Archive for the ‘citizen science’ Category

Thoughts on Goodchild (2010)

Monday, September 18th, 2017

Goodchild concludes his paper “Twenty Years of Progress” by realizing a need for greater interaction between the fields of geography, computer science, and information science in the future of GIScience. Seven years ago, when this paper was written, neogeography was an emerging concept. RFID and GPS location collection operations were still relatively small scale. Goodchild notes the benefits of having such large real-time datasets, as well as the implications such data would have on personal privacy. I’m not sure if Goodchild could have predicted the roles that the private sector would have in advancing location-based technology.

Many datasets that have been collected by tech companies are invaluable to actors in the public sector and academia. Google and Uber data would surely benefit transportation planners, and Instagram geospatial data might be of use to a board of tourism. Goodchild asks the right questions about the future of real-time location data, but today might ask more questions specific to the privatization of such datasets. Are the developers of location-based applications members of the GIScience community? Do they recognize the significance of the geospatial data they are collecting? Or do they seek to make a profit over the advancement of science?

I would argue that in 2017 the actors on the stage of GIScience include much more geographers, computer scientists, and information scientists. Goodchild correctly predicts that the average citizen will become “both a consumer and producer of geographic information,” but fails to mention the elephants, the private tech companies that provide VGI-fed services to the newest generation of smartphone owners. App developers are as much a part of GIScience as the transportation planners that install sensors to measure traffic flow, and the computer scientists that use agent-based modeling to optimize emergency services in the event of a terrorist attack. I hope that academic GIScientists such as Goodchild are changing the way they see GIScience to bridge the gap between private collectors of geospatial data.

Citizen scientists working with scientists

Tuesday, May 1st, 2012

Good article on assessing data quality of volunteered contributions from citizen scientist:

Christopher Nagy, Kyle Bardwell, Robert F. Rockwell, Rod Christie and Mark Weckel. 2012. Validation of a Citizen Science-Based Model of Site Occupancy for Eastern Screech Owls with Systematic Data in Suburban New York and Connecticut. Northeastern Naturalist 19(sp6):143-158.


We characterized the landscape-level habitat use of Megascops asio (Eastern Screech Owl) in a suburban/urban region of New York and Connecticut using citizen-science methodologies and GIS-based land-use information. Volunteers sampled their properties using call-playback surveys in the summers of 2009 and 2010. We modeled detection and occupancy as functions of distance to forest and two coarse measures of development. AICc-supported models were validated with an independent dataset collected by trained professionals. Validated models indicated a negative association between occupancy and percent forest cover or, similarly, a positive association with percent impervious cover. When compared against the systematic dataset, models that used forest cover as a predictor had the highest accuracy (kappa = 0.73 ± 0.18) in predicting the occupancy observations in the systematic survey. After accounting for detection, both datasets support similar owl-habitat patterns of predicting occupancy in developed areas compared to highly rural. While there is likely a minimum amount of forest cover and/or maximum level of urbanization that Screech Owls can tolerate, such limits appear to be beyond the ranges sampled in this study. Future research that seeks to determine this development limit should focus on very urbanized areas. The high accuracy of the citizen-science models in predicting the systematic dataset indicates that volunteer-based efforts can provide reliable data for wildlife studies.