OPERAS Data Management Working Group (DMWG) is a cross-team entity established to coordinate, standardize, and optimize data-related activities within the OPERAS research infrastructure. This group functions as a first step toward a central authority for data governance and covers three interconnected domains: Personal data (GDPR Compliance), Service data, and Data trends and opportunities. The Personal data domain ensures legal compliance by creating and maintaining Records of Processing Activities (ROPAs), updating Privacy Notices for all services, establishing Data Processing Agreements with third-party processors, and aligning Service Level Agreements (SLAs) and Operational Level Agreements (OLAs). The Service data domain focuses on the strategic management and quality assurance of non-personal data from both internal services (like Matomo, Mattermost, and GitLab) and the external services portfolio (e.g., Discovery and Analytics). This includes managing the service data inventory, ensuring FAIRification, and developing standardized Data Management Plans (DMPs) for project/grant compliance with funder requirements. The Data trends and opportunities domain monitors the data ecosystem for business opportunities, EOSC integration, and scholarly infrastructure developments. The presentation highlights the significant structural change being driven by AI-mediated discovery, which is decoupling content discovery from publisher platforms and making usage measurement less representative. To address these challenges, which disproportionately affect Diamond Open Access publishers, collective actions are required on technical (structured metadata, API-first architecture), legal (licensing for AI ingestion, metrics access), and political fronts (industry standards on AI retrieval metrics and EU AI Act advocacy).
Maxim N. Kupreyev (Wed,) studied this question.