Data integration is an important task in order to create comprehensive RDF knowledge bases. Many data sources are used to extend a given dataset or to correct errors. Since several data providers make their data publicly available only via Web APIs they also must be included in the integration process. However, APIs often come with limitations in terms of access frequencies and speed due to latencies and other constraints. On the other hand, APIs always provide access to the latest data. So far, integrating APIs has been mainly a manual task due to the heterogeneity of API responses. To tackle this problem we present in this paper the FiLiPo (Finding Linkage Points) system which automatically finds connections (i.e., linkage points) between data provided by APIs and local knowledge bases. FiLiPo is an open source sample-driven schema matching system that models API services as parameterized queries. Furthermore, our approach is able to find valid input values for APIs automatically (e.g. IDs) and can determine valid alignments between KBs and APIs. Our results on ten pairs of KBs and APIs show that FiLiPo performs well in terms of precision and recall and outperforms the current state-of-the-art system.
翻译:数据整合是一项重要任务,目的是创建全面的 RDF 知识基础。 许多数据源被用于扩展特定数据集或纠正错误。 由于一些数据提供者仅通过网络 API 公开其数据,因此也必须将其纳入整合过程。然而,由于时间迟缓和其他限制, API往往在访问频率和速度方面受到限制。 另一方面, API 总是提供访问最新数据的机会。 到目前为止, 整合API 主要是由于API 反应的异质性而需要人工操作的工作。 为了解决这一问题,我们在本文件中提出了FILIPO(查找链接点)系统,该系统自动发现API 和当地知识基础提供的数据之间的连接(即连接点)。 FILiPo是一个开放源样本驱动的系统,其模式是API 服务作为参数化查询。 此外,我们的方法能够自动为API 找到有效的输入值(例如IDs), 并能够确定 KBs 和 APIs 之间的有效匹配。 我们在 10-B 和 ASFI 和 API 系统中显示当前精度和 的系统运行状态。