Because of my internship, I am more aware of digital humanities technologies and I am more skilled in applying them to data visualization. It sparks my further interest in how to present a research result and my interest in data science.
In many ways, my internship with the Smithsonian Cultural Initiative—mapping cultural heritage sites destroyed in war-torn countries—is a good practice of interdisciplinary research. It demands digital skills, data management and curation, and public exhibition design. All of these are a step further from my major field (history). The hands-on experience in the mapping project prompted me to look into professional websites of web developers, such as Github and stackoverflow. I did not expect to have an overlapped area with computer science majors but, thanks to the internship, I had this chance to receive suggestions from tech people all over the world after I posted my questions and to look for answers in the questions posed by other people. It is an amazing and inspiring research experience that enhanced my digital skills and gave me new thoughts on the old points I had understood.
My internship work is data visualization using Mapbox and JavaScript language but I exercised multiple skills in the process. The first one is the research ability to find enough information in a short time. At the beginning of the project, there were many options for mapping tools, such as GIS, Geoda, Kepler.gl and Palladio. I had some experience with some but had to research others. After studying the nature and scope of the project and datasets we have, the team has decided to use Mapbox which demands intensive coding. Other tools either have graphic shortcomings or are better suited to other projects.
The second skill I gained in this mapping project is data management. To present the big data on a map, it takes a few steps: data mining, cleaning, storage, filtering and integrating. Each step teaches me something new when I work on them. For example, Mapbox requires the data format to be geojson, a very popular geospatial data format. In my past experience the software tools can take csv.file which can be easily converted from an Excel sheet. I spent some time on researching how to make geojson file, its format and storage. Mapbox does not take large datasets but you can use a weblink to store the data and when the code runs, it extracts data from the weblink. But this link has to end with “.geojson”. So my research extended to a new knowledge of geospatial mapping. Moreover, I have better understanding of Microsoft Excel thanks to data cleaning experience. Usually after storing data on a Github page, it will make a preview map. If this map doesn’t show, it means there is something irregular in the dataset. This confused me at the beginning because the dataset in Excel looked perfect. Actually, there were some cells causing the problem. The original datasets are collaborative work which pieces together the datasheets made by other interns. Sometimes cells have different formats, though they look the same, and when I copy and paste them into my own sheet designed for the mapbox map, they cause problems and need fixing. It took a great deal of time to figure this out.
My internship is a great learning and hands-on experience. I enjoy this research-learning process and the progress I made in it. Currently, I am very interested in data visualization and look into some tools though I don’t need to use them in my current project. Python is great in handling data but it’s not good for interaction. After signing up for Python courses, I understand why most front-end development, like the mapping projects I do, uses JavaScript. Excel is great, it can do some amazing data visualization such as graphs, charts and spirals just in Excel sheets, sometimes with little plug-ins. I guess many people do not know this hidden treasure and only see it as a datasheet. Programming languages such as Python and JavaScript are ultimate, but for most people, ready-made software tools are good enough to handle most situations and save you from the deep learning curves of a programming language.
In short, because of my internship, I am more skilled in digital humanities and interdisciplinary research. I owe many thanks to my team for their support, patience and kindness. I look forward to using the experience I get from my internship in the future digital humanities projects. Below are the two maps I have been working on: cultural heritage sites destroyed by war in Syria and Bosnia. They are still under construction.
Syria
Bosnia
