A new approach is needed to ensure that the digital objects created today are available and useful for future generations of users. As scientific, engineering, and media assets and their related metadata are generated across different lifecycle phases, in a continually evolving environment, the concept of a fixed and stable "final" version becomes less relevant. The highly dynamic and complex digital objects that result from such an environment mean that human appraisal is increasingly infeasible. Automated or computer-assisted mechanisms are needed to address the long-term sustainability of this content, dealing not only with technological obsolescence (such as hardware, software, file formats), but also with "semantic drift" of digital assets (e.g. due to changes in terminology), and with disciplinary and societal changes (socialisation of the data).PERICLES will address these challenges by developing extensions to current preservation and lifecycle models that address the evolution of dynamic, heterogeneous resources and their dependencies in changing environments, including policies, processes, semantics, and users, as well as the content itself. Maintaining the complex dependencies between the components of the preservation ecosystem is key to achieving "preservation by design", through models that capture intents and interpretative contexts, and thus enabling content to remain relevant to changing communities of users. These models will be complemented with a suite of tools that implement functionality in support of these models. PERICLES also has a strong focus on facilitating the future commercial exploitation of these outputs, which is reflected in the make-up of the consortium.The project outputs will be validated against a corpus of user scenarios relating to the preservation of highly complex and dynamic and/or large-scale digital assets, derived from real-life contexts in (i) digital media and contemporary art, and (ii) space science. Media assets will include software-based art installations as well as digital images and video, together with contextual information generated during the creation process or through social media. Scientific datasets will include experimental (e.g. biophysics, material science) and observational (e.g. space weather) data, as well as related data (e.g. auxiliary data, calibration curves) and engineering and operations documentation.The project will involve partners of a range of complementary types, including six academic partners, one multinational corporation, two SMEs and two non-academic public sector organisations.