The historiography of data refers to the study of the history of data, including its origins, development, and use over time. This field of study encompasses the history of data collection, storage, analysis, and dissemination, as well as the cultural, social, and political context in which data has been used. It also includes the study of the different ways data has been represented, stored and managed over time, as well as how data has been used to inform decision-making, knowledge production and to shape the way we see the world.
The historiography of data can be traced back to the early days of computing, when data was primarily used for scientific and military purposes. “Data” prior to this was predominately book keeping. Works like Inventing Accuracy shows how data and metadata evolved. Data on missile accuracy rates, ranges, or circular error probabilities (CEPs) across different periods of time was the “data stuff” that made up the Cold War. Weapons technology and their delivery was the focus of both the politics and the economy of these decades leading to spin off technologies like the cell phone, personal computer and the internet itself.
As technology progressed in the 1960s and data storage and processing capabilities improved, data became more widely used in various fields, including business, government, and society at large. With the advent of the internet and the proliferation of digital devices, data has become an integral part of daily life, and its collection, storage, and analysis have become big businesses.
The study of the historiography of data also includes the examination of data’s impact on society, such as how it has been used to shape public policy, influence elections, and impact individuals’ privacy. There has been a growing interest in the field of late, with scholars and researchers across various disciplines, such as history, sociology, computer science, and information studies, exploring different aspects of the history of data.
Visual representation and the historiography of data are two fields of study that are deeply interconnected. Both are concerned with understanding how information is presented, stored, and interpreted, and both have a profound impact on our understanding of the world around us. In this post, we will explore the academic connection between these two fields and how they interact with each other and how this interaction implicates art history.
In the field of visual representation, the focus is on how images, charts, maps, and other forms of visual media are used to convey information. This includes studying the design principles behind effective visual communication, as well as the social and cultural factors that shape the way we interpret visual data. By understanding the ways in which visual representation can influence our perceptions, we can develop a better understanding of the role of images in shaping our understanding of the world.
The historiography of data, on the other hand, is concerned with the history of data, including its origins, development, and use over time. This field of study encompasses the history of data collection, storage, analysis, and dissemination, as well as the cultural, social, and political context in which data has been used. It also includes the study of the different ways data has been represented, stored and managed over time, as well as how data has been used to inform decision-making, knowledge production and to shape the way we see the world.
When we bring these two fields of study together, we can start to see how visual representation and the historiography of data are intertwined. For example, we can see how early forms of data visualization, such as maps and charts, were used to convey information to rulers and leaders, and how this use of visual representation has evolved over time to include everything from data visualization in scientific research to infographics in news articles.
We can also see how visual representation and the historiography of data have been used to shape public policy, influence elections, and impact individuals’ privacy. By understanding the ways in which visual representation and data have been used in the past, we can develop a more nuanced understanding of the ways in which these tools are being used today, and how they may be used in the future.
Visual representation and the historiography of data are closely connected. By understanding the ways in which visual representation has been used to convey information throughout history, and how data has been collected, stored, and analyzed, we can gain a deeper understanding of the world around us and how it has been shaped by the information we use to make sense of it. As we continue to live in an increasingly data-driven world, it is crucial that we understand the ways in which visual representation and the historiography of data interact with each other, to better navigate and make sense of the information that surrounds us.
So doesn’t that mean that art history is important here as well?
Maybe the title of this blog post should be: Art history, the historiography of visual culture, and data science.
Art history is the study of art and visual culture throughout history, including the study of art movements, artists, and the social and cultural context in which art was created. The historiography of visual culture is similar, but it also encompasses the study of non-artistic visual media, such as photography, film, and advertising. Both art history and the historiography of visual culture focus on understanding how visual media has been used to convey meaning and how it has been shaped by the cultural, social, and historical context in which it was created.
Data science, on the other hand, is the study of the collection, storage, analysis, and interpretation of data. This includes the use of statistical and computational methods to extract insights and make predictions from data. In recent years, data science has increasingly been applied to the study of art and visual culture. For example, researchers have used data science techniques to study art movements, identify patterns in artworks, and to analyze the styles of individual artists.
One of the ways in which art history, the historiography of visual culture and data science are related is through the use of computational techniques to analyze and interpret visual data. For example, data scientists might use machine learning algorithms to classify artworks by style or to identify patterns in the way that artists use color. This can help art historians and other scholars to better understand the visual culture of the past and to identify patterns that would have been difficult to detect through more traditional research methods.
The use of data visualization techniques can also be used to present and analyze the information collected through art historical research. This can help to make the data more accessible and understandable to a wider audience.
Art history, the historiography of visual culture, and data science are related in the sense that they all deal with the understanding and interpretation of visual data, but they approach it from different angles and perspectives. Data science techniques and tools can be used to enhance the study and understanding of art and visual culture, and art historical research can provide context and meaning to the data generated by data science methods.