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This paper aims to explore the objectives and methods of teaching engineering and technology education (ETE) through the lens of three educational taxonomies in cognitive, knowledge and problem-solving perspectives. This analysis is useful in light of today's increasing interest in teaching engineering and technology in K-12 education, instead of crafts or manual skills.

This is an exploratory study. Technology and engineering education is a relatively new area in K-12 education, and little has been written about the use of general educational taxonomies for analysing and designing the teaching and learning of this subject.

The literature analysis teaches us that fostering students' higher-order capabilities such as design and problem solving in engineering and technology cannot take place in isolation from specific knowledge. Instruction should be designed to: develop a certain degree of factual, procedural, conceptual and meta-cognitive knowledge in relevant areas of technology, science and mathematics; and engage learners in assignments of increasing cognitive levels, from simple to complex ones.

This work is original and valuable in that it explores ETE through tools often used in the educational literature and research, rather than regarding technology education as an exceptional school subject. This could encourage making engineering and technology a core component in the overall curriculum.

The purpose of this paper is to examine how the rapid pace of technological change, attrition rate, global complexities and the increasing amount of data and information available have complicated the task of managing knowledge for third‐party logistics (3PL) service providers. Based on literature, there is a need for research into the development of a generic taxonomy components framework (GTCF) for the implementation of knowledge management (KM) solution for 3PL service providers.

A four‐stage model has been devised for the development of a GTCF to implement KM solution for 3PL service providers. The authors proposed modified Q‐sort method and also used Delphi analysis in the four‐stage model. The KM components were identified through literature study and discussion with subject experts. The hierarchical structure of the taxonomy was derived and refined through a survey among 3PL experts by employing Q‐sort method.

This paper makes several important contributions toward the objective of better understanding the role of 3PL operations in knowledge creation. The feedback from the respondents shows that the GTCF is of potential employment by 3PL service providers irrespective of the nature of the primary service they offer.

The GTCF has been devised based on survey responses gathered from 3PL experts in India. The findings of this study have implications for understanding the key KM components required for 3PL service provider relationship and also the weightage for KM components.

The aim of this research is for the development of a GTCF which can be taken as the base for implementation of KM solutions for 3PL service providers.

The contribution of this study lies in extending the body of knowledge of KM for 3PL service providers. It tests a proposed framework which has only limited empirical validation, and provides a broader understanding of KM components required for 3PL service provider.

The purpose of this paper is to explore theoretically and empirically the understanding and implementation of an information taxonomy in the UN organization World Food Programme (WFP) by analysing users’ information behaviour and by establishing a minimum set of cross-silo metadata (taxonomy).

The study implies the use of both qualitative and quantitative methods. This includes desk review of key documents and interviews with information architecture staff from various WFP units; data collection carried out as semi-structured staff interviews in WFP; log analyses of search log-files from WFP intranet portal (WFPgo) from September to November 2013, the results were applied and a suggested taxonomy tested at workshops conducted for the staff in headquarters.

The results reveal an organization with a high demand for easier access to information and knowledge, greater internal collaborations and stronger links with various sources of knowledge. Staff participating in the various workshops pointed out that work processes as well as the human resources component cannot be left out of a solution development.

There has been little research carried out on current taxonomy projects in corporate environments and international emergency response organizations and few has touched on how knowledge organization systems can enhance or constrain staff’s ability to access online content.

This paper aims to summarise a literature review undertaken to determine whether or not information taxonomy work, as a specific activity within the broader field of knowledge organisation system construction, can usefully be compared to a process of scientific enquiry. The theories of objectivity and subjectivity proposed by Helen Longino are considered, to determine their relevance to taxonomists and classification theorists.

The review assesses and synthesises relevant best practice and theoretical literature from information science, sociology of science, and related disciplines, including linguistics, epistemology, and psychology.

Although requirements of objectivity in science and in taxonomy work differ significantly, the achievement of consensus within communities is similar. This warrants development of Longino's theories for application to taxonomy work.

The potentially relevant literature represents too vast and diverse a body of scholarship for comprehensive review of every area, so a synthetic interdisciplinary approach has been taken, highlighting aspects worthy of further investigation.

Subjectivity and objectivity are deemed significant for information taxonomists, especially regarding usability and accessibility of systems, while the sociology of science provides frameworks that could be adapted to offer methods of assessing the subjectivity and objectivity of taxonomies. This suggests much potential for developing Longino's theories into a framework or set of heuristics for taxonomy practitioners.

Current literature on taxonomy work, as distinct from classification, categorisation, and similar topics within the broader knowledge organisation field, is scant, and academic and interdisciplinary approaches scarce. Relating the sociology of science to information taxonomy work is a novel approach. By exposing this relationship, a starting point is provided for researchers who wish to develop understanding of these fields and theoretical understanding of taxonomies and professional best practice is enhanced.

The purpose of this paper is to report an explicit taxonomy of maritime operations (MO) to guide harbour masters (HMs) of smaller ports in planning more sustainable operations.

This research presents strategies for building theory to promote more sustainable port management in a two-stage research design. Starting from a base taxonomy in research Stage 1, ethnographic content analysis (ECA) of a sparse prior literature on MO generated a tentative taxonomy. In Stage 2, interviews to capture tacit practitioner knowledge refined the tentative taxonomy into a credible practitioner-informed final taxonomy.

ECA offers researchers a powerful tool to analyse complex operational problems. In this paper MOs are represented in an explicit taxonomy.

A final taxonomy of MOs guides sustainability strategy formulation by HMs and assists them to protect vital commercial revenues which serve supply chains and local communities.

An explicit final taxonomy of MO is derived using a novel methodology. The taxonomy guides sustainability strategy formulation and underpins subsequent planning of sustainable development policies.

This paper aims to develop a conceptual taxonomy for building requisite knowledge capabilities for different supply chain network (SCN) types. Specifically, it examines knowledge capabilities required for three types of SCNs: efficient, collaborative and agile SCNs.

This paper integrates two bodies of thought (i.e. knowledge management and organisational learning) and applies them to SCNs. An abductive research process is used to develop this conceptual taxonomy.

The conceptual taxonomy details three archetypical knowledge capabilities – exploitation, exploration and ambidextrous. Those knowledge capabilities are required for efficient, collaborative and agile SCNs, respectively.

This paper is conceptual and theory-based. The next stages of the research seek to further strengthen the explanatory value of the taxonomy through empirical validation.

The taxonomy developed in this paper provides a valuable and pragmatic tool for managerial decision-making in the context of SCNs. Specifically, it provides a roadmap for practitioners since the study develops an understanding of the relationship between knowledge capabilities and types of SCNs.

This is one of the earliest studies that attempt to unearth requisite knowledge capabilities for different types of SCNs.

Potential and benefits of classification schemes and thesauri in building organizational taxonomies cannot be fully utilized by organizations. Empirical data of building an organizational taxonomy by the top‐down approach of using classification schemes and thesauri appear to be lacking. The paper seeks to make a contribution in this regard.

A case study of building an organizational taxonomy was conducted in the information studies domain for the Division of Information Studies at Nanyang Technology University, Singapore. The taxonomy was built by using the Dewey Decimal Classification, the Information Science Taxonomy, two information systems taxonomies, and three thesauri (ASIS&T, LISA, and ERIC).

Classification schemes and thesauri were found to be helpful in creating the structure and categories related to the subject facet of the taxonomy, but organizational community sources had to be consulted and several methods had to be employed. The organizational activities and stakeholders' needs had to be identified to determine the objectives, facets, and the subject coverage of the taxonomy. Main categories were determined by identifying the stakeholders' interests and consulting organizational community sources and domain taxonomies. Category terms were selected from terminologies of classification schemes, domain taxonomies, and thesauri against the stakeholders' interests. Hierarchical structures of the main categories were constructed in line with the stakeholders' perspectives and the navigational role taking advantage of structures/term relationships from classification schemes and thesauri. Categories were determined in line with the concepts and the hierarchical levels. Format of categories were uniformed according to a commonly used standard. The consistency principle was employed to make the taxonomy structure and categories neater. Validation of the draft taxonomy through consultations with the stakeholders further refined the taxonomy.

No similar study could be traced in the literature. The steps and methods used in the taxonomy development, and the information studies taxonomy itself, will be helpful for library and information schools and other similar organizations in their effort to develop taxonomies for organizing content and aiding navigation on organizational sites.

The purpose of this paper is to propose a taxonomy of artificial intelligence (AI) literacy to support AI literacy education and research.

This study makes use of the facet analysis technique and draws upon various sources of data and information to develop a taxonomy of AI literacy. The research consists of the following key steps: a comprehensive review of the literature published on AI literacy research, an examination of well-known AI classification schemes and taxonomies, a review of prior research on data/information/digital literacy research and a qualitative and quantitative analysis of 1,031 metadata records on AI literacy publications. The KH Coder 3 software application was used to analyse metadata records from the Scopus multidisciplinary database.

A new taxonomy of AI literacy is proposed with 13 high-level facets and a list of specific subjects for each facet.

The proposed taxonomy may serve as a conceptual AI literacy framework to support the critical understanding, use, application and examination of AI-enhanced tools and technologies in various educational and organizational contexts.

The proposed taxonomy provides a knowledge organization and knowledge mapping structure to support curriculum development and the organization of digital information.

The proposed taxonomy provides a cross-disciplinary perspective of AI literacy. It can be used, adapted, modified or enhanced to accommodate education and learning opportunities and curricula in different domains, disciplines and subject areas.

The proposed AI literacy taxonomy offers a new and original conceptual framework that builds on a variety of different sources of data and integrates literature from various disciplines, including computing, information science, education and literacy research.

This paper reports on a taxonomy design project involving graduate students in information science (MLIS degree) working as intern-consultants under the guidance of an information science faculty member. The consulting team developed a taxonomy that would reflect current academic departmental structures and be used to optimise publisher tools for generating metrics and interpretive assessment.

In this case study, three students worked under the direction of a faculty member on a consulting team for a Silicon Valley company that provides business analytics to academic publishers. Tasked with designing a taxonomy of disciplinary knowledge to support the company’s analytical software tools, the students developed methods for environmental scans, vocabulary design, validation and taxonomy management for the project objectives.

The consulting experience proved to be highly beneficial for the students as an opportunity to take concepts learned in their coursework and apply them in practice. The project team delivered to the company the most detailed taxonomy of academic disciplines in the marketplace, along with recommendations for its maintenance and management for ongoing support of business objectives. The company was supportive throughout the internship programme, generating collaborative contributions from all stakeholders.

As more students earning an Master of Library and Information Science (MLIS) or similar degree move into a wide array of careers within business environments, internship experience through consulting can be an essential advantage to their preparation.

The purpose of this paper is to explore the connection between the various layers of roles and tasks of librarians with the various knowledge types and methods. Although there are multiple benefits anticipated with knowledge management (KM) schemes in libraries, the practical side of it among Library and Information Science (LIS) professionals is not yet notable or evident.

Taxonomy building and Delphi method were two means of research deployed to achieve the declared purpose.

It was possible to achieve several steps into structuring a taxonomy but yet further work has to be accomplished in order to consummate the taxonomy. For this, means of group interviewing method along with perhaps sponsorship of association relevant to librarianship might be an appropriate approach.

Delphi process was not possible to be fully exercised and completed due to limitations of limited number of participants as well the overwhelming feeling of participants had toward the unfamiliar content. It would have been more rewarding to have physical meeting in groups to overcome such limitations.

This paper lays the foundation stone of a multi-layer taxonomy for roles of librarians toward KM. The taxonomy also unveils a dimension that librarians often miss when discussing KM. It also models the categories of knowledge types for LIS. Thus, the LIS community is urged to contribute in the development of this taxonomy which could become the handbook of reference in KM for librarianship.