10 Chapter 10: Emerging Trends and Disciplines

10.1 Introduction

The information and knowledge professions can be best described as one that deals with data and information throughout their lifecycle from creation to disposal with the objective of adding value in the form of actionable knowledge. According to Bates (2015), the information discipline is a unique field that does not fit in the spectrum of traditional disciplines. She referred to the information discipline as a meta-discipline field like education and philosophy. Such disciplines deal with a body of knowledge from different perspectives and from a particular orientation. The idea stems from the fact that data and information are not unique and part of every discipline where there is a need to apply the same method and techniques for collecting, organizing, storing, retrieving, and processing information for further action. Every profession has both academic disciplinary aspects and professional practice aspects. However, many see the information science discipline as an interdisciplinary field in which scholars from related disciplines such as library science, computer science, communication, behavioral science, and business, come together to create a body of knowledge that laid the foundations for the information profession. This was the case with the evolution of the information retrieval field where work by Salton, McGill, Spärck Jones, and others in the seventies and eighties created a body of knowledge that served as the basis for the development of the current information systems.

10.2 The Transformation of a Profession

Historically, librarians, archivists, and record managers assumed the duty of gathering, processing, organizing, and disseminating information for many reasons including the advances of science and the protection of cultural heritage. The evolution of the information and knowledge professions has been shaped over time by many technological advances, such as the invention of paper, the printing press, and the development of computers. Formal education in the information and knowledge professions started when Melvil Dewey became the librarian at Columbia College in 1883. He offered the first class in library economy in 1887. Melvil Dewey is not much known for his role in library and information science education as much as his role in creating the famous Dewey Decimal Classification (DDC) system. Dewey’s library classification system was based on the classification of knowledge by Sir Francis Bacon (Wiegand, 1998). Dewey recognized the importance of working with other disciplines and helped establish the American Library Association (ALA) in 1876. In 1926, the Carnegie Corporation funded the first Graduate Library School at the University of Chicago (Richardson, 2010).

The big shift and major transformation happened in the field was with the invention of computers and the automation of library functions. The automation of the card catalog and the ability to access bibliographic records online marked an important step in the transformation of library profession. Prior to that Vannevar Bush (1945) published an article under the title “As We May Think” where he discussed mechanizing the process of storing and retrieving books with a higher degree of speed and flexibility. Three years later in 1948, Holmstrom described the possibility of using the UNIVAC computer in searching bibliographic records (Sanderson and Croft, 2012). Early library automation efforts started in the 1930s with the use of punch card devices to automate the circulation and acquisition functions. Dr. Ralph H. Parker Created a circulation control system at the University of Texas at Austin using IBM Punched card equipment (Bolvin, 1970).

As computer technology advanced in hardware and software in the 1960s, integrated library automation systems started to evolve. The development of the machine-readable cataloging (MARC) standard facilitated sharing of bibliographic records between different libraries. The advances in information technology and the automation of various library functions enabled a more efficient method of information storage and retrieval. Research in information retrieval picked up steam in the seventies with the formation of the first large information retrieval research group by Gerard Salton. Salton was one of the information science pioneers in modern information retrieval (Sanderson and Croft, 2012). Progress made in information retrieval research work in the 1970s and 1980s paved the way for the current Internet indexing and searching services, such as Yahoo and Google. Work by Spärck Jones in the seventies and eighties extended Luhn’s term frequency work to include the statistical analysis of the word occurrence in the document and across a collection of documents. Inverse document frequency (IDF) which was introduced by Spärck Jones measures the significance of a term in a document in relation to a given document corpus (Jones, 2004).

During the 1990s, a wide range of technologies were introduced which built on the successes made in information retrieval in the previous two decades. New technologies such as scanning and OCR allowed the capture and conversion of documents from paper into digital format. As a result, a new generation of information systems developed including full text databases, document management systems, hypermedia, multimedia, and virtual reality. The ability to scan, store, and display images of documents on the screen revolutionized the way information is stored and accessed. Also, the advent of the Internet and the web in the 1990s made global access to information a reality. Access to information on the Web was made possible by the development of hypertext transfer protocol (HTTP), the hypertext markup language (HTML), and web browsers. Internet search engines were developed to provide efficient and fast methods of locating and retrieving information. Web 2.0 moved the web from static web pages to more dynamic and interactive where access to information in real time is made possible. The concept of knowledge portals and enterprise portals started to emerge by integrating a diverse range of applications and providing SSO access technologies.

At the turn of the century and in the year 2000s, a new era started which is characterized by globalization and the increase emphasis on knowledge as a factor of growth. The shift toward the knowledge-based economy has given rise to intellectual capital, intellectual property, and the wider concept of the knowledge management. It has also given rise to mega-corporations such as Google, Amazon, Netflix, and Facebook just to name a few. The relationship between technology, people, and information has also given birth to the information schools or what become known as the iSchools movement.

The iSchools movement was born out of the need for a new generation of library and information science professionals capable of keeping up with the rapid advances in information and communication technologies. In 2005, several library and information science schools realizing that their programs had the capacity to reach a broader audience and students can be prepared to work in other fields beyond librarianship, elected to change their name by dropping the word library to reflect the broader nature of the information profession. It is important to note that several institutions who joined the iSchools consortium later were not library schools and are part of the CRA. The iSchools vision as stated on the iSchool.org website is to expand their presence internationally and being recognized for creating innovative information solutions and systems to benefit individuals, organizations, and the society at large.

10.3 The Information and Knowledge Domains

The information and knowledge domains continue to expand rapidly due to profound changes in technology. Since the first library school was established at Columbia in 1883 by Melvil Dewey, libraries have played a key role in the transformation of the information professions. For over a century, libraries and librarians occupied the center of the Copernican universe of the information and knowledge professions (Marchionini and Moran, 2012). However, recent advances in the field of information communication technologies have transformed the library profession and increased the need to prepare a new generation of information and knowledge professionals, such as data curators, data scientists, information architects, web developers and designers, social media strategists, knowledge managers, digital librarians, and archivists.

The transformation of the profession from a library-centered approach to an information-centered approach was echoed by Lancaster (1984) in his discussion of a paper by Giuliano in 1969. In his article, Lancaster pointed out the image problem and the misguided perception of the public of what librarians do. Due to the increased use of computers and the increased digitization of library materials, library work has been transformed. The shift from the library as a place to the library as a collection of services that can be delivered from anywhere and anytime has impacted the types of skills and competencies needed to perform the job. Responding to the changes that took place in the library and information profession, Bates (2015) pointed out that “at this historical moment, we are taking part in an extraordinary sea change in how information science, libraries, archives, and all the information-related disciplines are viewed.”

Bates (2015) argued that information science needed to be seen as a different type of discipline, in comparison to the usual array of disciplines. She described information science as a meta-discipline like education and philosophy. The use of the information domain and knowledge domain interchangeably illustrates the inseparable relationship between information and knowledge. The discussion about the type of skills and competency needed for librarians to assume the role of information and knowledge professionals is not new. Hawamdeh and Foo (2001) identified a set of skills and competencies needed by information specialists to assume the role of information and knowledge managers in the information society. Since then, several studies have been carried out in efforts to highlight the changes taking place due to advancements in information technologies and the need to develop advanced programs and specializations to prepare the next generation of information professionals (Ajgaonkar and Neelam, 2020; Bishop et al., 2015; Federer, 2018; Yatim et al., 2019).

One approach to analyzing the information and knowledge domain is to examine the intersection between data, information, and knowledge rather than the transformation from one state to another as described in the data, information, knowledge, and wisdom (DIKW) model. The DIKW model assumes that data creates information, information creates knowledge, and knowledge creates wisdom. While the DIKW model is easy to visualize, it has been criticized as an attempt to oversimplify a complex problem (Weinberger, 2010). The Venn diagram (Figure 10.1) illustrates the types of activities happened at the intersection of data, information, and knowledge. We placed analytics at the heart of the Venn diagram or at the intersection of the three areas (data, information, and knowledge) to symbolize the types of activities that takes place when the three elements interact with each other and with people and technology. People and technology are not explicitly shown in the diagram on the basis that these are essential and fundamental elements in the analysis of any domain. At the intersection of information and knowledge, it is possible to visualize topics such as information seeking behavior, social networks, communication, sensemaking, and information visualization. At the intersection of data and information, it is possible to visualize topics such as information architecture, data curation, metadata, taxonomies, and ontologies. At the intersection of data and knowledge, it is possible to visualize topics such as knowledge discovery, knowledge mapping, natural language processing, and deep learning.

The widening scope of the information profession and the emergence of new disciplines, such as data science and knowledge management, require information professionals to embrace change and resume high-level responsibilities that should go beyond their traditional roles. Information and knowledge professionals of the future must be technologically savvy and have a better understanding of the strategies and methods needed to leverage knowledge resources, pursue lifelong learning, and nurture a culture of innovation and entrepreneurship.

10.4 Emerging Disciplines

In the last 50 years, researchers and scholars from related and allied disciplines have converged on the information profession and left their marks on the type of theories and methods developed to cement the information science field as we know it. Claude Shannon’s paper “A Mathematical Theory of Communication” published in 1948 paved the way to the modern understanding of the role of information communication (Ephremides, 2009). Shannon presented a unifying theory for the transmission of information that could be applied to telephones, radio, television, or any other system.

The theoretical transformation of any profession happened normally when a group of scholars and researchers from related and allied disciplines followed in the footsteps of Claude Shannon, finding interest in indexing and information retrieval an area revolutionized by the invention of computers. In the 1960s, Gerard Salton, first at Harvard University and then at Cornell University, started the first information retrieval research group. Work in this spanned three decades of intensive and fruitful work in the areas of indexing, storage, and retrieval. The most notable work in the 1970s and 1980s is Luhn’s term frequency (tf) which is based on the statistical analysis of the keywords in a document. The work by Spärck Jones then extended the work of Luhn’s term frequency to include the statistical analysis of the word occurrence in the document and across the collection of documents. Spärck John introduced the concept of inverse document frequency (idf) which measures the significance of the term in a given document corpus (Jones, 2004).

The 1980s and the 1990s are considered the start of the digitization era with the development of full text databases, document imaging systems, scanning, optical character recognition (OCR), and optical storage (Al-Hawamdeh, 1989; Saffady, 1992). The ability to store large amounts of text and perform free text indexing opened the door to a more efficient way of capturing and processing information. Free text using keywords provided higher flexibility in formulating queries enabling automatic indexing of large quantities of text which otherwise would have been slow and costly. Automatic indexing using inverted files allow the creation of indexing services using abstracts in the eighties and then expanded to include full text and imaging in the nineties. In 1990, the field of information was further expanded by the development of several major areas, such as multimedia, document management systems, hypermedia, and virtual reality.

The birth of the Internet and the web in the nineties and the use of automatic indexing and free text searching led to the development of web search engines, such as Yahoo, AltaVista, and Google. This opened the door to a borderless society and enabled access to information globally. The development of hypertext transfer protocol (HTTP), the hypertext markup language (HTML), and web browsers changed the way people use information. As web applications started to replace traditional information systems and take advantage of the Internet’s open platform, new types of opportunities and challenges emerged. The development of Web 2.0 created more dynamic and real time use to information. Real time information transactions revolutionized the communication channels and paved the way for more integrated enterprise knowledge systems with SSO access technologies.

At the turn of the century, the library profession expanded to include new areas of emphasis, new specializations, and new disciplines. In the next three sections, we discuss information science, knowledge management, and data science.

10.4.1 Information Science

As discussed earlier, the field of library science emerged as an academic discipline after Melvil Dewey started to offer classes in library economy at Columbia College in 1887. Dewey was recognized as a pioneer in the field of library science in which one of his signature achievements is the creation of the Dewey Decimal Classification (DDC) system. Librarians until then did not have formal education and many learned the profession through mentoring and apprenticeship. In England, the library association was the first to offer examinations and certification for librarians. Following in the footsteps of Dewey, colleges and universities started to offer formal library education at the undergraduate level. In 1928, the University of Chicago Graduate Library School offered the first master’s degree in library science. Gradually, universities and colleges in the United States started to offer library science certification and gradually moved away from undergraduate certification. The argument for offering library science education at the master’s level allows people with different subject backgrounds to enter the profession and therefore enhance the interdisciplinary nature of the profession.

Information science and information retrieval are terms introduced in the 1960s with the invention of computers and the increased automation of libraries. The term information science can be traced back to Jason Farradane in an article published in 1955 regarding the education of information scientists (Farradane, 1955). The first use of the combined terms library and information science started in 1964 when the University of Pittsburgh School of Library Science added the term information science to become the School of Library and Information Science at the University (Galvin, 1977). Later on, many library and information science schools dropped the word library and shifted more toward information science influenced by changes in technology and the digital revolution, and identified with works, such as Shannon’s information theory, Gerrald Salton, Spärck Jones, and others’ work in information retrieval and other related topics. The iSchools movement has had a considerable influence on the changes that took place in the library and information science field.

10.4.2 Knowledge Management

The second area that is closely related to the information profession domain is knowledge management. Knowledge management gained momentum in the 1990s because of many factors related to advances in information communication technology, organizational effectiveness, management of intellectual capital, and the realization of the importance of knowledge and human capital in the knowledge economy. The publication by Nonaka (1991) in Harvard Business Review followed by a book by Ikujiro Nonaka and Hirotaka Takeuchi (1995) on “The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation” has helped popularize the terms tacit knowledge and knowledge management.

While there is still no agreed-upon definition for knowledge management, though several attempts have been made to define knowledge management. According to Davenport and Prusak (1998), knowledge management is

…a fluid mix of framed experience, values, contextual information, and expert insight that provides a framework for evaluating and incorporating new experiences and information. It originates and is applied in the minds of knowers. In organizations, it often becomes embedded not only in documents or repositories but also in organizational routines, processes, practices, and norms. (p. 5)

Wiig (1999) approached knowledge management from an organizational perspective through the systematic and deliberate application of knowledge to achieve organizational effectiveness and maximize return on investment. Sveiby (1997) viewed knowledge management as consisting of an IT-track (management of data and information) and the people perspective labeled as the people-track (people-centered approach). We view knowledge management as an interdisciplinary approach to dealing with all aspects of knowledge processes and practices; that is, it is the amalgamation of people, technology, and processes.

Knowledge management is still evolving as a discipline and, despite the strong interest from private and public institutions; it has yet to establish itself as a discipline with a clear formalized certification. Several knowledge management programs at the level of master’s and PhD were established by several universities around the world. These programs are housed in different colleges and departments, such as library and information science schools, business schools, and education. One of the challenges for knowledge management as an emerging field is the fact that information and knowledge are inseparable entities. Information does not exist without knowledge and knowledge is a byproduct of contextualizing data as an object into information as an activity. This implies that information science and knowledge management after all might not be different, and these two fields may be converging into one entity as the information and knowledge profession.

10.4.3 Data Science

Another area that emerged in the last decade is data science. The interest in data science came about due to the exponential growth of data and digital information as well as recognizing the importance of data as an organizational asset. The first use of the term data science was in a book by Peter Naur entitled Concise Survey of Computer Methods in 1974. The book proposes a survey on contemporary data processing methods for different applications. Naur considered data science as part of the field of computer science; however, in November 1997, a new definition of data science emerged that highlighted this term as closely related to statistics (Wu, 1997). Cleveland (2001) proposed changing the name of the field of statistics to data science based on the technical work areas of computer science. According to Cleveland, the six technical areas covered by data science should be as follows: (1) 25% multidisciplinary investigation; (2) 20% models of methods for evaluation; (3) 15% computing with data; (4) 15% pedagogy; (5) 5% tool evaluation; and (6) 20% theory.

There is no shortage of definitions of data science (Kempler and Mathews, 2017). Most of these definitions are focused on data science as an interdisciplinary field that used methods, processes, and algorithms from related fields such as statistics, computer science, and information science. Data science extends and builds on previous work in the areas of big data, data mining, machine learning and knowledge discovery from databases.

10.5 Conclusion

In this chapter, we discussed emerging trends and disciplines in the information and knowledge professions, as well as the profound impact of technology on the library profession and the historical transformation of library education over the years. The changing role of librarians from gatekeepers to information specialists and knowledge professionals requires them to attain a higher level of skills to accommodate the continued expansion of the information and knowledge domains. The theoretical transformation happened when scholars and researchers from related and allied disciplines came together to develop theories and models that laid the basis for information science to emerge as a disciple. The three different general areas that are currently dominating the discussion today are information science, knowledge management, and data science. We argued in this chapter that while these areas seem to be emerging as separate disciplines, they are also converging into the broader concept of information and knowledge professions.

Discussion Questions

• What is a profession?
• What are the main characteristics of a profession?
• What is an information domain?
• What is a knowledge domain?
• What are information and knowledge domains?
• Is knowledge management a science?
• What are the main drivers for knowledge management?
• What is the difference between data science and information science?
• Discuss the evolving role of the information and knowledge professional in the knowledge economy.

References

Al-Hawamdeh, S., & Willett, P. (1989). Paragraph-based nearest neighbour searching in full-text documents. ELECTRON. PUBL., 2(4), 179-192.

Ajgaonkar, S., and Neelam, N. (2020). Skills and competencies of information technology professionals: A systematic literature review. In Handbook of Research on the Role of Human Factors in IT Project Management (pp. 36–56).

Bates, M.J. (2015). The information professions: Knowledge, memory, heritage. Information Research, 20(1), paper 655. Retrieved from http://InformationR.net/ir/20-1/paper655.html

Bishop, B. W., Cadle, A. W., and Grubesic, T. H. (2015). Job analyses of emerging information professions: A survey validation of core competencies to inform curricula. The Library Quarterly, 85(1), 64–84.

Bolvin, B. M. (1970). A survey of mechanization and automation in large university libraries. University of Southern California.

Bush, V. (1945). As we may think. The Atlantic Monthly, 176(1), 101–108.

Cleveland, W. S. (2001). Data science: An action plan for expanding the technical areas of the field of statistics. International Statistical Review, 69(1), 21–26.

Ephremides, A. (2009, August). How information theory changed the world-a brief review of the history of the information theory society. In 2009 IEEE Conference on the History of Technical Societies (pp. 1–7). IEEE.

Farradane, J (1955). Professional education of the information scientist. In Congrès International des Bibliothéques et des Centres de Documentation, Brussels, 11–18 September 1955 (Vol. IIb, pp. 76–81). La Haye: Martin Nijhoff.

Federer, L. (2018). Defining data librarianship: A survey of competencies, skills, and training. Journal of the Medical Library Association: JMLA, 106(3), 294.

Galvin, T. J. (1977). Pittsburgh. University of Pittsburgh Graduate School of Library and Information Sciences. In A. Kent, H. Lancour, and J. E. Daily (Eds.), Encyclopedia of Library and Information Science (Vol. 22, pp. 280–291). New York: Marcel Dekker.

Giuliano, V. E. (1969). The relationship of information science to librarianship—problems and scientific training. American Documentation, 20(4), 344–345. https://doi.org/10.1002/asi.4630200414

Hawamdeh, S., and Foo, S. (2001). Information professionals in the information age: Vital skills and competencies. In Proc. International Conference for Library and Information Science Educators in the Asia Pacific Region (ICLISE 2001), Kuala Lumpur, Malaysia, June 11–12.

Kempler, S., and Mathews, T. (2017). Earth science data analytics: Definitions, techniques and skills. Data Science Journal, 16(6), 1–8.

Lancaster, F. W. (1984). Implications for library and information science education. Library Trends, 32, 337–348.

Marchionini, E. G., and Moran, B. B. (2012). Informational Professionals 2050: Educational possibilities and pathways, University of North Carolina at Chapel Hill.

Nonaka, I. I. (1991). The knowledge-creating company. Harvard Business Review, 69, pp. 96-105.

Nonaka, I., and Takeuchi, H. (1995). The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation. New York, NY: Oxford University Press.

Richardson, J. (2010). History of American library science: Its origins and early development. In Encyclopedia of Library and Information Sciences (pp. 1–9).

Saffady, W. (1992). Optical Storage Technology 1992: A State-of-the-Art Review. (Report).

Sanderson, M., and Croft, W. B. (2012). The history of information retrieval research. Proceedings of the IEEE, 100 (Special Centennial Issue), 1444–1451.

Sveiby, K. E. (1997). The New Organizational Wealth: Managing and Measuring Knowledge-Based Assets. Berrett-Koehler Publishers.

Weinberger, D. (2010). The problem with the data-information-knowledge-wisdom hierarchy. Harvard Business Review, 2. Available online at: https://hbr.org/2010/02/data-is-to-info-as-info-is-not

Wiegand, W. A. (1998). The “Amherst method”: The origins of the Dewey decimal classification scheme. Libraries and Culture, 33(2), 175–194.

Wiig, K. M. (1999). Knowledge Management: An Emerging Discipline Rooted in a Long History. Knowledge Research Institute.

Wu, C. F. J. (1997). Statistics=data science. HC Carver Professorship Lecture, Ann Arbor: The University of Michigan. Available at http://www2.isye.gatech.edu/~jeffwu/presentations/datascience.pdf

Yatim, N. M., Nasharudin, N., Samsudin, N. F., Said, S. M., and Tarsik, N. F. (2019). Recognizing the personal competencies of future information professionals. Acta Informatica Malaysia (AIM), 3(1), 21–23.