Identifying values as the drivers of human behavior constitutes the first step towards responsible and trusted sharing. A value-aligned and responsible sharing schema for AI assets aims to generate, over and above hard law, a ‘for benefit’ culture and can serve as a driver for responsible AI practices. In the present work, we propose a methodology that allows licensors to self-reflect about their values set with respect to the licensed AI asset, based on Schwartz’s personal values vocabulary and convey licensors permissions and restrictions accordingly through licensing. The proposed value-aligned responsible sharing license blueprint integrates the licensor’s values along with typical open licensing elements (BY-SA-NC-ND) that are employed in a dual form, both for copyright and responsibility (r) treats. We demonstrate the application of VaRS methodology through the datasets of the VAST project, an EU-funded H2020 research and innovation action. The VaRS blueprint integrates the VAST consortium’s responsibility treats and demonstrates how licensors’ value-alignment can be reflected in the license.