The case for using citizen science in research design

Mr Peter Brenton1, Mr Kheeran Dharmawardena1

1Atlas of Living Australia, CSIRO, Canberra, Australia, 


As a way of “doing science”, citizen science has existed since well before science was first recognized as a discipline. The rise of professional science through the 19th and 20th centuries saw citizen science diminished to a pursuit for amateurs that was frequently discredited and prejudiced by professionals as producing unreliable and untrustworthy data and results.

The term “citizen science” is frequently misunderstood and misused, but in essence it refers to the participation in scientific endeavor by members of the public, specifically people who are not “qualified scientists”. Endeavor in this context refers to the pursuit of answers to questions using scientific methods and participation can be in any or all parts of the scientific process.

In the 21st century, citizen science is most frequently associated with crowd-sourced data collection in biodiversity and environmental projects, but it has also been successfully applied in any many other fields of research including social, cultural, economic, technological, medical, astronomical, and others. It has also been applied in different aspects of the scientific process, other than just data collection, such as data quality assurance (validation, verification, etc.), analysis and even publication.

Designing citizen science components into research projects can be rewarding for both researchers and citizen scientists. Reasons for doing so include:

  • Research can be costly, in particular when it involves extensive data gathering and processing. Incorporating public participation into some of the more time consuming and costly aspects of projects can significantly reduce overall costs;
  • Research teams can’t be everywhere all of the time, but involving the public in projects significantly increases the number of human sensors on the ground, thus providing much greater spatial and temporal coverage than would be possible using conventional research approaches;
  • Some data generation processes are computationally intensive and require human interpretation in ways that machine processing cannot currently perform. Breaking tasks down for crowd-sourced processing has proven very successful in these cases;
  • Involving the public in science projects increases social understanding and engagement, as well as ownership of issues. This is particularly important when changes to social paradigms and behaviours are required, such as in the debates around climate change, plastics in the environment, impacts on the Great Barrier Reef, etc.;
  • Involving the public in scientific processes makes the science real for people, allowing them to connect with projects and their outcomes more fully; and
  • In cases where social and/or political institutions fail to protect or deliberately undermine the interests of citizens, citizen science can produce sound data and analyses to counter vested interests working against truth or the public good. Citizen science–based activism has some well documented cases in the USA, such as The Public Lab [1] and the domestic water supply contamination saga in Flint Michigan [2]).

A cautionary note however, is that citizen scientists are not just free resources to be exploited for the benefit of projects. They should be treated respectfully as stakeholders and contributors who have an interest in what projects are aiming to achieve. Therefore projects incorporating aspects of citizen science should thoughtfully include science communications, science engagement and science literacy into the project design.


Data generated by citizen science projects is unfortunately often discounted by many professional scientists as biased, unreliable, untrustworthy, or of inconsistent quality. These views are also often held by many researchers about data from other researchers too, unless those suppliers are known and trusted as individuals. Are such criticisms valid or appropriate? Maybe, it depends on purpose for which the data was collected and the purpose for which it is being used. Before casting criticism at citizen science data simply because it is sourced through citizen science, it is important and appropriate to assess it on it’s merits, methods and fitness for the purpose for which it is to be used, just as one would for any dataset.

Older tools and field methods relied heavily on the skills and documentary discipline of individual data collectors/recorders to accurately and comprehensively document their observations. Tools such as GPS, mobile and field-based data collection systems incorporating configured database validation and quality assurance measures were not available then as they are now. Such technologies are now ubiquitous in platforms which are readily and freely available to citizen science practitioners, significantly reducing, and often eliminating many data quality related issues at the heart of most criticisms. Therefore many citizen science generated data are at least as good if not better quality than professionally generated data of the past and probably on-par with many of today’s professionally generated datasets.

Considerations around methodology in respect to fitness for use are therefore arguably more significant nowadays than data quality per-se and it is fair to say that currently many citizen science projects do not document methodology well, though this too is improving. In addition, the lack of a (or poorly) documented methodology should not necessarily discount a citizen science dataset from use, as often both quality and method can be readily determined by a superficial assessment of the data itself, eg. Collecting bias along access routes. Where collecting bias is an issue, even those data may still be usable after application of statistical methods to remove/minimize the bias.


The presentation will illustrate points raised above using examples from a selection of successful citizen science projects including: EchidnaCSI [3], Upper Murrumbidgee [4], DigiVol [5], Fold-it [6], EyeWire [7], and GalaxyZoo [8].


  1. The Public Lab,
  2. Stefaan Verhulst Citizen Science and the Flint Water Crisis, Posted on March 2, 2016, in GovLab Digest. Available from:, accessed 9th June 2018.
  3. EchidnaCSI,
  4. Upper Murrumbidgee Waterwatch,
  5. DigiVol,
  6. Fold-it,
  7. EyeWire,
  8. GalaxyZoo,


Mr. Kheeran Dharmawardena, MBA, BComp, is the Program manager at the Atlas of Living Australia. Kheeran has over 2 decades of experience in delivery of many ICT services within the higher education and research sector, including infrastructure delivery, service delivery, data management, IT & enterprise architecture and eResearch. He has a special interest in the socio-technical challenges involved in the delivery of effective services.

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