Ovopub: Modular data publication with minimal provenance

TL;DR

Ovopub is a modular data publication model designed to enhance provenance tracking, data integrity, and selective querying, especially useful in life sciences and Semantic Web applications.

Contribution

It introduces the ovopub RDF specification and key design patterns for modular, provenance-aware data publication and referral.

Findings

Supports encapsulation and aggregation of data statements

Enables integrity checking of published data

Facilitates selective-source query answering

Abstract

With the growth of the Semantic Web as a medium for creating, consuming, mashing up and republishing data, our ability to trace any statement(s) back to their origin is becoming ever more important. Several approaches have now been proposed to associate statements with provenance, with multiple applications in data publication, attribution and argumentation. Here, we describe the ovopub, a modular model for data publication that enables encapsulation, aggregation, integrity checking, and selective-source query answering. We describe the ovopub RDF specification, key design patterns and their application in the publication and referral to data in the life sciences.