Data

Estimated time: 40 minutes

Overview

Questions

• What is data in the humanities?
• What are the distinctions between different types of data?

Objectives

After completing this episode, participants should be able to

• differentiate between analogue data, digitised data, and born-digital data,
• understand how data is categorized, collected, and utilized within humanities research,
• explore the implications of different data types for different research methods and outcomes.

Types of Data

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Analogue Data: Analogue data originates in physical, non-digital formats like handwritten documents, photographs, or physical artefacts.

digitised Data: digitised data refers to analogue information that has been converted into digital formats through processes such as scanning, encoding, or transcription. This transition expands the accessibility and usability of analogue resources, facilitating modern research methods. Understanding different aspects of digitised data is critical for recognizing how non-digital resources have been adapted to meet digital needs.

Born-Digital Data: Born-digital data is inherently created in digital environments and exists only in these formats . It includes databases, digital texts, or media files that have never existed in physical, analogue form. This distinction highlights how digital-first practices shape contemporary research in the humanities, emphasizing the real-time creation and accessibility of data through digital platforms.

Exercise

Analogue vs. Digital – What Are We Really Looking At?

This exercise invites you to explore how analogue and digital data differ by looking at a cultural heritage object. It focuses on what happens when physical artworks are made accessible through digital media. Let’s take some data from the Metropolitan Museum of Modern Art’s collection.

Guiding Question

What kind of data are we working with when we interact with digitised cultural objects? What happens to the qualities of analogue objects when they are transformed into digital representations?

Step 1: Observation

Choose a digital image of an object from the Metropolitan Museum of Modern Art’s online collection (or from another digital museum resource). Reflect on the following questions: What kind of object is this originally? What can you observe on the screen? What might be missing compared to experiencing the object in person?

Step 2: Guided Discussion

With the following questions: If the original artwork is analogue (physical), and we’re viewing it on a screen, what kind of data are we really working with? What happens to the object’s materiality when it is digitized? How does digital representation affect our understanding or interpretation? What do we gain, and what do we lose, in this transformation?

Step 3: Reflection

Consider: What qualities of an object are difficult or impossible to capture digitally? Which digital formats (e.g., high-resolution images, 3D models, metadata) attempt to compensate for these limitations? In your own field of study, where do you encounter the analogue-to-digital transformation? How does it affect your research or interpretation?

Output

We’re viewing the painting on a computer screen. Everything we see is displayed digitally. Although the original object is analogue, our interaction with it is entirely digital. The painting has been digitized—converted into data (e.g., pixels, metadata) that can be stored, processed, displayed by computers, shared, searched, and manipulated. We are not interacting with the analogue object itself, but with its digital representation. This transformation allows broader access but also introduces limitations: aspects like scale, texture, or true colour may be lost, and we experience only a digital approximation. Understanding this transformation is key to working with data in the digital humanities and is critical for thinking about how cultural knowledge is shaped by the digital medium.

By analogue data, we mean the physical artefacts in the museum. The museum’s collection includes numerous physical objects such as sculptures, paintings, and other artefacts that exist solely in their original, non-digital form. For instance, the collection of ancient Egyptian art in the Metropolitan Museum comprises approximately 30,000 objects, as you can see here.

By digitised data, we mean for example digitised images. High-resolution photographs of artworks and artefacts, such as paintings, sculptures, and archaeological findings, have been digitised for research and accessibility. These images are accessible through the museum’s online collection database.

Born-Digital Data are some born-digital photographs or videos, as well as digital records and databases of the museum’s collections, including metadata and detailed descriptions of artworks. The museum’s archives include born-digital materials such as exhibition records, curatorial files, and administrative documents created and stored digitally.

Affordances and challenges associated with each data type, and their interactions within the broader research ecosystem:

These types of data are utilized in different ways, each shaping and supporting distinct research practices.

Analogue data, preserved in magazines, archives, or physical collections, provides the foundation for historical and material studies, offering direct engagement with original sources. Analogue data’s tactile and contextual elements are invaluable for understanding its provenance and authenticity. Still, these data are often constrained by access limitations, requiring researchers to travel to specific locations.

digitised data transforms the accessibility of these physical sources, enabling remote access through digital platforms and repositories. This shift democratizes research by bridging geographic barriers and facilitating comparative studies. Additionally, digitization often incorporates metadata and search functionalities, enhancing the discoverability and usability of analogue sources. However, the process of digitization raises concerns about data integrity, potential loss of context, and the prioritization of certain collections over others.

Born-digital data is, by contrast, inherently dynamic, designed for integration into digital environments. It supports collaborative and interdisciplinary research, as it can be shared, updated, and analyzed in real-time. The computational possibilities of born-digital data, including machine learning and data visualization, open new avenues for exploration, particularly in fields like Digital Humanities, data science, and social network analysis. Nonetheless, this type of data also poses challenges, such as ensuring long-term preservation, managing data privacy, and addressing the ephemerality of digital formats.

Moreover, these types of data often interact within hybrid research workflows. For instance, digitised analogue data can be enriched through computational analysis alongside born-digital datasets, creating new layers of insight. Similarly, born-digital data may prompt the re-examination of analogue sources, fostering a cyclical process of discovery and reinterpretation. This interplay highlights the evolving landscape of knowledge production, where diverse data types converge to address complex research questions.

Outcome

How do institutional infrastructures, such as libraries, archives, and data centres, support these processes and navigate the challenges of balancing preservation, access, and innovation?

Key Points

• Analogue data is preserved in magazines, archives, or physical collections.
• digitised data is a transformation of analogue data into digital form.
• Born-digital data has no analogue representation.