[Recap, Resources & More] DataPub #2 OpenLitterMap, energy conservation & making the world a better place

[Recap, Resources & More] DataPub #2  OpenLitterMap, energy conservation & making the world a better place

Open data and publicly available datasets make so many things possible - check out how our April DataPub guest speakers' projects use its power to fight pollution and advocate for energy conservation.

We recently launched DataPub, our new virtual meetup focused on connecting like-minded open data enthusiasts from around the world, and we just wrapped up our second event. This month’s theme: using open datasets to make the world a better place.

Given the positive responses, we’re looking forward to making this a long-running tradition, even when in-person events return 🎉.

If you attended this session, thank you! If you missed it, we’ve published the recording – and we hope to see you at DataPub #3 later this month.

  • RSVP for Tuesday, May 19
  • If you can’t attend live, register anyway, and we’ll send you a recording, resources, and more.

Check out the below to learn more about our guest speakers, their (amazing) projects, how they’re using open data, and where to get involved or started with open datasets.  

Guest speakers lineup and session summary

Mike Freedman, Timescale co-founder & CTO, warmed us up for an hour of talks, briefly explaining how we (Timescale) believe all data is times-series data. We’ve built TimescaleDB to make it easier for anyone to do interesting, important things with the data they collect - including saving the world.

Like DataPub #1 (see recap here), our live attendees spanned the globe, and this month’s speakers dialed in from Ireland and New Zealand.

Speaker #1: Seán Lynch, OpenLitterMap founder: “Intro to OpenLitterMap & Citizen Science”

Seán started studying and mapping litter in 2008 while working on his Geography dissertation– and, when he was introduced to OpenStreetMap in 2013, it opened his eyes to the world of open data. With his background in geography (including 2 Masters’ in Geographical Information Systems & Remote Sensing and Coastal & Marine Environments), he realized that he could create a system that allowed citizens to report litter from their device and minimize plastic pollution.

OpenLitterMap was born. Through a combination of 10+ years of research, open data APIs, and various technologies (including Vue.js, React Native, and TensorFlow), Seán’s building the “Snapchat of Litter.” His project not only gamifies the litter reporting process, it empowers everyone to upload and access data about local pollution, anywhere around the world.  

As you watch the session, you’ll see how to use OpenLitterMap to view litter by region and litter type distribution by area, identify trends, see data update in real-time, add your own reports, and more.

Throughout, Seán reiterates why open data is important, the role of Citizen Science in reducing pollution (and solving many societal and environmental problems), and his vision for the future of OpenLitterMap.

OpenLitterMap UI, showing a litter "heatmap," filterable by type
OpenLitterMap UI, showing a litter "heatmap," filterable by type

His goals are two-fold: make it fun, easy, and rewarding for people to share data and curate a large, fully open data ecosystem that students, citizens, and governments can use to learn, create policies, and beyond.

Seán’s slides

Speakers #2 & #3: John Gorman and Matt Magoffin, SolarNetwork Foundation co-founders - “Using TimescaleDB for Holistic Distributed Energy Management of the Future”

John and Matt met on a playground in New Zealand 12 years ago, and quickly bonded over being two American expats passionate about sustainability and renewable energy.

Driven by the idea that open-source is the catalyst for change and the need for transparency about energy consumption, they started their open-source project, the SolarNetwork platform, in 2008 – and brought the SolarNetwork Foundation (their non-profit organization) to life in 2017.

While they started by collecting time-series data (they’re long-time TimescaleDB community members and users)* from solar panels and other solar energy sources, they’ve evolved the project to include a rich, curated set of APIs that allow developers, consumers, and organizations to ingest energy-related data ranging from electric car charging stations to wind direction.

John and Matt share how they’ve architected the SolarNetwork platform to allow anyone to start collecting, visualizing, and analyzing energy data from hundreds of sources.

Want to try it yourself? Check out their GitHub repo Developer Guide.

Example energy consumption visualization, by day and week
Example energy consumption visualization, by day and week
Slide showing basic SolarNetwork architecture, including 4 components: cloud server, offline analysis, on-site data acquisition client, and apps using API
John takes us through how they've architected SolarNetwork to ensure accurate data readings from various sources

*For more technical details and example queries, check out Matt’s Community Spotlight: “How SolarNetwork Fuels Energy Conservation with TimescaleDB.”

John & Matt’s slides.

In closing

Thank you to everyone who helped make this yet another successful event, from our speakers Seán Lynch, John Gorman, and Matt Magoffin to the folks who registered (and/or attended live!), and the Timescale team members behind the scenes.

We’re committed to supporting the open data community, and, if you feel the same, or just want to learn what “open data” is all about, join our next session on May 19 (1pm PT/ 4pm ET / 8pm GMT)!

In May, you’ll hear from:

  • Chris Whong, NYC urban planning and data viz pro, who’ll take us through “Taming the MTA’s Unruly Turnstile Data"
  • Jonathan Leek, data architect at St. Louis’ Community Innovation & Action Center, on “Building a City Vacancy Portal in St. Louis.”
  • RSVP.

If you have an open data project that you would like to share with the rest of the community, please reach out to [email protected]

Ingest and query in milliseconds, even at terabyte scale.
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