Google Fusion Table

The Task

The first assessment task for the module ‘Data Management and Analytics’ is to create a Google Fusion Table intensity map. Google Fusion tables enables the user to take existing (or new) data that is stored in tables and combine/merge the dataset for the purpose of creating a visual that is easy to understand. It allows for an almost immediate understanding of data represented visually as opposed to analysis that would required inspecting an excel sheet that may have hundreds/thousands of rows of data.

I hadn’t come across Google Fusion tables before, it is free to use and only requires an active Google account. The task is to create an intensity distribution of county colour’s for the Republic of Ireland. The two data files provided are ‘Irish County 2011 Population’ data, located here and Irish KML Data file, located here. KML stands for Keyhole Markup Languages and is an XML based file format that allows you to visualise data in conjunction with a map using Google Earth, Google Maps, and Google Maps for mobile etc.

And we’re off

To begin I first had to clean up some of the data as for example Dublin was broken down into regions Dublin City, Dun Laoghaire-Rathdown, Fingal, South Dublin.   The data for each region was compiled and added to a single region/county i.e. Dublin. I cleaned up some headings too. With the data sets cleansed, it was time to create the intensity map.

To achieve the intensity map, I had to first upload the Irish County 2011 Population data, followed by the Irish KML data. I then merged the two data files. When you have this done you are presented with the following map (see Figure 1), indicating (I think), that you are on the right track and that the merging of the data sets was successful.

Figure 1

Next up was to add a colour scheme and to add shades of colour that would facilitate the data being meaningful upon visual inspection, you can change style types and add a legend (explain map’s appearance). To achieve this I choose green and divided the buckets into 6, using varying shades of green to indicate least populated counties (light green) to most populated counties (dark green) counties (see Figure 2).

Figure 2

Map: Population

The information that could be gleamed from the map is that Dublin, Cork and Galway have the largest populations. There appears to be a cluster of boarding counties with smaller populations, Roscommon, Longford, Leitrim. In terms of how the data could be used, I think given the infrastructural problems the country faces, the intensity map could be used in the planning of future building projects, such as roads, housing, schools, hospitals. The growing population and housing crisis calls for major scale government investment in Ireland’s infrastructure.

Map: Households no Internet

When looking for other ideas/concepts that could be represented in the intensity map, I came across the website data.gov.ie and a data set ‘PC and Internet Access’ located here. I took the data, which related to the 2011 Census, which looked at ‘Households without Internet Access’ and added it to the existing 2011 population data set. I created an intensity distribution of county colour’s in shades of blue for the Republic of Ireland (see Figure 3).

Figure 3

The information gleamed from this intensity map was not what I expected. The counties with households with the least amount of Internet access were in fact Dublin, Cork. Dublin has 90,427 homes without Internet access. If you had asked me last week what are the counties with the highest instances of households without internet access, I would not have guessed Dublin or Cork. This has opened my mind to the possibilities of viewing large data sets but in a way that’s aesthetically pleasing and easy to digest on first impressions.

Two things I couldn’t work out … and then I did

First – when creating my first map for Irelands population, and colour coding the population data green, I increased the opacity from 50% to 100% thinking I’d have a greener colour scheme than leaving it on the default opacity value. I didn’t check the outcome of the colour change straight away and when I returned to view my work, I could no longer see any of the county names. When I hovered over the counties the pop-up data still existed but the county names were no more. It took me a while to work out,  but it was increasing the opacity from 50 – 100% essentially wiped out the county names leaving the map pointless but bright green.

Second – when creating my second map for homes without Internet Access in Ireland, I created new ranges in the ‘change map features’. They worked fine but when I went back to view my green population map, the blue buckets with the Internet data were now showing. I couldn’t work this out but as my population map was still green I knew I hadn’t over-written it. The fix, well I logged out of Google drive and logged back in and sure enough both maps and the bucket data and colour schemes were in tact – lesson learned.

References

MulinBlog: A digital communication blog, (2014). ‘Google maps tutorial (part 5/5): How to create a free heat map with Google Fusion Tables’.  Available at: http://www.mulinblog.com/how-to-create-a-free-heat-map-with-google-fusion-tables-a-tutorial-for-beginners/ (Accessed Oct. 2016).

DATA.GOV.IE, (2011). ‘PC and Internet Access (T15) ED’.  Available at: https://data.gov.ie/dataset/pc-and-internet-access-t15-ed (Accessed Oct. 2016).

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