Characterizing Utilitarian Aggregation of Open Knowledge

Abstract

Recent initiatives in "open data" have resulted in good quality, freely available, tabular datasets on the web. However, such datasets are fragmented and arbitrarily structured and are not of much utility in isolation. To address this, there are several "open knowledge" initiatives that aim to stitch together open data elements into semantically meaningful structures. But such efforts are met with unique challenges. We argue in this paper that knowledge aggregation can be of two kinds -- encyclopedic aggregation, which aims to elucidate, and utilitarian aggregation, which aims to create actionable knowledge elements. We also argue that utilitarian aggregation is a characteristically different problem from that of conventional efforts like Freebase or DBpedia that address encyclopedic aggregation. In addition, when it comes to utilitarian knowledge, we observe that openness is not a binary condition and instead there is a need to distinguish between knowledge that is "open-ended" and knowledge that is "open." We formalize the notion of open knowledge based on how much knowledge or control does the creator of the knowledge element have about its consumers. Based on these arguments, we propose an underlying knowledge representation framework for encoding open utilitarian knowledge.