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 board provides a brief description of the exercises.
A new article entitled “Facilitating open exchange of data and information” published in the January 2015 issue of Springer’s Earth Science Informatics journal has strong ties to the discussions we have had on this blog and in our book, namely to developments in and implications of open data. In the article, authors James Gallagher, John Orcutt, Pauline Simpson, Dawn Wright, Jay Pearlman, and Lisa Raymond are clear that while open data offers great value, there are “a number of complex, and sometimes contentious, issues that the science community must address.”
In the article, the authors examine the current state of the core issues of Open Data, including interoperability; discovery and access; quality and fitness for purpose; and sustainability. The authors also address topics of governance and data publication. I very much like the approach that the authors take–they don’t sugar coat these issues, but acknowledge that “each of the areas covered are, by themselves, complex and the approaches to the issues under consideration are often at odds with each other.” Indeed, “any comprehensive policy on Open Data will require compromises that are best resolved by broad community input.”
The authors’ research stemmed from the activities of an Open Data Working Group as part of the NSF-funded OceanObs Research Coordination Network, and hence has an ocean and atmosphere focus. On a related note, in this blog, we recently wrote about crowd sourcing coastal water navigational data. However, the open data implications that the authors describe span all disciplines that care about location.
The authors cover many topics germane to the purpose of our book and blog, and cover it so well, from their treatment of copyright and creative commons to their down-to-earth realistic recommendations that the community must do to move forward, that I consider this article “required reading” for anyone interested in open geospatial data.
Billed as a stop-gap solution on the path towards emulating some of the larger data portals (such as data.gov.au and open-data.europa.eu), GovPond is an Australian public sector data portal providing access to over 3,600 hand-curated datasets and 11 Government catalogues, including:
- Landgate SLIP
- Australian Ocean Data Network
The motivation to develop the site stemmed from a previous exercise to collate public sector data sets after the site hosts discovered ‘an enormous number of tables and tools and maps and spreadsheets that were tucked away in dark, dusty corners of the internet, near-impossible to find with a quick search.’
For all the recent advances in liberating public sector data, it seems there’s still a niche for initiatives like these to get to those corners of the Internet and provide access to data resources that might otherwise elude all but the most determined data tracker.
The USGS National Elevation Dataset (NED) is transitioning to a Lidar-based elevation model. This transition is part of the 3D Elevation Program (3DEP) initiative, whose goal is to systematically collect enhanced elevation data in the form of Lidar data over the conterminous United States, Hawaii, and the U.S. territories, with data acquired over an 8-year period. Interferometric synthetic aperture radar (IFSAR) data will be collected over Alaska, where cloud cover and remote locations preclude the use of Lidar over much of the state (yes, physical geography still matters!).
This initiative was born in response to a study funded by the USGS named “The National Enhanced Elevation Assessment.” The study documented business uses for elevation needs across 34 federal agencies, agencies from all 50 States, selected local government and Tribal offices, and private and not-for profit organizations. Each need was characterized by the following:
- Data accuracy.
- A refresh cycle for the data.
- Coverage for geographic areas of interest.
Conservative annual benefits for flood risk management alone are $295 million; for infrastructure and construction management, $206 million; and for natural resources conservation, $159 million. Results are detailed in the Dewberry report on the National Enhanced Elevation Assessment, which details costs and benefits, how the data will be collected, standards and specifications, and organizations involved in the effort. An additional report details how the data could help in terms of taking action for climate change.
How will this affect us in the geospatial data community? The NED activities and website will continue until a full transition to 3DEP is completed. 3DEP planning and research is underway at the USGS to transition to a unified service that will provide both gridded bare earth data products and point cloud data, along with capabilities to produce other derived elevation surfaces and products from 3D data. When the data does appear, data users should notice the difference in resolution and quality. In our book, we detailed the rise of Lidar data, and since its publication, these data sets have greatly expanded in quality and availability.
I recently purchased a new tablet device and was a little surprised to see it didn’t have a calculator app installed. Undeterred, I headed off to the online store, selected what seemed like a reasonable solution and started to install it. No sooner had it touched my device than it asked me was it OK to access my location information.
Why would a calculator app need access to my location information? Is subtraction optimised at sea-level, is addition better at altitude? There was no attempt to explain why the app wanted access to this information or what use the information would be put to. It felt decidedly ‘creepy’. The only two possible scenarios I could think of were:
- The location information would be harvested and sold on to pay the ‘free’ app I’d just downloaded.
- Or by tracking my location were the app developers hoping to profile my behaviour and send other app or service recommendations my way based on where I’d been?
Our location histories says so much about what we do, what we like, where we work and so on, that to marketing companies and other interested parties, location data seem to be the holy grail of consumer metrics. Any opportunity to gather that information is not to be missed.
I said No to the calculator app to using my location data but if I had been given more information, I might have been prepared to say Yes.
According to Esri’s 2014 Open Data year in review, over 763 organizations around the world have joined ArcGIS Open Data, publishing 391 public sites, resulting in 15,848 open data sets shared. These organizations include over 99 cities, 43 countries, and 35 US states. At the beginning of 2015, the organizations represent 390 from North America, 157 from Europe, 121 from Africa, 39 from Asia, and 22 from Oceania. Over 42,000 shapefiles, KML files, and CSV files were downloaded from these sites since July 2014. Recently, we wrote about one of these sites, the Maryland Open Data Portal, in this blog. Another is the set of layers from the city of Launceton, in Tasmania, Australia.
While these initiatives are specifically using one set of methods and tools to share, that of the ArcGIS Open Data, the implications on the data user community are profound: First, the adoption of ArcGIS Open Data increases availability for the entire user community, not just Esri users. This is because of the increased number of portals that result, and also because the data sets shared, such as raster and vector data services, KMLs, shapefiles, and CSVs, are the types of formats that can be consumed by many types of GIS online and desktop tools. Second, as we have expressed in our book and in this blog, while there were noble attempts for 30 years on behalf of regional, national, and international government organizations to establish standards, to share data, and to encourage a climate of sharing, and while many of those attempts were and will continue to be successful, the involvement of private industry (in this case, Esri), nonprofit organizations, and academia will lend an enormous boost to government efforts.
Third, the advent of cloud-based GIS enables these portals to be fairly easily established, curated, and improved. Using the ArcGIS Open Data platform, organizations can leave their data where it is–whether on ArcGIS for Server or in ArcGIS Online–and simply share it as Open Data. Esri uses Koop to transform data into different formats, to access APIs, and to get data ready for discovery and exploration. Organizations add their nodes to the Open Data list and their data can then be accessed, explored, and downloaded in multiple formats without “extraneous exports or transformations.” Specifically, organizations using ArcGIS Open Data first enable the open data capabilities, then specify the groups for open data, then configure their open data site, and then make the site public.
I see one of the chief ways tools like ArcGIS Open Data will advance the open data movement is through the use of tools that are easy to use, and also that will evolve over time. Nobody has an infinite amount of time trying to figure out how to best serve their organization’s data, and then to construct the tools in which to do so. The ability for data-producing organizations to use these common tools and methods represents, I believe, an enormous advantage in the time savings it represents. As more organizations realize and adopt this, all of us in the GIS community, and beyond, will benefit.
The signing of the Open Data Charter by G8 leaders in 2013 promised to make public sector data open, free of charge and available to all in re-usable formats. However, despite the attention open data subsequently received, a recent report by the World Wide Web Foundation (featured in a BBC article) highlighted some ongoing problems making the pledges enshrined in the Open Data Charter a reality. Many countries have failed to deliver what the report referred to as a policy framework for open data.
Although the UK and USA were at the top of the global rankings for countries providing access to open data, they and many other countries still have a lot of work before they can claim to have fully open government. Of particular note in the UK is the ongoing debate over access to the Royal Mail’s Postcode Address File (PAF). Although the PAF dataset is cited as the ‘definitive source of postal address information’ in the UK and used in many digital mapping applications, the current charges and licensing arrangements deter many potential users of the dataset. Many commentators have argued that the PAF dataset could become the standard address resource for commercial and non-commercial uses in the UK if it was made available in an easy to use and open format. This would encourage much wider adoption of the dataset and prevent the further proliferation of alternatives sources of address information. With the spotlight back on open access to address data, will 2015 be the year the PAF joins the growing list of open, and free of charge, spatial datasets?
An infographic on The Visual Communication Guy website from Dr Newbold, whose background is Rhetorics, Communication, and Information Design, offers a way to fairly quickly and easily help data users decide if and how they can use copyrighted online images. Given the ease of sharing of data in our cloud-based GIS world, we write frequently in this blog and focus part of our book on discussing copyright. While Dr Newbold’s infographic is intended for those using still photography, much can be applied to spatial data. Keeping with our theme of being critical of data, however, verify this infographic against other sources before beginning any project using imagery and data that are not your own.
My rule of thumb in using photography in web maps, storymaps, map layouts, web pages, and in other ways is to use my own photographs whenever possible, such as on this story map, since according to copyright law, I own the copyright to them. Lacking my own images, I then turn to US government or other non-copyrighted images, or images marked as Creative Commons, such as most images from Wikimedia. If all of these sources do not result in the images I need, and I truly want to use a copyrighted image, such as a few on this Colorado map I created, I ask permission, clearly stating my (educational) intent, and I do not use the image unless the permission is granted.
Clear, helpful definitions of key terms accompany the graphic: (1) Copyright: The protection given to any created image or work from being copied or distributed without permission. All images are immediately given copyright to the creator when the image is created. (2) Fair Use: The legal right to use copyrighted images as long as the images are used for educational, research, or personal use or as long as the image benefits the public good in some way. (3) Creative Commons: Images that are copyrighted but the creator has put provisions on their use. A creative commons license might stipulate, for example, that an image can be used as long as it isn’t modified in any way. (4) Public Domain: Images that no longer have copyright restrictions either because the creator willingly relinquished their copyright or because the creator is dead and no one owns the copyright.