Sarah's Semesterly Recap, September 9th, 2020

This is my recap of the class’s blogs posted in Week 3.

It is not a typical activity for most people to think about what data is exactly supposed to be. And while most people might think of data as being specifically tied to scientific papers and reports, the digital world, and computer programs, data is not exclusive to these. Data is everywhere. For instance, a nutrition facts label on a box of cereal contains data. The names of the macronutrients, such as fats and carbohydrates, and the names of the micronutrients, such as the vitamins and minerals, along with the corresponding number for each, are all examples of data. All of these pieces of data put together communicates to us valuable information about the nutrition content of the food item. Kailey gives a great explanation of what data is: Data is scalar and compound, it can be numbers and words and pictures, and more.

In any case, individual pieces of data are usually not enough to give information about a place, thing, or concept. Data must always be presented with the proper context and with other supporting data in groups to become information. Without these qualities, data can be easily misconstrued and misused to push alternative narratives with false information. More than that, without any of the proper support for the data, it can not be properly communicated and might be difficult to understand. Articles, websites, and figures are some of the many ways to organize data into proper, meaningful information. Data visualizations can take on many different forms, including, but not limited to: graphs, charts, and timelines. It is required for one to have some creativity to go about how to organize the data and find the best way to communicate the data in meaningful ways. Scalar, dictionary compound, and list compound data are combined to make up the majority of websites and visualizations.

Interestingly, data requires someone to manipulate the data, and that human touch is what turns the data into meaningful forms of information. Coding could be regarded as a form of writing, and as such, coding is also a form of expression and requires creativity. Programming and coding has an unwarranted, widespread reputation of being extremely rigid and completely based on perfect structures, but there is still a degree of flexibility needed to solve certain problems that may arise. In actuality, coding is not only for the mathematically inclined and the algorithmically minded. Coding is a skill, just like writing, that requires practice and time in order to learn and improve. The most common thought of writing is expressing words on a page. Those words make up sentences, and those sentences make up paragraphs, be it through pen to paper or typing on a computer. However, code is forgotten. The language of code is overlooked as noted by Murphy Scott. The words and numbers can make up strings. Those strings can contribute to making specific functions, and those functions can all be put together to create a single project.

Thinking about the writing in these less thought about digital spaces is new, unexplored territory for many people. Be that as it may, the various similarities between the typical practices of writing and coding is remarkable. It is notably vital for both writing and visualizations to think about the audience, as in the piece of work should be as relatable as it possibly can be. We look at writing and ask ourselves what can be done not only to make it more effective, but also more persuasive and more organized. In like manner, we can look at data visualizations, which are representing the results of the data – the information, and ask the same questions. There is a structure required for submitting academic papers and for scientific lab reports. Stories need planning with storyboards. Similarly, data visualizations need easy to navigate structures. Websites have links under the different tabs, which can be represented by lists, and inside these lists links there can be a dictionary. People can write in digital spaces because of data, but people can also write the data that allows writing in digital spaces.

It has dawned upon me that writing is everywhere and escapes no one. The people behind making digital artifacts are not often thought of as writers, but perhaps they actually are. These databases can not enter themselves; these visualizations can’t render themselves. Writing within these digital spaces requires more than being a code monkey. To program, one requires critical thinking and problem solving skills, along with a healthy dose of creativity.