Data visualization, most commonly associated with infographics and reports, concerns how a body of information is presented. Consider now how your bookshelf is a set of data with many different ways to organize and present it. Books, spanning genres, authors and time periods, at first spread across a bookshelf in an unorganized manner. The audience of this piece is people who wish to visualize their bookshelves in a new way, dependent upon individual goals. Book data visualization is important because it can communicate what is within a set of book data within larger collections of books. And sometimes, you just want to spice up your bookshelf and make it look prettier. 

Your starting point: an unorganized set of data. How to proceed from here?

First: consider your data set. Are there any patterns? Are there many series within the set or just standalones? Fiction and/or non-fiction? Many or few genres? Knowing your data set can make the visualization process easier when deciding which methodology to move forward with.

Much like how a researcher must consider their audience when deciding how to present their data, you too must decide how to present your book data. I have detailed some potential methodologies of visualization below based on different intents and goals.

1. By color (Goal: make the room look pretty and aesthetically pleasing)

This is considered similar to making a bar graph’s colors fit a color palette or adding an abundance of pie charts just because you have the data accessible to you. The focus here is not fully, if at all, focused on the books themselves. When seeking out new books, you may even select a new volume based solely on the color of its cover. This method is the least effective for actually reading the books on the shelf, but it will surely impress your guests.

1. By length (Goal: knowing how much time you have to read and successfully selecting a book of appropriate length)

A benefit to this method is that not only is it more efficient than organizing solely by color, but it also looks pretty. Structurally, the method is also beneficial to your bookshelf. Shorter books shelved on higher shelves and longer books shelved on lower shelves can help ensure the structural integrity of your bookshelf. Data visualization relies almost entirely upon intent, and if your specification is a time restriction, then this is the methodology for you. 

1. Chronologically, by when books were written (Goal: follow how themes and genres evolve over time)

This method could be beneficial for cataloguing within a certain style of bookstore or café, where there is a strong emphasis upon writing over time. One could foresee the bookshelves at the front of the store being the newest and the ones in the back being the oldest. 

In thinking upon this method, another alternate one also comes to mind: chronologically by what time period the book takes place in. This is a theoretical method and could run into difficulties. Where does sci-fi go if a year is not specified? Fantyujasy in a world that does not follow the same concept of time as realistic fiction books? That being said, there is much confidence within the field that this method could prove substantive if proper time and effort is put in. 

1. By genre (Goal: after previously identifying the desired genre, easily choose between books within that genre)

Scores of book data visualization researchers have found the genre method to be the most effective. The method is well-regarded and widespread. But just because a method is popular does not mean it is automatically the method for you. Does your book data contain a wide range of genres, or is the data focused within one category? This method is ideal for a diverse genre collection. If your data specializes in Westerns or fantasy or any genre in particular, you should seek out a different visualization technique entirely. 

1. Dewey Decimal System (Goal: make your books easily accessible to people who have never visited your bookshelf before)

Using a standardized method is never frowned upon. This method in particular is especially dependent upon your set of book data. (For instance, if your data consists solely of cookbooks—about 641.5 in the Dewey Decimal System—you may want to consider visualizing based upon region of origin to differentiate.) The Dewey Decimal System is beneficial for handling large quantities of non-fiction data and having low interest in color aesthetics. The data will be easily navigable but not pretty to those unfamiliar with the system. For smaller scale data operations (and if you are unfamiliar with the numbers), it may also be labor intensive to locate the Dewey Decimal numbers when categorizing book data. 

There may also be a blended method (combination of two or more standard methods) that works best for your book data. Perhaps you want to organize books by color within each genre. In this instance, one would proceed by first categorizing by genre and then shelving by color. Regardless, book data visualization is a highly important field, for your own enjoyment of your bookshelf and for others to locate books on your shelf. Happy organizing!