The World Bank recently announced the release of a new Spatial Agent app for iOS and Android (web version also available). The app curates an already impressive collection of public domain spatial datasets in a variety of formats from over 300 web services, with the developers promising to add more iconic datasets. App users can choose between the following data sources:
- Indicators (for example % of female employees in agriculture or % of forested land areas)
- Map layers
- Other (for example the Nepalese major river system or hydro power plants in Malawi)
The data can be displayed against a back-drop of one of four base map sources:
- Shaded relief (NOAA)
- Street map
- Topographic map
- World imagery
with the option to set the area of interest by Country, Basin or Region.
In this example a layer of CIESIN’s earthquake hazard frequency and distribution data is displayed against a backdrop of world imagery.
Each dataset is accompanied by a short description of the source and intended purpose and as the datasets are public domain, they may be shared through email and/or social media.
The World Bank hope that the app will help spread the news about public domain data and go some way to organising the ‘current big data cosmos’.
A theme running throughout our book The GIS Guide to Public Domain Data is to be critical of the data that you are using–even data that you are creating. Thanks to mobile technologies and the evolution of GIS to a Software as a Service (SaaS) model, anyone can create spatial data, even from a smartphone, and upload it into the GIS cloud for anyone to use. This has led to incredibly useful collaborations such as Open Street Map, but this ease of data creation means that caution must be employed more than ever before, as I explain in this video.
For example, analyze a map that I created using Motion X GPS on an iPhone and mapped using ArcGIS Online. It is shown below, or you can interact with the original map if you prefer. To do so, access www.arcgis.com/home (ArcGIS Online) and search for the map entitled “Kendrick Reservoir Motion X GPS Track” or go directly to http://bit.ly/Rx2qVp. Open the map. This map shows a track that I collected around Kendrick Reservoir in Colorado USA. This map was symbolized on the time of GPS collection, from yellow to gradually darker blue dots as time passed.
Note the components of the track to the northwest of the reservoir. These pieces were generated when the smartphone was just turned on and the track first began, indicated by their yellow color. They are erroneous segments and track points. Notice how the track cuts across the terrain and does not follow city streets or sidewalks. Change the base map to a satellite image. Cutting across lots would not have been possible on foot given the fences and houses obstructing the path. When I first turned on the smartphone, not many GPS satellites were in view of the phone. As I kept walking and remained outside, the phone recorded a greater number of GPS satellites, and as the number of satellites increased, the triangulation was enhanced, and the positional accuracy improved until the track points mapped closely represented my true position on the Earth’s surface.
Use the distance tool in ArcGIS Online to answer the following question: How far were the farthest erroneous pieces from the lake? Although it depends on where you measure from, some of the farthest erroneous pieces were 600 meters from the lake. Click on each dot to access the date and time each track point was collected. How long did the erroneous collection continue? Again, it depends on which points you select, but the erroneous components lasted about 10 minutes. At what time did the erroneous track begin correctly following my walk around the lake? This occurred at 11:12 a.m. on the day of the walk. [Take note of the letters I drew along the southwest shore of the reservoir!]
This simple example points to the serious concern about the consequences of using data without being critical of its source, spatial accuracy, precision, lineage, date, collection scale, methods of collection, and other considerations. Be critical of the data, even when it is your own!
If you are a frequent reader of this blog or of technology related news feeds, it should come as no surprise that location has rapidly become one of the basic means of communicating, marketing, and crowdsourcing in our modern world. Is the data that you are inadvertently communicating through your mobile device that powers many web mapping services via crowdsourcing making our world more efficient and sustainable? Take the common example of your position moving through traffic, communicated from location information on your smartphone, calculated using the miracle of web mapping technology into speed, and combined with others to create real-time information about which routes are currently running sluggishly and which are running quickly in your metropolitan area. Most would argue that yes, this does make people’s commutes more efficient by saving time. Moreover, it saves fuel through a multiplier effect if even a fraction of the vast number of people commuting at any given time around the world adjust their behavior by avoiding traffic snarls and idling their engines.
Is that same data compromising your personal privacy? Most would probably argue that while each of us gives up a bit of location privacy for these real time traffic feeds, the resulting public benefit far outweighs the costs. An analogy from the 1990s might be the personal information that most of us shared with grocery businesses in order to obtain a ‘discount card’ from our local food store.
The “tipping point” of concern for some on the personal privacy seems to be where location services allow you, and by extension, depending on the application, anyone, to see your own personal location and movements over time. For example, examine this page describing how location reporting from an iPhone and iPad allows Google to store a history of your location devices where you are logged into your Google account and have enabled location history, or related articles about Android devices. There are ways to override this location history, but it takes just that–overriding the defaults, and–will this override be possible in the future?
I checked, and I don’t have any location history, at least in Google. But would it matter if I did? As a person who loves and works with maps on a daily basis, part of me was a little disappointed, actually, that I couldn’t see what I thought might be a fascinating set of maps showing some of my field work over the past few months, which included some brisk but pleasant walks along the lakefront in Chicago during the AAG annual meeting and a trek through a wetland in Wisconsin afterwards.
I frequently work with secondary and university students, and in my conversations with them, I’ve noticed that the younger generation generally doesn’t see a problem with sharing anything in the digital world, whether it is their location, photos, videos, links, whatever. So, is it just my generation that is a wee bit nervous about the potential harm that could result from personal data being mined? Should other generations be concerned? Our goal in this blog and in our book is to raise awareness of the power and utility of geospatial information, and also to critically assess its quality,use, and implications.