Nathan R. Prestopnik

Motivation and Data Quality in a Citizen Science Game: A Design Science Evaluation

Citizen science is a form of social computation where members of the public are recruited to contribute to scientific investigations. Citizen-science projects often use web-based systems to support collaborative scientific activities. However, finding ways to attract participants and ensure the accuracy of the data they produce are key issues in making such systems successful. In this paper we describe the design and preliminary evaluation of a simple game that addresses these two concerns for the task of species identification.

Purposeful gaming & socio-computational systems: a citizen science design case

Citizen science is a form of social computation where members of the public are recruited to contribute to scientific investigations. Citizen-science projects often use web-based systems to support collaborative scientific activities, making them a form of computer-supported cooperative work. However, finding ways to attract participants and confirm the veracity of the data they produce are key issues in making such systems successful. We describe a series of web-based tools and games currently under development to support taxonomic classification of organisms in photographs collected by citizen-science projects. In the design science tradition, the systems are purpose-built to test hypotheses about participant motivation and techniques for ensuring data quality. Findings from preliminary evaluation and the design process itself are discussed.

Gaming for (Citizen) Science: Exploring Motivation and Data Quality in the Context of Crowdsourced Science through the Design and Evaluation of a Social-Computational System

Citizen Sort, currently under development, is a web-based social-computational system designed to support a citizen science task, the taxonomic classification of various insect, animal, and plant species. In addition to supporting this natural science objective, the Citizen Sort platform will also support information science research goals on motivation for participation in social-computation and citizen science. In particular, this research program addresses the use of games to motivate participation in social-computational citizen science, and explores the effects of system design on motivation and data quality. A design science approach, where IT artifacts are developed to solve problems and answer research questions is described. Research questions, progress on Citizen Sort planning and implementation, and key challenges are discussed.

Citizen science system assemblages: understanding the technologies that support crowdsourced science

We explore the nature of technologies to support citizen science, a method of inquiry that leverages the power of crowds to collect and analyze scientific data. We evaluate these technologies as system assemblages, collections of interrelated functionalities that support specific activities in pursuit of overall project goals. The notion of system assemblages helps us to explain how different citizen science platforms may be comprised of widely varying functionalities, yet still support relatively similar goals. Related concepts of build vs. buy and web satisfiers vs. web motivators are used to explore how different citizen science functionalities may lead to successful project outcomes. Four detailed case studies of current citizen science projects encompassing a cross-section of varying project sizes, resource levels, technologies, and approaches to inquiry help us to answer the following research questions: 1) What do typical system assemblages for citizen science look like? 2) What factors influence the composition of a system assemblage for citizen science? 3) What effect does the assemblage composition have on scientific goals, participant support, motivation, and satisfaction? and 4) What are the design implications for the system assemblage perspective on citizen science technologies?

Exploring Data Quality in Games With a Purpose

A key problem for crowd-sourcing systems is motivating contributions from participants and ensuring the quality of these contributions. Games have been suggested as a motivational approach to encourage contribution, but attracting participation through game play rather than scientific interest raises concerns about the quality of the data provided, which is particularly important when the data are to be used for scientific research. To assess whether these concerns are justified, we compare the quality of data obtained from two citizen science games, one a “gamified” version of a species classification task and one a fantasy game that used the classification task only as a way to advance in the game play. Surprisingly, though we did observe cheating in the fantasy game, data quality (i.e., classification accuracy) from participants in the two games was not significantly different. As well, the quality of data from short-time contributors was at a usable level of accuracy. These findings suggest that various approaches to gamification can be useful for motivating contributions to citizen science projects.

Cooperative visualization: A design case

Purpose – In this design case, a participatory approach to visualizing a complex computational pipeline was adopted, with the goal of exploring what benefits might be derived when groups of people visualize complex information for themselves.Design/methodology/approach – Several visualization artifacts were developed to support collaborative process at the Laser Interferometer Gravitational Wave Observatory (LIGO). Researchers adopted a participatory approach, engaging directly in LIGO activities and drawing together explicitly codified data from the LIGO computational pipeline as well as structural knowledge tacitly held by project scientists. Both sources of information were critical to producing meaningful visualizations and progressing design and research efforts.Findings – This design case revealed several benefits realized when individuals or groups visualize information for themselves, especially improved communication and enhanced understanding of complex systems of information.Originality/value –...

Gamers, citizen scientists, and data

Two key problems for crowd-sourcing systems are motivating contributions from participants and ensuring the quality of these contributions. Games have been suggested as a motivational approach to encourage contribution, but attracting participation through game play rather than intrinsic interest raises concerns about the quality of the contributions provided. These concerns are particularly important in the context of citizen science projects, when the contributions are data to be used for scientific research.To assess the validity of concerns about the effects of gaming on data quality, we compare the quality of data obtained from two citizen science games, one a gamified version of a species classification task and one a fantasy game that used the classification task only as a way to advance in the game play. Surprisingly, though we did observe cheating in the fantasy game, data quality (i.e., classification accuracy) from participants in the two games was not significantly different. As well, data from short-time contributors was also at a usable level of accuracy. Finally, learning did not seem to affect data quality in our context.These findings suggest that various approaches to gamification can be useful for motivating contributions to citizen science projects. Two citizen science games are compared, one points-based and one story-based.The study explores the scientific usefulness of data contributed by volunteer players of the games.Data quality in the two games is comparable, and is good enough to be used for scientific purposes.Games can be valuable for motivating participation; different types of games motivate different kinds of participants.Some games encourage play behaviors (e.g. cheating) that should be controlled for.

Forgotten island: a story-driven citizen science adventure

Forgotten Island, a citizen science video game, is part of an NSF-funded design science research project, Citizen Sort. It is a mechanism to help life scientists classify photographs of living things and a research tool to help HCI and information science scholars explore storytelling, engagement, and the quality of citizen-produced data in the context of citizen science.

Arena: designing an adventure video game for second language engagement and acquisition

In this poster abstract we describe an ongoing design science project: the implementation and study of a story-based language learning game called Arena. We adopt the view that games can be a powerful mechanism for motivating learning through informal mechanisms. However, our design process has revealed a number of deep challenges that we continue to contend with. In this poster we reflect particularly on the fatigue players feel when engaging with stories and play in an unfamiliar language, as well as the difficulty of connecting play interactions to language tasks.