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COVID-19 and Privacy Concerns

March 25, 2020 2 comments

Geospatial technology and spatial data are being used to tackle all major world issues, including the current COVID-19 situation.  And because the COVID-19 situation is so tied to individuals and their movements over space and time, it is no surprise that needs for data bump into privacy issues.   A recent article entitled, “As COVID-19 Accelerates, Governments Must Harness Mobile Data to Stop Spread” with a subtitle of, Despite privacy concerns, “contact tracing” using GPS data may be our best bet to contain this large and fast-growing pandemic, was recently published here, via MIT Press.

In the article, the authors, Shekhar and Shekhar, from the University of Minnesota and the Yale School of Medicine, respectively, argue that smartphone-enabled location tracing without explicit permission from the smartphone owner needs to be implemented without delay to save lives.  The authors even lay out a specific plan for it to happen, and also comment that, “If smartphone trajectories of non-infected individuals need to be excluded for privacy reasons, the locations and times of potential exposure could be publicly shared without divulging patient names or sensitive medical information.”

No doubt that in the days and weeks to come, societies will have to make some difficult decisions regarding data and privacy, given the challenges before us.

–Joseph Kerski

 

Potential Harm from Geotagging Photographs

March 22, 2020 9 comments

Recently, National Geographic staff wrote an interesting and thoughtful piece about the potential harm of “over-loving” a place resulting from tourists posting geotagged photographs:   https://www.nationalgeographic.com/travel/features/when-why-not-to-use-geotagging-overtourism-security/

As a geographer, I confess that I have mixed feelings about this.   As someone keenly interested in the protection of natural places such as caves (as a lifelong caver and a geographer), riparian zones, beaches, lava fields, prairies, woodlands, and many other special places, part of me wants to see few visitors tramping on those places.  Hence, I see the point that the article makes about overexposure to places, whether from guidebooks, tweets, Instagram posts, Google map posts, or other means.  But as someone who at the same time wants to know about these places so I can too can explore them, I appreciate the crowdsourcing happening on our planet–the sharing of ordinary and extraordinary places on our planet for the sheer joy of them, and telling others about them, from ordinary people–citizen scientists.  Does a solution exist reconciling these two viewpoints?  Please share in the comments section.

On the potential downside of geotagging photos, we wrote a synopsis of the following story a few years ago; in this case, potential harm to rare species from location-tagged data:  https://spatialreserves.wordpress.com/2017/11/20/potential-harm-to-rare-species-from-location-tagged-data/

–Joseph Kerski, showing one of my favorite places and viewpoints on the planet, below.  Should I share where I took this photo so others can go there and enjoy the view?  Or just leave it untagged so only a few will visit?

aa_wellington

Mystery location. 

Possible implications to census data from Disclosure Avoidance System

The new Disclosure Avoidance System (DAS) being used for the 2020 US Census counts could have implications for all users of census data.  First, from the National Conference of State Legislatures, see this informative overview: https://www.ncsl.org/research/redistricting/differential-privacy-for-census-data-explained.aspx.   To dig deeper, see this US Census Bureau story map and this dashboard as well as this NY Times article.

From a GIS perspective, here is an essay about spatial analysis and differential privacy from Lauren Scott Griffin: https://storymaps.arcgis.com/stories/ec6d9711a3364d3db5c18fc9061e312f

And for a map-based set of examples, compare places on this Esri dashboard: https://arcgis-content.maps.arcgis.com/apps/opsdashboard/index.html#/04451f90e7b049f39aa6647a41b986ac

Why should you care?  This is all extremely relevant to the central theme of this blog–be critical of the data.  Know what methods are used to gather the data, and the models or algorithms employed to generate the results, and be a more informed data consumer.

–Joseph Kerski

Categories: Public Domain Data Tags: ,

Creating fake data on web mapping services

February 16, 2020 2 comments

Aligned with our theme of this blog of “be critical of the data,” consider the following recent fascinating story:  An artist wheeled 99 smartphones around in a wagon to create fake traffic jams on Google Maps.  An artist pulled 99 smartphones around Berlin in a little red wagon, in order to track how the phones affected Google Maps’ traffic interface.  On each phone, he called up the Google Map interface.  As we discuss in our book, traffic and other real-time layers depend in large part on data contributed to by the citizen science network; ordinary people who are contributing data to the cloud, and in this and other cases, not intentionally.  Wherever the phones traveled, Google Maps for a while showed a traffic jam, displaying a red line and routing users around the area.

It wasn’t difficult to do, and it shows several things; (1) that the Google Maps traffic layer (in this case) was doing what it was supposed to do, reflecting what it perceived as true local conditions; (2) that it may be sometimes easy to create fake data using web mapping tools; hence, be critical of data, including maps, as we have been stating on this blog for 8 years; (3) the IoT includes people, and at 7.5 billion strong, people have a great influence over the sensor network and the Internet of Things.

The URL of his amusing video showing him toting the red wagon around is here,  and the full URL of the story is below:
https://www.businessinsider.com/google-maps-traffic-jam-99-smartphones-wagon-2020-2

I just wonder how he was able to obtain permission from 99 people to use their smartphones.  Or did he buy 99 photos on sale somewhere?

–Joseph Kerski

 

 

 

Key Global Biodiversity and Conservation Data Sources

February 2, 2020 Leave a comment

Advances in the following two resources and the sheer volume and diversity of data they contain merit mention in this data blog and, I recommend, considering investigating as part of your own work.

  1.  The Global Biodiversity Information Facility (www.gbif.org) contains point data on an amazing number and diversity of species.  It also over 12 million research-grade  observations from the i-Naturalist citizen science using community.
  2. IUCN:  The International Union for Conservation of Nature:  You can filter and use the data with IUCN Spatial data downloads for polygon boundary layers from their data portal, at https://www.iucnredlist.org/resources/spatial-data-download.  The IUCN Red List of Threatened Species™ contains global assessments for 112,432 species. More than 78% of these (>88,500 species) have spatial data.  The spatial data provided on the site are for comprehensively assessed taxonomic groups and selected freshwater groups.  The site indicates that some species (such as those listed as Data Deficient) are not mapped and that subspecies, varieties and subpopulations are mapped within the parental species. The data are in Esri shapefile format and contain the known range of each species, although sometimes the range is incomplete. Ranges are depicted as polygons, except for the freshwater HydroBASIN tables.

To use either resource, all you need is a free account.  The data sets can be combined, after which you can examine potential outliers, perform hot spot analysis, use the data in space time cubes, create habitat suitability models and risk models, and much more.

Joseph Kerski

gbif.PNG

Some of the resources available from the Global Biodiversity Information Facility (GBIF).  

Curated list of thousands of ArcGIS server addresses

January 19, 2020 1 comment

Joseph Elfelt from mappingsupport.com recently added many government ArcGIS server addresses to his curated list. The list features over 2,200 addresses for ArcGIS servers from the federal level to the city level. All links are tested by his code once per week and bad links are fixed or flagged, and a new list is posted every Wednesday morning. The list is here,  While we have written about this very useful list in the past, such as here, this is a resource that is worth reminding the community about. And, as a geographer, I find the geographic organization of this list quite easy to follow.

While browsing the list recently, I found, among many other things, an Amtrak train route feature service (shown below), resources at the Wisconsin historical society, and water resources data from the USGS Oklahoma Water Sciences Center.

Joseph is also actively maintaining his “GISsurfer” application, which allows the user community to examine GIS data in a map-centric manner.

amtrak

Amtrak routes data service, which I found to be fascinating and which I discovered on Joseph Elfelt’s server listing.

I highly recommend that you browse this list if you are in need or anticipate being in need of geospatial data!

–Joseph Kerski

Dangermond and Goodchild on building geospatial infrastructure

January 5, 2020 2 comments

A new open access article from Dangermond and Goodchild on building geospatial infrastructure is germane to this blog and our book’s focus on geospatial data.  Moreover, at the dawn of the new decade, I regard this article as an important one to read and to reflect upon.

The article’s abstract states, “Many visions for geospatial technology have been advanced over the past half century. Initially researchers saw the handling of geospatial data as the major problem to be overcome. The vision of geographic information systems arose as an early international consensus. Later visions included spatial data infrastructure, Digital Earth, and a nervous system for the planet. With accelerating advances in information technology, a new vision is needed that reflects today’s focus on open and multimodal access, sharing, engagement, the Web, Big Data, artificial intelligence, and data science. We elaborate on the concept of geospatial infrastructure, and argue that it is essential if geospatial technology is to contribute to the solution of problems facing humanity.”

Besides providing a concise yet insightful history of the evolution of GIS and spatial data, one of the most thought provoking statements in the article, in my opinion, is that “a digital twin should also replicate how the Earth works, by using software to reproduce the processes that modify the Earth’s physical and social systems.”  In other words, for us to solve the complex problems of our 21st Century world, GIS must be able to show how the Earth’s systems interact and work, and moreover, how they should work; that is, how can we use GIS and spatial data to plan a more resilient future?

I also found the following statement to be wonderfully useful, “Today we think of the basic element of geospatial technology as a tuple <x,y,z,t,a> where x, y, and z are location in three-dimensional space, t is time, and a is an attribute of that location in space-time.”  And I have personally used Jack Dangermond’s metaphor of GIS being an intelligent nervous system for the planet, mentioned in the article, dozens of times in my own presentations over the past four years.

But the article is much more than an account of history and a conceptualization of how to understand GIS–it offers challenges to us in the GIS community.   For example, it states that “little advance has been made in measuring, representing, and dealing with the uncertainty that is always present when geographic reality is measured and captured in digital data, but not always present in published maps.  The article also takes special note of key progress that has led us to this very exciting moment in the use of geospatial technology, including (1) portals, (2) open data, (3) engagement, (4) collaboration, (5) story maps, (6) device independence, and (7) Cloud GIS.  These are not just ideas, they are happening now, with real tools and infrastructure that enable people to accomplish real tasks.  The article also highlights some advancements that can lead us the very real possibility that GIS can “break wide open” (my phrase) in the decade of the 2020s with (1) GeoAI, (2) scripting and workflows, (3) replicability, (4) predictive modeling, and (5) real-time analysis.

The article concludes with what I believe to be an excellent question that cuts to the heart of what we in the industry should be asking:  “What, then, should be the goals of geospatial infrastructure, and how should it be configured?”  In other words, the advancements are great, but we need to ask ourselves, where should we be taking the technology, if we are seeking a more sustainable future?  It’s not enough to ride on the ship; we need to steer it.  Dangermond and Goodchild lay out some challenges in this section, such as the following statement, which I think points to “think outside of the software box and re-engineer the software tool if necessary” — “Decisions that were made during periods of very limited computing power become enshrined in practices that may be very hard to shake.”  They also discuss resilience, protecting biodiversity, collaboration, and ensuring individual privacy.   The authors end with this statement, which is I believe a challenge for all of us to take seriously, “But what is missing in our view is a vision, a “moonshot,” a statement of principles against which progress can be measured.”

–Joseph Kerski