Natural and artificial library classifications represent two distinct approaches to organizing information, each serving unique purposes in different contexts. Natural classification, grounded in the inherent relationships and characteristics of the subjects or entities being classified, aims to reflect the true affinities and evolutionary connections within a system. This approach aligns with the natural order of things and is often employed in biology and taxonomy. On the other hand, artificial library classification involves a systematic and intentional arrangement of information based on predetermined principles, categories, or codes. Typically applied in libraries and information management systems, this method prioritizes practicality and accessibility, allowing for efficient retrieval and organization of resources. Both natural and artificial classification systems play vital roles in facilitating the understanding, retrieval, and utilization of information, albeit in different domains and with distinct methodologies.
Natural Library Classification:
Natural Library Classification is a method of organizing library materials based on their inherent characteristics and natural relationships. This system aims to classify items in a way that reflects their intrinsic connections within a specific subject field or domain. In other words, materials are grouped together according to the subject’s inherent structure or the natural order that exists between them. This approach seeks to mirror the way knowledge and information are naturally related, creating an intuitive structure for organizing content.
For example, in a natural classification system, works related to botany would be grouped together, and within that group, materials on plant physiology, plant ecology, and plant classification might be further subdivided. Similarly, works on different species of animals would be grouped based on their biological relationships, such as mammals, birds, or reptiles. The natural classification system thus places emphasis on the interconnections between subjects, which can make it easier for users to locate related materials.
One of the key strengths of natural classification is that it aligns more closely with the way knowledge evolves and is structured in the real world, making it more intuitive for users who are familiar with the subject matter. However, natural classification systems can also be less flexible and more difficult to standardize, especially when dealing with interdisciplinary subjects or newly emerging fields of study. Despite these challenges, natural classification remains an important method for organizing library resources, ensuring that related materials are kept together in a meaningful way for the benefit of the users.
Artificial Library Classification:
Artificial Library Classification is a system used to organize library materials based on human-defined categories or frameworks rather than their natural or inherent relationships. In this method, information is grouped into pre-determined categories and subcategories that are designed to provide practical and systematic access to resources. The focus is not on how the subject matter is naturally related but on creating a standardized structure that is consistent, easy to apply, and useful for the classification and retrieval of information.
For example, popular artificial classification systems like the Dewey Decimal Classification (DDC) or the Library of Congress Classification (LCC) divide knowledge into a series of broad categories such as science, literature, history, and technology. These categories are further subdivided into more specific topics, but these divisions are based on a functional framework rather than any inherent connection between subjects. This means that, within the artificial classification, materials may be grouped together based on their subject’s utility or practical categorization rather than their natural relationship to one another.
One of the primary benefits of artificial classification is its efficiency in organizing a vast amount of information in a standardized manner, which is especially useful in large libraries and institutions. It provides a consistent approach that can be applied universally, allowing for the easy location of materials regardless of where the library is located. However, a key limitation is that it can sometimes obscure the natural relationships between topics, particularly when dealing with interdisciplinary fields or rapidly evolving subjects that do not fit neatly into predefined categories. Despite this, artificial classification remains a cornerstone of library organization, helping ensure that resources are easily accessible and manageable for both library staff and users.
Difference between Natural classification and Artificial Library Classification
Library classification is a vital process for organizing knowledge and ensuring easy access to information. Two significant approaches to classification in libraries are Natural Classification and Artificial Classification. While both systems serve the same purpose of categorizing materials for easy retrieval, they differ in various ways. Below is a detailed point-by-point comparison of the two systems:
| Aspect | Natural classification | Artificial Classification |
|---|---|---|
| Basis of Classification | This method organizes materials based on their inherent or natural relationships. Subjects are grouped together according to their intrinsic connections and logical hierarchy within the field of study. | In artificial classification, materials are organized according to human-defined categories and functional criteria, which may not necessarily align with the natural relationships between subjects. |
| Organizational Approach | The grouping of materials is based on the actual structure and order of knowledge within a discipline. For example, scientific fields such as biology and chemistry are organized by their inherent properties or interrelationships (e.g., taxonomy in biology). | This system organizes information into predefined categories that are often practical and easy to use. Systems like the Dewey Decimal Classification (DDC) or Library of Congress Classification (LCC) organize knowledge into broad areas such as science, history, or literature, regardless of natural interconnections. |
| Flexibility | Natural classification systems tend to be less flexible, especially when dealing with interdisciplinary or emerging fields that may not fit into established categories. | Artificial classification systems are more adaptable. They can be modified to incorporate new categories or areas of knowledge without disrupting the overall structure. |
| Handling Interdisciplinary Knowledge | Natural classification can struggle with interdisciplinary fields, as subjects that span multiple areas may not fit neatly into one category (e.g., environmental science combining biology, chemistry, and geography). | Artificial systems, due to their structured nature, often allow for cross-referencing or multiple categorizations, making them more effective in organizing interdisciplinary materials. |
| Standardization | This system is less standardized as it reflects the organic, natural relationships within a subject. It may vary based on the specific field of knowledge and its natural structure. | Artificial classification is highly standardized and provides a consistent framework for organizing materials across different libraries, making it easier for users to locate resources regardless of the institution. |
| Practicality and Ease of Use | It is often more intuitive for experts or those familiar with the subject matter since it reflects the real-world relationships between topics. | Artificial systems are generally easier for the general public to use. The categories are straightforward and serve the practical need for organizing diverse collections, even for users who may not be experts in a particular subject. |
| Accuracy in Categorization | This system tends to be more accurate in grouping materials that are closely related to a specific subject field. However, boundaries between categories can be blurred, especially when dealing with interdisciplinary topics. | Artificial systems can be very accurate within their predefined categories, but they may force materials into categories that don’t fully represent their content, particularly if they span multiple disciplines. |
| Development and Maintenance | Developing and maintaining a natural classification system can be more complex and time-consuming. It requires deep subject knowledge and continual updates as new research or developments emerge in a field. | Artificial systems are easier to develop and maintain, as they are based on a set of rules or standards. Adjustments can be made relatively easily to accommodate new subjects or areas of study. |
| Cultural and Regional Bias | While it reflects the true nature of knowledge, natural classification systems can still be influenced by cultural or academic perspectives, as the classification may depend on a particular worldview or scientific paradigm. | As artificial systems are human-made, they can be shaped by regional, cultural, or institutional biases. The categories and divisions are created based on what is deemed necessary or useful by the designers. |
| Example Systems | Examples of natural classification include biological taxonomy, where organisms are classified based on evolutionary relationships, or the periodic table of elements, which groups elements by their chemical properties. | Well-known examples include the Dewey Decimal Classification (DDC) and Library of Congress Classification (LCC), which divide knowledge into structured categories like philosophy, history, science, and literature. |
The choice between natural and artificial classification depends on the specific needs and goals of the library or institution. Natural classification is ideal for fields with clear, intrinsic relationships among subjects, while artificial classification offers a flexible, standardized solution that can cater to a wide range of disciplines and user needs. Both systems play critical roles in the effective organization of library collections, and often, a combination of both approaches is used to maximize efficiency and accessibility for library users.
3 Comments
It’s a good guide to library classification research I appreciate thanks alot.
thank you.
But this is complete nonsense. The DDC and LCC groups materials by subject, so these are not artificial classification systems. On the other hand, all library classification systems are actually artificial because a code is always given to arrange materials. If these so-called artificial classification systems group materials by subject and therefore content, these are inherent relationships and therefore a natural classification.