Policies are authoritative assets that are present in multiple domains to support decision-making. They describe what actions are allowed or recommended when domain entities and their attributes satisfy certain criteria. It is common to find policies that contain geographical rules, including distance and containment relationships among named locations. These locations' polygons can often be found encoded in geospatial datasets. We present an approach to transform data from geospatial datasets into Linked Data using the OWL, PROV-O, and GeoSPARQL standards, and to leverage this representation to support automated ontology-based policy decisions. We applied our approach to location-sensitive radio spectrum policies to identify relationships between radio transmitters coordinates and policy-regulated regions in Census.gov datasets. Using a policy evaluation pipeline that mixes OWL reasoning and GeoSPARQL, our approach implements the relevant geospatial relationships, according to a set of requirements elicited by radio spectrum domain experts.
翻译:支持决策的权威性政策是多个领域的权威性资产,描述了在域实体及其属性满足某些标准时允许或建议采取的行动;常见的做法是找到包含地理规则的政策,包括指定地点之间的距离和封闭关系;这些地点的多边形往往可以在地理空间数据集中找到编码;我们提出了一个方法,利用OWL、PROV-O和GeoSPARQL标准,将地理空间数据集的数据转换为链接数据,并利用这一代表方法支持基于本体的自动决策;我们采用对位置敏感的无线电频谱政策,以确定Census.gov数据集中无线电发射器坐标和政策管制区域之间的关系;我们采用将OWL推理与GeoSPARQL混合的政策评价管道,根据无线电频谱域专家提出的一系列要求,实施相关的地理空间关系。