Tag Archives: Technology

DISCOVER ZOONIVERSE PROJECTS IN A WHOLE NEW WAY

We’re happy to introduce an updated Projects page on Zooniverse, designed to make it easier, faster and more enjoyable to find projects that match your interests.

The new page brings together improved navigation, long-requested features like sorting by language, and a refreshed visual design that aligns with Zooniverse’s evolving front-end experience.

Read on to learn more or go explore the new Projects page at
https://www.zooniverse.org/projects.

Filter Projects by Language

One of the most requested features from our global community is finally here: project filtering by language.

Zooniverse is used by volunteers all over the world. Thanks to our amazing translators, projects are increasingly available in multiple languages. The new language filter makes it much easier to discover projects you can participate in comfortably, whether you’re looking for projects in Japanese, Czech, French, Italian or other languages.

This update helps make Zooniverse more accessible and more welcoming to the diverse community that makes participatory science possible.

Explore Projects by Organisation

The new Projects page also introduces the ability to browse projects by organisation.

On Zooniverse, organisations are research groups, institutions, observatories, universities, museums, and other teams that host and manage projects on the platform. Many organisations – such as Notes from Nature and Rubin Observatory – run multiple projects over time, often connected by shared research goals or themes.

With organisation listings now visible on the Projects page, it’s easier to discover related projects from the same research team, follow the work of organisations you’re interested in and get a clearer sense of the research communities behind the projects.

A Refreshed Look and Feel

Alongside these new features, the Projects page has been visually redesigned to match Zooniverse’s new front-end design system.

The updated layout improves consistent navigation across the platform. Project cards, filters and search tools are more clearly structured, making it simpler to scan, compare, and jump into projects that catch your eye.

This design update reflects ongoing work across Zooniverse to create a more cohesive and intuitive experience for everyone who takes part.

Built for Discovery

Whether you arrive knowing exactly what you’re looking for or just want to browse and see what’s happening across Zooniverse, the new tools are there to help you discover projects that match your interests and curiosity.

Take a look, try out the filters, explore new navigation, and enjoy the updated experience.

Have fun, and happy classifying!

AI Ethics Workshop Series: Update #1

This post is part of our Kavli Foundation-funded series, Ethical Considerations for Machine Learning in Public-Engaged Research. Read our project announcement blog post here.

We’d like to thank everyone who participated in the first of four surveys to help shape the future of AI and public-engaged research. We received over 1000 responses to the first survey, which informed priorities for the first workshop and helped Zooniverse leadership understand some of your interests, concerns, and ideas around this important topic.

Our second survey is launching today, and will be accepting responses through July 18th. We hope you will participate!

In case you missed it, check out the project announcement blog post to learn more about Zooniverse’s effort to develop recommendations for running AI-engaged projects on the Zooniverse platform.

Who is running this study? The Project Director is Dr. Samantha Blickhan, Zooniverse Co-Director and Digital Humanities Lead.

Who is funding this research? This research is funded by The Kavli Foundation.

How can I contact the team? Questions can be addressed to hillary@zooniverse.org or samantha@zooniverse.org

​​Ethical Considerations for Machine Learning in Public-Engaged Research

Highlights

  • With support from the Kavli Foundation, the Zooniverse team is launching a project to help us develop a set of recommendations for running Machine Learning (ML) and Artificial Intelligence (AI)-engaged projects on the Zooniverse platform.
  • The project will bring together subject matter experts, Zooniverse leadership, and platform participants in a series of workshops and working sessions.
  • The project deepens partnerships among Zooniverse and its participant community, as well as the Kavli Institute for Cosmological Physics, UC-Berkeley Kavli Center for Ethics, Science, and the Public, and the SkAI AI Astro Institute. 
  • Zooniverse participants have an opportunity to get involved and follow along in a number of ways!

Developing recommendations for ML/AI projects on Zooniverse

As ML/AI has become more prevalent—now in about ⅓ of Zooniverse projects—it has sparked a range of reactions on the Talk message boards within the participant community, reflecting broader societal discourse. Zooniverse participants have surfaced concerns and insights on issues like ownership, agency, transparency, and trust. It is crucial to address the risks, opportunities, challenges, and broader ethical questions. 

In response, we developed a project to create a set of recommendations for running ML/AI-engaged projects on the Zooniverse platform. In this project we will explore the tensions of integrating ML/AI within online public-engaged research. We hope that these recommendations will also be useful for related fields incorporating ML/AI in public-engaged research processes. 

Collaborative workshops

With funding from The Kavli Foundation, this project will bring together Zooniverse leadership, platform participants, researchers, and experts in topics like communications, ethics, law, and ML/AI in a series of workshops and working sessions. The project deepens partnerships among Zooniverse and its participant community, as well as the Kavli Institute for Cosmological Physics, UC-Berkeley Kavli Center for Ethics, Science, and the Public, and the SkAI AI Astro Institute.

Workshop themes cover topics raised by Zooniverse participants and project research teams as well as gaps in existing knowledge, resources, and guidance. 

  • Workshop 1 (June) will focus on Transparency and Communication Best Practices. It will inform guidelines that will support researchers in effectively communicating with participants when integrating ML/AI into their public-engaged research projects. 
  • Workshop 2 (July) will cover Ethical Approaches to ML/AI. It will invite discussions that explore and identify foundational elements of an ethical approach to ML/AI-focused public-engaged research, addressing risks while leveraging opportunities. 
  • Workshop 3 (August) will focus on Deepening Contextual Understanding. It will expand on the ethical considerations raised in Workshop 2 by examining a matrix of factors including disciplinary differences, task type affordances, and the varied needs of stakeholders (e.g., researchers, participants, platform maintainers). We anticipate that ethical principles may at times conflict within this matrix, making it essential to foster a shared understanding of how, why, and when we will draw from different elements as we develop these recommendations. 
  • Workshop 4 (September) will consider Downstream Data Protection. It will inform recommendations for licensing frameworks to use with public-engaged research data outputs that align with platform values, particularly in relation to projects that incorporate ML/AI. 

Call to action: We want you to participate!

Zooniverse participants have an opportunity to get involved and follow along in a number of ways:

1. Help shape the future of ML/AI and public-engaged research. Options include:

  • Complete four short surveys throughout the duration of the project, starting with this one.
  • Survey responses will be considered as we draft the recommendations for running ML/AI-engaged projects on the Zooniverse platform.
  • We’ll also be reaching out to a subset of our community about participating in the workshops.

2. Follow along:

  • We’ll be posting updates on Talk and on our Zooniverse blog during the process, and project results will be shared broadly.
  • You can opt in to receive project updates by completing the first survey here.


Who is running this study? The Project Director is Dr. Samantha Blickhan, Zooniverse Co-Director and Digital Humanities Lead.

Who is funding this research? This research is funded by the Kavli Foundation.

How can I contact the team? Questions can be addressed to hillary@zooniverse.org or samantha@zooniverse.org

Zooniverse: Live

Yesterday we pushed Zooniverse Live to be… er… live. Zooniverse Live is a constantly updated screen, showing live updates from most of our projects. You’ll see a map displaying the location of recent Zooniverse volunteer’s classifications and a fast-moving list of recently classified images. Zooniverse Live is on display in our Chicago and Oxford offices, but we thought it would be cool to share it with everyone.

At the time this screenshot was taken, the USA was very active and Snapshot Serengeti was busy.
At the time this screenshot was taken, the USA was very active and Snapshot Serengeti was busy.

The Zooniverse is a very busy place these days and we’ve been looking for ways to visualize activity across all the projects. Zooniverse Live is a fairly simple web application. Its backend is written in Clojure (pronounced Closure) and the front end is written in JavaScript using a library for data visualization called D3. The Zooniverse Live server listens to a stream of classification information provided by the Zooniverse projects – via a database technology called Redis. Zooniverse Live then updates its own internal database of classifications on the backend, with the front end periodically asking for updates.

The secret sauce is figuring out where users are classifying from. Zooniverse Live does that using IP Addresses. Everyone connected to the internet is assigned an IP Address by their Internet Service Provider (ISP). While the IP address assigned may change each time a computer connects to the internet, each address is unique and can be tied to a rough geographical area. When Zooniverse projects send their classifications to Zooniverse Live, they include the IP Address the user was classifying from, letting Zooniverse Live do a lookup for the user’s location to plot on the map. The locations obtained in this way are approximate, and in most cases represent your local Internet exchange.

Hopefully you’ll enjoy having a look at Zooniverse Live, and we’d love to hear ideas for other Zooniverse data visualizations you’d like to see.