The property graph is an increasingly popular data model. An important task when dealing with property graphs is pattern matching. Given a property graph schema S, a property graph G and a query pattern P, all expressed in language L, pattern matching is the process of finding, merging and annotating subgraphs of G that match P. Expressive pattern languages support topological constraints and property values constraints, as well as negation, quantification, grouping, aggregation, and path semantics. Calculated properties may be defined for vertices, edges, and subgraphs, and constraints may be imposed on their evaluation result. Query-posers would like to pose complex queries in a manner that is coherent with the way they think. They want to do it with minimal technical training, minimal effort, and minimal trial and error. The ability to express patterns in a way that is aligned with their mental processes is crucial to the flow of their work, and to the quality of the insights they can draw. Since the capabilities of the human visual system with respect to pattern perception are remarkable, it is a matter of course that query patterns were to be expressed visually. Visual query languages have the potential to be much more 'user-friendly' than their textual counterparts in the sense that patterns may be constructed and understood much more quickly and with much less mental effort. A long-standing challenge is to design a visual query language that is generic, has rich expressive power, and is highly receptive and productive. V1 is a declarative visual pattern query language for schema-based property graphs. V1 supports property graphs with mixed (both directed and undirected) edges and half-edges, with multivalued and composite properties, and with null property values. V1 is generic, concise, has rich expressive power, and is highly receptive and productive.

中文翻译：

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V1：属性图的可视化查询语言

属性图是一种越来越流行的数据模型。处理属性图时的一项重要任务是模式匹配。给定一个属性图模式 S、一个属性图 G 和一个查询模式 P，都用语言 L 表示，模式匹配是查找、合并和注释 G 与 P 匹配的子图的过程。表达模式语言支持拓扑约束和属性值约束，以及否定、量化、分组、聚合和路径语义。可以为顶点、边和子图定义计算属性，并且可以对其评估结果施加约束。查询提出者希望以与他们思考的方式一致的方式提出复杂的查询。他们希望以最少的技术培训、最少的努力和最少的试验和错误来做到这一点。以与他们的心理过程相一致的方式表达模式的能力对于他们的工作流程以及他们可以得出的见解的质量至关重要。由于人类视觉系统在模式感知方面的能力是非凡的，因此当然要以视觉方式表达查询模式。视觉查询语言有可能比它们的文本对应物更“用户友好”，因为可以更快地构建和理解模式，并且花费更少的脑力。一个长期存在的挑战是设计一种通用的、具有丰富表达能力并且具有高度接受性和生产力的可视化查询语言。V1 是一种用于基于模式的属性图的声明式可视模式查询语言。V1 支持具有混合（有向和无向）边和半边、多值和复合属性以及空属性值的属性图。V1 通用、简洁，具有丰富的表现力，具有很强的接受性和生产力。