Related papers: The Building Data Genome Directory -- An open, com…
Smart cities are data driven and collect data from a variety of sources. Certain types of data such as building data is under-represented and remains harder to find despite its value. Our goal is to incentivise the stakeholders to make…
The energy transition has recently experienced a further acceleration. In order to make the integration of renewable energies as cost-effective, secure and sustainable as possible and to develop new paradigms for the energy system, many…
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…
Technology companies have been leading the way to a renewable energy transformation, by investing in renewable energy sources to reduce the carbon footprint of their datacenters. In addition to helping build new solar and wind farms,…
In multicenter biomedical research, integrating data from multiple decentralized sites provides more robust and generalizable findings due to its larger sample size and the ability to account for the between-site heterogeneity. However,…
The proliferation of sensors in buildings has given us access to more data than before. To shepherd this rise in data, many open data lifecycles have been proposed over the past decade. However, many of the proposed lifecycles do not…
The systems that operate the infrastructure of cities have evolved in a fragmented fashion across several generations of technology, causing city utilities and services to operate sub-optimally and limiting the creation of new value-added…
Construction and operating of buildings is one of the major contributors to global greenhouse emissions. With the inefficient usage of energy due to human behavior and manual operation, the energy consumption of buildings is further…
The installation and operation distributed energy resources (DER) and the electrification of the heat supply significantly changes the interaction of the residential building stock with the grid infrastructure. Evaluating the mass…
In the digital twin and building information era, many building automation companies searched for scalable methods to extract and analyze different building data, including Internet of Things (IoT) sensors, actuators, layout sections,…
In energy modelling, open data and open source code can help enhance traceability and reproducibility of model exercises which contribute to facilitate controversial debates and improve policy advice. While the availability of open power…
Nowadays, we have the emergence and abundance of many different data repositories and archival systems for scientific data discovery, use, and analysis. With the burgeoning data sharing platforms available, this study addresses how natural…
Spanning two decades, the Encyclopaedia of DNA Elements (ENCODE) is a collaborative research project that aims to identify all the functional elements in the human and mouse genomes. To best serve the scientific community, all data…
Over the last 20 years, there has been an explosion of genomic data collected for disease association, functional analyses, and other large-scale discoveries. At the same time, there have been revolutions in cloud computing that enable…
In the digital era, user interactions with various resources such as databases, data warehouses, websites, and knowledge graphs (KGs) are increasingly mediated through digital platforms. These interactions leave behind digital traces,…
When data on building features is unavailable, the task of determining how to improve that building in terms of carbon emissions becomes infeasible. We show that from only a set of images, a Large Language Model with appropriate prompt…
Many sensors/meters are deployed in commercial buildings to monitor and optimize their performance. However, because sensor metadata is inconsistent across buildings, software-based solutions are tightly coupled to the sensor metadata…
Building environments are significant sources of global energy consumption. To create energy efficient buildings, the first step is to sense and monitor all the energy-consuming appliances in the buildings and record all the energy…
Energy systems generate vast amounts of data in extremely short time intervals, creating challenges for efficient data management. Traditional data management methods often struggle with scalability and accessibility, limiting their…
High-quality data on existing bicycle infrastructure are a requirement for evidence-based bicycle network planning, which supports a green transition of human mobility. However, this requirement is rarely met: Data from governmental…