Hat Tip to arstechnica for this article
This is a classic example of why we need to question where our data comes from. Once you stop to think about it, there are a number of possible explanations as to how this island came to be on charts and maps when it most likely never was. Effective spatial data analysis needs people’s brains to actually check out any anomalies thrown up when combining datasets. Algorithms can alert us to there being something that ‘needs a closer look’ but the actual looking is probably best done by someone who understands geographic information.
Similarly, any response to a spatial data anomaly must be informed by a number of factors, including things such as:
- where the data was sourced from
- who collected it and why
- what we are using it to do
In some instances a conservative response is the best way to go, in others, we may get away with ignoring the fact that an anomaly was even found. What we shouldn’t do is assume that there is a “correct response” that will then apply for all possible instances – real life just doesn’t work that way.
Unless you happened to be, or know, an oceanic vulcanologist, ‘floating pumice islands‘ are probably not the explanation that comes to mind!
The second “LiDAR as Art” competition is underway and the entries are totally worth a look! I have several favourites, including:
The ILMF 2013 “LiDAR as ART” Contest, organised by GeoDigital International, has online voting open to the public till Feb 5th. Check out all the images in the flicker stream as many of them have explanations of how they were made and go vote for your favourites!
and they should!
Amanda Ripley @ PopTech 2012 looks at why different areas perform as they do when compared using standardised tests. Her approach is well represented by the quote included in the Vimeo posting of the talk:
“Kids have strong opinions about school. We forget as adults how much time they sit there contemplating their situation.”
(Hat Tip: Scott McLeod @ Dangerously Irrelevant)
While this is an American talk focusing on the American situation, it makes some really interesting observations.
Continue reading “Kids have strong opinions about school”
“The Russian weather satellite, Elektro-L, has captured what is claimed to be the highest resolution, single-capture image ever taken of Earth from space.” From Spatial Source
Shows off the images obtained between May 14th and May 20th, 2011:
Simon Sharwood from the website The Register has written about the online mapping problems caused by weak GPS and sloppy check-ins to social media services from smartphones:
“Next time you check in with foursquare or Facebook, please stand right outside the venue, make sure your smartphone has a very good GPS signal and describe the location accurately.
That’s the wish of the spatial data community, which is getting grumpy about user-generated spatial data.
To understand why…”
Click here to read the full article
Read the comments too!
Particularly if you are wondering about this post’s title…
Brandon Brown observes that the users of GIS services
“want to be able to find without looking, understand without learning, and do it all fast.”
Which sounds about right to me!
The article contains selected Zen-based sayings that have been interpreted into strategies that his team follow in the quest for GIS communication enlightenment in their work at the City of Dublin.
Having finally created a twitter account, and ‘following’ some IRL and online contacts, I was introduced to the Flowing Data via a link from one of the tweets. The whole site looks fascinating but the self-surveillance category has some really interesting posts, including:
From a GI S&T perspective, all of these self-surveillance tools are likely to be of interest in one way or another.
From a cartographic perspective, the post “Van Gogh for the colorblind” talks about research that applied various colour filters to Van Gogh’s paintings which highlights the importance of picking colours wisely and thinking about how your maps and diagrams look to others. A link to an online tool by Kazunori Asada that allows you to apply three colour vision types to your own images.