There is a link between economic growth and carbon emissions. Considering that world GDP is growing, breaking this link will be crucial to achieving climate goals. Decoupling economic growth from carbon emissions is the answer. How to do it is the question. Some see IT and technologies playing a big role. But not everyone agrees. Against this background, the EU-funded Decoupling IT project will study how sociocultural change is generated in the spaces between IT, climate change and capitalism. Specifically, it will shed light on how IT professionals and enterprises articulate climate change as a problem in demand of IT-generated change. While both climate change and IT are manifested in globally diverse ways, their interrelationship must be studied.
SSH Knowledge and Business Sustainability Database
This project critically analyses the sustainability efforts of large Danish companies in the face of multiple climate crises. Such organizations are required by law to detail their efforts to combat climate change in their annual reports, and this research project seeks to use this open data to 1) create a research infrastructure with easy access to the data for others to use and 2) analyze what kind of sustainability efforts companies engage in, and what kind of expertise and knowledge they are based on. The project leverages overlapping traditions such as infrastructure studies, digital methods and the emerging field of digital sustainability, exploring how sustainability is being reported and providing a better overview for further research into this topic.
The Democratic Innovations in a Green Transition (DIGT) project examines the impact of Denmark’s climate citizens’ assembly on the Danish political system. In what way does the assembly strengthen support for green transition policies, and to what extent does it affect existing channels for public debate and democratic decision-making? DIGT aims to answer these questions through a new framework that combines the study of deliberative democracy with affect theory, new materialism, and science and technology studies (STS). The goal is to show how the climate citizen’s assembly can contribute positively to green transition through new modes of democratic participation.
In the Amazônia 4.0 research project, we aim to understand how the use of new technologies and the practice of bioeconomic principles can enable a sustainable and inclusive industrialization of the Amazon. The project is the result of a collaborative effort between Professor Steffen Dalsgaard, Assistant Professor Priscila Santos da Costa, and the team of Brazilian researchers who have launched the technological initiative Amazônia 4.0.
Bicycle Network Analysis
We use computational methods from network and data science with GIS tools to improve the analysis and planning of bicycle networks. Our research typically focuses on the big picture, for example how to develop a bicycle network for a whole city. It also makes frequent use of crowdsourced data sets, such as OpenStreetMap data, and develops free and open source software.
The Making Sense of Urban Air Project uses ethnographic methods to explore how the introduction of Google’s ‘Project Air View’, which measures polluting particles in Copenhagen, has had an impact on definitions and perceptions of ‘air quality’.
The variety and complexity of data-intensive applications and systems have been increasing drastically the past decade. Tasks from a SQL-based big data analytics request running on Apache Spark can be very different from tasks from deep learning training using TensorFlow framework. Nevertheless, these data-intensive applications increasingly run on shared powerful hardware resources in data centers and high-performance computing (HPC) centers or resouce-constrained edge/Internet-of-Things(IoT) devices. These hardware resources are also diverse today ranging from general-purpose CPUs and GPUs to programmable FPGAs and specialized machine learning hardware like TPUs. There is a pressing need for a more resource-aware infrastructure that orchestrates the different data-intensive tasks over the heterogeneous processing units effectively. In order to achieve this, our approach is to first investigate the resource consumption characteristics of different data-intensive workloads, and then to establish and implement guidelines for hardware resource management for data-intensive systems. These days, our team more specifically focuses on resource-aware and resource-constrained machine learning. This research has been supported by Independent Research Fund Denmark.
The Sociocultural Carbon Project (SOCCAR) is aimed at gaining a novel understanding of the social and cultural challenges of living with ‘carbon’ in the form of emission data. Such data are today circulating in various forms through digital and informational technologies, whereby they present a moral ‘metric’ of the human as a climate subject. But in what way do they inform human agency or generate any lasting social or cultural change? The project draws upon methodologies and theories from across the social sciences but especially anthropology, sociology, geography, and science and technology studies (STS). It is funded by a Sapere Aude Starting Grant from the Independent Research Fund Denmark (Danmarks Frie Forskningsråd).