This piece was inspired by the concept of ourselves living in a surveillance society, where, we may be under constant observation. I was very interested in exploring the paradox of seeing and not seeing, and I felt that I could achieve this through utilizing this concept. This video was created by accessing live-streaming footage at insecam.org. This website broadcasts live feeds of Axis, Panasonic, Linksys, Sony, TPLink, Foscam and a range of other network video cameras that are available online without a password. This website highlights how easy it has become to watch an unsecured network camera from anywhere in the world.
The video seeks to convey how our own ignorance to facts like this allow us to invite viewers into our lives unknown to ourselves, or sometimes, even become viewers ourselves. This video aims to convey an eerie and uncomfortable atmosphere while entertaining the idea that we might perhaps be intruding on something that is not meant to be watched.
I recorded the live streaming video using Debut Video Capture, once I had captured a satisfactory amount of footage, I then began editing the video in Adobe Priemere Pro CC.
I organized the footage into four sections of a square. Each video was chosen based on its individual aesthetic and how it fit within the overall concept. I distorted the colour of the top right and bottom left videos – giving them sickly yellow and pink hues. The goal here was to encourage the impression and atmosphere of unease. The aesthetics of this video were based in the grainy elements of VHS rips and based on glitch art; both elements of art that are popular online today.
Finally, I downloaded some samples of cameras zooming and clicking and looped them over a synth. This was to add a final eerie touch to the video and hopefully drive home the concept of being watched/being the watcher.
When I began my work on this assignment, I spent some time trying to decide what sort of dataset I was interested in creating a narrated visualization on. This was a surprisingly difficult decision to make as I was unsure of the exact argument that I wanted to make. Despite not knowing my exact argument in the beginning, I did know that I wanted to focus on a dataset that concentrated on technology and information society.
After spending a considerable amount of time browsing the Central Statistics Office’s available datasets, I finally settled on two datasets that interested me under ‘ICT Usage by Persons’: ‘Persons Aged 18 Years & Over by Sex, Purchases Made Online & Year’ and ‘Persons Aged 18 Years & Over by Purchases Made Online, Region & Year.’ These datasets spanned from 2011 to 2015, however, for this assignment, I decided to focus on the year 2015.
I decided to dive right into exploring these datasets by firstly organizing them in an Excel spreadsheet in order to make sense of them. After I had done this, I then concentrated on constructing the data into a visual representation.
I chose Piktochart as the medium I would use to create and display this visualization. I chose this tool for a few reasons: firstly, Piktochart is an incredibly user friendly tool for creating infographics and presentations, meaning that for a novice to data visualization like me, using this tool would not seem too daunting. Secondly, it gives the option of importing your data in CSV, XLS, XLSX, Google Sheets or by directly copying and pasting in order to create your chart or graphic. Finally, Piktochart offers a large variety of graphics and visuals that one can incorporate into their presentation or infographic in order to illustrate findings or arguments appropriately.
In order to visualize the data that I had downloaded from the CSO, I settled on using three types of charts in illustrating the information: vertical bar charts were used to illustrate purchases by sex and purchases by region would be illustrated via a map and horizontal bar charts. Both datasets show the percentage of a particular type of online purchase according to sex or region. There was a large range of purchase types listed in these datasets, ranging from food and groceries to travel arrangements and (almost) everything in between. There was a total list of 17 types of purchases in these datasets. In order to keep the visualization clear and understandable, I decided it best to concentrate on the purchases made online with the highest percentages by sex and by region in 2015.
In the process of organizing these datasets into understandable visualizations, one thing became glaringly clear; in 2015, persons of both sexes and in most regions of Ireland were making a lot of online purchases related to travel. Many of the other top online purchases included clothing and tickets for events. You can see the information I found in this dataset in the infographic below:
As the online purchases related to travel peaked my interest, I thought it might be useful to investigate whether this had any relation to the weather in Ireland in 2015. Considering many media reports had listed 2015 as being a particularly wet year, I wanted to determine whether there was any truth to this, and if it might be reason for the online purchases related to travel. In order to do this, I thought it best to locate records on Ireland’s rainfall and records on tourism from Ireland.
While I was unable to access any datasets from the Central Statistics Office on rainfall in 2015, I was able to access Met Eireann’s annual weather reports. Met Eireann calculates the annual rainfall in Ireland compared to Long Term Averages (LTA). It is usual to place current weather events in context by comparing them to LTAs or ‘Normals’. These are defined as 30 year averages of a weather element such as rainfall.
What I gathered from the Met Eireann annual reports ranging from 2014 to 2015 was as follows: 2014 had relatively varied weather across the country, although there were drier conditions where some stations reported rainfall totals below Long Term Averages. However, some counties such as Louth reported high rainfall.
According to the 2014 report, “The majority of annual rainfall totals were above their Long-Term Average (LTA) with below LTA values reported at some stations mainly in Cork, Donegal, Galway Kerry, Mayo and Waterford. Percentage of LTA values ranged from 62% at Inishbofin, Co Galway with the years lowest rainfall total of 803.4 mm to 150% at Dundalk (Ballymakellett), Co Louth with 1531.1 mm, its highest annual total on available record since 1944.”
Finally, 2015 was in fact a very wet year, with total rainfall landing on or above Long Term Averages. The wettest conditions were reported in December, when parts of the south of Ireland reported 300% or more of normal rainfall. Several stations had reported their wettest year since open or on record.
According to the 2015 report, “Annual precentage of LTA values ranged from 96% at Mace Head, Co Galway with 1281.66mm to 137% at Knock Airport, Co Mayo with 1852.0mm, its wettest years since the station opened in 1996. Malin Head, Co Donegal reported an annual total of 14839mm (134% of LTA) and its wettest year since records began at the site in 1885. Newport, Co Mayo, reported the highest annual rainfall with 2078.8mm (129% of LTA), its wettest since the site opened in 1960, while most other stations in the West, South and Midlands reported that it was their wettest year in six to 13 years. The highest daily rainfall was at Malin Head on December 5th during Storm Desmond with 80.7mm, the wettest day at the station since 1955. The number of annual wet days ranged from 144 at Dublin Airport to 236 at Newport”.
Once I had gathered some information on rainfall in 2014 and 2015, I then returned to the CSO website to find a dataset on tourism from Ireland. I successfully located and downloaded a dataset titled ‘Overseas Trips to and from Ireland by Reason for Journey, Year and Statistic’. This dataset ranged from 2009 – 2015 with a variety of options. I selected the options of ‘Overseas Trips by Irish Residents’ and ‘Holiday/leisure/recreation’, I then chose to examine the years 2014 and 2015.
From this dataset, I was then able to determine that in the year 2015, there was a 5.11% increase in overseas trips for holiday/leisure/recreation.
From examining these records, I was able determine that 2015 was wetter than 2014. It seems natural that because of the high levels of rain that we receive in Ireland, that one of our top online purchases would be travel-related. In order to support this theory, I was able to determine that there was an increase in overseas travel in 2015 for holiday/leisure/recreation. To support my argument, I made a final infographic that illustrates the data that I collected for this assignment, as seen below.
To look up a weather report, click here.
For information on Long Term Averages, click here.
For the 2014 weather report, click here.
For the 2015 weather report, click here.
For information on online purchases by sex, click here.
For information on online purchases by region, click here.
For information on overseas travel to and from Ireland, click here.