Revolution #8: Alternate Entry Points

Today’s revolution is a preview of a coming feature of GeoQuery we’ve been working on – the ability to “roll your own” entry points into the GeoQuery database. You can see an example (unless it crashes – beta!) at http://umd.geoquery.org .

A big concern we have regarding the sustainability of GeoQuery is it’s ability to not just serve our audience (mostly international development practitioners), but a broad audience across many different disciplines.  While we’re succeeding on that front in many ways, our reach will always be limited to users that are willing to use our tool, on our website.  Believe it or not, not everyone knows we exist!

So, enter the GeoQuery whitelabels.  Working with partner organizations that cater to different groups than us (i.e., the UMD example above focuses on conflict), we are working to create versions of GeoQuery tailored for other research groups.  Right now our ability to customize is fairly limited – i.e., aesthetics – but we’re working on more options such as what datasets are displayed, boundary files, and even some features.  These “whitelabel” websites dial into the exact same backend infrastructure hosted here at William and Mary, so are very light-weight for other groups to implement, and only require a minimal stack of software.

Another big advantage is it enables a fair exchange with data providers.  Instead of us just hoovering down data from all sources, we can provide a unique portal for data providers.  It’s a nice win-win; we get more users from more sources, and data providers can give their users an easy way to get at data.

We have a number of conversations ongoing now; future revolutions will likely highlight more of these as they become more robust / “production ready”.

About the author: Daniel Runfola

Dan's research focuses on the use of quantitative modeling techniques to explain the conditions under which aid interventions succeed or fail using spatial data. He specializes in computational geography, machine learning, quasi-observational experimental analyses, human-int data collection methods, and high performance computing approaches. His research has been supported by the World Bank, USAID, Global Environmental Facility, and a number of private foundations and donors. He has published 34 books, articles, and technical reports in support of his research, and is the Project Lead of the GeoQuery project. At William and Mary, Dr. Runfola serves as the director of the Data Science Program, and advises students in the Applied Science Computational Geography Ph.D. program.