Upon completion of this lesson, you will be able to:
Information science is an interdisciplinary field primarily concerned with the life cycle of information objects representing concepts from a domain and the information universe in which the objects exist.
Information science predates computer science and is a broad, interdisciplinary field, incorporating not only aspects of computer science, but often diverse fields such as archival science, cognitive science, communications, library science, museology, management, mathematics, philosophy, public policy, and the social sciences. It is decidedly not computer science, data science, information systems, management information systems, nor library science, but it definitely draws on aspects from all of them.
Information science deals with all the processes and techniques pertaining to the life cycle of information objects, including discovery, capture, generation, representation, classification, organization, packaging, dissemination, transformation, refinement, usage, storage, communication, protection, presentation, etc. in any possible manner and not restricted to computer systems.
Information systems do not need to be computer-based and digital, they can also be analog or non-digital. For example, we generally think of an archive of information as a database or files in a file system, but the archive might as well be information written on index cards and filed using some scheme in a card catalog. Recall the organization of libraries before the advent of digital repositories: books and other material were cataloged on card files organized in large drawer-based catalogs (acting as an “index”) and the shelves containing the actual books were organized using the Dewey Decimal System.
The Dewey Decimal System (DDS) is (still) a widely used method for classifying and organizing library materials. Developed by Melvil Dewey in 1876, this system assigns a numerical code and a subject heading to each book or item in the library. Here’s a basic breakdown of how it works – appreciate the “classification” mechanism of the DDS.
Ten Main Classes: The Dewey Decimal System divides all knowledge into ten main classes, with each class assigned a hundred numbers (000-999). These classes cover everything from general knowledge to history.
Ten Divisions: Each of the ten main classes is further divided into ten divisions.
Ten Sections: Each division is then divided into ten sections.
For example, the number 500 represents “Science,” 510 is for “Mathematics,” 520 is for “Astronomy,” and so forth.
Each book or item is given a unique number, known as the “call number.” This number is based on the subject of the book. The call number includes not just the Dewey Decimal classification but often a combination of letters and other numbers that help in pinpointing the exact location of the item on the library shelves.
Before digitization, library organization relied heavily on physical systems like card catalogs. Each book in the library had a corresponding card (or multiple cards for larger libraries) in the catalog, which provided the book’s title, author, subject, and its call number. Librarians and patrons used these card catalogs to find books and their locations in the library.
The Dewey Decimal System, combined with card catalogs and physical organization of books on shelves, was the primary method of organizing and finding books in libraries before the advent of digital databases and online catalogs. This system made it easier for librarians and patrons to find specific books in a large collection and ensured a consistent organization across many libraries.
There are several definitions that have emerged over the years that seek to define information science. The definitions agree that information science is an interdisciplinary field principally concerned with the collection, storage, retrieval, analysis, classification, manipulation, transmission, dissemination, and protection of information. Information science was originally restricted to library science but its definition and approach has widened over the years. It is now considered an interdisciplinary science that encompasses computer science, data science, linguistics, psychology, sociology, cognitive science, and human computer interaction.
One has to be careful, though, not to confuse information science with information systems. Information science is much broader than just the study of the design and construction of systems that store and process information. Lastly, it is also necessary to distinguish information science from data science. The modern field of data science is concerned with the automated extraction of information from large amounts of data, while information science encompasses also the provenance, quality, representation, and use of the information.
Information Scientists are practitioners within the field of information science who study the provenance, quality, representation, archiving, and use of information in organizations, along with the interaction between people, organizations and information systems, with the aim of creating, replacing, improving, or understanding information systems that aid in information-based decision-making.
An information scientist often conducts:
When we discuss information, we need to understand where the information comes from (provenance) and how good it is (quality). Part of information quality is having an understanding of the veracity of the information which helps assess its reliability and how much we can trust the information as part of the decision making process.
Information is a somewhat ephemeral term. It encompasses information contained in information assets such as documents, emails, systems, processes, databases, among others. We can distinguish between “knowing what something is” and “knowing how to do something”. So, on the one hand we must define information objects and on the other we must understand information processes.
In Defining Knowledge, Information, Data, the author lays out some definitions for information, data, versus knowledge. He argues that data is unorganized and raw facts and numbers, while information is contextualized and categorized. Knowledge is know-how, understanding, and insight.
Again, it becomes increasingly clear that there is no simple and universal definition of information.
Naturally, when one studies a new discipline, it is worthwhile to ask what contributions that field has made and what some of its biggest achievements were. This letter by Trudi Bellardo Hahn titled What Has Information Science Contributed to the World? sheds some light on this question. In the letter she states that among the key contributions are the creation of the field of bibliometrics, innovations in digital indexing systems, digital document and information management, and the study of users’ interactions with information. Of course, she listed additional contributions but those are some of the most important ones.
In a response to the letter, Albert Henderson wrote, “[…] even if they [humans] had perfect retrieval systems they would be presented with so many items that they could not assimilate and process them”. Henderson goes on to say that information scientists “commit…to handling information with sophistication and meaning, not merely mechanically”. So, one can argue that information scientists have one of the most difficult jobs in the world: to gather and understand information and to disseminate and present it to users of that information so that they can apply it to form courses of action and make decisions. They aren’t part of only one aspect of that, rather they are required to have skills that span the whole lifecycle of information.
What complicates the job of information scientists in the fact that much of the information in an organization is not easily shared and is frequently tacit within systems, processes, and people. The SECI Model first proposed by Nonaka & Takeuchi (1996) helps clarify the process of how information emerges in organizations.
Read Chapter 1 in Davis and Shaw (2011) to get a better understanding of where information comes from in our modern world, some of the effects of information overload, how to evaluate the veracity and validity of information, and how to manage information.
Chapter 1: Our World of Information. In Information Science and Technology. (Davis and Shaw, 2011)
Read excerpts of Chapter 2 in Davis and Shaw (2011) to see their view of the differences between information, data, and knowledge, as well as the data-inforamtion-knowledge-wisdom hierarchy. In the chapter, the authors also introduce the classic Shannon-Weaver model of communication on which much of information thoery and modern information communication and transmission is based. Lastly, the chapter explains how information is disseminated and how all of that leads to their definition of information science.
In this lecture, Dr. Schedlbauer attempts to shed some light on information science as a discipline, the SECI model, and a definition of the terms data, information, and knowledge.
Slide Deck: Information Science as a Discipline
In summary, it becomes clear that information science is neither data science, nor computer science, nor simply data visualization. It is not just about knowledge, or data, or information. It is not just making statements about what defines information quality. Nor is it simply about working with organizations to collect, organize, and manage their information. It is not even only about utaking data and distilling it into information then knowledge to support decisions making. It is about all of these things and more.
Nonaka, L., Takeuchi, H., & Umemoto, K. (1996). A Theory of Organizational Knowledge Creation. International Journal of Technology Management, 11(7-8), 833-845.
Davis, C. H., & Shaw, D. (Eds.). (2011). Introduction to Information Science and Technology. American Society for Information Science and Technology.