Abstract Summary
This session consists of two parts. First, we will present a scientific paper on the development of dynamic product passports for IT hardware. Second, we will demonstrate a new tool, Circular Resource Planning for IT (RePlanIT), that successfully implements academic research to empower end users of IT to make science-based circular decisions in purchasing, maintaining and upgrading their IT environment. The exponentially growing digitisation of services has resulted in a rising materials demand for hardware manufacturing. ICT devices such as laptops and data servers are used on average for 3 and 4-5 years [1] respectively, while research shows that they should last 7 years before replacement [2]. Currently, the ICT sector is responsible for 3-6% of global CO2 emissions (comparable to the cement industry) with a predicted increase of up to 14% in 2040, without sustainable interventions. A solution is to transition from a linear to a circular economy (CE). To facilitate this paradigm shift and boost the data economy and digital innovation in the field, the EU has introduced the concept of digital product passports (DPPs). These should provide information about a product's lifetime and facilitate circular choices [3]. However, several (technological) challenges delay adoption, including the lack of findable, accessible, interoperable, and reusable (FAIR) ICT and materials data to support its interpretation for decision-making by both humans and machines. In this paper we present our solution to overcoming these challenges. Based on utilising Semantic Web technologies (ontologies and knowledge graphs), an extensive literature survey [4] and analysis of existing work in the field, we have built the RePlanIT [5;6] ontology. This is a novel unified machine-readable representation, which interconnects the ICT, materials and CE domains, and can support and motivate more sustainable human-decision making (e.g., ICT procurement). Following the scientific discussion, we will host a demonstration of the RePlanIT tool that has successfully validated the scientific approach in real-world settings. This is combined with an interactive interview of the involved people from Gemeente Amsterdam (expected collaborators for this session) and Rijkswaterstaat or KPN (possible collaborators for this session). We present two use cases: 1. Extending the life of laptops at Gemeente Amsterdam, and 2. Using machine learning to optimize lifespan of servers at KPI, balancing energy consumption, e-waste and performance, at KPN and Rijkswaterstaat. The goal is to show how science can facilitate practical tools to lower the ecological footprint of digital infrastructures and inspire the audience to adopt life-extending measures in their own work environment. Target audience is, next to researchers, the ICT hardware owners and buyers, and policy makers working on digitalization strategies, both from private and public sector. *references in PDF attachment*
