In the Digital Humanities class we proposed to create a map that reveals a set of information about the restaurants in Abu Dhabi. The intent of the Food network Projects is to find the context of a relationship between different restaurants either in the context of one of the categories such as Average price and location.
For this post I will be providing a detailed description of the process. To me the process was a thesis question more than the research itself.
The process can be divided into two different process which is creating the Data set and visualising the data set. During the process I was made to work around the programs of visualising the data rather than be content with using their interface directly. The Carto Builder sort of created a barrier where I could no longer directly access the data but use it indirectly.
Before we could visualise the data, the first step crowd sourcing the information. Through the fulcrum app each individual can input in already defined buckets on location. The buckets are categorised as :
- Average price
- Number of Tables
- Date Established
- Origin Food and its subcategories
- Whether they deliver to Saadiyat or not
- A photograph of the restaurant.
- The geolocation.
As a collective we decided to create the categories on our definitions of the foods genre which was difficult as classifications such as cafe and “food nationality” did not have the capacity to fully relate to the data input. For example I find stores that tend to have identical menus but classify themselves as different ethnicities and include subcategories in their own description that do not relate to their menu or space features.
Another issue was the Date established. The question could not be attained only thought he direct contact of the experienced water or owner which were not always available during he interview process. It also created more questions that if the date established was meant for all of the branches or only the location the shop.
The categories made it difficult to define the answer. What was easy to define were numerical data such as delivery time and number of tables. This data can be defined as discrete quantitative data (1). Questions that were not theory based and are related to the present status of the restaurant were more successful in comparison to the other questions.
I enjoyed this process the most as it had gave me a direct interaction with the source of the data. Instead of relying on a second source of information that could have been edited I had a complete control of what information inserted to the data set. This does not save it from being incomplete or unedited as there are factors such as transportation and time limitation that edited my capability of selecting information to certain spaces along with language barriers.The parameters of information was only set on my mobility rather than the access of information through a second source.
The second process was visualising the data which was simple in theory only. The process required for me to export the dataset from fulcrum to Carto. Carto immediately visualises the information into a map after loading the data in a tabulates format. The difficult process was trying to create different layers and be specific with my visualisation without using an option called SQL code. Basically working only with the options that Carto provides is an issue as there is a barrier that stops me from directly interpreting the information and requires me to rely on Carto’s interpretation of the same data set.
Moreover while working with Carto I realised that the information is placed as layers and requires me to reorder it. The layers indicate there is a hierarchy of information I must determine for the viewer. I am currently working on allowing the viewer to control the information rather than have myself control information for them. Carto Builder has these widgets that are provided which enables me to analyse and create relations between the different restaurants. It was a mater of expectations where I saw information being accessible not necessarily in a Raw format but in a method where the viewer can access all the information simultaneously. My expectation that the Data will be fully realised by the Carto Builder made me question my extreme faith towards an application that can do all and much more without requiring my commands. The upsetting matter that Carto had decided the options that I need versus the ability to create my own options which I assume can be managed by the SQL code.
What freaked me out the most was HTML code and the inability to drag and drop Cartos map onto my blog post like an image or video. At this stage I am required to co-ordinate different factors to display the information set by working with html codes. The invisibility of these codes make me assume that there is a universal language and the site of the map can easily become part of the word press along with several Iframes which was not the case. The wordpress does not have the capacity to hold this information automatically and required me to add something which is a widget. I was surprised that even the transfer of the map from Carto to this blog post required another level of coordination.
I intended to detail the steps of visualising the information as though we are watching this blogpost dressing itself cause it is important that we talk about these different steps. The mediation and rendition of information through different applications and interfaces are an integral part of reinterpreting the data that started with a question to the waiter.
When I see other posts that is minimal and displays only the information of the research there is the misconception that most of the effort is in collecting and analysing the data set and not the coordination and visualisation of information. The process of visualisation is important as it dictates the perception of the information.
The Information and the Analysis
My final product in the end was a simple map using the analysis tool of Carto. Through the tools I decided to think about three factors which is the number of tables, the average price, delivery times and the years established. Through these factors I wanted to correlate that the prices are directly proportional to the amount of tables in the restaurant.