Case Management is a paradigm to support knowledge-intensive processes. The different approaches developed for modeling these types of processes tend to result in scattered information due to the low abstraction level at which the inherently complex processes are represented. Thus, readability and understandability are more challenging than in imperative process models. This paper extends a case modeling language—the fragment-based Case Management (fCM) language—to a so-called fCM landscape (fCML) with the goal of modeling a single knowledge-intensive process from a higher abstraction level. Following the Design Science Research (DSR) methodology, we first define requirements for an fCML, and then review how literature—in the fields of process overviews and case management—could support them. Design decisions are formalized by specifying a syntax for an fCML and the transformation rules from a given fCM model. The proposal is empirically evaluated via a laboratory experiment. Quantitative results imply that interpreting an fCML requires less effort in terms of time—and is thus more efficient—than interpreting its equivalent fCM case model. Qualitative results provide indications on the factors affecting case model interpretation and guidelines for future work.

案例管理是支持知识密集型流程的范例。由于代表固有复杂过程的低抽象级别，为这些类型的过程建模而开发的不同方法往往会导致信息分散。因此，可读性和可理解性比命令性过程模型更具挑战性。本文将案例建模语言（基于片段的案例管理（fCM）语言）扩展到所谓的fCM景观（fCML），其目标是从更高的抽象级别对单个知识密集型过程进行建模。遵循设计科学研究（DSR）方法，我们首先定义fCML的要求，然后回顾过程概述和案例管理领域的文献如何为它们提供支持。通过指定fCML的语法和给定fCM模型的转换规则来形式化设计决策。该建议通过实验室实验进行经验评估。定量结果表明，与解释其等效的fCM案例模型相比，解释fCML所需的时间更少，因此效率更高。定性结果表明影响案例模型解释的因素和未来工作的指南。