There are a ton of free data being made available, but alas, how do we know of their quality and completeness? I just read an article in the UK Independent -
Public 'misled' over emissions statistics (
http://www.independent.co.uk/environment/climate-change/public-misled-over-emissions-statistics-1806663.html). The story alerts us to the general blind 'trust in numbers' and to the issue of a lack of completeness and context in data that are being disseminated.
Many of the
open data initiatives do not include adequate metadata that include the methodology which explains how those data were compiled, the data authors, nor models of accuracy, reliability and authenticity. The Geomatics people include seven elements of data quality -
Elements of Spatial Data Quality (The International Cartographic Association) by Stephen C. Guptill (Editor), Joel L. Morrison (Editor):
- positional accuracy,
- attribute accuracy,
- completeness,
- logical consistency,
- lineage,
- semantic accuracy and
- temporal information
Most of what I see in open data initiatives do not consider these. Also, how will we know & assess if the datasets that are being shared are the complete picture?
For instance, I had a conversation with my academic advisor about the use of remote sensing data being used for human rights. He reminded me that it was satellite images of tanks going to Kuwait that were used as evidence for military action. The problem with those images was their time stamp, according to my advisor, shortly thereafter, the tanks turned around and went back. Those later images were not shared nor used to inform the decisions to intervene. He also informed me of a team of magicians and illusionists was hired during the second world war to conceal major infrastructure from air recognicance. There are some great stories of deceptin in Cryptonimicon (
http://www.harpercollins.com/books/9780060512804/Cryptonomicon/index.aspx?).
There was also that really interesting series of blog posts and articles from Lessig urging the enthusiasts to be critical about what they are asking for, to think about the larger implications of the shift to openess. This UK article in my mind forwarns us to be cautious about the data we use and the assumptions we make. This does not mean to twart enthusiasm, but it does mean that we should consider the implications of what we are doing and be ready for smoke and mirrors along with the open data movement.
--
Tracey P. Lauriault
613-234-2805
https://gcrc.carleton.ca/confluence/display/GCRCWEB/Lauriault
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