Human-Machine Collaboration over Linked Data

This study presents a framework to allow human and machine agents to reason and coordinate actions without direct communication mechanisms by sharing distributed Linked Data resources. This framework addresses the problems of querying frequently-updating distributed datasets and guaranteeing consistency in case of concurrent updates. The motivation for this framework comes from the use-case of opportunistic automation of humans-generated procedures. This use-case is based on existing real-world Linked Data representations of human instructions and their integration with machine functionalities.