Category: Crowdsourcing and design for participation

'Resonating with different frequencies' – notes for a talk on the Le Show archive

I met dr. rosa a. eberly, associate professor of rhetoric at Pennsylvania State University when she took my and Thomas Padilla's 'Collections as Data' course at the HILT summer school in 2018. When she got in touch to ask if I could contribute to a workshop on Harry Shearer's Le Show archive, of course I said yes! That event became the CAS 2023 Summer Symposium on Harry Shearer's "Le Show".

My slides for 'Resonating with different frequencies… Thoughts on public humanities through crowdsourcing in a ChatGPT world' are online at Zenodo. My planned talk notes are below.

Banner from Harry Shearer's Le Show archive, featuring a photo of Shearer. Text says 'Vogue magazine describes Le Show as "wildly clever, iconoclastic stew of talk, music, political commentary, readings of inadvertently funny public documents or trade magazines and scripted skits."'

Opening – I’m sorry I can’t be in the room today, not least because the programme lists so many interesting talks.

Today I wanted to think about the different ways that public humanities work through crowdsourcing still has a place in an AI-obsessed world… what happens if we think about different ways of ‘listening’ to an audio archive like Le Show, by people, by machines, and by people and machines in combination?

What visions can we create for a future in which people and machines tune into different frequencies, each doing what they do best?

Overview

  • My work in crowdsourcing / data science in GLAMs
  • What can machines do?
  • The Le Show archive (as described by Rosa)
  • Why do we still need people listening to Le Show and other audio archives?

My current challenge is working out the role of crowdsourcing when 'AI can do it all'…

Of course AI can't, but we need to articulate what people and what machines can do so that we can set up systems that align with our values.

If we leave it to the commercial sector and pure software guys, there’s a risk that people are regarded as part of the machine; or are replaced by AI rather than aided by AI.

[Then I did a general 'crowdsourcing and data science in cultural heritage / British Library / Living with Machines' bit]

Given developments in 'AI' (machine learning)… What can AI/data science do for audio?

  • Transcribe speech for text-based search, methods
  • Detect some concepts, entities, emotions –> metadata for findability
  • Support 'distant reading'

–Shifts, motifs, patterns over time

–Collapse hours, years – take time out of the equation

  • Machine listening?

–Use 'similarity' to find sonic (not text) matches?

[Description of the BBC World Archive experiments c 2012 combining crowdsourcing with early machine learning https://www.bbc.co.uk/blogs/researchanddevelopment/2012/11/the-world-service-archive-prot.shtml]

Screenshot of Le Show website

Le Show (as described by Rosa)

  • A  massive 'portal' of 'conceptual and sonic hyperlinks to late-20th- and early-21st-century news and culture'
  • A 'polyphonic cornucopia of words and characters, lyrics and arguments, fact and folly'
  • 'resistant to datafication'
  • With koine topoi – issues of common or public concern 

'Harry Shearer is a portal: Learn one thing from Le Show, and you’ll quickly learn half a dozen more by logical consequence'

dr. rosa a. eberly

(Le Show reminds me of a time when news was designed to inform more than enrage.)

Why let machines have all the fun?

People can hear a richer range of emotions, topics and references, recognise impersonations and characters -> better metadata, findability

What can’t machines do? Software might be able to transcribe speech with pretty high accuracy, but it can't (reliably)… recognise humour, sarcasm, rhetorical flourishes, impersonations and characters – all the wonderful characteristics of the Le Show archive that Rosa described in her opening remarks yesterday. A lot of emotions aren’t covered in the ‘big 8’ that software tries to detect.

Software can recognise some subjects that e.g. have Wikipedia entries, but it’d also miss so much of what people can hear.

So, people can do a better job of telling us what's in the archive than computers can. Together, people and computers can help make specific moments more findable, creates metadata that could be used to visualise links between shows – by topic, by tone, music and more.

A 1950s black and white photo of a man knitting while relaxing in an armchair
Jay Yoder with His Knitting

Could access to history in the raw, 'koine topoi' be a super-power?

Individual learning via crowdsourcing contributes to an informed, literate society

It's not all about the data. Crowdsourcing creates a platform and a reason for engagement. Your work helps others, but it also helps you.

I've shown some of my work with objects from the history of astronomy; playbills for 19th c British theatre performances, and most recently, newspaper articles from the long 19th c.

Through this work, I've come to believe that giving people access to original historical sources is one of the most important ways we can contribute to an informed, literate society.

A society that understands where we've come from, and what that means for where we're going.

A society that is less likely to fall for predictions of AI dooms or AI fantasies, because they've seen tech hype before.

A society that is less likely to believe that 'AI might take your job' because they know that the executives behind the curtain are the ones deciding whether AI helps workers or 'replaces' them.

I've worried about whether volunteers would be motivated to help transcribe audio or text, classify or tag images, when 'AI can do it'. But then I remembered that people still knit jumpers (sweaters) when they can buy them far more quickly and cheaply.

So, crowdsourcing still has a place. The trick is to find ways for 'AI' to aid people, not replace them. To figure out the boring bits and the bits that software is great at; so that people can spend more time on the fun bits.

Harry Shearer's ability to turn something into a topic, 'news of microplastics', of bees', is something of a super power. To amplify those messages is another gift, one the public can create by and for themselves.

National approaches to crowdsourcing / citizen science?

This is a 'work in progress' post that I hope to add to as I gather information about national portals for crowdsourcing / citizen science / citizen history and other forms of voluntary digital / online participation.

While portals like SciStarter, Crowds4U and platforms like Zooniverse, FromThePage, HistoryPin etc are a great way to search across projects for something that matches your interests, I'm interested in the growth of national portals or indexes to projects (they might also be called 'project finders'). It's not so much the sites themselves that interest me as the underlying networks of regional communities of practice, national or regional infrastructure and other signs of national support that they might variously reflect or help create. If you're interested in specific projects outside the UK-US/English-language bubble, check out Crowdsourcing the world's heritage. I've also shared a 2015 list of 'participatory digital heritage sites' that includes many crowdsourcing sites.

If you know of a national portal or umbrella organisation for crowdsourcing, please drop me a line! Last updated: Feb 7, 2023.

Austria

Jan Smeddinck emailed to share the LBG Open Innovation in Science Center https://ois.lbg.ac.at/

Brazil

Lesandro Ponciano nominated 'Civis, which is the Brazilian Citizen Science platform. The link is https://civis.ibict.br/ Civis was built by using the same software developed by Ibercivis in Spain for the eu-citizen.science platform. Civis was launched in 2022 – the event (in Portuguese) is recorded on YouTube at
https://www.youtube.com/live/_nPqmcq0gos '

Canada

The Canadian Citizen Science portal

France

This post was inspired by the apparently coordinated approach in France. The Archives nationales participatives site has 'Projets collaboratifs de transcriptions, annotations et indexations' – that is, participatory national archives with collaborative transcription, annotation and indexing projects.

They also have Le réseau Particip-Arc, a 'network of actors committed to participatory science in the fields of culture', supported by the Ministry of Culture and coordinated by the National Museum of Natural History.

European Union

EU-citizen.science is a 'platform for sharing citizen science projects, resources, tools, training and much more'.

Germany / German-language projects

The German / German-language citizen science portal

Netherlands

Alastair Dunning pointed to the Citizen Science network, run by @CitSciLab (Margaret Gold).

Norway

Agata Bochynska said, 'Norway has recently formed a national network for citizen science that’s coordinated by Research Council of Norway' – Nasjonalt nettverk for folkeforskning (folkeforskning translates as 'folk research' according to Google).

Scotland

The Scottish Citizen Science portal

Slovenia

https://citizenscience.si/ lists current and completed citizen science projects in Slovenia, infrastructure available to support projects, and events and other activities. Hat tip Mitja V. Iskrić on mastodon.

Sweden

David Haskiya reports: 'medborgarforskning.se/ Provides an intro to citizen science, a catalogue of Swedish projects, etc. Seems to be part of an EU-network of such sites. Summary in English here https://medborgarforskning.se/eng/'

A Swedish national hub for everyone interested in citizen science (medborgarforskning). The project was funded by Vinnova – Sweden’s innovation agency, the University of Gothenburg, the Swedish University of Agricultural Sciences, Umeå University.

United Kingdom

gov.uk lists some volunteering portals but they don't make it easy to find online-only opportunities.

United Nations

https://app.unv.org/ lists online and on-site (i.e. in-person) opportunities around the world, although some of them might stretch the definition of 'voluntary roles'.

Wales

Rita Singer reports: 'In Wales, we have the People's Collection, which functions as a citizen archive of Wales' history and heritage.' https://www.peoplescollection.wales/

Crowdsourcing as connection: a constant star over a sea of change / Établir des connexions: un invariant des projets de crowdsourcing

As I'm speaking today at an event that's mostly in French, I'm sharing my slides outline so it can be viewed at leisure, or copy-and-pasted into a translation tool like Google Translate.

Colloque de clôture du projet Testaments de Poilus, Les Archives nationales de France, 25 Novembre 2022

Crowdsourcing as connection: a constant star over a sea of change, Mia Ridge, British Library

GLAM values as a guiding star

(Or, how will AI change crowdsourcing?) My argument is that technology is changing rapidly around us, but our skills in connecting people and collections are as relevant as ever:

  • Crowdsourcing connects people and collections
  • AI is changing GLAM work
  • But the values we express through crowdsourcing can light the way forward

(GLAM – galleries, libraries, archives and museums)

A sea of change

AI-based tools can now do many crowdsourced tasks:

  • Transcribe audio; typed and handwritten text
  • Classify / label images and text – objects, concepts, 'emotions'

AI-based tools can also generate new images, text

  • Deep fakes, emerging formats – collecting and preservation challenges

AI is still work-in-progress

Automatic transcription, translation failure from this morning: 'the encephalogram is no longer the mother of weeks'

  • Results have many biases; cannot be used alone
  • White, Western, 21st century view
  • Carbon footprint
  • Expertise and resources required
  • Not easily integrated with GLAM workflows

Why bother with crowdsourcing if AI will soon be 'good enough'?

The elephant in the room; been on my mind for a couple of years now

The rise of AI means we have to think about the role of crowdsourcing in cultural heritage. Why bother if software can do it all?

Crowdsourcing brings collections to life

  • Close, engaged attention to 'obscure' collection items
  • Opportunities for lifelong learning; historical and scientific literacy
  • Gathers diverse perspectives, knowledge

Crowdsourcing as connection

Crowdsourcing in GLAMs is valuable in part because it creates connections around people and collections

  • Between volunteers and staff
  • Between people and collections
  • Between collections

Examples from the British Library

In the Spotlight: designing for productivity and engagement

Living with Machines: designing crowdsourcing projects in collaboration with data scientists that attempt to both engage the public with our research and generate research datasets. Participant comments and questions inspired new tasks, shaped our work.

How do we follow the star?

Bringing 'crowdsourcing as connection' into work with AI

Valuing 'crowdsourcing as connection'

  • Efficiency isn't everything. Participation is part of our mission
  • Help technologists and researchers understand the value in connecting people with collections
  • Develop mutual understanding of different types of data – editions, enhancement, transcription, annotation
  • Perfection isn't everything – help GLAM staff define 'data quality' in different contexts
  • Where is imperfect, AI data at scale more useful than perfect but limited data?
  • 'réinjectée' – when, where, and how?
  • How does crowdsourcing, AI change work for staff?
  • How do we integrate data from different sources (AI, crowdsourcing, cataloguers), at different scales, into coherent systems?
  • How do interfaces show data provenance, confidence?

Transforming access, discovery, use

  • A single digitised item can be infinitely linked to places, people, concepts – how does this change 'discovery'?
  • What other user needs can we meet through a combination of AI, better data systems and public participation?

Merci de votre attention!

Pour en savoir plus: https://bl.uk/digital https://livingwithmachines.ac.uk

Essayez notre activité de crowdsourcing: http://bit.ly/LivingWithMachines

Nous attendons vos questions: digitalresearch@bl.uk

Screenshot of images generated by AI, showing variations on dark blue or green seas and shining stars
Versions of image generation for the text 'a bright star over the sea'
Presenting at Les Archives nationales de France, Paris, from home

Talk notes for #AIUK on the British Library and crowdsourcing

I had a strict five minute slot for my talk in the panel on 'Reimagining the past with AI' at Turing's AI UK event today, so wrote out my notes and thought I might as well share them…

The panel blurb was 'The past shapes the present and influences the future, but the historical record isn’t straightforward, and neither are its digital representations. Join the AHRC project Living with Machines and friends on their journey to reimagine the past through AI and data science and the challenges and opportunities within.' It was a delight to chat with Dave Beavan, Mariona Coll Ardanuy, Melodee Wood and Tim Hitchcock.

My prepared talk: A bit about the British Library for those who aren't familiar with it. It's one of the two biggest libraries in the world, and it’s the national library for the UK. 
 
Its collections are vast – somewhere between 180 and 200 million collection items, including 14 million books; hundreds of terrabytes of archived websites; over 600,000 bound volumes of historical newspapers, of which about 60 million pages have been digitised with partners FindMyPast so far)… 
 
We've been working with crowdsourcing – which we defined as working with the public on tasks that contribute to a shared, significant goal related to cultural heritage collections or knowledge – for about a decade now. We've collected local sounds and accents around Britain, georeferenced gorgeous historical maps, matched card catalogue records in Urdu and Chinese to digital catalogue records, and brought the history of theatre across the UK to life via old playbills. 
 
Some of our crowdsourcing work is designed to help improve the discoverability of cultural heritage collections, and some, like our work with Living with Machines, is designed to build datasets to help answer wider research questions. 
 
In all cases, our work with crowdsourcing is closely aligned with the BL's mission: it helps make our shared intellectual heritage available for research, inspiration and enjoyment. 
 
We think of crowdsourcing activities as a form of digital volunteering, where participation in the task is rewarding in its own right. Our crowdsourcing projects are a platform for privileged access and deeper engagement with our digitised collections. They're an avenue for people who wouldn't normally encounter historical records close up to work with them, while helping make those items easier for others to access.
 
Through Living with Machines, we've worked out how to design tasks that fit into computational linguistic research questions and timelines… 
 
So that's all great – but… the scale of our collections is hard to ignore. Individual crowdsourcing tasks that make items more accessible by transcribing or classifying items are beyond the capacity of even the keenest crowd. Enter machine learning, human computation, human in the loop… 
 
While we're keen to start building systems that combine machine learning and human input to help scale up our work, we don't want to buy into terms like 'crowdworkers' or ‘gig work’ that we see in some academic and commercial work. If crowdsourcing is a form of public engagement, as well as a productive platform for tasks, we can't think of our volunteers as 'cogs' in a system. 
 
We think that it's important to help shape the future of 'human computation' systems; to ensure that work on machine learning / AI are in alignment with Library values . We look to work that peers at the Library of Congress are doing to create human-in-the-loop systems that 'cultivate responsible practices'. 
 
We want to retain the opportunities for the public to get started with simpler tasks based on historical collections, while also being careful not to 'waste clicks' by having people do tasks that computers can do faster. 
 
With Living with Machines, we've built tasks that provide opportunities for participants to think about how their classifications form training datasets for machine learning. 
 
So my questions for the next year are: how can we design human computation systems that help participants acquire new literacies and skills, while scaling up and amplifying their work?

Screenshot of Zoom view from the conference stage with a large green clock and red countdown timer
The conference 'backstage' view on Zoom

Introducing… The Collective Wisdom Handbook

I'm delighted to share my latest publication, a collaboration with 15 co-authors written in March and April 2021. It's the major output of my Collective Wisdom project, an AHRC-funded project I lead with Meghan Ferriter and Sam Blickhan.

Until August 9, 2021, you can provide feedback or comment on The Collective Wisdom Handbook: perspectives on crowdsourcing in cultural heritage:

We have published this first version of our collaborative text to provide early access to our work, and to invite comment and discussion from anyone interested in crowdsourcing, citizen science, citizen history, digital / online volunteer projects, programmes, tools or platforms with cultural heritage collections.

I wrote two posts to provide further context:

Our book is now open for 'community review'. What does that mean for you?

Announcing an 'early access' version of our Collective Wisdom Handbook

I'm curious to see how much of a difference this period of open comment makes. The comments so far have been quite specific and useful, but I'd like to know where we *really* got it right, and where we could include other examples. You need a pubpub account to comment but after that it's pretty straightforward – select text, and add a comment, or comment on an entire chapter.

Having some distance from the original writing period has been useful for me – not least, the realisation that the title should have been 'perspectives on crowdsourcing in cultural heritage and digital humanities'.

About 'a practical guide to crowdsourcing in cultural heritage'

book cover

Some time ago I wrote a chapter on 'Crowdsourcing in cultural heritage: a practical guide to designing and running successful projects' for the Routledge International Handbook of Research Methods in Digital Humanities, edited by Kristen Schuster and Stuart Dunn. As their blurb says, the volume 'draws on both traditional and emerging fields of study to consider what a grounded definition of quantitative and qualitative research in the Digital Humanities (DH) might mean; which areas DH can fruitfully draw on in order to foster and develop that understanding; where we can see those methods applied; and what the future directions of research methods in Digital Humanities might look like'.

Inspired by a post from the authors of a chapter in the same volume (Opening the ‘black box’ of digital cultural heritage processes: feminist digital humanities and critical heritage studies by Hannah Smyth, Julianne Nyhan & Andrew Flinn), I'm sharing something about what I wanted to do in my chapter.

As the title suggests, I wanted to provide practical insights for cultural heritage and digital humanities practitioners. Writing for a Handbook of Research Methods in Digital Humanities was an opportunity help researchers understand both how to apply the 'method' and how the 'behind the scenes' work affects the outcomes. As a method, crowdsourcing in cultural heritage touches on many more methods and disciplines. The chapter built on my doctoral research, and my ideas were roadtested at many workshops, classes and conferences.

Rather than crib from my introduction (which you can read in a pre-edited version online), I've included the headings from the chapter as a guide to the contents:

  • An introduction to crowdsourcing in cultural heritage
  • Key conceptual and research frameworks
  • Fundamental concepts in cultural heritage crowdsourcing
  • Why do cultural heritage institutions support crowdsourcing projects?
  • Why do people contribute to crowdsourcing projects?
  • Turning crowdsourcing ideas into reality
  • Planning crowdsourcing projects
  • Defining 'success' for your project
  • Managing organisational impact
  • Choosing source collections
  • Planning workflows and data re-use
  • Planning communications and participant recruitment
  • Final considerations: practical and ethical ‘reality checks’
  • Developing and testing crowdsourcing projects
  • Designing the ‘onboarding’ experience
  • Task design
  • Documentation and tutorials
  • Quality control: validation and verification systems
  • Rewards and recognition
  • Running crowdsourcing projects
  • Launching a project
  • The role of participant discussion
  • Ongoing community engagement
  • Planning a graceful exit
  • The future of crowdsourcing in cultural heritage
  • Thanks and acknowledgements

I wrote in the open on this Google Doc: 'Crowdsourcing in cultural heritage: a practical guide to designing and running successful projects', and benefited from the feedback I got during that process, so this post is also an opportunity to highlight and reiterate my 'Thanks and acknowledgements' section:

I would like to thank participants and supporters of crowdsourcing projects I’ve created, including Museum Metadata Games, In their own words: collecting experiences of the First World War, and In the Spotlight. I would also like to thank my co-organisers and attendees at the Digital Humanities 2016 Expert Workshop on the future of crowdsourcing. Especial thanks to the participants in courses and workshops on ‘crowdsourcing in cultural heritage’, including the British Library’s Digital Scholarship training programme, the HILT Digital Humanities summer school (once with Ben Brumfield) and scholars at other events where the course was held, whose insights, cynicism and questions have informed my thinking over the years. Finally, thanks to Meghan Ferriter and Victoria Van Hyning for their comments on this manuscript.

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Useful distractions: help cultural heritage and scientific projects from home

Today I came across the term 'terror-scrolling', a good phrase to describe the act of glancing from one COVID-19 update to another. While you can check out galleries, libraries, archives and museums content online or explore the ebooks, magazines and other digital items available from your local library, you might also want to help online projects from scientific and cultural heritage organisations. You can call it 'online volunteering' or 'crowdsourcing', but the key point is that these projects offer a break from the everyday while contributing to a bigger goal.

Not commuting at the moment? Need to channel some energy into something positive? You can help transcribe historical text that computers can't read, or sort scientific images. And don't worry – these sites will let you know what skills are required, you can often try a task before registering, and they have built-in methods for dealing with any mistakes you might make at the start.

Here's a list of sites that have a variety of different kinds of tasks / content to work on:

Some of these sites offer projects in languages other than English, and I've collected additional multi-lingual / international sites at Crowdsourcing the world’s heritage – I'm working on an update that'll make it easy to find current, live projects but (ironically, for someone who loves taking part in projects) I can't spend much time at my desk right now so it's not ready just yet.

Keynote online: 'Reaching out: museums, crowdsourcing and participatory heritage'

In September I was invited to give a keynote at the Museum Theme Days 2016 in Helsinki. I spoke on 'Reaching out: museums, crowdsourcing and participatory heritage. In lieu of my notes or slides, the video is below. (Great image, thanks YouTube!)

Crowdsourcing in cultural heritage, citizen science – September 2016

More new projects and project updates I've noticed over September 2016.

Gillian Lattimore @Irl_HeritageDig has posted some of her dissertation research on Crowdsourcing Motivations in a GLAM Context: A Research Survey of Transcriber Motivations of the Meitheal Dúchas.ie Crowdsourcing Project. dúchas.ie is 'a project to digitize the National Folklore Collection of Ireland, one of the largest folklore collections in the world'.

A long read on Brighton Pavilion and Museums’ Map The Museum, '#HeritageEveryware Map The Museum: connecting collections to the street' includes some great insights from Kevin Bacon.

Meghan Ferriter and Christine Rosenfeld have produced a special edition of a journal, 'Exploring the Smithsonian Institution Transcription Center' with articles on 'Crowdsourcing as Practice and Method in the Smithsonian Transcription Center' and more.

Two YouGov posts on American and British people's knowledge of their recent family history provide some useful figures on how many people in each region have researched family history.

Richard Light's posted some interesting questions and feedback for crowdsourcing projects at The GB1900.org project – first look.

'Archiving the Civil War’s Text Messages' provides more information about the Decoding the Civil War project.

Zooniverse blog post 'Why Cyclone Center is the CrockPot of citizen science projects' gives some insight into why some projects appear 'slower' than others.

A December 2015 post, 'How a citizen science app with over 70,000 users is creating local community' (HT Jill Nugent ‏@ntxscied) and an interesting contrast to 'Volunteer field technicians are bad for wildlife ecology'. A nice quote from the first piece: 'Young says that the number one thing that keeps iNaturalist users involved is the community that they create: “meeting other people who are into the same thing I am”'.

iNaturalist Bioblitz's are also more evidence for the value of time-limited challenges, or as they describe them, 'a communal citizen-science effort to record as many species within a designated location and time period as possible'.

Micropasts continue to add historical and archaeological projects.

Survey of London and CASA launched the Histories of Whitechapel website, providing 'a new interactive map for exploring the Survey’s ongoing research into Whitechapel' and 'inviting people to submit their own memories, research, photographs, and videos of the area to help us uncover Whitechapel’s long and rich history'.

New Zooniverse project Mapping Change: 'Help us use over a century's worth of specimens to map the distribution of animals, plants, and fungi. Your data will let us know where species have been and predict where they may end up in the future!'

New Europeana project Europeana Transcribe: 'a crowdsourcing initiative for the transcription of digital material from the First World War, compiled by Europeana 1914-1918. With your help, we can create a vast and fully digital record of personal documents from the collection.'

'Holiday pictures help preserve the memory of world heritage sites' introduces Curious Travellers, a 'data-mining and crowd sourced infrastructure to help with digital documentation of archaeological sites, monuments and heritage at risk'. Or in non-academese, send them your photos and videos of threatened historic sites, particularly those in 'North Africa, including Cyrene in Libya, as well as those in Syria and the Middle East'.

I've added two new international projects, Les herbonautes, a French herbarium transcription project led by the Paris Natural History Museum, and Loki a Finnish project on maritime, coastal history to my post on Crowdsourcing the world's heritage – as always, let me know of other projects that should be included.

 

Survey of London
Survey of London site

Crowdsourcing in cultural heritage, citizen science – recent updates

A small* collection of links from the past little while.

Projects

  • A new Zooniverse project, Decoding the Civil War, launched in June: 'Witness the United States Civil War by transcribing and deciphering messages and codes from the United States Military Telegraph'.
  • Another Zooniverse project, Camera CATalogue: 'Analyze Wildlife Photos to Help Panthera Protect Big Cats'.

Articles

  • Palmer, Stuart, and Deb Verhoeven, ‘Crowdfunding Academic Researchers–the Importance of Academic Social Media Profiles’, in ECSM 2016: Proceedings of the 3rd European Conference on Social Media (Academic Conferences and Publishing International, 2016), pp. 291–299
  • Preece, Jennifer, ‘Citizen Science: New Research Challenges for Human–Computer Interaction’, International Journal of Human-Computer Interaction, 32 (2016), 585–612 <http://dx.doi.org/10.1080/10447318.2016.1194153>
  • Dillon, Justin, Robert B. Stevenson, and Arjen E. J. Wals, ‘Introduction: Special Section: Moving from Citizen to Civic Science to Address Wicked Conservation Problems’, Conservation Biology, 30 (2016), 450–55 <http://dx.doi.org/10.1111/cobi.12689> – has an interesting new model, putting citizen sciences 'on a continuum from highly instrumental forms driven by experts or science to more emancipatory forms driven by public concern. The variations explain why citizens participate in CS and why scientists participate too. To advance the conversation, we distinguish between three strands or prototypes: science-driven CS, policy-driven CS, and transition-driven civic science.'
    …

    'We combined Jickling and Wals’ (2008) heuristic for understanding environmental and sustainability education (Jickling & Wals 2008) and M. Fox and R. Gibson's problem typology (Fig. 1) to provide an overview of the different possible configurations of citizen science (Fig. 2). The heuristic has 2 axes. We call the horizontal axis the participation axis, along which extend the possibilities (increasing from left to right) for stakeholders, including the public, to participate in setting the agenda; determining the questions to be addressed; deciding the mechanisms and tools to be used; choosing how to monitor, evaluate, and interpret data; and choosing the course of action to take. The vertical (goal) axis shows the possibilities for autonomy and self-determination in setting goals and objectives. The resulting quadrants correspond to a particular strand of citizen science. All three occupied quadrants are important and legitimate.'

    A heuristic of citizen science based on Wals and Jickling (2008).
    A heuristic of citizen science based on Wals and Jickling (2008). From Dillon, Justin, Robert B. Stevenson, and Arjen E. J. Wals (2016)

    * It's a short list this month as I've been busy and things seem quieter over the northern hemisphere summer.