The Data Privacy Vocabulary (DPV) is a machine-readable, interoperable, and standards-based representation for describing the processing of personal data, developed by the W3C Data Privacy Vocabularies and Controls Community Group (DPVCG). DPV 2.0, the latest iteration, expands its scope to include any data or technology, supporting regulations such as the EU's Data Governance Act (DGA) and Artificial Intelligence Act (AI Act). It introduces versioned IRIs for better version control and provides RDFS+SKOS and OWL2 serializations for semantic interoperability. DPV 2.0 includes 2394 concepts, with 1017 added and 805 removed compared to DPV 1.0. The DPVCG plans to refine its TECH and AI extensions and develop vocabularies for key data and AI regulations. DPV has been widely adopted in academia, industry, and standards, with contributions from various organizations and projects. The article discusses the motivation, methodology, design principles, and future work of DPV 2.0.The Data Privacy Vocabulary (DPV) is a machine-readable, interoperable, and standards-based representation for describing the processing of personal data, developed by the W3C Data Privacy Vocabularies and Controls Community Group (DPVCG). DPV 2.0, the latest iteration, expands its scope to include any data or technology, supporting regulations such as the EU's Data Governance Act (DGA) and Artificial Intelligence Act (AI Act). It introduces versioned IRIs for better version control and provides RDFS+SKOS and OWL2 serializations for semantic interoperability. DPV 2.0 includes 2394 concepts, with 1017 added and 805 removed compared to DPV 1.0. The DPVCG plans to refine its TECH and AI extensions and develop vocabularies for key data and AI regulations. DPV has been widely adopted in academia, industry, and standards, with contributions from various organizations and projects. The article discusses the motivation, methodology, design principles, and future work of DPV 2.0.