Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

How Data are Classified: Categorical Data01:11

How Data are Classified: Categorical Data

29.3K
A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
29.3K
Schemas01:42

Schemas

10.8K
A schema is a mental construct consisting of a cluster or collection of related concepts (Bartlett, 1932). There are many different types of schemata, and they all have one thing in common: schemata are a method of organizing information that allows the brain to work more efficiently. When a schema is activated, the brain makes immediate assumptions about the person or object being observed.
10.8K
Social Foundations of Self IV: Self in Digital Communication01:30

Social Foundations of Self IV: Self in Digital Communication

283
Since the early 2000s, computer-mediated communication (CMC) has grown rapidly, playing a crucial role in self-development. A key distinction between CMC and real-life interactions is the lack of a physically present partner. This absence makes non-verbal cues such as facial expressions, body language, and paralinguistic signals unavailable in CMC platforms like email, instant messaging, or social media. The lack of these cues can create ambiguity and complicate how feedback is interpreted.The...
283
How Data are Classified: Numerical Data00:59

How Data are Classified: Numerical Data

27.1K
Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...
27.1K
Classification of Systems-I01:26

Classification of Systems-I

742
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
742
Classification of Systems-II01:31

Classification of Systems-II

651
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
651

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Fish see further than you might think.

The Behavioral and brain sciences·2026
Same author

The evolutionary functions of consciousness.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences·2025
Same author

How should the advancement of large language models affect the practice of science?

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

Alternative models of funding curiosity-driven research.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

Advancing paleoanthropology beyond default nulls.

The Behavioral and brain sciences·2025
Same author

Language-of-thought hypothesis: Wrong, but sometimes useful?

The Behavioral and brain sciences·2023

Related Experiment Video

Updated: May 4, 2026

Creating Objects and Object Categories for Studying Perception and Perceptual Learning
14:38

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

13.6K

Cross-cutting categorization schemes in the digital humanities.

Colin Allen1,

  • 1Department of History and Philosophy of Science and Program in Cognitive Science, Indiana University, Bloomington, Indiana 47405, USA. colallen@indiana.edu

Isis; an International Review Devoted to the History of Science and Its Cultural Influences
|December 18, 2013
PubMed
Summary

Researchers face challenges in accessing digital humanities texts. This study explores categorizing philosophical concepts using the Indiana Philosophy Ontology (InPhO) to improve digital resource usability for both humans and machines.

More Related Videos

Hybrid-Cut: An Improved Sectioning Method for Recalcitrant Plant Tissue Samples
09:38

Hybrid-Cut: An Improved Sectioning Method for Recalcitrant Plant Tissue Samples

Published on: November 23, 2016

21.6K
A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.1K

Related Experiment Videos

Last Updated: May 4, 2026

Creating Objects and Object Categories for Studying Perception and Perceptual Learning
14:38

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

13.6K
Hybrid-Cut: An Improved Sectioning Method for Recalcitrant Plant Tissue Samples
09:38

Hybrid-Cut: An Improved Sectioning Method for Recalcitrant Plant Tissue Samples

Published on: November 23, 2016

21.6K
A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.1K

Area of Science:

  • Digital Humanities
  • Philosophy
  • Information Science

Background:

  • Scholarly text digitization presents challenges and opportunities for humanities research.
  • High-quality content representation is crucial for machine and human usability of digital resources.
  • Relating different categorization schemes is a key problem for diverse digital humanities projects.

Purpose of the Study:

  • To discuss the rationale for categorizing philosophical concepts.
  • To survey approaches for categorizing continuously changing scholarly materials.
  • To present the Indiana Philosophy Ontology (InPhO) project's goals and methods.

Main Methods:

  • Discussing the rationale behind concept categorization in philosophy.
  • Surveying existing approaches for categorizing dynamic scholarly content.
  • Describing the Indiana Philosophy Ontology (InPhO) project's methodology.
  • Illustrating analytical possibilities with powerful modeling methods.

Main Results:

  • Categorization schemes must be adaptable for evolving digital resources.
  • The Indiana Philosophy Ontology (InPhO) offers a framework for organizing philosophical concepts.
  • Advanced modeling enables new forms of analysis for digital humanities data.

Conclusions:

  • Effective categorization is essential for leveraging digital humanities resources.
  • Ontologies like InPhO can bridge the gap between human and machine understanding of complex data.
  • Sophisticated modeling techniques unlock deeper insights from digitized scholarly texts.