ABSTRACT
[This corrects the article DOI: 10.1016/j.wdp.2020.100234.].
ABSTRACT
World Librarians is a socio-technical system that strives to solve the information access problem many remote offline schools and libraries have in lesser developed contexts. In this Case Report, we describe the system we have developed over the course of three years, where we first establish solar-powered computer labs in remote schools and libraries in Malawi, and then provide them digital information that they want, rather than what we in the Global North think they need. After providing background on these issues, we describe the socio-technical underpinnings and workflow in the World Librarians program. This involves the establishment of "Requester nodes" in the offline schools and libraries, the management of these deployments using a cloud-based WL app, and the operations of the WL "Searcher node" at the University of Massachusetts Amherst, as well as a novel micro-payment system that enables the transfer of large digital datasets through the use of teacher or librarian cell phones and data plans. We close the report with findings from a preliminary survey suggesting that the WL program is making a positive impact on the schools and libraries served. At its core, WL represents a global librarian support system working to remove the barriers to educational information for all global citizens, with central attention and awareness to Global North/South information power dynamics.
ABSTRACT
The rapid growth and increasing popularity of smartphone technology is putting sophisticated data-collection tools in the hands of more and more citizens. This has exciting implications for the expanding field of citizen science. With smartphone-based applications (apps), it is now increasingly practical to remotely acquire high quality citizen-submitted data at a fraction of the cost of a traditional study. Yet, one impediment to citizen science projects is the question of how to train participants. The traditional "in-person" training model, while effective, can be cost prohibitive as the spatial scale of a project increases. To explore possible solutions, we analyze three training models: 1) in-person, 2) app-based video, and 3) app-based text/images in the context of invasive plant identification in Massachusetts. Encouragingly, we find that participants who received video training were as successful at invasive plant identification as those trained in-person, while those receiving just text/images were less successful. This finding has implications for a variety of citizen science projects that need alternative methods to effectively train participants when in-person training is impractical.
Subject(s)
Cell Phone , Introduced Species , Light , Plants , Humans , Plants/classificationABSTRACT
There is a critical need to locate innovative forest management institutions that significantly impact forest cover change. This research presents an initial "proof of concept" methodology which combines deforestation theory with satellite image change analysis to identify forested areas that, theoretically, should probably not be there. Ten such "forest anomalies" are identified using temporal analysis of Landsat TM imagery of the Chitwan district in Nepal, linked with a GIS database on roads and a visual estimation of topography. A rapid field reconnaissance is undertaken to determine which of these anomalies exhibit interesting forest management innovations. Based on this information, one case is selected for detailed field study: this turns out to be a major case of community forestry and a premier ecotourism initiative that we were not aware of until we undertook this analysis. The utility and limitations of the method are described for monitoring trends in forest cover change.
