Part 1. Putting Data Driven Research In Perspective
Part 1. Putting Data Driven Research In Perspective
1.1 What is Data Driven Research?
What is Data Driven Research?
Data Driven Research is a subset of the field of Digital Humanities that deals particularly with data analytic and visualization methodologies. This field broadly consists of theories and methodologies from a range of humanities disciplines that inform how a researcher gathers, analyzes, and filters datasets to gain insight about a particular subject.
When data is processed, organized, structured or presented in a given context so as to make it useful, it is called information. Data are the facts or details from which information is derived. Individual pieces of data are rarely useful alone. For data to become information, data needs to be put into context.
With data driven research, scholars are able to harness the power of spreadsheets, text mining software, and public archives to produce visualizations that communicate findings and insight into fields of study. Producing visual stories for online discourse is just one of the exciting possibilities of data driven research. Therefore, we must develop a general working knowledge of data analytics in order to derive insights from datasets.
In this chapter, we will (1) provide a general overview of data driven research; (2) explain why spreadsheets are valuable tools for data analysis; (3) explain how humanists and social scientists can make key contributions to the field of data analysis; (4) use a data visualization to demonstrate how data driven research allows us to comprehend large scale analysis of topics.
Keywords: Data, Datasets, Data Curation, Data Visualization, Spreadsheet, Quantitative Data, Qualitative data.
Understanding Quantitative and Qualitative Data
Data is organized into collections known as datasets, which are foundational for data-driven research. Datasets contain quantitative and qualitative data (sometimes both).
Quantitative data can be numbers and values. It can be used to ask the questions “how much?” or “how many?” Qualitative data is descriptive and conceptual. Also, it can be categorized based on traits and characteristics like serial codes and social security numbers since these categorical values are unique to one item or person. Collections of data can be used to perform different types of analyses, derive insight, and produce information.
The most common format for datasets is a spreadsheet, especially .csv formats. These documents are a single file organized as a table of rows and columns. These files can be opened on common spreadsheet applications like Microsoft Excel or Google Sheets. These types of files can also be stored in other formats ranging from a Microsoft Excel document to multiple datasets in a zip file.
Despite there being several advances in computational humanities, however, the role of data curation is often times overlooked, especially when it comes to the humanities and other scholarly disciplines.
Data curation is the work of org