Integrating Know-How into the Linked Data Cloud

TL;DR

This paper introduces a novel framework for representing, linking, and automatically acquiring procedural knowledge as Linked Data, enhancing integration and retrieval of online know-how from unstructured web sources.

Contribution

It presents the first comprehensive framework for integrating procedural knowledge into the Linked Data Cloud, including automatic acquisition and linking of know-how resources.

Findings

Framework effectively represents procedural knowledge as Linked Data.

Automatic linking improves integration of know-how resources.

Outperforms manual community-driven integration efforts.

Abstract

This paper presents the first framework for integrating procedural knowledge, or "know-how", into the Linked Data Cloud. Know-how available on the Web, such as step-by-step instructions, is largely unstructured and isolated from other sources of online knowledge. To overcome these limitations, we propose extending to procedural knowledge the benefits that Linked Data has already brought to representing, retrieving and reusing declarative knowledge. We describe a framework for representing generic know-how as Linked Data and for automatically acquiring this representation from existing resources on the Web. This system also allows the automatic generation of links between different know-how resources, and between those resources and other online knowledge bases, such as DBpedia. We discuss the results of applying this framework to a real-world scenario and we show how it outperforms existing manual community-driven integration efforts.