Welcome

April 16, 2012 5 comments

Welcome to the Spatial Reserves blog.

The GIS Guide to Public Domain Data was written to provide GIS practitioners and instructors with the essential skills to find, acquire, format, and analyze public domain spatial data. Some of the themes discussed in the book include open data access and spatial law, the importance of metadata, the fee vs. free debate, data and national security, the efficacy of spatial data infrastructures, the impact of cloud computing and the emergence of the GIS-as-a-Service (GaaS) business model. Recent technological innovations have radically altered how both data users and data providers work with spatial information to help address a diverse range of social, economic and environmental issues.

This blog was established to follow up on some of these themes, promote a discussion of the issues raised, and host a copy of the exercises that accompany the book.  This story map provides a brief description of the exercises.

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A review of the North Dakota State GIS Portal

October 9, 2017 2 comments

I recently had the honor of co-keynoting the North Dakota GIS conference.  While preparing for the conference, I re-acquainted myself with the North Dakota State GIS portal.  The timing was perfect because a team of dedicated and expert collaborators from many organizations had just completed work on a new portal that replaced their old Hub Explorer resource.  The new portal, accessible here, includes information on how to connect with the state’s GIS community through events and networking.  More germane to our topic in this blog, though, it also contains a link to the data sets themselves via the Hub Data Portal.   The portal is thoughtfully laid out, with the ability to view data by content type and topics.  The North Dakota GIS Hub Data Portal uses DKAN, the Drupal-based version of CKAN, the world’s leading open-source open data publishing platform. It provides a complete open source software solution for data publishers, and adheres to the API, data, and functionality standards of CKAN. The goal of this project is to combine the utility of CKAN with the ease of maintenance and extensibility of Drupal.

The portal is designed with the data user in mind:  It doesn’t include a lot of bandwidth-consuming, unnecessary graphics and maps, but allows the user to quickly go to what he or she needs.  The site also provides many options for the data user–the raw data to download, CSVs, HTMLs, XMLs, and even rest endpoints that allow the data to be consumed in web GIS platforms such as ArcGIS Online.  See the example for wildlife management areas here.  And the data sets can be very detailed, too, such as the recent addition of one-foot contours for Bismarck and Mandan.

This portal is unique in that the site includes stories about interesting projects involving people and the land in the state, with links to infographics, maps, and data.  These stories in my opinion provide good “elevator speeches” as to the positive benefits that are derived from the use of GIS, and they also provide good case studies to give students and others ideas for research projects.  The Groups tab gives useful links to “who’s who” in the state.

The site also includes a “Visual ND” site with a rich set of applications, maps, data, documents, and web sites.  The historical aerial photographs of North Dakota are also being scanned, and are available here in TIFF format.  It is my hope that these photos will eventually have REST endpoints that will allow them to be displayed directly into ArcGIS Online and other web mapping applications, such as the resource that we reviewed in Iowa, here.

We have reviewed many data portals in our book and on this blog–some good, some not-so-useful.  The North Dakota GIS Hub data portal is one of the most useful I have ever seen.

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The front page of the North Dakota GIS Hub Data Portal.

Categories: Public Domain Data

Review of the Spatial Reserves Exercises

September 26, 2017 Leave a comment

We’re currently reviewing the exercises that were developed to illustrate some of the issues discussed in the GIS Guide to Public Domain Data publication and here on the Spatial Reserves blog, with the intention of releasing an updated set of exercises next year. The proposed style and format of the updated exercises is the subject of my dissertation as part of a M.Sc. in Digital Education at the University of Edinburgh.

Here’s where you can help …  I’m looking for volunteers to review a presentation on two exercises and complete four short questionnaires. This should only take 10-15 minutes of your time.

The study is available at Digital Education – Multi-media study

Thanks in advance,

Jill C.

 

Era of Big Data is Here: But Caution Is Needed

September 25, 2017 Leave a comment

As this blog and our book are focused on geospatial data, it makes sense that we discuss trends in data–such as laws, standards, attitudes, and tools that gradually helping more users to more quickly find the data that they need.  But with all of these advancements we continue to implore decision makers to think carefully about and investigate the data sources they are using.  This becomes especially critical–and at times difficult–when that data is in the “big data” category.  The difficulty arises when big data is seen as so complex that often it is cited and used in an unquestioned manner.

Equally challenging and at times troublesome is when the algorithms based on that data are unchallenged, and when access to those algorithms are blocked to those who seek to understand who created them and what data and formulas they are based on.  As these data and algorithms increasingly affect our everyday lives, this can become a major concern, as explained in data scientist Cathy O’Neil’s TED talk,  who says “the era of blind faith in big data must end.”

In addition, the ability to gain information from mapping social media is amazing and has potential to help in so many sectors of society.  This was clearly evident with the usefulness of social media posts that emergency managers in Texas and Florida USA mapped during the August-September 2017 hurricanes there.  However, with mapping social media comes an equal if not greater need for caution, as this article that points out the limitations of such data for understanding health and mitigating the flu.  And from a marketing standpoint, Paul Goad cautioned here against relying on data alone.

It is easy to overlook an important point in all this discussion on data, big data, and data science. We tend to refer to these phenomena in abstract terms but these data largely represent us – our lives, our habits, our shopping preferences, our choice of route on the way to work, the companies and organisations we work for and so on. Perhaps less data and data science and more humanity and humanity science.  As Eric Schmidt, CEO of Google, has said, “We must remember that technology remains a tool of humanity.  How can we, and corporate giants, then use these big data archives as a tool to serve humanity?”

Understanding your data

Use caution in making decisions from data–even if you’re using “Big Data” and algorithms derived from it.    Photograph by Joseph Kerski. 

Categories: Public Domain Data

Ethics in Geospatial Decision-Making

September 11, 2017 Leave a comment

Our book and this blog frequently focus on the importance of making wise decisions when using geospatial data.  We often discuss the two-edged sword in which we are living with regard to the modern GIS era:  ‘Tis wonderful to have a plethora of geospatial data services at our fingertips, many of which are in real time, many are capable of being visualized in 3-D, and many are updated and curated with regularity.  Coupled with these services are a variety of easy-to-use spatial analysis tools that come coupled with desktop and web-based GIS software platforms.  But with this availability of data and easy-to-use tools brings increasing likelihood that decisions will be made based on them without regard to the data’s sources, scales, update frequency, map projection, completeness of attributes, and other measures of quality.

Decisions are still in large part made by humans, and the human element has always been laden with ethical decisions, whether we realize it or not.  Adding to the ethical element is the fact that geospatial decisions involve land, which has economic but also personal and inherent value, and affects people who live on that land.  Geospatial decisions also affect the very air we breathe and water we drink.

How can we be more purposefully aware of ethical elements in our decisions based on geospatial data?  Some insightful chapters and articles will, I think, be of help.  One is the new chapter on Professional and Practical Ethics of GIS&T in the UCGIS GIS&T Body of Knowledge project by David DiBiase.  Another is a 7-Step guide to ethical decision-making, written in 1999 but still incredibly relevant.  I particularly like the tests that the author describes–the harm test, the publicity test, the defensibility test, the reversibility test, the colleague test, and the organization test.

Another excellent resource is Penn State’s ethics education resource for geospatial professionals, which lists interesting and pertinent case studies, codes of ethics, university course syllabi, and other resources.  In a recent article in Directions Magazine, Dr Diana S. Sinton explores how ethics can be integrated into geospatial education.   She advocates that ethics be threaded throughout even an introductory GIS course rather than be relegated to one lecture, as is often the case.

What are your thoughts regarding ethics in GIS?

jjk_question.PNGGeospatial decisions are ethical decisions as well.

Categories: Public Domain Data

Evaluating GIS costs and benefits

August 28, 2017 1 comment

One of the themes in our book and this blog is to carefully evaluate the costs and benefits of geospatial data.  This should be considered if you are a consumer of data, and are debating whether to purchase data that may be “cleaned up”, thereby saving you time, or to download a free “pre-processed” version of that data, which saves you up-front money but may require quite a few hours or your time or your staff’s time.  However, a data producing organization should also evaluate costs and benefits when they decide how to serve it, and if and how to charge for it.

Chapter 4 of our book delves into these questions: “What is the true cost and value of spatial data?  How can the cost and value of spatial data be measured?  How do the policies determining cost and access ultimately affect the availability, quality, and use of spatial data?”

Other resources might be helpful:  One of my favorite pieces is this essay from Geospatial World on the Economic Value of Geospatial Data–The Great Enabler as is this economic studies for GIS operations document from NSGIC.  A series of 10 case studies are summarized in an e-book from Esri entitled Return on Investment, and here is the results of research of 82 cost-benefit assessments across multiple countries.  One of my favorite “benefits from GIS implementation” pieces is this recent brief but pointed document from Ozaukee County.  A dated but still solid chapter on this topic from Obermeyer is here, with a case study in Ghana here.  The economic impact infographic that has probably received the most attention is from Oxera’s well-done “Economic impact of Geo Services” study.

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The top of the “Economic Impact of Geo Services” infographic from Oxera’s study.

What are your thoughts?  Should organizations still be charging for data in the 21st Century?  Should all geospatial data be open for anyone to use?  How should organizations pay for the creation and curation of geospatial data as the audience and uses for that data continue to expand?  Once geospatial data services are online, how can they best be updated and curated?

Best Available Data: “BAD” Data?

August 14, 2017 3 comments

You may have heard the phrase that the “Best Available Data” is sometimes “BAD” Data. Why?  As the acronym implies, BAD data is often used “just because it is right at your fingertips,” and is often of lower quality than the data that could be obtained with more time, planning, and effort.  We have made the case in our book and in this blog for 5 years now that data quality actually matters, not just as a theoretical concept, but in day to day decision-making.  Data quality is particularly important in the field of GIS, where so many decisions are made based on analyzing mapped information.

All of this daily-used information hinges on the quality of the original data. Compounding the issue is that the temptation to settle for the easily obtained grows as the web GIS paradigm, with its ease of use and plethora of data sets, makes it easier and easier to quickly add data layers and be off on your way.  To be sure, there are times when the easily obtained is also of acceptable or even high quality.  Judging whether it is acceptable depends on the data user and that user’s needs and goals; “fitness for use.”

One intriguing and important resource in determining the quality of your data can be found in The Bad Data Handbook, published by O’Reilly Media, by Q. Ethan McCallum and 18 contributing authors.  They wrote about their experiences, their methods and their successes and challenges in dealing with datasets that are “bad” in some key ways.   The resulting 19 chapters and 250-ish pages may make you want to put this on your “would love to but don’t have time” pile, but I urge you to consider reading it.  The book is written in an engaging manner; many parts are even funny, evident in phrases such as, “When Databases attack” and “Is It Just Me or Does This Data Smell Funny?”

Despite the lively and often humorous approach, there is much practical wisdom here.  For example, many of us in the GIS field can relate to being somewhat perfectionist, so the chapter on, “Don’t Let the Perfect be the Enemy of the Good” is quite pertinent.   In another example, the authors provide a helpful “Four Cs of Data Quality Analysis.”  These include:
1. Complete: Is everything here that’s supposed to be here?
2. Coherent: Does all of the data “add up?”
3. Correct: Are these, in fact, the right values?
4. aCcountable: Can we trace the data?

Unix administrator Sandra Henry-Stocker wrote a review of the book here,  An online version of the book is here, from it-ebooks.info, but in keeping with the themes of this blog, you might wish to make sure that it is fair to the author that you read it from this site rather than purchasing the book.  I think that purchasing the book would be well worth the investment.  Don’t let the 2012 publication date, the fact that it is not GIS-focused per se, and the frequent inclusion of code put you off; this really is essential reading–or at least skimming–for all who are in the field of geotechnology.

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Bad Data book by Q. Ethan McCallum and others. 

 

Data Practitioner Profile Document Reviewed

July 31, 2017 2 comments

The recent document entitled “Profile of the Data Practitioner” (created by a panel with a diverse background, published by EDC Newton Massachusetts USA) is useful in several ways.  First, it succinctly outlines many of the issues we have focused on in this blog and in our book–data quality, critical thinking, domain knowledge, and others.  Second, it lists skills, knowledge, and behaviors, and therefore is an excellent though brief supplement to the Geospatial Technology Competency Model.  Third, it lists equipment, tools, and supplies, future trends, and industry concerns.  Fourth, page 2 of the document is a practical application of the Geographic Inquiry Model, as it describes how the data practitioner initiates a project, sources the data, transforms the data, analyzes the data, closes out the project, and engages in professional development.

The document should be helpful for those pursuing their own career path in GIS and data science, and for those designing and teaching courses and workshops in GIS in academia, nonprofit organizations, private companies, and government agencies.  I only wish the document was longer or linked to a longer report that would provide more detail.  Still, for a succinct document summarizing some key items that data practitioners need to have in place, this document is worth spending time reviewing and telling others about.