做城市计算或交通预测的可以看看，这个数据集把站点、道路、POI串成了知识图谱，还开放了链接数据，比纯表格好用。
RTSKG是一个专门为城市级轨道交通站点任务设计的知识图谱数据集，显式建模了站点、道路段和兴趣点等异构城市实体间的空间与语义交互。该数据集采用统一模式组织数据，并以Linked Data形式在https://w3id.org/rtskg/开放访问。在站点周边商店推荐和知识增强的客流预测两项评估中，RTSKG展现了有效性，表明其能支持城市级轨道交通站点分析。
RTSKG: Building a Rail Transit Station Knowledge Graph Dataset
Rail transit systems play a vital role in urban mobility and economic development. As key components of such systems, rail transit stations function as critical transport hubs that enhance urban accessibility and stimulate development in surrounding areas. City-level rail transit station related tasks (e.g., ridership prediction) require large-scale urban data, but current studies often neglect complex interactions among various urban entities in terms of data organization. In this paper, to address the above issue, we build a Rail Transit Station Knowledge Graph (RTSKG) dataset which explicitly models the spatial and semantic interactions among different kinds of urban entities, to benefit city-level rail transit station related tasks. RTSKG integrates heterogeneous urban entities, such as rail transit stations, road segments, and points of interest, with a specially designed unified schema, and is accessible as Linked Data at https://w3id.org/rtskg/. Evaluations on station-area store recommendation and knowledge-enhanced ridership prediction demonstrate the effectiveness of RTSKG, highlighting its potential to support city-level rail transit station analysis.