Citizen Sciences and their uses/abusesOct 05, 2017 · Citizen Sciences and their uses/abuses...

Citizen Sciences and their uses/abuses

Martin Dittus · Oxford Internet Institute · @dekstop

Addressing Communications in Disaster Research: digital culture, geographic information systems and citizen science

Hull · 5th Oct 2017

Martin Dittus · @dekstop

I’ll talk about processes to coordinate volunteers towards shared outcomes, and ask questions about the power relationships underlying such processes.

I will show you a large number of concepts in a short time. Many of them might already be familiar to you. Don't try and remember them all; simply remember the ones you like, or that you're curious about. You're in groups: you each come from a particular and partial perspective, and hopefully together you can then find a stronger synthesis .

I will then ask you to discuss three questions: #1: How and why does such volunteer work happen? #2: Who benefits, how? #3: How should we recognise/reward contributions?

https://twitter.com/dekstop


About meData science, mass participation platforms, collectivist practice.

My last decade: • “Big data” analysis platforms at Last.fm

(software developer) • Citizen science and citizen sensing research at

CASA (MRes) • Crowd mapping research at UCL (EngD) • Darknet economic geography at OII (postdoc)



What is citizen science?Aim: to coordinate volunteer participation towards shared outcomes, typically with a scientific purpose.

“A citizen scientist is a volunteer who collects and/or processes data as part of a scientific enquiry.” (Silvertown 2009)

There's a century of tradition. I will focus on more recent forms that employ online platforms and other digital technologies:

“...in the right circumstances, citizen science can work on a massive scale and is capable of producing high quality data as well as unexpected insights and innovations.” (Wiggins 2010)



Why are we discussing it here?

Citizen science research has yielded useful conceptual building blocks that are transferrable to similar contexts.

Three recurring themes in such research: • Participant motivations• Coordination practices• Assessing and improving data quality



Relating it to comparable practices

In the last 20 years, emergent concepts in other domains were introduced to describe similar kinds of concerns:

Citizen sensing, crowd mapping, disaster mapping, crowdsourcing, crowd labour, peer production, open innovation, … (check my litreviews)

All of these terms have complex relationships with "citizen science". Frequently, the boundaries are blurry.

Many are relevant for our discussion today.



Exemplary projects



• Zooniverse: a large citizen science web portal. Galaxy Zoo is focused on astronomy

• Using volunteer labour for large-scale scientific data collection and analysis

• Mainly used for simple classification and labelling tasks: easily distributed

• Data used in more than 100 scientific publications

Zooniverse and Galaxy Zoo



• An online puzzle game about protein folding

• Participation requires significant skill & time

• A focus on competitive mechanics: leaderboards, competitions, etc

• Yielded multiple publications

Protein Folding with Foldit



• iNaturalist: a global project with >1M geo-referenced nature observations

• BugGuide, with 1M location-attributed insect photos

• EcoEngine: a Berkeley project to document ecological diversity via field observations

• … and many more

Bird watching and beyond



• Now offline. An early platform for DIY sensor data.

• Environmental sensing, garden appliances, radiation monitors, … anything that produces streams of data.

• There was no explicitly collective purpose, but most data was made public. It is maybe comparable to a “Flickr of data streams”.

Citizen sensing: Pachube/Cosm/Xively



Cosm data integration attempt• A data revolution! Thousands of

environmental sensors in the U.K., collected by self-interested and independent individuals!

• Can we combine these citizen measurements into larger environmental models?

• (It failed. Many causes: a lack of standardised annotations, badly calibrated sensors, few long-term participants, … essentially: a lack of coordination.)



Crowd mapping and disaster mapping for social good.

In many ways setting a high standard: • Standardized workflows, task

allocation, interfaces • Highly responsive to emergent

needs (currently: Puerto Rico, others)

• Outcomes have significant social benefit: often the first maps of their kind. These maps can save lives.

The Humanitarian OpenStreetMap Team (HOT)



HOT mapathons

Social interactions to foster skills and engagement



HOT data validation

Expert review and feedback for contributions



HOT activity over time

Activity follows emergent demand, quite common to see episodic participation during peak events.



Theoretical frames



Motivations to participateWhy do people volunteer their time? • Six basic motivational categories drive volunteering:

values such as altruism, social experience, self-improvement and a positive self-image (Clary et al, 1998)

• Charitable giving: perceived social urgency (Schervish and Havens, 1997)

• Wikipedia: fun, ideology (Nov, 2007) • Interest in the domain

A common observation: people join with an initial motivation, this shifts over time. E.g. when one-time participants become organisers. (Rotman et al. 2012)



IncentivisationWhen using behavioral techniques to drive sustained participation…. • Extrinsic rewards can

counteract intrinsic motivations (Cameron et al. 2001)

• Competition may benefit some, but can demotivate others (Tauer, Harackiewicz, 1999)

• Low achievement in a competitive environment can be discouraging (Massung et al. 2013)



Recognition

How can we fairly recognise and reward people’s contributions?



Lightweight & heavyweight models of peer production

Haythornthwaite (2009) observes a dichotomy of roles in collaborative peer production

• Lightweight: micro-participation by many towards a shared purpose, relying on authority and rules to establish order. Contributions are often standardised.

• Heavyweight: strong ties between a committed group of more autonomous members. Participants are typically named, negotiate their contributions with their peers, and gain status based on the nature of their contributions. A wide range of contribution types.



Typology of Participation

Haklay (2013)



Participation Ladder(s)

Arnstein (1969)



Participation inequality

• When a small number of contributors do most of the work.

• Aka the 1% rule, the pareto principle, etc.

• (Very typical, unless there are structures in place to work against it.)



Demographic bias

Whose perspectives are captured?



Mechanisms for Data Quality

(Wiggins et al 2011)



[other useful concepts that are worth discussing in this context?]



Three provocations



The session format: speculative project design

• Pick one or more project opportunities that you would like to discuss as a group.

• It helps if everyone is broadly familiar with the problem domain: start with a very brief summary.

• Using my three questions, try to understand them quite deeply. What are some of the essential considerations?



#1. How and why does volunteer work happen?

• How will people find out about the project? • Is participation open to all? • Why will people join?• Do people need prior knowledge?

Are they being trained? • How is participation encouraged or rewarded? • How long are people participating?

Is there a natural end?



#2. Who benefits, how?

• Who organises and coordinates the project? • Where do the questions (task descriptions)

come from? • What primary outputs are produced? • What are some of the secondary outcomes and

potential unintended side-effects? • Who benefits from each of these?



#3. How should we recognise or reward contributions?

• Can we identify equitable arrangements? • Where is the boundary between participation

for pleasure, and unpaid labour? • A simple test: did this use to be a job?



Citizen Sciences, uses and abuses

Pick one or more project opportunities. #1. How and why does volunteer work happen? #2. Who benefits, how?#3. How should we recognise or reward contributions?

Discussion tips: • Share your own experiences, as researchers and participants. • There often is no single “right” answer.

If you finish early: • Do we need new terms for such arrangements? Is it still labour if

people voluntarily choose their own tasks for enjoyment? • Project your observations into the future. What does this mean for

future volunteering practice? What might be extreme expressions?


Citizen Sciences and their uses/abusesOct 05, 2017 · Citizen Sciences and their uses/abuses...

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