An open platform for citizen science wildlife monitoring with DIY motion sensing cameras

[mozfest-bot]

[ ID ] 96fbfa61-744b-4876-9780-3263918b5718

[ Submitter's Name ] Pen-Yuan Hsing [ Submitter's Affiliated Organisation ] Durham University

[ Space ] science [ Secondary Space ] badges

[ Format ] demo, fireside, hands-on, format-not-sure

Description

We're developing a platform - MammalWeb (www.MammalWeb.org @MammalWeb) - where communities & schools use motion sensing "camera traps" to photograph local wildlife, upload those images to the website for crowdsourced classification, and collaboratively explore the data. Our web infrastructure is designed to be generalised and deployable by other communities interested in monitoring their own wildlife. This is a break from traditional ecological research that's driven by a few "scientists", and really takes citizen science into the hands of "ordinary" citizens.

We hope to share our experience building this platform, but more importantly start a discussion on (1) effective crowdsourcing of classifying large image datasets, perhaps with the use of Open Badges; (2) how to better develop this web platform; (3) overcoming the high barrier to entry for using motion sensing camera traps - They are expensive and proprietary, and we hope to make an open source version with your help!

Agenda

Start with an introductory talk about what we've done and what we've learned. In addition to getting feedback and criticism, the hope is to talk about about the challenges we face when creating a community-led citizen science web platform.

The session is flexible depending on the group's interest. We will bring working off-the-shelf camera traps for people to investigate, and brainstorm what it would take to develop an open source version that anyone can build. Such a product has great potential for STEM education!

Alternatively, we are interested in the gamification of crowdsourced processing of open data. In this case, the data are large sets of photos (>100,000!) whose classification/processing need to be efficiently crowdsourced. This is a great topic for computer vision enthusiasts or big data geeks.

Finally, we hope to explore how citizens can not only help scientists, but how science can help us be better citizens.

Participants

For just a few participants, we can easily have a round table discussion around the issues with brainstorming and networking. If there are more participants, it might start with a more formal talk followed by questions. This can all include a session where people can interact with camera traps, our web platform, and the accompanying material. If we can identify some people to help us, we'd love to have an open hack session where people can just drop in and think about how to build your own camera trap!

Outcome

After what's hopefully an stimulating discussion/brainstorming session around building a citizen science community and developing a DIY camera trap, we hope to build a group of enthusiastic people who can take the development forward. Other participants would have been introduced to the web platform, and can continue citizen science participation by classifying photos and learning about wildlife. We also hope to establish partnerships with other groups focused on open science, citizen science, hacking/building, and science education.

[thornet]

cc @ileddigital for possibly connections with London Zoo / meercat

[penyuan]

(updated description for programme) Description We're developing a platform - MammalWeb (www.MammalWeb.org @MammalWeb) - where communities & schools use motion sensing "camera traps" to photograph local wildlife, upload those images to the website for crowdsourced classification, and collaboratively explore the data. Our web infrastructure is designed to be generalised and deployable by other communities interested in monitoring their own wildlife. This is a break from traditional ecological research that's driven by a few "scientists", and really takes citizen science into the hands of "ordinary" citizens. We hope to share our experience building this platform, but more importantly start a discussion on (1) effective crowdsourcing of classifying large image datasets, perhaps with the use of Open Badges; (2) comparing different citizen science platforms; (3) what it means to be a citizen scientist; (4) and what we wish for these platforms so they can help us be better participating citizens. Agenda Start with an introductory talk about what we've done and what we've learned. In addition to getting feedback and criticism, the hope is to talk about about the challenges we face when creating a community-led citizen science web platform. The session is flexible depending on participants’ interest. We will bring working off-the-shelf camera traps for people to investigate, and can brainstorm what it would take to develop an open source version that anyone can build. Such a product has great potential for STEM education! Most importantly, we are interested in what citizen science web platforms can do to help everyone to not only help scientists process data, but also for the science to help all of us become better citizens. So there will be lots of open discussion, and at the end we can hope to produce a wish list for what citizen science platforms can do in the future. Participants For just a few participants, we can easily have a round table discussion around the issues with brainstorming and networking. If there are more participants, it might start with a more formal talk followed by questions. This can all include a session where people can interact with camera traps, our web platform and others, and the accompanying material. If we can identify some people to help us, we'd love to have an open hack session later where people can just drop in and think about how to build your own camera trap! Outcome After what's hopefully a stimulating discussion/brainstorming session around building a citizen science community, participants would have been introduced to different citizen science web platforms, and can continue citizen science participation by classifying photos and learning about wildlife. We also hope to establish partnerships with other groups focused on open science, citizen science, hacking/building, and science education.

[KirstieJane]

@arlissc - did you catch this updated description yet? Want me to send an email?

Edit: I just looked in your sheet - you did! Whoooo hooooo :tada:

[penyuan]

Sorry can I add a sentence to the end of the main Description?

Since we'll be exploring citizen science web platforms, please bring your laptop if you can!