Depth classification

Meaning of depth classification

Depth classification, as defined by S.R. Ranganathan, refers to a classification scheme that aims to achieve comprehensive and expressive categorization of complex ideas with multiple facets and levels of abstraction. It involves organizing and structuring information in a hierarchical manner, incorporating intricate relationships and isolates of high order within various facets. In this context, depth classification extends the scope of a general classification scheme by incorporating additional levels or dimensions to capture the nuanced aspects of the subject matter being classified. By employing a depth classification scheme, the goal is to create a comprehensive framework that facilitates effective organization and retrieval of information.

Need of depth classification:

The need for depth classification arises from various factors and pressures faced by social institutions, including libraries, to effectively organize a vast and diverse universe of subjects. With the increasing specialization and emergence of micro thoughts, there is a demand for systematic organization techniques. Depth classification schemes are required to provide expressive and unique class numbers to micro thoughts within multiple facets and phases.

Ranganathan emphasizes the role of depth classification in research communication, preventing isolated individuals from conducting research in isolation. These schemes serve as a link in the chain of communication, enabling the collaboration and exchange of ideas. Additionally, depth classification is crucial for bringing together all aspects of a subject, facilitating a comprehensive understanding.

The need for depth classification schemes can be specifically stated as follows:

• General classification schemes often lack the necessary level of detail to represent complex subjects found in contemporary papers and reports handled by documentation systems.
• Broad classification schemes may not offer an optimal sequence for organizing subjects in a helpful manner.
• Highly specialized subjects, which are often compound in nature, require flexible combinations of subject headings. Depth classification allows for the formation of diverse combinations, accommodating the complexity and specificity of these subjects.

The need for depth classification arises from the limitations of general schemes, the requirement for an effective sequence of subjects, and the flexibility needed to handle complex and specialized topics in documentation systems. Depth classification schemes play a crucial role in organizing and representing micro thoughts within a comprehensive and expressive framework.

Depth classification and documentation activities

Depth classification plays a crucial role in documentation activities, particularly in information storage and retrieval systems. The efficiency of such systems depends on two key factors: selecting standard terms to represent micro subjects and creating compound headings by arranging component terms in a helpful order.

General or broad classification schemes often struggle to serve both self-arrangement and documentation needs effectively. Depth classification schemes, on the other hand, fulfill these requirements by listing micro subjects and providing rules for synthesizing the various terms that represent the subject. The faceted nature of depth classification allows for complete flexibility in coordinating terms within compound phrases. This flexibility is essential because a term in a compound phrase may be part of numerous combinations. Depth classification schemes employ various means to minimize the size of the classification schedule.

Recognizing the usefulness of depth classification, Ranganathan estimated a need for approximately 5000 depth classification schedules. In response, India has constructed about 100 depth classification schedules covering around 120 basic subjects, with a focus on engineering and technology fields. However, there has been less attention paid to social sciences and interdisciplinary subjects. This research aims to address this gap by constructing a depth classification schedule specifically for Library and Information Science (LIS), an interdisciplinary subject.

Depth classification plays a vital role in documentation activities by facilitating the selection of standard terms, creating compound headings, and providing flexibility in coordinating terms within compound phrases. It is an important tool for efficient information storage and retrieval systems, and efforts are being made to expand its application to various subject fields, including interdisciplinary subjects like LIS.

Approaches/methods used in the construction of this classification scheme

The construction of a depth classification scheme involves various approaches and methods. Here are the key approaches mentioned:

1. Speculative Approach: Also known as the a priori approach, this method involves constructing the classification scheme based on conjecture or theoretical assumptions. It relies on the expertise and knowledge of the classifier to anticipate the subject content and design appropriate categories.
2. Pragmatic Approach: Also referred to as the literary warrant approach, this method suggests that the classification scheme should be constructed based on the existing literature or actual documents in the field. It emphasizes aligning the scheme with the subjects and topics found in real-world publications, ensuring practical relevance and accuracy.
3. Blending Approach: Ranganathan recommended the blending approach, which involves combining elements of both the speculative and pragmatic approaches. This approach aims to strike a balance, leveraging theoretical considerations while also incorporating empirical evidence from the literature.

The construction of a depth_classification scheme involves several steps, which are explained by Ranganathan in his article published in 1964. Neelameghan and Gopinath have provided examples and methodologies for constructing depth classification schemes. Additionally, M. A. Gopinath has published a manual that offers step-by-step instructions for constructing depth classification schemes. B. C. Vickery has prepared a comprehensive manual specifically focused on the construction of faceted classifications.

These resources and studies provide guidance and methodologies for classificationists to develop effective depth_classification schemes, ensuring that the scheme accurately represents the subject content and facilitates efficient organization and retrieval of information.

Common isolates and the depth classification schemes

In the context of depth_classification schemes, common isolates refer to specific elements or characteristics that are shared across multiple main classes or facets. In the classification scheme based on the Colon Classification (CC), the isolates primarily pertain to the Personality facet, but there are also some isolates related to the Matter (MP) and Energy (E) facets.

The CC provides a methodology for identifying common Matter (MP) isolates, as described by Ranganathan in 1960. This methodology assists in determining those isolates that are applicable to multiple main classes within the classification scheme. Additionally, the seventh edition of CC includes a list of common matter properties and common energy isolates, which further highlights these shared elements.

By including common isolates, depth_classification schemes aim to capture the universal aspects or attributes that transcend specific subject areas. These isolates contribute to the overall cohesiveness and consistency of the classification scheme, allowing for effective cross-referencing and retrieval of information.

Lengthy class numbers of depth classification schemes- a justification:

The justification for the lengthy class numbers in-depth_classification schemes lies in their ability to represent micro subjects and facilitate individualization of specialized topics. Since micro subjects require multiple terms to adequately represent their components, the resulting class numbers naturally become longer.

Depth_classification schemes aim to provide comprehensive coverage by representing every component of a compound subject. This inclusiveness ensures that the class number accurately reflects the subject matter being classified. However, due to the incorporation of more digits and connecting symbols, the resulting class numbers can be cumbersome and lengthy.

In choosing between a non-coextensive, short, and easy class number offered by a general classification scheme and a coextensive, lengthy class number provided by a depth_classification scheme, the emphasis is placed on achieving excellence in librarianship and information storage and retrieval. The latter option, despite its length, allows for greater precision and specificity in organizing and retrieving information. It supports the unique and comprehensive representation of micro subjects, which is crucial for effective information organization and retrieval in specialized fields.

The rationale for selecting CC as a model for designing the present depth classifications schedule:

Species of classification schemes available for selecting as a basis for designing a depth classification schedule are:

1. Purely enumerative

2. Almost enumerative

3. Almost faceted

4. Rigidly faceted

5. Freely faceted

Amongst these species of classification schemes, only the freely faceted classification scheme offers freedom in the sequence and number of facets. So only the freely faceted classification schemes can be of use in the depth classification of newly emerging micro subjects. A more detailed explanation for using a freely faceted species for designing a depth classification schedule is provided by Ranganathan (1966).

A freely faceted scheme analyzes a subject and arranges the facets available in it in a helpful sequence. It also provides rules for number building by synthesizing appropriate facets. This is why the faceted schemes are also called analytico-synthetic classification schemes. The seventh edition of CC belongs to the freely faceted species of classification and so it is chosen as a model for designing the present depth classification schedule. In addition to this justification, the following two reasons substantiate the decision favoring CC as a model for designing the depth classification schedule.

(i) CC is based on a sound theoretical foundation. It’s normative principles, canons, postulates, principles of facet sequence and the various devices guide objectively in the design of depth classification (Ranganathan, 1989i).

(ii) Notational qualities: CC uses mixed notation consisting of Roman alphabets, both upper and lower case, Indo-Arabic numerals, various punctuation marks, and mathematical symbols. This extensive base of the notational system provides tremendous scope for the interpolation and extrapolation through various devices. The large base of this notational system also helps to have shorter class numbers.

2.2 Notational system:

Ranganathan provides a descriptive account of a notational system useful for designing a depth_classifications scheme. He explains it with a case study of a classification schedule of ‘Push bicycle’ (Ranganathan, 1972). Neelameghan and Sangameswaran (1966) explain the use of array division with packet notation. 

Reference Article:

1. Kumbhar, R. M. (2003). Contruction of vocabulary control tool thesaurus for library and information science. retrieved from: http://hdl.handle.net/10603/150911