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.
Geoff White, technology producer for Channel 4 News in the UK, recently published an interesting article documenting the secret lives of phones. As part of the Data Baby project the team at Channel 4 set up a mobile phone with some pre-installed and downloaded apps and a fake virtual identity. They then began to monitor the activity on the phone over a 24 hour period. Although much of the activity on the phone was to be expected – the messaging and communication traces from calls, texts and Internet surfing – some of the activities on the phone came as a bit of a surprise to the researchers. Even when the phone wasn’t engaged in any deliberate user activity and was for all intents and purposes idle, thousands of messages were sent by the phone to various servers around the world.
Along with the text, images and other data packages, precise location details were being transmitted. In some cases that location information, along with details about the phone, was sent to advertising companies who subsequently used the data to target their advertising. Ad campaigns aside, it does raise some other questions about who else could have access to the data? The Channel 4 News team used a special device to intercept all the communication from the phone. Who else could use such a device and how else could that data be used?
The recent combination of always being connected to phone and wi-fi networks and the increasing use of data hungry and data generous apps have been responsible for this significant increase in the amount data about us and our devices that is transmitted. But how do we combat this? Is the solution to only have our phones on when we actually need to use them? That may appeal to some, but for many others the ‘always on’ lifestyle is here to stay. For most, myself included, The Channel 4 News article was probably a bit of an eye-opener. However, the more we know about how our devices and apps behave, the more chance we have of taking back control over the information we once thought was private.
Last year we blogged about the AsiaPop and AfriPop projects that had been established to produce detailed and freely available population distribution maps for Asia and Africa. Last month the WorldPop project was launched, combining the AfriPop, AsisPop and AmeriPop population mapping projects into ‘a single open access archive of spatial demographic data for Central & South America, Africa and Asia for development and health application‘.
The following free datasets can be downloaded (as a zipped GeoTiff file) from the WorldPop site:
- Population distribution datasets for African and Asian countries
- Age/sex structured population distribution datasets for Africa 2000-2015
- New 2000-2010 Asia population distribution datasets incorporating satellite-derived urban growth maps
- Births/pregnancies distribution datasets for eleven countries
- Multidimensional and consumption-based poverty rate datasets for five countries
Metadata is provided with each data download and for those interested in finding out about how the data were produced, the methodological details are available on the WorldPop website. In the coming months additional datasets will be made available including:
- Population distribution datasets for Central & South America
- Age/sex structured datasets for Central & South America and Asia
- Births/pregnancies datasets for 75 countries
- Multiple updates on existing population rate datasets through new input data and methods
A recent, rather low-key, announcement from Google reported the launch of their new public data program. As part of the Google Maps Engine project, which allows users to create custom maps online, the public data program aims to make public data more discoverable by allowing users to (optionally) publish their data through Google. The published data will be added to the content that may be searched via other Google tools such as Google Maps, Google Maps Gallery and Google Earth.
The public data publishing service is free, users retain ownership of their data, which may be removed at any time, and user restrictions or end user licensing conditions may be attached to the content. The goal is to help ‘authoritative publishers to overlay their content on top of Google’s base map and make it accessible and useful’. By authoritative publishers Google means public data providers and governments who capture and maintain data that is of public interest and who wish to make that data available as a public good. Some examples of the type of mapping content Google are interested in publishing include:
- Crisis and emergency management data
- Statistics ( elections, demographics, health)
- Government (administrative boundaries, local services, transport)
Given the prevalence of Google’s existing mapping interfaces, the public data program seems set to take advantage of Google’s already strong presence in the online mapping market. It will be interesting to see how much more public data are published.
Earlier this year, I discussed the CRAAP test on spatial data quality, focusing on measures of Currency, Relevance, Authority, Accuracy, and Purpose. Since then, data quality has been a topic of discussion more frequently than ever before–not just in GIS circles, but in general daily news. Why is data quality important, and how can it be measured? I thought it therefore appropriate to create a new video reflecting upon some of these considerations.
We can download a wide variety of data; we can also stream data from a variety of sources that Jill Clark and I describe in this blog and in our book The GIS Guide to Public Domain Data. As data become easier to use, they become easier to misuse. It is easy to pull data from a variety of different sources, scales, dates, organizations, and lineages without a second thought, and then use those disparate data sources to make a key decision.
Don’t get me wrong–I don’t pine for the days when simply getting any data set into a GIS environment was a long, laborious process. I still vividly recall, for example, the month-long effort I went through in spring 1993 to get one county’s worth of census tract demographic data, plus streets and the census tract polygons, into ArcInfo version 4. I love the ability we have today to quickly gather and analyze data–and more and more of it possible in a cloud-based environment. I just want people to be more mindful than ever about the implications to making decisions with GIS. All of those decisions are ultimately based on the data that were used as inputs. And the above test is one way to assess whether that data is any good.