Our Missions
VautBiblio tackles the pervasive problem of spam emails from predatory publishers that flood researchers after posting articles online. By integrating fast article dissemination with a comprehensive screening system, VautBiblio identifies and blocks predatory publishers, issuing certificates of trustworthiness to safeguard the academic community. This protection ensures the reliability of the unified BibTeX database repository, which streamlines reference management across disciplines. The editorial management system, available both on-premise and in the cloud, supports efficient peer review workflows and helps editors avoid references to predatory journals. Together, these interconnected services aim to eliminate predatory practices and foster a trustworthy, sustainable scholarly publishing environment.
Our Approach
Maintaining a continuously updated database of predatory publishers powered by machine learning and expert verification protects researchers from unethical publishing practices. Peer monitoring driven by the research community enables identification and exclusion of predatory publishers. Preprint repositories undergo thorough sanitization to remove content from predatory sources before distribution. A unified BibTeX database is cleansed to ensure the integrity and reliability of references. The editorial management system integrates tightly with this sanitization ecosystem, enabling secure and efficient workflows.
The Ecosystem
A machine learning-powered database tracks predatory publishers with expert verification. Researcher-led peer monitoring identifies new predatory entities. Preprint repositories and a unified BibTeX database are sanitized to exclude predatory sources. APIs provide real-time identification of predatory publishers for integration with external systems. The editorial management system integrates directly with this ecosystem to support secure, efficient workflows and prevent predatory references. Continuous updates come from community feedback and editorial actions, keeping the ecosystem accurate and effective.
Our Team
DERaC LLC manages and operates this service, led by Tetsuya Saito (Ph.D.), an expert in machine learning, economics, and AI research. With extensive academic and industry experience, including professorships and leadership roles, the team is committed to advancing trustworthy academic publishing through cutting-edge technology and community-driven solutions.