Believe It or Not: Adding Belief Annotations to Database

We propose a database model that allows users to annotate a database with belief statements. Our motivation comes from scientific database applications, where a community of users is working together to assemble, revise, and curate a shared data repository. As the community accumulates knowledge and the database content evolves over time, it may contain conflicting information and members can disagree on the information it should store. For example, Alice believes that a tuple should be in the database; Bob disagrees and believes the tuple should not be in the database. He may also insert the reason why he thinks Alice believes the tuple should be in the database. In this paper, we propose a formal model for Belief Databases that allows users to annotate data with belief statements. The annotations can refer both to the base data and to other annotations. We give a formal semantics based on a fragment of multi-agent epistemic logic, and define a query language over belief databases. We then prove a key technical result, stating that every belief database can be encoded as a canonical Kripke structure. We use this structure to describe a relational implementation of a belief database, and give an algorithm for translating queries over the belief database into standard relational queries. Finally, we report first experimental results with our prototype implementation on synthetic belief databases.