Big Data

I really enjoyed “Beyond the geotag: situating ‘big data’ and leveraging the potential of the geoweb” by Crampton et al (2013). It explores the possibilities and limitations associated with the analysis of Geo-web generated Big Data. They advocate for a more comprehensive ontology of space, one that goes beyond xy coordinates to include a temporal and relational dimension, as well as a more complete understanding of geo-web generated data to include ancillary non-human produced data, as well as non user-generated data.
This article debunks the promise of the explanatory potential of Bid Data analytics and stresses the importance of choice of data and analytical techniques to provide meaningful findings. Moreover, they emphasized that Big Data created from the Geoweb represents information from a small subset of the population, undermining the external validity of findings, and potentially marginalizing ‘unplugged’ individuals.
The implications for GIScience are significant: How do we realize the potential of geospatial Big Data? What are the societal implications of Big Data analytics? How do create metadata for Big Data efficiently and comprehensively? How do you effectively geovisualize Big Data to both explore and represent data?
Geospatial Big Data gives rise to questions that build upon those generated by ‘small data’ analytics. Issues of quality are still relevant and are not supplanted by large volumes of data. GIScience will evolve rapidly and will likely intersect with other disciplines to fully realize the potential of Big Data.


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