Path Outlines: Browsing Path-Based Summaries of Knowledge Graphs
This addresses a specific bottleneck for data producers working with knowledge graphs, offering a practical tool to improve efficiency and accuracy in data exploration.
The paper tackles the problem of data producers struggling to gain meaningful overviews of knowledge graphs due to the high cognitive cost of reconstituting chains of triples, and introduces path outlines as conceptual objects with descriptive statistics, showing in an experiment that their tool is 3 times faster, leads to better task completion, fewer errors, and is preferred by participants.
Knowledge Graphs have become a ubiquitous technology powering search engines, recommender systems, connected objects, corporate knowledge management and Open Data. They rely on small units of information named triples that can be combined to form higher level statements across datasets following information needs. But data producers face a problem: reconstituting chains of triples has a high cognitive cost, which hinders them from gaining meaningful overviews of their own datasets. We introduce path outlines: conceptual objects characterizing sequences of triples with descriptive statistics. We interview 11 data producers to evaluate their interest. We present Path Outlines, a tool to browse path-based summaries, based on coordinated views with 2 novel visualisations. We compare Path Outlines with the current baseline technique in an experiment with 36 participants. We show that it is 3 times faster, leads to better task completion, less errors, that participants prefer it, and find tasks easier with it.