Crowdsourcing Large-Scale Ecological Monitoring: Identifying Design Principles to Motivate Contributors
Addressing the impact of humans on the environment is arguably one of the biggest challenges society faces, and large-scale ecological monitoring is needed to reliably assess the impact and establish relevant policies. However, such large-scale monitoring
- PDF / 136,174 Bytes
- 10 Pages / 439.37 x 666.14 pts Page_size
- 0 Downloads / 178 Views
Abstract Addressing the impact of humans on the environment is arguably one of the biggest challenges society faces, and large-scale ecological monitoring is needed to reliably assess the impact and establish relevant policies. However, such large-scale monitoring is often infeasible, primarily owing to resource limitations. Recently, organizations have started to use information technologies to enable public participation in such efforts. One major problem is how to motivate people to contribute and, more importantly, to encourage sustained participation. In this conceptual paper, we integrate research from crowdsourcing, human–computer interaction, and motivational affordances to propose design principles enhancing the intrinsic motivation of contributors to large-scale ecological monitoring projects. Specifically, drawing on research on crowdsourcing and motivational affordances, we argue that instantiating design principles addressing people’s needs for autonomy, competence, and relatedness can increase participants’ motivation and present recommendations for designers of systems supporting such projects.
1
Introduction
One of the biggest issues society faces is the impact of humans on our environment [23]. Particularly, researchers have noted that our limited ability to assess and predict the impacts of human activity on the ecosystems we live in is one of the main factors hindering conservation efforts [4, 41]. In particular, a challenge is being able to separate the impacts arising from natural changes from impacts created by human action [35]; C. Schneider (*) City University of Hong Kong, Kowloon Hong Kong SAR F. von Briel Department of Information Systems, City University of Hong Kong, Kowloon, SAR, Hong Kong e-mail: [email protected]; [email protected] H. Linger et al. (eds.), Building Sustainable Information Systems: Proceedings of the 2012 International Conference on Information Systems Development, DOI 10.1007/978-1-4614-7540-8_39, © Springer Science+Business Media New York 2013
509
510
C. Schneider and F. von Briel
predicting such impacts necessitates repeatedly measuring the ecosystems’ responses to disturbances [10, 12], so as to create a continuous feedback loop, helping to establish, prioritize, and adapt policies and conservation efforts [3, 36]. For example, researchers are interested in recording and analyzing changes to fauna and flora, temperatures, or pollutant concentrations. In order to assess long-term trends on a large geographical scale, large-scale ecological monitoring is needed [16, 39]. Yet, as such large-scale ecological monitoring can quickly become very costly, it is conducted less frequently than desired [3], and examples show that even wellfunded programs often fail [4]. Recently, researchers have called for harnessing the power of the crowds for large-scale ecological monitoring. Termed “citizen science,” this form of crowdsourcing uses ordinary citizens for collecting field data [34] that can be analyzed by researchers. Advances in mobile technolo
Data Loading...
