Hello! We are a group of researchers from HCDE. We are looking to recruit participants with experience designing data visualizations of race and other demographic data for a study on the impacts of the positionality, beliefs and biases of visualization designers on their design process and the visualizations they create.

If you are interested, please take a few minutes to complete our screening survey: https://uwashington.qualtrics.com/jfe/form/SV_55QbBhwtvyR41hk. If you meet the eligibility criteria, we’ll contact you with additional information. Please share this with folks who might be interested! If you have any questions, please feel free to reach out! Thank you!

As data visualization enthusiasts, we understand the importance of having access to high-quality, reliable data sources. I recently stumbled upon a platform called sCompute that I believe could have interesting implications for the data visualization community.

sCompute is a decentralized marketplace that connects data providers with data consumers, facilitating the exchange of high-quality datasets across various domains. The platform places a strong emphasis on data quality, integrity, and ethical sourcing.

I wrote an article that explores the potential benefits of using sCompute for sourcing data for visualization projects:

• Access to a wide range of high-quality datasets from verified providers
• Decentralized approach to data sharing and monetization
• Emphasis on data quality and integrity, crucial for creating accurate and meaningful visualizations
• Potential for collaboration and data sharing within the data visualization community

While the article primarily focuses on the machine learning applications of sCompute, I believe the platform's focus on high-quality data sourcing is equally relevant to data visualization.

Article link

I'm curious to hear your thoughts on platforms like sCompute and their potential impact on the way we source and utilize data for our visualization projects. Have you used similar platforms before? How do you think access to high-quality, diverse datasets could enhance the insights we derive from data visualizations?

I'd love to start a discussion on how we can leverage platforms like sCompute to improve the quality and variety of the data we use in our data visualization work, and how this could lead to more meaningful and impactful visual stories.

Please share your experiences, insights, and examples of how high-quality data has made a difference in your data visualization projects.

Please explain me what is going wrong with my code. The correlation not showing in each cells of the heatmap even I already had "annot"

Hello everyone,

I'm developing a dashboard to visualize data from multiple IoT sensors, each measuring different phenomena (e.g., temperature in Celsius, humidity in percentage, Co2 in ppm). I am exploring ways to represent this diverse data on a single chart without using multiple y-axes, as it can get overly complicated when more than two sensors are involved.

I'm considering using normalization to scale all measurements to a common percentage range (0-100%). Here’s a particular challenge I am facing: When a user specifies a preferred unit of measurement for the y-axis on the chart, should the system restrict sensor selection to only those sensors operating within the specified unit, thereby maintaining direct comparability of data? Alternatively, should the system employ a normalization approach, converting all selected sensor outputs to a common scale (e.g., 0-100%), thus allowing the inclusion of diverse sensor types regardless of their native units?

I'm looking for practical advice on how to manage this in a way that is both straightforward for users and scientifically correct. How do you usually handle this situation? I’d greatly appreciate any insights, experiences, or recommendations you could share!

I can't seem to find a non-coder-friendly tool that allows me to link image URLs to each data point and create an intuitive grouped chart like a treemap or bubble chart or something of the like. Do any of you know of a tool like this?

Thanks.

I'm trying to find a data vis site or tool that I saw once probably 3-5 years ago and I can't figure out how to locate it. Here's what I remember: The data tool would live update and the visualization basically looked like a bunch of dots going crazy (live scatter plot I assume) around a screen because the data was either live or animating out data. I know this is really vague but if you have any idea what I'm talking about I would greatly appreciate being pointed in the right direction. Thanks!

Hi !

I'm currently working on a personal project, where i'm keeping track of where I'm sleeping throughout the years (I've started in 2021 and since then, I've slept in about thirty different places and four different countries).

To visualize this data, I thought about placing dots on the locations with diameters proportional to the number of nights, and coded it in Python, but it doesnt look as good as I'd hoped : zoomed out, the dots are barely noticeable, and zooming in is not that interesting since only one location is visible at a time.

For the sake of privacy I won't show you the map, but I'd love to hear if you have any advice or ideas to make this data visualization more interesting.

Thank you for your help !

I want to compare big LLM models by their parameters size and launch date. It can help us understand:

1. How aggressively company is pushing models and what's the parameter-wise difference?
2. Who is a clear winner in terms of most & first model launch ?!

I lack visualization skills, so any help would be greatly appreciated.

https://preview.redd.it/c45yuc474suc1.png?width=1434&format=png&auto=webp&s=af3a720679574299e94870bb086eaad6650c5fd6

Hi everyone,

I am currently taking first semester of data analytics (so basically I am new to Python).

I got an assignment csv file which includes lots of countries in the data frame, I wanna examine the trend in this data frame (it's about data visualization) However the number of countries variables made me feel overwhelm and do not know where to start.

So I need you guys recommendation on this. Thankkk youuu so muchhh!

Hey r/visualization! I'm curious to know what the most interesting infographic you've ever come across is.

What made it stand out to you? Was it the design, the data, or something else?

Hi guys, I am amazed by this visualization from NASA. It shows lots of 3D models, textures, animations and interactions. I assume they likely contracted someone to program the whole thing from ground up. Do you know any tools that can help create something similar? Thank you.

https://science.nasa.gov/eclipses/future-eclipses/eclipse-2024/

https://preview.redd.it/u5484g4k9gtc1.png?width=1194&format=png&auto=webp&s=dfb58be4dcdcab57da21fbe652bd72ac41c97360

They have lots of other visualizations like this:

https://eyes.nasa.gov/apps/mars2020/#/home

https://eyes.nasa.gov/apps/asteroids/#/story/asteroids_missions?slide=slide_2

Hi folks,

I'm back again with another track from my upcoming LP Microcosms. This track features a collection of field recordings and electro-magnetic frequencies I gathered from Mainstage East at Leeds Festival. One of my jobs outside of performing is building festivals/rigging, so I took my field recording equipment to Leeds festivals, sampling hundreds of sounds from big amp racks, to TV walls etc. Once I processed all of these sounds, I then put them into my modular synthesiser and created what you're listening to today at the MONOM studios in Berlin. Creating this work on a 57 speaker system was an amazing experience, and these bodiless sounds really came into their own.

I'd love to hear from you; let me know what you like (or don't) about this work! If you like this work, please consider subscribing to my Youtube channel. Many thanks.

R-9A Arrowhead MK. II [Youtube]

https://preview.redd.it/3julpxi5f1tc1.png?width=1920&format=png&auto=webp&s=4a005cb25c9377ad0305f538217a11d3d2929f09

Any guesses on which Graph Library might be at use here?

​

https://preview.redd.it/f9czdio6dzsc1.png?width=3974&format=png&auto=webp&s=2bae3b2740e1b1791d5035a50b0088800a97e821