Denise A. D. Bedford

Knowledge Management Education and Training in Academic Institutions in 2012

The academic discipline of Knowledge Management is maturing. The maturity of knowledge management scholarship has been considered as well as its curricular coverage and alignment with the needs of business. This research suggests that a mature academic discipline is grounded on a mature academic programme. The research defines five dimensions of a mature academic discipline, including: (1) curriculum design; (2) nature and coverage of research programmes; (3) faculty credentials and status; (4) academic programme administration; and (5) programme goals. Maturity factors are identified for each of the five dimensions. In 2012, an open public survey was conducted to determine the level of maturity of academic programmes in knowledge management. The survey results suggest that while there is notable maturity in curriculum design, the remaining four dimensions — research, faculty credentials, programme administration and programme goals — are immature. The research suggests that additional focus be given to these maturity factors in terms of standards. The research further suggests that an annual survey is needed to track progress towards a mature academic discipline.

Introduction to the Special Issue: Knowledge Management Models and Theories

Knowledge Management (KM) is a discipline which is based on a diverse set of reference disciplines (Holsapple and Wu, 2008; Serenko and Bontis, 2013). The editors trace the eld of KM back to its mid-20th century emergence from the elds of economics, business, arti cial intelligence, cognitive science and linguistics. Since those early days, a rich set of knowledge related models and theories have appeared in the literature (Heisig, 2009). In 2015, KM as a discipline has clearly entered a new phase. There is an emerging educational foundation, and there is increasing adoption among diverse types of organisations. While some challenges remain, KM is a discipline whose value is acknowledged by organisations and individuals. As evidence of its growing recognition as an academic and professional discipline, KM has a core set of peer-reviewed journals (Serenko and Bontis, 2009), and there are acknowledged thought leaders (Serenko and Bontis, 2004), established and recurring conferences (Serenko et al., 2009), and academic programs (Ruth et al., 2003; Chaudhry and Higgins, 2003; Al-Hawamdeh, 2005; Bontis et al., 2006; Bedford, 2013), standards (Kelleher and Levene, 2001; Coviello et al., 2002; Global Knowledge Economics Council, 2002a, 2002b, 2002c; Standards Australia International, 2003a, 2003b; Comit e Europ een de Normalisation, 2004; Standards Australia International, 2004; European Foundation for Quality Management, 2005; Standards Australia International, 2005; Deutsches Institut fur Normung, 2006a, 2006b; Verein Deutscher Ingenieure, 2009; Standards Institution of Israel, 2011; Deutsches Institut fur Normung, 2012) and theories (Grant, 2002; Heisig, 2009). There are both challenges and opportunities in the future of KM. First, emerging disciplines, particularly those which are transor interdisciplinary, present opportunities for testing new ideas and practices. Problems, models, methods and theories look di®erent at the boundaries of disciplines. There is a need to continuously examine and align new ideas with the foundation. Second, the growth of the knowledge economy and a knowledge society has incentivised organisations to learn more about and experiment with KM ideas and practices. These ideas and practices emerge from business and industry rather than from academia, and provide new perspectives from which to review our core models, methodologies and theories. Third, there are signs that the historical evolution of disciplines may be changing given an increasingly knowledgeable workforce, widespread access to ideas, and affordable access to technology. Historically, a discipline emerged around a core set of theories, progressed through design and development, and ultimately produced practical methods and practices. Today, disciplines may emerge around common practices, promote design principles based on practice, and as a nal stage explore underlying theory. This is the case with KM where a strong set of practices emerged in the 1990s around technology, at the same time the core theories and models were emerging. Fourth, KM methods and practices are increasingly referenced in other disciplines and economic Journal of Information & Knowledge Management, Vol. 14, No. 4 (2015) 1502002 (4 pages) #.c World Scienti c Publishing Co. DOI: 10.1142/S0219649215020025 January 27, 2016 5:46:50pm WSPC/188-JIKM 1502002 ISSN: 0219-6492 FA1

Knowledge translation in health sciences: Knowledge Translation in Health Sciences

Knowledge Translation (KT) is a term used by healthcare professionals and practitioners to represent a process of ensuring that what is learned in research is applied in the field. Knowledge Translation includes all stages in the research and research uptake life cycle. In the knowledge management field, the concept of Knowledge Translation is characterized as knowledge transfer, knowledge exchange, knowledge sharing and knowledge use. This panel brings together these two perspectives around a common application area – delivery of health services to a multicultural community by international development organizations. The goal of the program is to build a shared view of the concept, and to expand our understanding of the challenges and opportunities of “doing” knowledge translation in a complex environment.

Global human trafficking seen through the lens of semantics and text analytics: Global Human Trafficking Seen Through the Lens of Semantics and Text Analytics

Human trafficking is understood as a modern‐day form of slavery. It involves the recruitment, transportation, transfer, harboring, or receipt of persons by improper means (such as force, abduction, fraud, or coercion) for an improper purpose including forced labor or sexual exploitation. Human trafficking is global, is found in every country, affects all genders, and persons of all ages. While pervasive, it is also invisible. Quantitative and qualitative research methods into human trafficking have significant challenges. This program presents collegial collaborative research by the U.S. Department of State and Georgetown University into the use of text analytics and semantic analysis methods to map trafficking, to identify trafficking hubs around the world, and to expose human trafficking.

Role of Culture in Adoption of Enterprise Collaboration Technologies: Case Study

The primary goal of this case study is to understand the complexities of organizational culture, and the role that culture plays in using and in implementing collaboration technologies. Culture is defined by E. H. Schein as “a pattern of shared basic assumptions learned by a group as it solved its problems of external adaptation and internal integration.” The levels and types of cultures present in all organizations are explored. Collaboration is defined as the act of working together with other people or organizations to create or achieve something. Collaboration exists in all organizations in some form, structured or unstructured, formal or informal. Organizations often fail to consider existing collaboration practices when introducing new technologies. This research takes the form of a case study of a large international development organization. The case study describes the initial successful adoption of collaboration technologies in the late 1990s and considers the reasons for that success. The case study follows the organization through the next generation of collaboration technologies, and highlights how and why the original successes were lost. Ten common points of failure experienced by organizations are described. The case study suggests that success is unlikely where collaboration technologies are not aligned with existing collaboration models and where the culture of the organization is not collaboration oriented. Perspectives and experiences are shared in the hope that others can learn from these successes and failures.

Our journey to digital curation of the Jeghers Medical Index

Background Harold Jeghers, a well-known medical educator of the twentieth century, maintained a print collection of about one million medical articles from the late 1800s to the 1990s. This case study discusses how a print collection of these articles was transformed to a digital database. Case Presentation Staff in the Jeghers Medical Index, St. Elizabeth Youngstown Hospital, converted paper articles to Adobe portable document format (PDF)/A-1a files. Optical character recognition was used to obtain searchable text. The data were then incorporated into a specialized database. Lastly, articles were matched to PubMed bibliographic metadata through automation and human review. An online database of the collection was ultimately created. The collection was made part of a discovery search service, and semantic technologies have been explored as a method of creating access points. Conclusions This case study shows how a small medical library made medical writings of the nineteenth and twentieth centuries available in electronic format for historic or semantic research, highlighting the efficiencies of contemporary information technology.

Neighborhood-level index of knowledge and intellectual capital

This poster presents a rationale and architecture for a neighborhood‐ and city‐level index of knowledge and intellectual capital. The Index is grounded on established models of intellectual capital and knowledge transactions. The architecture includes seven components that support analytics and engagement. The analytics component includes data harvesting, harmonization, management, dashboards and reports. The engagement component is grounded on GIS components and is designed to enable a citys citizens to leverage the Index to achieve their vision of a Knowledge City. Six facets of a Knowledge City are defined, and factors that contribute to the incentivizing or Disincentivizing of knowledge transactions are proposed. The model and methodology are currently being implemented in four cities – Columbus and Youngstown Ohio, Baltimore Maryland, and Fredericksburg Virginia.

Impact-driven work: tearing down the firewalls between research and practice

This panel will showcase information research that aims to have strong impact on community at the local or national level and offer ideas for increasing the impact of information research on communities. It will also engage audience members in an interactive discussion of ideas for increasing the real‐life impact of information research.

Knowledge management in LIS education: bridging research and practice

This panel provides a state of the art review of knowledge management (KM) education approaches in the LIS field. The panelists will share thoughts and experiences pertaining to the current treatment of knowledge management concepts in Library and Information Science education. The panel is comprised of professionals who have experience in both the knowledge management and LIS disciplines, in both academic and in practical roles. Furthermore, panelists represent perspectives from several contributing disciplines.

The Knowledge Management Information Landscape — Awareness, Access, Use and Value of Sources

Information landscape is a critical component of professional and scholarly disciplines. Established disciplines have a managed information foundation covering primary, secondary and tertiary sources, targeted search capabilities, discipline-specific knowledge organisation tools and services, and quality controlled review processes. The information landscapes of emerging disciplines may be more chaotic and unsettled, and present challenges for professionals. This research considers the information landscape of the knowledge management discipline. An open public survey of knowledge professionals provides insights into three factors that affect the landscape including: (1) information awareness; (2) information use and access; and (3) information valuation. Findings highlight key information management challenges, and offer suggestions for solutions.