An Ontological Approach to Modelling and Analysing System Performance

本研究集中在集成系统设计和分析的一个方面，即系统性能测量的形式化、标准化和自动化分析(以下简称Metrics)。我们希望研究的一类系统是城市，而我们希望形式化和分析的绩效衡量标准是“城市指标”。城市指标衡量城市服务和功能，包括教育、卫生、安全、交通和水。“有数千套不同的城市(或城市)指标，数百家机构对其进行汇编和审查。…然而，这些指标通常不是标准化的、一致的或可比较的(随着时间的推移或跨城市)。(Hornweg等人，2007年)。“开放数据”运动加剧了这一问题。在“开放数据”运动中，城市发布了大量数据，但没有两个城市或城市内的部门使用相同的数据模型(Fox，2013a)。开放数据的这种“巴别塔”式的后果是，很难对城市数据进行组合、分析和比较。问题并不是就指标的表面定义达成一致，因为定义中的每个术语都必须进一步界定(即有根据)，并提供佐证数据。 我们相信有可能为Metrics识别和创建一个通用的、可重用的本体。我们相信，一个本体可以通过组合现有的基础、异质的本体，并用跨基础公理来扩展它们来创建。异构性指的是跨越分析模型(例如，比率)、统计模型(例如，人口测量)、地理空间模型(例如，城市边界)、时间模型(例如，时间段)和描述逻辑模型(例如，学生、教师等的定义)的本体。而且还包含了诸如出处、有效性和信任等元知识。我们相信，本体将使自动向下钻取和检测支持的异类数据中的不一致成为可能。因此，我们的第一个目标是使用语义Web中实现的形式本体技术来形式化度量的定义。 我们相信，有可能创建一种度量学分析的逻辑理论。我们相信，一致性分析为检测指标变化的根本原因提供了基础。因此，我们的第二个目标是开发一种可重用的、可互操作的度量纵向和横向分析的逻辑理论。我们将扩展Metrics的一致性公理，以解决跨异类模型的纵向(时间)和横向(跨城市)一致性。 强大、成功的城市是一个强大、充满活力的国家的先决条件。在加拿大，目前超过80%的加拿大人生活在城市地区。因此，城市区域的可持续性(在环境、社会和财政方面)及其对人为和自然大型事件的适应能力，对我们的福祉和生活质量具有首要的国家重要性。智能和有效地处理城市管理和设计的复杂问题需要使用现有的最佳信息、分析和决策支持工具。该计划的贡献包括： ·标准的正式定义，为系统性能提供精确、明确和机器可解释的定义， ·能够根据指标的定义对指标进行一致性分析和比较分析(与特别软件实施相对)，以及 ·就城市而言，术语的标准化，从而使城市能够使用通用词汇或本体发布其开放数据。

This research focuses on one aspect of the design and analysis of integrated systems, namely the formalization, standardization and automated analysis of system performance measurement (referred to as Metrics from here on in). One class of systems we wish to study is cities and the performance measures we wish to formalize and analyze are “city indicators.” City indicators measure city services and functions, including Education, Health, Safety, Transportation, and Water. "There are thousands of different sets of city (or urban) indicators and hundreds of agencies compiling and reviewing them. … However, these indicators are usually not standardized, consistent or comparable (over time or across cities) ...” (Hornweeg et al., 2007). This problem has been exacerbated by the “Open Data” movement where cities are publishing vast amounts of data, but no two cities nor departments within a city use the same data models (Fox, 2013a). A consequence of this “babel” of open data is that it is difficult to combine, analyze and compare city data. The problem does not end with an agreement on the surface definition of an indicator, as each term within the definition has to be further defined (i.e., grounded) and supporting data provided. We believe it is possible to identify and create a generic, reusable ontology for Metrics. We believe an ontology can be created by combining existing foundation, heterogeneous ontologies, and extending them with trans-foundation axioms. By heterogeneous, we mean ontologies that span analytical models (e.g., ratios), statistical models (e.g., population measurements), geo-spatial models (e.g., city boundaries), temporal models (e.g., time periods) and description logic models (e.g., definitions of students, teachers, etc.). But also incorporate meta-knowledge such as provenance, validity and trust. We believe that the ontology will make it possible to automate the drilling down and detection of inconsistencies in the supporting, heterogeneous data. Hence, our first objective is to formalize the definition of Metrics using the technology of Formal Ontologies as implemented in the Semantic Web. We believe it is possible to create a logical theory of Metrics analysis. We believe that consistency analysis provides a basis for detecting root causes in changes in Metrics. Hence, our second objective is to develop a reusable, interoperable logical theory of longitudinal and transversal analysis of Metrics. We will extend the Metrics’ consistency axioms to address longitudinal (temporal) and transversal (cross city) consistency across heterogeneous models. Strong, successful cities are prerequisites for a strong, vibrant nation. In Canada, over 80% of Canadians currently live in urban areas. The sustainability of urban regions (in environmental, social and fiscal terms), and their resilience to both man-made and natural large-scale events, are thus of first-order national importance to our well-being and quality of life. Dealing intelligently and effectively with the complex problems of urban management and design requires use of the best information, analysis and decision-support tools available. This program’s contributions include: • The formal definition of Metrics that provide precise, unambiguous and machine interpretable definitions of system performance, • The ability to perform consistency and comparative analyses of Metrics based upon their definitions (as opposed to ad hoc software implementations), and • In the case of cities, the standardization of terminology thereby enabling cities to publish their open data using common vocabularies or ontologies.