Jump to content

Visual Analytics for Sustainability and Climate Change/Alex Stinson

Add links
From Meta, a Wikimedia project coordination wiki
VIZWP Project Activities Community Articles Requirements Tool DMP Report Credits

Interview with Alex Stinson by Iolanda Pensa and Chiara Somajni, 27 January 2026, CC BY 4.0.

Alex Stinson is a digital knowledge strategist based in Uruguay who works independently at the intersection of climate action, artificial intelligence, data, and open knowledge. His current work includes collaborations with the Data Uruguay collective, participation in the Work on Climate community, and advisory roles across climate, AI, and digital public infrastructure initiatives. Previously, he served as Lead Program Strategist at the Wikimedia Foundation, where he led international programmes across Wikipedia, Wikidata, Wikimedia Commons, and other Wikimedia projects, including WikiForHumanRights and 1Lib1Ref. Before joining the Foundation, he was a digital humanist at Kansas State University, building collaborations among researchers, educators, libraries, and cultural institutions. A long-time Wikimedia volunteer known as Sadads, his work focuses on community building, open knowledge ecosystems, and applying data and digital technologies to strengthen climate action, civic participation, and knowledge equity.

Notes from the interview

notes to be edited!


links shared:

https://www.mediawiki.org/wiki/Translation_suggestions:_Topic-based_%26_Community-defined_lists

https://www.mediawiki.org/wiki/Translation_suggestions:_Topic-based_%26_Community-defined_lists/How_to_use_the_features

https://en.wikipedia.org/wiki/Bar_(food)

https://bambots.brucemyers.com/cwb/bycat/Agriculture.html


Suggested elements to visualize

  • Citations older than 5 years

Warning! Articles with old citations (clear signals)

  • Missing sections (somethings new contributors have difficulties to find). Important aspect to identify gaps
  • include articles not about science but broader. The centre of the topic is where everyone works but the edges are the most important ones.
  • considering how articles are connected (page views)
  • pageviews are reducing. we need to consider other criteria. comparing what the internet knows about topics
  • visualisations are changing (and reducing)
  • persona - consider who are you working for. people with 200 edits have lots of difficulties.

Worked for WMF Active in the Climate change wikiproject.


Wikiprojects Collaboration Campaign Edit-a-thon List of people List of articles Series of actions

Writing articles will not be the focus With AI

Important Validating the quality of the information How it is sources Good organisation, bad organisation

Estracting a list of a wikipage. API  ?? check?? Active curation https://www.mediawiki.org/wiki/Translation_suggestions:_Topic-based_%26_Community-defined_lists

ttps://www.mediawiki.org/wiki/Translation_suggestions:_Topic-based_%26_Community-defined_lists/How_to_use_the_features


What is interesting for humans Identify tasks - meaningful Identify gaps We have signs

  • Citations older than 5 years

Warning! Articles with old citations (clear signals)

  • Missing sections (somethings new contributors have difficulties to find). Important aspect to identify gaps

People are looking for hints. What am I missing.

Structure diagnostics. How do i fill that gap using AI 1. use AI and the visualisation 2. show me the four articles that are stubs, about humans/whatever

For climate change we need the action. help governments navigating the policies furing crisis... Navigate to energy, agriculture (SDG topics).... connected to climate. How to associate differnt topics to climate change. Es. corn (es. how to adapt corn).


Climate change is outside the science: policies, solutions, effects of climate change (aspects which are more vague - extansions - edges) Edges can inspire people. The centre of the topic is where everyone works but the edges are the most important ones.

Geographical relevant content. Relevant to people who use that language of Wikipedia.

Articles which are over-represented and guide you

[iolanda] working on connections combined with visualisations

+ AI access, less human: we will need other signals to track interest pageviews are reducing. we need to consider other criteria. comparing what the internet knows about topics (indicators to check, looking for interesting signals to idenfity gaps, overlaps, what is different and similar, what information or ) 

* stress-testing using different personae (student, politician...) to identify the quality of the article using AI - humanising the gaps. anticipating human needs
  • breakopen the scope of the research: provinding access to a larger knowledge

What i should do next. For some people is difficult to understand what to do. maybe people with 200 edits. Not experts. Consider the user story.

Wikiproject. The organic discovery is broken. https://en.wikipedia.org/wiki/Wikipedia:WikiProject_Climate_change/Small_to_medium_tasks

I target "mid-carreer" 200-300 and people interested in quality articles 5000. And suggest them what they can do

Suggested requirements

[edit]
  • Citations older than 5 years (Warning! Articles with old citations: this is a clear quality signal)
  • Include articles not about science but broader: the centre of the topic is where everyone works but the edges are the most important ones.
  • Consider how articles are connected (via pageviews)
  • Pageviews are declining: we need to consider other criteria.
  • Comparing what the internet knows about topics
  • Persona - consider who you are working for: people with 200 edits have lots of difficulties.

Gaps

[edit]
  • Missing sections (somethings new contributors have difficulties to find). This helps identify gaps.
Retrieved from "https://meta.wikimedia.org/w/index.php?title=Visual_Analytics_for_Sustainability_and_Climate_Change/Alex_Stinson&oldid=30852118"