The tExtended project will achieve its overall objective of reduction of textile waste by 80% by within industrial-urbal symbiosis developing and demonstrating effective textile recovery, waste valorisation and recycling processes combined with digital tools, sensing systems and data-driven solutions to support sustainable circularity of textiles. We will develop a knowledge-based Blueprint, i.e. a master plan for a sustainable textile ecosystem. The basis of the Blueprint is a Conceptual Framework which determines the optimized utilization of textile flows, aiming for retention of value of materials in a safe and sustainable way. Based on the Blueprint, we will implement a real scale demonstrator, verifying its replicability and potential to reduce textile waste. tExtended brings together a multidisciplinary group of experts with complementary skills needed for twin transition in sustainable textile sector. Different types of organizations, research, industry, and non-profit organizations such as NGOs and municipal waste management are included. The consortium consists of actors with different roles in the textile recycling ecosystem: waste management, recycling, textile materials and textile products manufacturing. Participation of forerunner companies and actors involved in textile recycling enables us also to spread best practises for textile recovery and recycling around Europe and across the sector.

Data analytics is one of the main cornerstones in many enterprise architectures and the data lake paradigm is more and more adopted to assist organizations in taking reliable, accurate, and fast decisions. Although the initial approaches to address these issues saw the data lakes as the evolution of data warehouses to be implemented on-premises, cloud providers are nowadays including in their offerings platforms able to setup and run them. Nevertheless, the increasing amount of data generated at the edge and the need to enable the data sharing among organizations are posing new challenges in terms of performances, energy efficiency, and privacy/confidentiality which can be properly addressed with data lakes which are deployed along the whole computing continuum as well as building a federation of such data lakes. The ambition of TEADAL is to provide key cornerstone technologies to create stretched data lakes spanning the cloud-edge continuum and multi-cloud, providing privacy, confidentiality, and energy-efficient data management. The TEADAL data lake technologies will enable trusted, verifiable and energy efficient data flows, both in a stretched data lake and across a trustworthy mediatorless federation of them, based on a shared approach for defining, enforcing, and tracking privacy/confidentiality requirements balanced with the need for energy reduction.