Tootfinder

The Jive Verification System and its Transformative Impact on Weather Forecasting Operations
Nicholas Loveday, Deryn Griffiths, Tennessee Leeuwenburg, Robert Taggart, Thomas C. Pagano, George Cheng, Kevin Plastow, Elizabeth Ebert, Cassandra Templeton, Maree Carroll, Mohammadreza Khanarmuei, Isha Nagpal
https://arxiv.org/abs/2404…

The Jive Verification System and its Transformative Impact on Weather Forecasting Operations
Forecast verification is critical for continuous improvement in meteorological organizations. The Jive verification system was originally developed to assess the accuracy of public weather forecasts issued by the Australian Bureau of Meteorology. It started as a research project in 2015 and gradually evolved into the operational verification system that went live in 2022. The system includes daily verification dashboards for forecasters to visualize recent forecast performance and "Evidence Tar…

🙀 Data Analysis Doesn't Have to Be Scary! 📊
Are you one of those people who breaks out in a cold sweat at the mere mention of Pivot Tables? I get it! They can seem super intimidating at first. But trust me, they're powerful tools that can transform the way you work with data.
That's why I made this new video tutorial all about breaking down Pivot Tables and making them approachable. In it, I'll guide you step-by-step through creating your own interactive Sales D…

Towards Model-Driven Dashboard Generation for Systems-of-Systems
Maria Teresa Rossi, Alessandro Tundo, Leonardo Mariani
https://arxiv.org/abs/2402.15257 ht…

Towards Model-Driven Dashboard Generation for Systems-of-Systems
Configuring and evolving dashboards in complex and large-scale Systems-of-Systems (SoS) can be an expensive and cumbersome task due to the many Key Performance Indicators (KPIs) that are usually collected and have to be arranged in a number of visualizations. Unfortunately, setting up dashboards is still a largely manual and error-prone task requiring extensive human intervention. This short paper describes emerging results about the definition of a model-driven technology-agnostic approach t…

Integrating urban digital twins with cloud-based geospatial dashboards for coastal resilience planning: A case study in Florida
Changjie Chen, Yu Han, Andrea Galinski, Christian Calle, Jeffery Carney, Xinyue Ye, Cees van Westen
https://arxiv.org/abs/2403.18188

Integrating urban digital twins with cloud-based geospatial dashboards for coastal resilience planning: A case study in Florida
Coastal communities are confronted with a growing incidence of climate-induced flooding, necessitating adaptation measures for resilience. In this paper, we introduce a framework that integrates an urban digital twin with a geospatial dashboard to allow visualization of the vulnerabilities within critical infrastructure across a range of spatial and temporal scales. The synergy between these two technologies fosters heightened community awareness about increased flood risks to establish a unifi…

This https://arxiv.org/abs/2302.00325 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

Privacy Dashboards for Citizens and corresponding GDPR Services for Small Data Holders: A Literature Review
Citizens have gained many rights with the GDPR, e.g. the right to get a copy of their personal data. In practice, however, this is fraught with problems for citizens and small data holders. We present a literature review on solutions promising relief in the form of privacy dashboards for citizens and GDPR services for small data holders. Covered topics are analyzed, categorized and compared. This is ought to be a step towards both enabling citizens to exercise their GDPR rights and supporting s…

#AGPL vs #SSPL
AGPL, add the requirement to include mgmt/monitoring/backup/storage/APIs/UIs such that you could run the service (e.g., other internal APIs or dashboards don't leak through in how AGPL is defined - only that library's API)
or, SSPL, but get rid of the "you aren't allowed to run a competing business" requirement (e.g., SSPL isn't truly open)
AGPL but more
SSPL but less

Wait wait wait, now I’m finally getting around to learning #Streamlit, and that week #Observable drops #ObservableFramework as a neat new way to generating data-driven dashboards? 😲

me looking at most dashboards:
https://www.youtube.com/watch?v=ncGHiVKJh0Y
"Everything you are doing is bad. I want you to know this."

From Keywords to Structured Summaries: Streamlining Scholarly Knowledge Access
Mahsa Shamsabadi, Jennifer D'Souza
https://arxiv.org/abs/2402.14622 http…

From Keywords to Structured Summaries: Streamlining Scholarly Knowledge Access
This short paper highlights the growing importance of information retrieval (IR) engines in the scientific community, addressing the inefficiency of traditional keyword-based search engines due to the rising volume of publications. The proposed solution involves structured records, underpinning advanced information technology (IT) tools, including visualization dashboards, to revolutionize how researchers access and filter articles, replacing the traditional text-heavy approach. This vision is …

Introducing ASP.NET Core metrics and Grafana dashboards in .NET 8
#dotnet #aspnetcore #grafana #aspire…

This https://arxiv.org/abs/2402.08812 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

Intelligent Canvas: Enabling Design-Like Exploratory Visual Data Analysis with Generative AI through Rapid Prototyping, Iteration and Curation
Complex data analysis inherently seeks unexpected insights through exploratory visual analysis methods, transcending logical, step-by-step processing. However, existing interfaces such as notebooks and dashboards have limitations in exploration and comparison for visual data analysis. Addressing these limitations, we introduce a "design-like" intelligent canvas environment integrating generative AI into data analysis, offering rapid prototyping, iteration, and comparative visualization manageme…

This https://arxiv.org/abs/2402.08812 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

Intelligent Canvas: Enabling Design-Like Exploratory Visual Data Analysis through Rapid Prototyping, Iteration and Curation
Complex data analysis inherently seeks unexpected insights through exploratory \re{visual analysis} methods, transcending logical, step-by-step processing. However, \re{existing interfaces such as notebooks and dashboards have limitations in exploration and comparison for visual data analysis}. Addressing these limitations, we introduce a "design-like" intelligent canvas environment integrating generative AI into data analysis, offering rapid prototyping, iteration, and comparative visualizatio…

Intelligent Canvas: Enabling Design-Like Exploratory Visual Data Analysis through Rapid Prototyping, Iteration and Curation
Zijian Ding, Joel Chan
https://arxiv.org/abs/2402.08812

Intelligent Canvas: Enabling Design-Like Exploratory Visual Data Analysis through Rapid Prototyping, Iteration and Curation
Complex data analysis inherently seeks unexpected insights through exploratory \re{visual analysis} methods, transcending logical, step-by-step processing. However, \re{existing interfaces such as notebooks and dashboards have limitations in exploration and comparison for visual data analysis}. Addressing these limitations, we introduce a "design-like" intelligent canvas environment integrating generative AI into data analysis, offering rapid prototyping, iteration, and comparative visualizatio…