Related papers: Planetary computing for data-driven environmental …
Spatial ecological networks are widely used to model interactions between georeferenced biological entities (e.g., populations or communities). The analysis of such data often leads to a two-step approach where groups containing similar…
Uncovering the structure of socioeconomic systems and timely estimation of socioeconomic status are significant for economic development. The understanding of socioeconomic processes provides foundations to quantify global economic…
The rapid growth in demand for HPC systems has led to a rise in carbon footprint, which requires urgent intervention. In this work, we present a comprehensive analysis of the carbon footprint of high-performance computing (HPC) systems,…
Data is the most powerful decision-making tool at our disposal. However, despite the exponentially growing volumes of data generated in the world, putting it to effective use still presents many challenges. Relevant data seems to be never…
Given that observational and numerical climate data are being produced at ever more prodigious rates, increasingly sophisticated and automated analysis techniques have become essential. Deep learning is quickly becoming a standard approach…
Social computing encompasses the mechanisms through which people interact with computational systems: crowdsourcing systems, ranking and recommendation systems, online prediction markets, citizen science projects, and collaboratively edited…
Understanding the causes and consequences of, and devising countermeasures to, global warming is a profoundly complex problem. Network representations are sometimes the only way forward, and sometimes able to reduce the complexity of the…
Government policies aim to address public issues and problems and therefore play a pivotal role in peoples lives. The creation of public policies, however, is complex given the perspective of large and diverse stakeholders involvement,…
Benchmarking, which involves collecting reference datasets and demonstrating method performances, is a requirement for the development of new computational tools, but also becomes a domain of its own to achieve neutral comparisons of…
Policy decisions relevant to the environment rely on tools like dashboards, risk models, and prediction models to provide information and data visualizations that enable decision-makers to make trade-offs. The conventional paradigm of data…
Existing attempts at utility computing revolve around two approaches. The first consists of proprietary solutions involving renting time on dedicated utility computing machines. The second requires the use of heavy, monolithic applications…
As software has become an integral part of scientific workflows, reproducible research practices must take it into account. In what way? Archiving source code is a necessary but insufficient condition. The ability to redeploy software…
The applicability of computational models to the biological world is an active topic of debate. We argue that a useful path forward results from abandoning hard boundaries between categories and adopting an observer-dependent, pragmatic…
Sustainable software ecosystems are difficult to build, and require concerted effort, community norms and collaborations. In science it is especially important to establish communities in which faculty, staff, students and open-source…
Human behavioral patterns and consumption paradigms have emerged as pivotal determinants in environmental degradation and climate change, with quotidian decisions pertaining to transportation, energy utilization, and resource consumption…
The Planetary project develops a general framework - the Planetary system - for social semantic portals that support users in interacting with STEM (Science/Technology/Engineering/Mathematics) documents. Developed from an initial attempt to…
Information Theory provides a fundamental basis for analysis, and for a variety of subsequent methodological approaches, in relation to uncertainty quantification. The transversal character of concepts and derived results justifies its…
Many current challenges involve understanding the complex dynamical interplay between the constituents of systems. Typically, the number of such constituents is high, but only limited data sources on them are available. Conventional…
This paper introduces Experiversum, a lakehouse-based ecosystem that supports the curation, documentation and reproducibility of exploratory experiments. Experiversum enables structured research through iterative data cycles, while…
Documenting the context in which data are collected is an integral part of the scientific research lifecycle. In field-based research, contextual information provides a detailed description of scientific practices and thus enables data…