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The purpose of this paper is to investigate the underlying meanings, effects and cultural patterns of metadata standards, focusing on Dublin Core (DC), and explore the ways in which anticolonial metadata tools can be applied to exercise and promote Indigenous data sovereignty.

Applying an anticolonial approach, this paper examines the assumptions underpinning the stated roles of two of DC’s metadata elements, rights and creator. Based on that examination, the paper considers the limitations of DC for appropriately documenting Indigenous traditional knowledge (TK). Introduction of the TK labels and their implementation are put forward as an alternative method to such limitations in metadata standards.

The analysis of the rights and creator elements revealed that DC’s universality and supposed neutrality threaten the rightful attribution, specificity and dynamism of TK, undermining Indigenous data sovereignty. The paper advocates for alternative descriptive methods grounded within tribal sovereignty values while recognizing the difficulties of dealing with issues of interoperability by means of metadata standards given potentially innate tendencies to customization within communities.

This is the first paper to directly examine the implications of DC’s rights and creator elements for documenting TK. The paper identifies ethical practices and culturally appropriate tools that unsettle the universality claims of metadata standards. By introducing the TK labels, the paper contributes to the efforts of Indigenous communities to regain control and ownership of their cultural and intellectual property.

Identifies a set of manufacturing data interfaces that could be standardized for the effective computer integration of the information required to operate an apparel manufacturing enterprise. The interfaces are called Application Protocols. Describes a method using pieces of information, referred to as Units of Functionality, as building blocks for designing Application Protocols.

The adverse effects of alcohol consumption are massive. Alcohol is deemed to be the major factor in four per cent of the global burden of disease mortality (World Health Organisation, 2004). It has been suggested that there are two quite separate approaches to alcohol control policies. These supposedly different approaches are called the ‘public health approach’ and ‘harm minimisation’ or ‘harm reduction’. In fact, while there has been a clear difference in emphasis between some expressions of these two approaches, so much of what their exponents advocate is the same that there would appear to be no merit in continuing to regard them as mutually exclusive or in conflict. The public health approach emphasises curbing the level of alcohol‐related problems by reducing the per capita alcohol consumption (eg. Bruun et al, 1975; Edwards et al, 1995; Babor et al, 2003). Harm minimisation or harm reduction is intended to reduce the level of alcohol's adverse effects without necessarily reducing per capita alcohol consumption (Plant et al, 1997).

The increased use of, and reliance upon, technology and digitalisation, especially in the galleries, libraries, archives and museums [GLAM] sector, has motivated innovative approaches to the curation of cultural material. These changes are especially evident when collaborating with Indigenous partners. Indigenous Data Governance [IDG] and Indigenous Data Sovereignty [IDS], with an emphasis on self-determination of Indigenous peoples, have called for an emerging focus on ethical and culturally sensitive approaches to data collection and management across a range of disciplines and sectors.

This chapter reports on broader discussions, specifically with mid-North South Australia, Indigenous community members around the appropriate and ethical collection, representation and curation of cultural material on Country applying digital formats. It investigates ways to create a ‘future identity’ through built form as well as providing a ‘safe’ place for preservation of their oral histories.

It highlights the many questions raised around the ethically and culturally sensitive aspects of the collection, curation and archiving of Indigenous cultural material. It documents the preliminary outcomes of these conversations in the context of current research on IDS best practices in the field. The non-Aboriginal authors acknowledge our supporting position in the realisation of effective IDS and self-determination of our Aboriginal partners.

To describe how academic libraries can support digital humanities (DH) research by leveraging established library values and strengths to provide support for preservation and access and physical and digital spaces for researchers and communities, specifically focused on cultural heritage collections.

The experiences of the authors in collaborating with DH scholars and community organizations is discussed with references to the literature. The paper suggests how research libraries can use existing expertise and infrastructure to support the development of digital cultural heritage collections and DH research.

Developing working collaborations with DH researchers and community organizations is a productive way to engage in impactful cultural heritage digital projects. It can aid resource allocation decisions to support active research, strategic goals, community needs and the development and preservation of unique, locally relevant collections. Libraries do not need to radically transform themselves to do this work, they have established strengths that can be effective in meeting the challenges of DH research.

Academic libraries should strategically direct the work they already excel at to support DH research and work with scholars and communities to build collections and infrastructure to support these initiatives.

The paper recommends practical approaches, supported by literature and local examples, that could be taken when building DH and community-engaged cultural heritage projects.

This study aims to explore the similarities and differences between the three concepts that are commonly used to describe the knowledge of traditional and indigenous communities, namely, indigenous knowledge, traditional knowledge and local knowledge, with a view to contributing to the discourse on conceptualizing indigenous knowledge.

Data was extracted from the Scopus database using the main terms that are used for indigenous knowledge, namely, “indigenous knowledge” (IK), “traditional knowledge” (TK) and “local knowledge” (LK). Data were analyzed according to the themes drawn from the objectives of the study, using the VOSviewer software and the analytical tool embedded in the Scopus database.

The findings indicate that whereas IK and LK are older concepts than TK, TK has become more visible in the literature than the former; there is minimal overlap in the use of the labels in the literature; the three labels’ literature is largely domiciled in the social sciences; and that there were variations in representation of the labels according to countries and geographic regions.

The author avers that the scatter of literature on the knowledge of traditional and indigenous peoples under the three main labels has huge implications on the accessibility and use the literature by stakeholders including researchers, students, information and knowledge managers and information service providers.

This study demonstrates the application of informetrics beyond is traditional use to assess trends, nature and types of research patterns and mathematical modeling of information patterns to encompass the definition of the scope of concepts as covered in the literature.

Although special education was built upon the foundation of the Civil Rights Act of 1964, the discrimination that many racialized students receiving special education services experience cannot be denied. Many culturally, ethnically, and linguistically diverse students receiving special education services encounter labels that perpetuate racism and ableism and lead to inequitable access to services and resources necessary for more positive postsecondary outcomes. By honoring intersectionality and dismantling the singular identity, educators can become change agents and shift the historic oppressive narrative to create a system of empowerment as these individuals transition from transitional kindergarten to age 21 special education programs (TK-21) schools into adulthood.

In an effort to better prepare pre-service candidates to work with all students and to respond to the current collaborative team teaching trend within New York City public schools, the authors who are professors of bilingual education and inclusive education/disability studies, respectively, combined their student teaching seminars in bilingual education and childhood education, in order to: (1) provide a model of co-teaching as well as an experience and perspective of being a student in a classroom with two teachers; (2) provide pre-service candidates with ongoing access to the expertise of two professors during their student teaching experience; (3) engage pre-service teachers in critical conversations about identifying and resisting deficit constructions of both emergent bilingual students and students with disabilities; (4) engage in a self-study of teaching practice within this collaborative context; (5) consider how well our respective programs currently prepare pre-service teachers. The Self-Study of Teacher Education Practices approach gleaned data from the co-instructors’ weekly reflective journals and student evaluations to reveal multiple benefits of a collaborative classroom context for pre-service teachers as well as the professors. These benefits included a rethinking of academic structures, spaces for interconnectedness across fields, and increased professor and student learning. The findings challenge teacher educators to consider whether or not a traditional approach to teacher preparation truly offers pre-service teachers the tools to serve diverse students. The authors call on schools of education to transgress traditional academic boundaries to adequately prepare pre-service teachers for the 21st century classroom.

The present study is about generating metadata to enhance thematic transparency and facilitate research on interview collections at the Research Documentation Centre, Centre for Social Sciences (TK KDK) in Budapest. It explores the use of artificial intelligence (AI) in producing, managing and processing social science data and its potential to generate useful metadata to describe the contents of such archives on a large scale.

The authors combined manual and automated/semi-automated methods of metadata development and curation. The authors developed a suitable domain-oriented taxonomy to classify a large text corpus of semi-structured interviews. To this end, the authors adapted the European Language Social Science Thesaurus (ELSST) to produce a concise, hierarchical structure of topics relevant in social sciences. The authors identified and tested the most promising natural language processing (NLP) tools supporting the Hungarian language. The results of manual and machine coding will be presented in a user interface.

The study describes how an international social scientific taxonomy can be adapted to a specific local setting and tailored to be used by automated NLP tools. The authors show the potential and limitations of existing and new NLP methods for thematic assignment. The current possibilities of multi-label classification in social scientific metadata assignment are discussed, i.e. the problem of automated selection of relevant labels from a large pool.

Interview materials have not yet been used for building manually annotated training datasets for automated indexing of scientifically relevant topics in a data repository. Comparing various automated-indexing methods, this study shows a possible implementation of a researcher tool supporting custom visualizations and the faceted search of interview collections.

This study aims to contribute by showing that although artificial intelligence (AI) practitioners have been faster to adapt, redefine and improve their remote working performance for routine tasks, they have instead decreased their tacit knowledge sharing and ability to perform extra tasks and manage the diverse time allocation.

Based on a grounded theory study of 57 in-depth interviews, conducted before the outbreak of the pandemic and after, this study investigates how remote work as a pandemic response measure affected AI practitioners.

Although remote working was a reality for AI practitioners before the COVID-19 pandemic, the overall remote working restrictions appear to have affected tacit knowledge sharing between AI practitioners, with a consequent negative impact on AI project output diversity.

The interactions of AI practitioners are partly embedded in AI tools and partly in human exchange. During the COVID-19 pandemic, these interactions appear to have become more obvious, even if the consequences have been unforeseen.