WorldKG: World-Scale Completion of Geographic Knowledge

OpenStreetMap(OSM)是公开可用的志愿地理信息的丰富来源。OSM被网络上和其他地方的各种现实世界应用程序所采用，包括在线路线规划和地理信息网站。然而，OSM中地理实体的表示具有高度的多样性和不完全性，仅限于很少的强制属性和异质标签，即用户定义的键值对；最近出现的知识图(即基于图的知识库)，如Wikidata、EventKG和DBpedia，提供了丰富的地理实体上下文信息来源，并支持语义查询。例如，2018年9月，维基数据包含了640多万个实体，包括位置、兴趣点、山峰等。知识图为地理实体提供了广泛的补充语义信息，对Web应用程序非常有用，但OSM和知识图之间的身份链接仍然很少，主要由志愿者手动定义。OSM数据集的链接发现问题由于规模大、内容丰富、WordKG项目的主要目标是促进描述不同地理区域的OSM数据集与知识图的世界级链接，以及使用OSM数据在知识图中完成空间知识。这一目标被转化为三个主要目标：1)在模式和实例级别发展OSM数据集和知识图的世界尺度对齐方法；2)通过实例融合和基于VGI信息创建新的语义实例，开发基于VGI的知识图完成方法。3)准备和发布由这些方法产生的数据以WorldKG知识图的形式其提供了地理信息及其上下文的全面语义表示。WorldKG项目的结果可大大有益于移动性方面的应用，通过对地理信息和背景信息的高质量语义表示，为信息地图和服务提供了基础。

OpenStreetMap (OSM) is a rich source of openly available volunteered geographic information. OSM is adopted by a variety of real-world applications on the Web and beyond, including online route planners and geographic information sites. However, representations of geographic entities in OSM are highly diverse and incomplete, being restricted to few mandatory properties and heterogeneous tags, i.e. user-defined key-value pairs.Recently emerged knowledge graphs (i.e. graph-based knowledge repositories) such as Wikidata, EventKG and DBpedia provide a rich source of contextual information about geographic entities and support semantic queries. For example, in September 2018 Wikidata contained more than 6.4 million entities including locations, points of interest, mountain peaks and others.Whereas knowledge graphs provide a wide range of complementary semantic information for geographic entities, highly useful for Web applications, identity links between OSM and knowledge graphs are still rare and are mainly manually defined by volunteers.The problem of link discovery for OSM datasets is particularly challenging due to the large scale, richness, heterogeneity and different localisation.The main goal of the WordKG project is to facilitate world-scale interlinking of OSM datasets describing different geographic regions with knowledge graphs as well as completion of spatial knowledge in the knowledge graphs using OSM data.This goal is translated into three main objectives:1) Development of methods for world-scale alignment of OSM datasets and knowledge graphs at the schema and instance level.2) Development of methods for VGI-based knowledge graph completion through instance fusion and creation of new semantic instances based on VGI information.3 ) Preparation and release data resulting from these methods in form of the WorldKG knowledge graph that provides comprehensive semantic representation of geographical information and its context.The results of the WorldKG project can substantially benefit applications in mobility, transportation, tourism and logistics domains, as well as provide a basis for informational maps and services through high quality semantic representation of geographical and contextual information.