Are there ways to fact check data? Aaron R. Hanlon , an English Professor at Colby in his talk on the Revolutions in Data, Big, and Little, has brought up that question that I bet many have not thought to ask. Hanlon opened his talk with how we take Data for granted. Data comes from the British tradition, entering the English language in the 1600s from Latin, where it was seen as fact and truth the way nowadays we view Google data. Hanlon discusses the way we misinterpret “data,” a conversation that would truly benefit people today as we are in the age of technology where “data” is attainable at a click of a button.
Professor Aaron Hanlon’s talk “Revolutions in Data, Big and Little,” made me consider the digital aspects of future history. Professor Hanlon talked through the history of data, from the genesis of the word through the scientific revolution into modern times. The more traditional forms of data, such as Robert Hooke’s drawing of the flea, were translations of observations into visual mediums that others could observe without firsthand experience. Today historians can look back on the pen and paper records that past data collectors have left. However, in today’s world, the bulk of data being produced today, including the n-grams that Professor Hanlon showcased, are digital. With the plethora of data available today, how will future historians be able to easily categorize the information of this age? Continue reading
In Aaron Hanlon’s presentation “Revolutions in Data, Big and Little”, Hanlon discussed the development of big data, and its relationship with advancements in technology. The concept of big data has emerged not only in scientific research, but also across a variety of disciplines. Moreover, with this big data, visual representations are crucial for comprehending the big picture and making information accessible to many populations. However, now that data has transformed to big data, what does this mean?
With the rise of the Internet, we have been quickly termed “the information age”. As Hanlon highlighted, big data has become visual, and this combined with the Internet’s accessibility in developed nations makes this data, and its meaning, more available and widespread. With this in mind, data’s importance for understanding daily issues and probable solutions has increased. Rather than go on intuition or point to religion, citizens of developed nations are beginning to turn to research. There are many future directions of these implications. Will the importance of data spread to developing and underdeveloped countries? It is reasonable to hypothesize this will occur soon for developing nations, as Internet is rapidly becoming more accessible. Underdeveloped nations also have potential, but given their ongoing statuses, I predict it will be longer for this rapid shift.
However, what does this shift towards depending on data mean? There are many issues with it, as data can be done incorrectly, and even if it is disproven its implications persist. For example, the statistic stating one in four (or five) women will be sexually assaulted on college campuses in the United States has been disproven countless times and somebody with a basic knowledge of statistics can read it and decipher where these well-intended researchers went wrong. However, despite studies retesting and disproving the one in four (or five) the meanings hold. This brings up an important necessity: Knowledge in data interpretation and questioning. Statistics has seen a rise in recent years, and it is crucial to educate future generations about how to interpret research and know when false meanings, or bad research, is being presented to them.
Despite this important concern, data provides wonderful insight. Despite depending on housewives tales, people can look at data and, most of the time, can make better, more informative decisions. It will be intriguing to see the continuation and expansion of big data, particularly with social media’s growing dominance in its presentation and the increasing role developing nations will play.
The revolutions explored so far this semester have mostly addressed events in the past; the periods of adjustment following these have ended, and their effects have been implemented in society. Khalid Albaih’s lecture addressed a current ongoing political revolution in Egypt. The societal implications of political revolutions can be overtly demonstrated to the rest of the world using images, publications, art. Other, more abstract, can be difficult to detect and their effects on society sometimes go unacknowledged. The world is currently going through one of these more abstract revolutions. With the development of technology, humans have obtained the ability to gather massive amounts of data, so much data, in fact, that we cannot review and process it all.
What is data? In latin it translates to “a thing given.” Facts and evidence are the results of sets of data, which help demonstrate the significance of data to society. The use of data arose as a tool in science around the 17th century. During the era of the Enlightenment and the Scientific Revolution people could no longer rely on their assumptions to explain phenomena of the natural world, they needed quantifiable proof.
Francis Bacon emphasized the use of images and visual representations of matter to describe natural phenomenon. The use of words to explain processes was considered to be less scientific than visual representations. Robert Hooke’s Micrographia was a perfect example of how images worked better than words to describe scientific knowledge. His book contained images of flies under a microscope, which allowed normal people to actually see what they looked like up close instead of relying on the words of scientists in combination their own imaginations for descriptions. Visual representations were seen as more scientifically accurate since they relinquished the influence of subjective imagination that follows literary descriptions.
Today, illustrations or pictures, like Hooke’s, are not considered to be the most effective way of demonstrating scientific knowledge to a community. To further purge subjectivity from scientific processes, people have started to show information in purely quantitative and measurable terms, numbers. Now, graph and charts are used to explain processes. For example, in the 19th and early 20th century scientists looked images of embryos at different under a microscope to visualize patterns of allometric growth. This comparing images would sufficiently serve as evidence of allometric growth patterns. Today, these images would need supplemental graphs comparing the precise measurements of allometric structures at different stages of growth. As data has become more complex, the modes are portraying the meanings of data have also evolved.
The development of complex software and computational tools have changed the way that we handle data. In the 17th century, scientists dealt with the question of whether or not a set of data was obtained under subjective procedures. Today, people rely on technology, which is assumed to be objective, to gather sets of data. The questions now are, what do we do with it all, how do we decide which data sets are worth exploring, and how can we portray this “big data” to society? Storing data is also a modern dilemma. The massive amounts of data produces with modern technology may be overwhelming and most of it probably serves no use for society at large. However, if people are able to create programs that can effectively collate and organize “big data,” more of it could be useful to society.