In our continuing quest to explore what goes on “under the hood” of digital humanities projects, this week we are moving from the front-end client-side user experience to the database “back end” on the server side, where all the data storage and information retrieval magic happens. In order to perform analysis, or present the results of our research to the public on the web, we first need to collect, categorize and store our data in a way that will give us the best combination of structure and flexibility.
Last time, we created individual timelines using Timeline JS, and entered the data in spreadsheets. We will explore the concept of metadata and data cleaning by trying to combine our different year bands into one group timeline.
Go to the Aggregate Google Sheet below, and add your group’s data from the sheet you created last time.
- Are the data compatible?
- Are they “clean”?
- What problems arise?
This works great for the timeline, but what if we wanted to do different things with the same data? What if we wanted to reorder our data by something other than chronology, or extract all the people or buildings, or add spatial locations? And what if we wanted to model the relationships between those elements? Our spreadsheet is just not flexible enough for this. In order to store complex data sets, we need a more sophisticated way to store it; enter the relational database.
There is a vast amount of literature out there on database design theory and practice, but the articles we read for this week provide a good starting point into the general characteristics of relational databases, and the raging debates over how to move beyond them in the brave new world of ‘big data‘ in humanities research.
The key takeaway from these debates is that “data” are not value free and neutral pieces of information. Any time we break information down and classify it into categories, we are imposing our human world view and experiences on the information, whether consciously or not. This is unavoidable, but the best way to deal with it honestly is to acknowledge our biases, document our decisions and explain our thinking at each step of the process. The resulting metadata (data about the data) are critical for successful scholarly projects, and we will discuss their importance throughout the course.
For today, we are interested primarily in exploring how relational databases work in a typical DH project, which often shares a lot of similarities with how web applications work in general. So we are going to stick with what we already know and get to know databases by exploring the backend of a WordPress site.
If you were going to do this the old fashioned way, you would need some space on a server running the LAMP stack (Linux, Apache, MySQL, and PHP) to install and run a fully customizable WordPress site, but we are going to using our cPanel in Reclaim Hosting which takes care of all the system administration work for us.
Most web applications and DH projects consist of two main components: files and a database. The main WordPress files you’ll interact with are the PHP files in the theme layer, which change the look and feel of your site, and the plugins in the plugins directory, which add functionality. Check out the Resources section below for more on how to customize these.
The database can be accessed via phpMyAdmin, a super helpful tool that lets you interrogate and take actions on the database without having to type SQL commands directly into a shell prompt.
- Explore your WordPress db, consulting the diagram at right,
- See if you can figure out how the data and metadata of a typical post, page and comment are broken up and stored in the db.
- Add a new plugin and a new theme to your site.
- Did either change the database? Which one? Why?
Continue to explore the guts of WordPress and ask yourself: how are the data are structured, stored, and ultimately rendered in the browser? Do you understand all the component parts?
- Continue exploring the server environment on your own, and try to see if you can understand how the different pieces fit together within the LAMP stack itself and within the MySQL relational databases.
- Continue to explore the WordPress backend and think about what this structure allows.
- Try to reproduce and populate some of the database that Stephen Ramsay describes in this article on your local host by either executing the SQL statements or using the phpMyAdmin graphical user interface that comes on your host.
- Finally, write a blog post that discusses the benefits and drawbacks of flat data structures like spreadsheets vs. relational databases.
- What are the pros and cons of each?
- What issues with data collection and metadata must be considered and solved before you get too far?