ISO/TS 19158:2012 地理信息 数据供应的质量保证
标准编号：ISO/TS 19158:2012
中文名称：地理信息 数据供应的质量保证
英文名称：Geographic information — Quality assurance of data supply
发布日期：2012-10
标准范围
ISO/TS 19158:2012提供了特定于地理信息的质量保证框架。它基于ISO 19157中确定的地理信息质量原则和质量评估程序，以及ISO 9000中定义的一般质量管理原则。ISO/TS 19158:2012中定义的框架使客户能够满足其内部和外部供应商能够提供所需质量的地理信息。该框架的基础是保证供应商理解和满足质量要求的能力。通过质量保证框架，客户和供应商都能够考虑在生产/更新过程中最早的机会所要求的质量。提供了促进框架的客户和供应商之间关系的原则和责任。质量评估程序的责任由客户和供应商共同承担。ISO/TS 19158:2012适用于所有地理信息的客户和供应商，在以下任何情况下，供应商的流程可能会影响产品质量:1） 有提供数据采集服务的协议或法规，2） 正在招标数据采集服务，以及3） 供应链中存在一个或多个供应商。ISO/TS 19158:2012不适用于提供遗留数据集或？无需管理进一步的数据生产或更新活动的现成产品。
ISO/TS 19158:2012 provides a framework for quality assurance specific to geographic information. It is based upon the quality principles and quality evaluation procedures of geographic information identified in ISO 19157 and the general quality management principles defined in ISO 9000.The framework defined in ISO/TS 19158:2012 enables a customer to satisfy itself that its suppliers, both internal and external, are capable of delivering geographic information to the required quality. Fundamental to the framework is the assurance of the supplier's ability to understand and meet the quality requirements. Through the quality assurance framework both the customer and the supplier are able to consider the quality required at the earliest opportunity in the production/update process.Principles and responsibilities of the relationship between the customer and the supplier that facilitate the framework are provided. The responsibility for the quality assessment procedure is shared between the customer and the supplier.ISO/TS 19158:2012 is applicable to customers and suppliers of all geographic information where the quality of the product may be impacted upon by the supplier's processes in any of the following scenarios:1) there is an agreement or legislation for the supply of data acquisition services,2) data acquisition services are being tendered for, and3) one or more suppliers exist in the supply chain.ISO/TS 19158:2012 is not applicable for the supply of legacy datasets or?off the shelf' products where there is no further data production or update activity to manage.
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