CEUS Special Issue on Census Analytics

Spatial analysis with census data: emerging issues and innovative approaches

In many countries data systems that have been in place for the better part of a century have started to change. Census data are still the major source for geographically detailed estimates of populations and economies. However, the national/state agencies that produce this data are increasingly under financial and political pressures to produce more accurate and more frequent estimates while survey response rates continue to decline and the cost of conducting surveys increases. In some countries there is strong demand to make better use of existing routinely collected administrative data such as medical, education, tax and welfare records for producing population estimates. The emergence of “big” data, such as social media, transactional databases and sensor systems, which are increasingly available in granular form, offers further potential opportunities to augment, refine, or supplement census data and reduce the costs of conducting a regular census.

These pressures and opportunities present fundamental methodological challenges for both Census agencies and users of Census data worldwide. These challenges include: how to integrate data from the Census, different types of surveys such as “rolling surveys”, administrative data and big data to produce accurate population estimates at varying spatial and temporal scales; how to measure, communicate and visualise uncertainty in estimates from these mixed modes; how to design suitable collection and output geographies e.g. which aid survey design, minimise uncertainty and/or ensure statistical disclosure control.

In this special issue we engage with a broad set of emerging issues around this new data economy. We are interested in papers that cover a wide range of topics, including, but definitely not limited to, the following:

  1. Can advances in computing technology, linkage of survey/census data and spatial big data be used to improve the collection, estimation and analysis of census estimates?
  2. Are there alternative spatial survey methodologies and/or conceptual frameworks that might yield improved small area estimates?
  3. How does one map (visualize) and/or detect change in period estimates? How does one visualize highly uncertain data? Does the inclusion of uncertainty in visualizations affect cognition and/or change the outcome of map-dependent tasks?
  4. Are there optimal ways to aggregate census geographies? If not, are there alternative ways to aggregate data that can preserve the social, economic, and spatial patterns of the data, while minimizing the risk of data hacking or statistical disclosure?
  5. Can geographic methods, such as dasymetric mapping and areal interpolation, improve the quality of census estimates?

Guest Editors
Seth Spielman, University of Colorado at Boulder
Ningchuan Xiao, Ohio State University
Samantha Cockings, University of Southampton
Robert Tanton, University of Canberra

Authors who are interested in contributing to the special issue are invited to submit an abstract of no more than 250 words by May 15, 2015. Submissions should be done electronically via the Elsevier Editorial System (EES) at http://ees.elsevier.com/ceus, by selecting the special issue title as the Article Type. After the abstracts are reviewed, notifications will be made by early June 2015. Full papers will be due on October 15, 2015, for publication in 2016. All inquiries about the special issue can be directed to the guest editors (Seth.Spielman@Colorado.EDU, xiao.37@osu.edu, S.Cockings@soton.ac.uk, and robert.tanton@canberra.edu.au)