A Foundation Ontology for City Data

城市数据的基础本体

• 批准号: RGPIN-2020-06393
• 负责人: Fox, Mark
• 金额: $ 1.89万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=741182
• 关键词: Foundation; Ontology; City; Data

The pursuit of smarter cities has many drivers, including doing more with less, making better decisions, being more citizen centred and better coordinating the divisions and their activities across the city. One thing shared by these drivers is the need for high quality data generated by a plethora of sources across the city. But due to the complexity of operating a city, they its divisions/services have evolved as silos where each silo has its own terminology and ways of modeling data. But in order to become smarter, cities need better communication and coordination. A critical factor in achieving greater communication and coordination is a shared understanding of the information upon which communication and coordination relies. If the silos do not understand each other, communication and coordination is more difficult. More formally, achieving a shared understanding requires Semantic Interoperability of city data. The goal of this research program is to design a City Ontology to represent the core concepts used to manage cities. A major barrier to interoperability is semantic heterogeneity: different applications, databases, and city departments may ascribe disparate meanings to the same terms or use distinct terms to convey the same meaning. Even when software applications use the same terminology, they often associate different semantics with the terms. This clash over the meaning of the terms prevents the seamless exchange of information across the city. Our objectives are to: 1.Identify candidate concepts and their use cases through a detail analysis of existing city vocabularies, ontologies and city enterprise software. 2.Reduce the candidate concepts from the different sources into a minimal set of core concepts. 3.Manage and curate an open process where Standards Development Organizations (SDOs) and other experts can comment on the core concepts (defined in step 2) and post modifications, use cases and new concepts. 4.Formalize and evaluate the resulting concepts from step 3. 5.Promulgate the results through the Standards Council of Canada and the International Standards Organization so that they will be adopted by cities around the world. In the short term we will focus on city level ontologies, and in the long term we will focus on service level ontologies. The novelty of this research lies in it being the first attempt identify and formalize city level concepts. To date, the development of Ontologies and Vocabularies for cities has either been at too high a level of abstraction (top level or generic), or ad hoc as they are driven by the needs of their particular application. In Canada, more than 80% of the population lives in urban areas. The creation of a city ontology can have a profound affect on the future operations of cities. It will enable the creation of smarter applications by allowing them to use data from across the city into their decision process.

对智能城市的追求有许多驱动因素，包括用更少的资源做更多的事情，做出更好的决策，更加以市民为中心，以及更好地协调城市中的部门及其活动。这些司机有一个共同点，那就是需要由城市中过多的来源产生的高质量数据。但由于运营城市的复杂性，其部门/服务已演变为孤岛，每个孤岛都有自己的术语和数据建模方法。但为了变得更智能，城市需要更好的沟通和协调。加强沟通和协调的一个关键因素是对沟通和协调所依赖的信息有共同的理解。如果竖井之间互不理解，沟通和协调就会更加困难。更正式地说，实现共享理解需要城市数据的语义互操作性。这个研究计划的目标是设计一个城市本体论来表示用于管理城市的核心概念。互操作性的一个主要障碍是语义异构性：不同的应用程序、数据库和城市部门可能会将不同的含义赋予相同的术语，或者使用不同的术语来传达相同的含义。即使软件应用程序使用相同的术语，它们也经常将不同的语义与术语相关联。这种对术语含义的冲突阻碍了全市信息的无缝交换。我们的目标是：1.通过对现有城市词汇、本体和城市企业软件的详细分析，确定候选概念及其用例。2.将来自不同来源的候选概念缩减为最小的核心概念集。3.管理和策划一个开放的过程，标准开发组织(SDO)和其他专家可以在其中对核心概念(在步骤2中定义)进行评论，并发布修改、用例和新概念。4.将步骤3中产生的概念形式化并进行评估。5.通过加拿大标准委员会和国际标准组织公布结果，以便它们将被世界各地的城市采用。短期内我们将专注于城市级别的本体，而长期内我们将专注于服务级别的本体。本研究的创新之处在于首次尝试对城市层面的概念进行界定和形式化。到目前为止，城市的本体和词汇表的发展要么处于太高的抽象水平(顶级或通用)，要么由于它们是由其特定应用的需求驱动的而临时进行的。在加拿大，80%以上的人口生活在城市地区。城市本体论的创建可以对城市未来的运营产生深远的影响。它将允许他们在决策过程中使用整个城市的数据，从而创建更智能的应用程序。