Return to search

Using Visual Media to Empower Citizen Scientists: A Case Study of the Outsmart App

To be successful citizen science projects need to do two key things: (1) they need to meaningfully engage the public and they must also provide people with the tools, expertise, and/or training needed to participate in rigorous research that can be used by the scientific community. In some ways, these requirements are potentially at odds. Emphasis on rigor and expertise risks excluding members of the public who do not feel qualified to participate in esoteric or technically difficult scientific research. Conversely, projects that eschew rigorous methods in favor of wider participation might lead to bad data that cannot be used to draw any meaningful conclusions to expand scientific understanding. How then do those who are aiming to design successful citizen science programs create tools and processes that facilitate both active engagement and meaningful scientific results for perceived non-expert researchers?
This paper uses a case study of the Outsmart Invasive Species Project (Outsmart) to explore how visual media shape the experiences of citizen scientists participating in a data collection project. Outsmart uses visual media such as photographs and videos to train users in identifying invasive species, and asks them to submit their own location-tagged pictures to a central database for review by a trained research team. Using ethnographic field observation, we focused on how visual media serve to improve engagement in non-expert Outsmart users by building confidence and expertise. Our work can provide guidance to other citizen science projects in how to best use visual media to empower citizens and improve scientific outcomes.

Identiferoai:union.ndltd.org:UMASS/oai:scholarworks.umass.edu:masters_theses_2-1871
Date29 October 2019
CreatorsKierstead, Megan E
PublisherScholarWorks@UMass Amherst
Source SetsUniversity of Massachusetts, Amherst
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceMasters Theses

Page generated in 0.0027 seconds