Digital Art Projects 2018

Source Code for Processing Sketch

void setup() {
size(displayWidth, displayHeight);
void draw() {
for (int i = 0; i < width/40; i = i + 1) {
for (int j = 0; j < height/40; j = j + 1) {
fill(random(255), random(255), random(255));
ellipse( 10 + 40*i, 10 + 40 *j, 10, 10);

Video: Digital Tribute to Artist Damien Hirst.

 Data-Driven Narrative, Unemployment and Crime, Is there a Connection?

See ‘Vizzes’ on Tableau Public to view data set behind these graphs and visualisations.!/


Data Driven Narrative from Lorraine Leahy on Vimeo.

Curated Data-Driven Narrative


The purpose of this current assignment in the context of Shawn Day‘s Humanities and New Technologies: Tools and Methodologies course involves selecting a dataset of interest from publicly available datasets (, determining useful visualisation techniques to analyse and then presenting our findings along with a narrative discussion.

An article by John McManus in The Irish Times (Oct 8, 2015) ran the startling headline “A thousand more on the dole in Garda district leads to extra 50 break-ins and thefts” (McManus). The basis of this article was a research paper by Enda Patrick Hargaden, Assistant Professor of Economics at the University of Tennessee. The research which forms a chapter of Hargaden’s Ph.D. dissertation investigated the effect of unemployment on crime in Ireland over the period from 2003 to 2014. Hargaden outlines the implicit Economic theory underlying his analysis in his paper Crime and Unemployment in Ireland, 2003-2016. Economic theory writes McManus “holds that crime is a rational alternative to traditional employment when it is not available and nowhere has it been more eloquently proven than in pre- and post-crash Ireland” (McManus).

Fig 1. Unemployment and Crime, Is there a connection?

The Google Trends Data Visualisation in Fig 1 quickly and effectively communicates the idea that as Hargaden suggests a relationship exists between unemployment and crime in Ireland. “Creating a narrative with data visualization is one of the most thrilling, powerful and satisfying approaches to handling data,” But as Michael Brenner goes on to outline in his article The Dangers of Visual Data Manipulation “the data always has to be our primary focus. All visualizations we make must be based upon the facts. We can make those facts look pretty, and we can draw attention to key pieces of insight which casual users may otherwise have missed, but we cannot simply invent a narrative which isn’t there” (Brenner).

Hargaden outlines in the abstract of Crime and Unemployment in Ireland, 2003-2016 that his research “paper investigates the relationship between crime and unemployment in Ireland during the Celtic Tiger boom, Great Recession, and subsequent economic recovery. Using unique administrative police station-level crime data and exploiting large variation in unemployment rates” (Hargaden,pg1). His central question related to how property crime responded to the changes in the economy.

Therefore, to ensure all visualisations are based upon fact involves the interrogation of the same dataset as analysed by Hargaden, I obtained data from The dataset Crimes at Garda Stations Level 2010-2016 is held on (Ireland’s open data portal, publishing Irish Public Sector data in open, free and reusable formats). This dataset contains original figures for criminal offences recorded in the 563 Garda Stations in the Republic of Ireland on an annual basis from 2010 to 2016. I located and downloaded a second dataset, namely, All Persons- Live Register. This CSV file contains a dataset regarding the total numbers signing on the Live Register in 124 Social Welfare Offices in the Republic of Ireland during the period 2008 to 2016.

Both datasets downloaded in the CSV files are quite substantial and therefore difficult to quite understand their impact. Both CSV files needed to be rearranged to extract only the data needed so the information available to us could be translated correctly in order to render meaningful visuals. Due to the volume and variety of data in both CSV file and in order to create visual displays of the data and to express information and enhance understanding of the conclusions drawn by Hargaden, we will hone in on the data from the Live Register and on property crimes for the area of Cork City and County only.

Edward Tufte outlined back in the early 1980’s that an excellent visualization expresses “complex ideas communicated with clarity, precision and efficiency” (Tufte 2001, pg13).  By using an interactive and imaginative data visualization tool of which there are many available on the Internet we can see that an excellent visualization can also tell a story through the graphical depiction of statistical information.

Tableau Public was the online data visualisation tool chosen. Tableau Public is open source and is an interactive data visualization program that does not require programming skills. Even though Tableau Public does require some understanding of database organization and graphics formats the interface proved easy for a beginner to navigate. Through the use of this digital tool, it is possible to extract from and contextualise the vast data, making sense of it faster and observe any patterns that might not be apparent from only looking at the stats.

Graph 1: Number of people signing on the Live Register in Cork City for the period 2008 to 2016.

Ireland, as we are all aware, entered into a severe recession in 2008 and the resultant economic downturn in Ireland between 2008 and 2010 was very dramatic. The scale of Irelands collapse was manifest very clearly in the labour market with a resurgence of outward migration and as shown herein Graph 1 a rapid growth in the rate of unemployment. Graphs are a good means of describing, exploring and visualising numerical data and help to highlight patterns and trends in the data. Line graphs, in particular, are used here to show time series data.

Graph 2: Number of People signing on the Live Register in Cork County for the period 2008 to 2016.

The Live Register data, as outlined above is collected at the Social Welfare Office Level and the figures are released monthly, the Garda Crime Figures are available on an annual basis therefore to ensure consistency I combined the Live Register figures to 12-monthly average (annual average) figures. The picture painted in both graph 1 and graph 2 very clearly highlights the soaring numbers recorded on the live register in Cork City and County in the 3 years following the collapse.

Graph 3: Total Crime Reported under 12 crime categories at Garda Station Level in Cork City, Peak in 2008.

Graph 4: Total crimes reported under 12 Crime Categories at Garda Station Level Cork County, Peak in 2008.

Already the line graphs indicate there is a strong relationship between unemployment and crime. It is interesting to find that crime levels rise and fall in tandem with employment in both the areas of Cork City and County outlined above.

Hargaden’s central question pertained to how property crime responded to these changes in the economy. He quantified the relationship between unemployment and property crime when he equated an increase of 1,000 in the numbers on the live register to 50 more break-ins and thefts. we are not calculating the maths behind Hargaden’s relationship but it can be seen from the data visuals how the trends developed in the timeframe 2003 – 2016.  Following the 2001 bursting of the dotcom bubble in the US, the levels of Foreign Direct Investment in Ireland went into a stark decline. Over the next three years, “30,000 manufacturing jobs were lost and one-third of all jobs in the computer and software industries were gone by 2004” (Kirby, pg38).  However, crisis and bust are avoided at this time through the building of a huge bubble in construction in Ireland. This resulted in a dramatic expansion of the numbers employed in construction, particularly housing, with hundreds of thousands of jobs created nationwide. Very interestingly the relationship as outlined by Hargaden between crime and changes in the economy is reflected in the line graphs 5 & 6, with the increase in Thefts reported for the period 2003 to 2005 following the job losses in the computer sector. Also, the decrease in Property crimes reported for the period of 2 years prior to the height of the property boom in 2007.

Graph 5: Thefts and related offences reported at Garda Station level Cork City 2003 – 2015.

The number of Thefts and related offences reported at Garda Station level in Cork city rose by 7.18% from 2007 to 2008. The number of reported Burglaries and related offences in Cork City rose by just over 10% in the same period.  Figures for these reported property crime offences see improvement over the most recent years where there has been a return to economic growth and improved employment opportunities.

Bar Graph 6: Number of Thefts and related offences reported at Cork City Garda Stations.

The summary of results of the 2016 Census outlined that in Cork City there were five Unemployment Blackspots. According to the Census, 2016 figures compiled by the Central Statistics Office highlighted Mayfield, Knocknaheeny, The Glen, Fairhill, and Farrenferris as five areas in Cork City that have unemployment rates between 28% and 33%. The Garda Stations situate Mayfield, Gurranabraher, Watercourse Road and Anglesea Street are responsible for policing these unemployment blackspots. See graph 6 for the number of Thefts and related offences reported at these Garda Stations.

Bar Graph 8 and Bar Graph 9: “A deterioration on labour market conditions is associated with an increase in property crime” (Hargaden, pg12).

This data story has shown the very distinct correlations between unemployment and property crime. Hargaden concludes “that a deterioration in labour market conditions is associated with an increase in property crime” (pg12). But one of the important lessons we take on board in data visualisation is that “correlation does not imply causation” (Tufte 2006, pg5). Correlation is not the final word on the subject, but a stepping stone to unearth a deeper understanding of the relationship. In the words of Data Visualisation expert Edward Tufte, “Correlation is not causation but it sure is a hint” (Tufte 2006, pg4).

There is more of course involved in the increase in crime rates across Ireland than employment or the lack of it. For the data source, All Persons Live Register used by Hargaden and in this data visualisation exercise being unemployed means not having a full-time job but actively seeking one. There are a number of different types of joblessness. Along with those who are actively seeking a full-time position, there are those out of the workforce as they are retired, working from home, caring for others. But also, there are those out of the workforce who are not seeking employment. Being out of work for any reason can affect people’s lives in many different ways, this study, for instance, does not question if joblessness can influence age groups differently. The link between unemployment and property crime is more complex.

The data visuals above only involved data from the property crime records, there are 12 crime categories reported in the Garda Station data sets. Economic growth alone does not divert everyone from a life of crime but as Hargaden writes “the overall picture suggests that job creation generates the positive externality of lower crime” (Hargaden, pg18).

Data storytelling is not just visualizing data effectively, it is much more than just creating visually-appealing data charts. It is the ability to understand your data, process it, extract value from it and most importantly to communicate data insights effectively.


Data Storytelling: The Essential Data Science Skill Everyone Needs, Brent Dykes. (



Data Sources:!/


Brenner, Michael. “The Dangers of Visual Data Manipulation.” Visual Matters, 31 Oct. 2016,

Dykes, Brent. “Data Storytelling: The Essential Data Science Skill Everyone Needs.” Forbes, Accessed 21 Mar. 2018.

Hargaden, Enda Patrick. Crime and Unemployment in Ireland, 2003-2016. 2016.

Kirby, Peadar. Celtic Tiger in Collapse: Explaining the Weaknesses of the Irish Model. Springer, 2010.

McManus, John. John McManus: Rural Crime Is about Jobs Not Garda Stations or the Bail Laws. Accessed 10 Mar. 2018.

Tufte, Edward R. The Visual Display of Quantitative Information. 2nd edition, Graphics Press, 2001.

Tufte, E. The Cognitive Style of PowerPoint: Pitching Out Corrupts Within (Cheshire, CT. Graphics Press LLC, 2006.