Lastly, it strengthens theoretical assumptions by grounding them in practical insights and offers an interdisciplinary research agenda following the taxonomy dimensions and characteristics.

在我们以数据为中心的社会中，确定数据价值的必要性已经上升。因此，本文提出了一个数据评估业务能力的分类法。利用源自系统文献综述的初始分类法版本，本文验证并扩展了分类法，最终形成四层、十二个维度和 59 个特征。分类验证是通过对 11 位主题专家进行半结构化专家访谈来完成的，然后对访谈进行聚类分析，从而得出包括实际扩展在内的分类热图。本文的含义是多方面的。首先，分类法促进了企业内部对数据估值的共同理解。其次，分类法有助于分类、评估和优化数据估值工作。第三，它为潜在的数据估值标准和工具包奠定了基础。最后，它通过将理论假设建立在实践见解的基础上来加强理论假设，并提供了遵循分类学维度和特征的跨学科研究议程。