DIGIPHYT: a qualitative inquiry into digital agriculture’s sustainability claims 

Digital Agriculture aims to transform how we grow food. By collecting and analyzing real-time data on plant life, these innovations promise to help farmers make more informed decisions about water usage, fertilizers, and pesticides, ultimately leading to more sustainable farming practices. But how are these promises translating into reality? Usually answered through quantitative means, DIGIPHYT takes a different approach to this question. The project develops an in-depth qualitative research that explores the relationship between sustainability claims and sustainable practices in technology-assisted plant cultivation. Using ethnographic and video-based methods, I observe specific digital agriculture innovations in action by documenting the daily activities of both developers and users, aiming to understand how humans, plants, and digital devices interact to create sustainable agricultural practices. To that effect, I aim to move from claims to practices - I take sustainability promises seriously and examine how participants define sustainability, as well as their efforts to develop sustainable practices in real-world settings. In studying those practices, I also aim to pay attention to all contributors , by documenting the active roles of often-overlooked non-human participants—plants and devices—in efforts to create sustainable outcomes. More info at mylt@itu.dk.

Superblockify

Modern urban planning has been shaped by a car-centric vision, which is reliant on fossil fuels and fosters health-related and socio-economic issues, making transportation within cities unsustainable. ‘Superblocks’, a set of adjacent urban blocks where through-traffic and high-speed driving are prevented, are one way of reducing car use and its impact. To assist the urban planning process, we’ve designed Superblockify, a Python package for partitioning an urban street network into Superblock-like neighborhoods and for visualizing and analyzing the partition results. It helps urban planners develop a city-wide or district-wide vision of where traffic could be reduced or removed, and is open and modular, allowing anyone to tailor the partition algorithm to specific needs and data.

Green Futures of Silicon Savannah: Navigating Sustainability, Development and Profit in the Global Agri-Tech Assemblage

Agriculture presently faces two major challenges: it contributes to climate change, producing as much as a third of all global CO2 emissions, while simultaneously being affected by it and having to feed up to 10 billion people by 2050. Increasingly, digitalization of agricultural technology (agri-tech) has been offered as a solution. This project explores the global agri-tech assemblage with a particular focus on Kenyan startups, addressing the tensions in global North-South interactions and between growth, development, and sustainability. It seeks to understand how various actors within this assemblage perceive agency, articulate climate change challenges, and envision sociotechnical futures, while reconciling climate solutions with narratives like ‘ICT for climate’, ‘ICT for development’ or ‘ICT for venture capital’. As such, this project helps us understand the role of dominant technoscientific narratives in a postcolonial context and the moral economies influencing technological development. For more information and questions, please reach out to tchw@itu.dk.

Decoupling IT? A Global Comparative Ethnography of the Role of IT in the Mitigation of the Climate Crisis

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. Read more on the project's blog page here.

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.

Democratic Innovations in a Green Transition (DIGT)

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.

Amazônia 4.0

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. 

Part of this project develops a method to order the growth of a bicycle network plan. Many cities worldwide are currently announcing extensive bicycle network development plans, typically outlining hundreds of kilometers of new links to be built over several years. However, the links in most of these plans are not ordered, and it is unclear how to prioritize them to reach a functional network as fast as possible. This project instead develops an automatized method that optimally prioritizes all links in a given bicycle network plan, yielding a time-ordered investment plan for the selected metric, with different strategies available in the modular framework to choose from. Besides that, the project aims to contribute to a growing debate on the ethics of translating critical qualitative goals into quantitative metrics to move beyond a utilitarian set of metrics to a wider understanding of human mobilities within Urban Data Science.

Making Sense of Urban Air

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’.

Resource-Aware Data Systems

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)

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).