When we think of model ensembling or ensemble modeling, there are many possibilities that come to mind in different disciplines. For example, one might think of a set of descriptions of a phenomenon in the world, perhaps a time series or a snapshot of multivariate space, and perhaps that set is comprised of data-independent descriptions, or perhaps it is quite intentionally fit *to* data, or even a suite of data sets with a common theme or intention. The very meaning of 'ensemble' - a collection together - conjures different ideas across and even within disciplines approaching phenomena. In this paper, we present a typology of the scope of these potential perspectives. It is not our goal to present a review of terms and concepts, nor is it to convince all disciplines to adopt a common suite of terms, which we view as futile. Rather, our goal is to disambiguate terms, concepts, and processes associated with 'ensembles' and 'ensembling' in order to facilitate communication, awareness, and possible adoption of tools across disciplines.

翻译：当我们考虑模型集成或集成建模时，不同学科中会浮现出多种可能性。例如，人们可能会想到对某一世界现象的一组描述——可能是时间序列或多元空间的快照——这组描述可能由独立于数据的描述组成，也可能是有意与数据拟合的，甚至是一组具有共同主题或意图的数据集。“集成”（ensemble）一词的本意——集合在一起——在不同学科乃至同一学科内部，都会引发对现象的不同理解。本文提出了一套关于这些潜在视角范围的类型学。我们的目标并非对术语和概念进行综述，也非试图说服所有学科采用一套通用术语（我们认为这徒劳无益），而是澄清与“集成”和“集成过程”相关的术语、概念和流程，以促进跨学科的交流、认知以及工具的可能采用。