Meaningful information about an RDF resource can be obtained not only by looking at its properties, but by putting it in the broader context of similar resources. Classic navigation paradigms on the Web of Data that employ a follow-your-nose strategy fail to provide such context, and put strong emphasis on first-level properties, forcing users to drill down in the graph one step at a time. We introduce the concept of semantic paths: starting from a set of resources, we follow and analyse chains of triples and characterize the sets of values at their end. We investigate a navigation strategy based on aggregation, relying on path characteristics to determine the most readable representation. We implement this approach in S-Paths, a browsing tool for linked datasets that systematically identifies the best rated view on a given resource set, leaving users free to switch to another resource set, or to get a different perspective on the same set by selecting other semantic paths to visualize.

中文翻译：

---

S路径：对基于语义路径驱动的链接数据的基于集合的可视化探索

关于RDF资源的有意义的信息不仅可以通过查看其属性来获得，还可以通过将其置于类似资源的更广泛的上下文中来获得。数据网络上采用跟随鼻子的策略的经典导航范式无法提供此类上下文，并且过分强调第一级属性，从而迫使用户一次只向下钻取一步。我们引入了语义路径的概念：从一组资源开始，我们遵循并分析三元组的链，并在其末端表征一组值。我们研究基于聚合的导航策略，该策略依赖于路径特征来确定最易读的表示形式。我们在S-Paths中实现了这种方法，S-Paths是一种用于链接数据集的浏览工具，可以系统地识别给定资源集上的最佳评分视图，