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Keyword: ‘location privacy’

The Invasion of the Data Snatchers: Privacy Implications for the GIS Community

February 17, 2013 1 comment

In a recent op-ed for the New York Times, Bill Keller lays out an interesting real scenario where a local editor legally obtains location information and proposes to publish it in the newspaper.  One of the points Bill raises is that just because we can increasingly map location information, it may be controversial to do so.  For example, when a newspaper mapped the names and addresses for 33,000 gun owners in two counties, thousands of protests came from gun owners and non-gun owners alike.  We may protest this type of mapping but we are also acquiescing to sweeping erosion of our privacy in many areas of life, prompting Bill to say, “when it comes to privacy, we are all hypocrites.”

What are the implications for the GIS community?  In our book, The GIS Guide to Public Domain Data and on the Spatial Reserves Blog, we dive into issues of privacy.  I first became aware of the dichotomy between personal information wariness and wanting to map that information while working for the US Census Bureau.  People may not relish divulging their own information for the census but appreciate  government grants to their communities stemming from census figures.  How did you feel back in the 1990s when grocery chains began offering plastic cards as a way to offer discounts?  You knew they would track your purchases, and they did!  But then consider the detailed data that you can obtain and map from consumer expenditure surveys based on that data.

Grocery Store

Grocery Store

I think that what makes people nervous is not so much the publishing or mapping of data in aggregated form, but the fact that individual records are stored online and potentially accessible by many.  And nearly on a daily basis, we read about those records being hacked or somehow compromised.  What is the solution?  Certainly the continued improvement of cyber security.  However, beyond the technology, it is my hope that through our work in education, that we can cultivate a generation that is ethical about data and will seek to protect and secure that data.

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Spatial Law and its Relevance to Geospatial Practitioners – Review

March 27, 2016 2 comments

Understanding the legal aspects of GIS has always been important, going back to its inclusion in the GIS&T Body of Knowledge and earlier, but with cloud-based data and services, UAVs, and other trends and tools, it is more important than ever.  A series of essays on spatial law and its relevance to geospatial professionals from the folks at the GIS Lounge provides an excellent resource to supplement our book and this blog.

In these three essays, Sangeeta Deogawanka defines spatial law and some areas that spatial law governs. She goes on to focus on remote sensing policies, Unmanned Aerial Vehicles and Unmanned Aircraft Systems (UAVs and UASs), GPS, and touches on the implications of GIS in the cloud.  She finishes by discussing how the purpose for gathering data can determine policies and regulations, including data capture, storage, use sharing, intellectual property rights, and privacy policies.

One of the resources provided at the end of the series is the site for the Centre for Spatial Law and Policy,  of which we have high regard, and to which we referred recently when we wrote about photograph location privacy.  Sangeeta also providees a useful link to 10 spatial laws and policies around the world.

What are your reactions to the relevance of spatial law to the geospatial profession and decision making?

 

GIS and the Top 10 Technology Trends

January 17, 2016 1 comment

Recently, information technology research and advisory company Gartner listed what it considers to be the Top 10 technology trends for 2016.  This insightful article, when considered in light of recent GIS developments, shows that these tech trends are both influenced by and are reflected by geotechnologies.  Whether or not you agree that the 10 trends listed here are the “most influential,” please consider their connections to GIS.  The first trend, The Digital Mesh, refers to “all devices are connected in an expanding set of endpoints people use to access applications and information, or interact with people, social communities, governments and businesses.”  GIS and GPS technologies are enabling the connections to occur, and conversely, influence the direction that GIS will go.

One manifestation of how the Digital Mesh is driving GIS is the attention over the past few years on building GIS apps.  If you would like to learn more about building your own GIS apps, consider enrolling in the free 5 week Esri MOOC “Do-it-yourself Geo Apps.“, by signing up for a free developer’s account on ArcGIS Online, or by building some of your own web apps such as with this tool.

Other trends include the “information of everything” and big data, and we’ve written about Big Data several times as well in this blog since 2012. Adaptive security architecture is another trend, developed in response to privacy breaches, and we’ve written about location privacy here and in our book.  We have also reflected about The Internet of Things, which through the sensor network is enabling GIS to become a sort of “nervous system of the planet.”  In fact, it is difficult to think of any of the trends identified without being able to identify numerous connections to GIS.

lyn_vocab

For those in the geotechnology community, it is important to stay current with the latest technology trends and reflect upon how those trends impact GIS.  This Gartner article will help.

Always on: The analysts are watching …

August 25, 2014 2 comments

We recently came across the Moves App, the always-on data logger that records walking, cycling and running activities, with the option to monitor over 60 other activities that can be configured manually. By keeping track of both activity and idle time calorie burn, the app provides ‘ an automatic diary of your life’  .. and by implication, assuming location tracking is always enabled as well, an automatic log of your location throughout each day. While this highlights a number of privacy concerns we have written about in the past (including Location Privacy: Cellphones vs. GPS, and Location Data Privacy Guidelines Released), it also opens up the possibilities for some insightful, and real-time or near real-time, analytical investigations into what wearers of a particular device or users of a particular app are doing at any given time.

Gizmodo reported today on the activity chart released by Jawbone, makers of the Jawbone UP wristband tracking device, which showed a spike in activity for UP users at the time a 6.0 magnitude earthquake occurred in the Bay Area of Central California in the early hours of Sunday 24th August 2014. Analysis of the users data revealed some insight into the geographic extent of the impact of the quake, with the number of UP wearers active at the time of the quake decreasing with increasing distance from the epicentre.

How the NAPA earthquake affected Bay Area sleepers

How the NAPA earthquake affected Bay Area sleepers.

Source: The Jawbone Blog 

This example provides another timely illustration of just how much personal location data is being collected and how that data may be used in ways never really anticipated by the end users. However, it also shows the potential for using devices and apps like these to provide real-time monitoring of what’s going on at any given location, information that could be used to help save lives and property. As with all new innovations, there are pros and cons to consider; getting the right balance between respecting the privacy of users and reusing some of the location data will help ensure that data mining initiatives such as this will be seen as positive and beneficial and not invasive and creepy.

 

 

10 Geospatial Predictions for 2013

December 30, 2012 Leave a comment

In our book The GIS Guide to Public Domain Data, we included several items from our colleague Matt Ball, who  has been writing about spatial data for many years.  His recent 10 geospatial predictions for 2013, http://www.sensysmag.com/dialog/perspectives/28845-ten-predictions-for-2013.html, touch on several key themes in our book, including growing scrutiny on location privacy, the growth of unmanned aerial vehicles and systems, cloud computing, government cuts, an increased ability to use place and location and associated tools in documentation and reporting, and government data “decrees.”

10 geospatial predictions for 2013

10 geospatial predictions for 2013

 

 

 

 

 

 

Which of these predictions do you think will come true?  Which have already happened and simply will gain momentum?  Which of these predictions do you believe have the most important implications for the field of GIS?

Latitude Mark II: All change and no change

April 18, 2017 2 comments

A recent article on BusinessInsider reported the re-launch of Google’s location sharing feature as an update to Google Maps. Originally available as Google Latitude, the first version prompted a report highlighting the risks of inadvertently sharing personal location information. Although the location sharing options seem similar second time around, the focus seems to be on the benefits of sharing this type of information and as the article notes, although the privacy concerns haven’t away, they are a footnote rather than the headline.

What has changed in the intervening years appears to be the perceptions about sharing personal location information. Is this because consumers of such services heeded the warnings and shared with discretion so fears were unfounded, or because the risks were not as great as originally thought? Other location sharing applications, such as Glympse and Swarm, stayed the course and developed their niche products away from the spotlight that tends to focus on Google. Have these services paved the way for Google to try again? Whatever the reason, Google is confident enough of a favourable reception to re-release their location sharing technology as part of their flagship application.

 

Lasers: The future of data capture and transmission?

December 12, 2016 Leave a comment

Over the last four years we have discussed some of the many challenges posed by the volume of data now available online – issues of quality, determining provenance, privacy, identifying the most appropriate source for particular requirements and so on. Being overwhelmed by the choice of data available or not always knowing what resources are available or where to start looking have been common responses from geospatial students and practitioners alike.

A recent report from the BBC on laser technology highlighted some current and future applications that have or will transform geospatial data capture, including the use of LiDAR and ultra precise atom interferometers that could be used to develop alternate navigation systems that do not rely on GPS. The article also discusses the inherent limitations of our current electronics-based computing infrastructure and the potential of silicon photonics, firing lasers down optical fibres, to help meet the demand for instant or near-instant access to data in the Internet-of-Everything world. If many feel overwhelmed now by the volumes of data available, what will technologies like silicon photonics mean for data practitioners in the future? Just because data may be available at unprecedented speeds and accessed more easily, that alone doesn’t guarantee the quality of the data will be any better or negate current concerns with respect to issues such as locational privacy. A critical understanding of these issues will be even more important if we are to make the most of these advances in digital data capture and transmission.

Pokémon GO, GIS, and Safety

July 31, 2016 5 comments

Pokémon GO has become very popular, with tens of millions of users in its first month alone, connecting users in the real world with a virtual world, using their own smartphones.  Behind the scenes Pokémon GO is powered by location based services, GIS, and GPS. Pokémon GO is built on Niantic’s Real World Gaming Platform for augmented reality, allowing users to find and catch more than a hundred species of Pokémon as they explore their surroundings. Players are represented on an augmented reality map of the real world. A user’s smartphone vibrates when it is near a Pokémon. When users encounter a Pokémon, they take aim on their smartphone’s touchscreen and throw a Poké Ball to catch it. Finding Pokémon has become much easier with the release of Pokevision, a Pokemon tracker and locator. It uses the Niantic API to grab the location of all Pokemon near you (or your selected location) and displays them on the map in real-time.

This is intriguing to me as a GIS professional for several reasons. First, Pokevision uses map tiles and geocoding services from Esri.  It is already the most popular app that uses Esri technology, which makes sense because it is aimed at the general public rather than GIS professionals.  Second, the game encourages users to explore the cities and towns where they live to capture.  As an outdoor education advocate, I am glad that people are using this game as an excuse to get outside and become active.   PokéStops are located at places that I am always encouraging people to visit, such as public art installations, trails, and historical markers and monuments. But I do want people to be safe and be aware of their surroundings whether they are using this game, any other game, their phone, or a GPS.  Third, as we discuss frequently in this blog, Pokémon GO is helping people think about the privacy and safety implications of location based services, including games.  For example, Chi Smith created a crowdsourcing story map for users to share safety tips.  As we discuss in this blog and in our book, location based services are powerful, engaging, and useful, and need to be used with care.

But like all of these technologies and the social forces surrounding them, on 1 August 2016 it was announced that the Pokemon GO developer shut down sites like Pokevision.  Keep checking this blog for updates.

pokevision.JPG

 view of the Santa Monica Pier in California.

Capturing the Great Indoors with Tango

June 27, 2016 Leave a comment

With the recent announcement of the first Tango-enabled smart phone, Google have taken a big step towards providing a crowd-sourced, indoor mapping solution. The phone’s inbuilt sensors and cameras capture the dimensions of a location and everything inside it, including the furniture. Once captured, all that internal detail becomes a potential back drop for a variety of augmented and virtual reality applications, including interior design and construction, shopping, education and gaming.

Although the data files collected are stored on each phone, Google hopes users will share their Tango data. Perhaps most appealing for Google, although not yet confirmed, the internal data collected and shared by Tango users will provide another platform for expanding their custom advertising and services.

As with other forms of location-based data, there are privacy implications to consider; it’s no longer just where you are or have been, that’s being shared, it is potentially detailed information about your home, your visits to other locations and what you did and saw there. Just how far people will be prepared to trade this new source of location data for services remains to be seen, but given the success of Google Maps and the increasing demand for better internal location information, Tango could help transform the indoor mapping scene.

 

2015 and Beyond: Who will control the data?

November 17, 2015 1 comment

Earlier this year Michael F. Goodchild, Emeritus Professor of Geography at the University of California at Santa Barbara, shared some thoughts about current and future GIS-related developments in an article for ArcWatch. It was interesting to note the importance attached to the issues of privacy and the volume of personal information that is now routinely captured through our browsing habits and online activities.

Prof. Goodchild sees the privacy issue as essentially one of control; what control do we as individuals have over the data that are captured about us and how that data are used. For some the solution may be to create their own personal data stores and retreat from public forums on the Internet. For others, an increasing appreciation of the value of personal information to governments and corporations, may offer a way to reclaim some control over their data. The data could be sold or traded for access to services, a trend we also commented on in a previous post.

Turning next to big data, the associated issues were characterised as the three Vs:

  • Volume—Capture, management and analysis of unprecedented volumes of data
  • Variety—Multiple data sources to locate, access, search and retrieve data from
  • Velocity—Real-time or near real-time monitoring and data collection

Together the three Vs bring a new set of challenges for data analysts and new tools and techniques will be required to process and analyse the data. These tools will be required to not only better illustrate the patterns of current behaviour but to predict more accurately future events, such as extreme weather and the outbreak and the spread of infectious diseases, and socio-economic trends. In a recent post on GIS Lounge Zachary Romano described one such initiative from Orbital Insights,  a ‘geospatial big data’ company based in California. The company is developing deep learning processes that will recognise patterns of human behaviour in satellite imagery and cited the examples of the number of cars in a car park as an indicator of retail sales or the presence of shadows as an indicator of construction activity. As the author noted, ‘Applications of this analytical tool are theoretically endless‘.

Will these new tools use satellite imagery to track changes at the level of individual properties? Assuming potentially yes, the issue of control over personal data comes to the fore again, only this time most of us won’t know what satellites are watching us, which organisations or governments control those satellites and who is doing what with our data.