Search results

Despite being an authentic carrier of various cultural practices, the human body is often underutilised to access the knowledge of human body. Digital inventions today have created new avenues to open up cultural data resources, yet mainly as apparatuses for well-annotated and object-based collections. Hence, there is a pressing need for empowering the representation of intangible expressions, particularly embodied knowledge within its cultural context. To address this issue, the authors propose to inspect the potential of machine learning methods to enhance archival knowledge interaction with intangible cultural heritage (ICH) materials.

This research adopts a novel approach by combining movement computing with knowledge-specific modelling to support retrieving through embodied cues, which is applied to a multimodal archive documenting the cultural heritage (CH) of Southern Chinese martial arts.

Through experimenting with a retrieval engine implemented using the Hong Kong Martial Arts Living Archive (HKMALA) datasets, this work validated the effectiveness of the developed approach in multimodal content retrieval and highlighted the potential for the multimodal's application in facilitating archival exploration and knowledge discoverability.

This work takes a knowledge-specific approach to invent an intelligent encoding approach through a deep-learning workflow. This article underlines that the convergence of algorithmic reckoning and content-centred design holds promise for transforming the paradigm of archival interaction, thereby augmenting knowledge transmission via more accessible CH materials.

Starting from the status quo, the paper outlines perspectives and challenges for the connection and interlinking of digitised and digital archival data. The following topics are addressed: Where are fields of action and what are the means of archives? Which functional and technical requirements are to be considered, and what is the role of portal infrastructures linking together various different institutions?

Considering needs of users and general framework conditions, the paper examines new approaches emerging in Germany. It outlines recent projects and considerations aiming to improve services and visibility of archives within the national data infrastructure in Germany.

Cross-connections are no new phenomenon, but change their appearance significantly in a digital context. In this respect, both smaller and bigger archives profit from participation in larger digital networks. Furthermore, archives need to keep in mind to reflect the quality of their digital (meta)data regularly and to offer or join systems that functionally and technically support cross-connection and interlinking of data.

The paper endeavours to show the importance of digital cross-connections and the role of portal infrastructures for visibility, online-distribution and use of digital archival metadata and data.

This research proposal aims to address the growing significance of artificial intelligence (AI) technology in the field of records and information management (RIM) within the African context. Despite the increasing prevalence of AI, there is a lack of comprehensive understanding regarding the factors influencing AI readiness and adoption in RIM. The primary purpose of this paper is to explore these factors and propose an AI readiness and adoption conceptual framework.

A comprehensive literature review was conducted to identify the proposed variables and support the hypothesis development. The theoretical foundation of the proposed conceptual framework is based on three theories: the technology acceptance model (TAM), the technology readiness index (TRI) and the cognitive appraisal theory (CAT).

The literature reveals that there is a lack of empirical investigation of AI readiness and adoption within the RIM context. Through the proposed conceptual model, the researcher anticipates uncovering critical insights into the factors influencing AI readiness and adoption in RIM practices across African nations.

The proposed model is not yet empirically tested and the study's scope is limited to African nations.

The proposed model takes a pioneering approach to empirically investigate AI readiness and adoption within the RIM field, specifically in an African context which is understudied.

Municipalities, as the front lines of service delivery, use websites as one of the tools to communicate information to the public. While it is considered a record, many organisations, including municipalities, do not manage websites as such. This study aims to explore the archiving of websites as records in the municipalities of KwaZulu-Natal (KZN) Province in South Africa by using the web archiving life cycle model.

This study used a mixed-methods research with an explanatory design, with quantitative data collected first through content analysis of websites and qualitative data collected through interviews. Researchers used multilevel sampling, first quantitatively analysing all available websites of the municipalities (52) in KZN, and then qualitatively selecting only records managers, information managers, web administrators, communication managers and website managers or designers from municipalities because of their understanding and involvement with websites in some way.

This study established that some records on municipal websites are often in paper format in record-keeping systems, whereas others are born digital and are not captured in the systems. Municipalities lack a dedicated web online harvesting tool as well as an archiving policy or strategy to guide website archiving. Furthermore, municipalities placed a high reliance on service providers to keep their websites operational.

It became clear during the interviews that most of the participants were unfamiliar with web archiving. As a result, only 12 of the 56 selected participants from the municipalities provided the required information in relation to the current study as others could not provide answers. Data for other participants were not analysed.

Due to a lack of infrastructure for ingesting digital records into archival custody, a framework for harvesting web content of value is proposed both internally in municipalities and externally to an archive repository.

Paper-based records management systems remain dominant in Tanzanian Government organisations despite the increase in digital records management systems adoption across the globe. To create an understanding of this state, this study aims to investigate the use of records management systems in Tanzanian public sector organisations.

A descriptive research design was used in this study, alongside quantitative and qualitative approaches. A total of 81 respondents were drawn from three public sector organisations. To get a sample, non-probability (convenience and purposive) sampling techniques were used. A cross-sectional survey questionnaire and interview methods were used to gather quantitative and qualitative data. To analyse quantitative and qualitative data, the researchers used a mixed-methods analysis.

The study reveals different types of records management systems used in public sector organisations. Besides, the findings suggest that a large proportion of records are created through the digitisation of existing records. Aside from that, the study has revealed different types of records managed in the systems by government organisations. According to the study, there are various factors that determine the effective use of records management systems in public sector organisations.

The implications of the present study are diverse. Specifically, its findings expand the theoretical body of knowledge by adding new insights regarding records management systems usage in government offices. The findings also provide the government with a basis for formulating and improving legal and regulatory frameworks to enhance records management. Apart from this, the findings are likely to benefit records practitioners by orchestrating inclusive strategies that will promote, not only effectiveness, but also sustainability in records management.

In Tanzania, a few studies have been conducted to examine digital records management practices and systems. These studies have not extensively highlighted the systems used to manage the records. This makes little to be known on the systems used to manage records in government offices. The present study has ascertained records management systems used in public sector organisations.

Recent archiving and curatorial practices took advantage of the advancement in digital technologies, creating immersive and interactive experiences to emphasize the plurality of memory materials, encourage personalized sense-making and extract, manage and share the ever-growing surrounding knowledge. Audiovisual (AV) content, with its growing importance and popularity, is less explored on that end than texts and images. This paper examines the trend of datafication in AV archives and answers the critical question, “What to extract from AV materials and why?”.

This study roots in a comprehensive state-of-the-art review of digital methods and curatorial practices in AV archives. The thinking model for mapping AV archive data to purposes is based on pre-existing models for understanding multimedia content and metadata standards.

The thinking model connects AV content descriptors (data perspective) and purposes (curatorial perspective) and provides a theoretical map of how information extracted from AV archives should be fused and embedded for memory institutions. The model is constructed by looking into the three broad dimensions of audiovisual content – archival, affective and aesthetic, social and historical.

This paper contributes uniquely to the intersection of computational archives, audiovisual content and public sense-making experiences. It provides updates and insights to work towards datafied AV archives and cope with the increasing needs in the sense-making end using AV archives.

Digital preservation of theses and dissertations (TDs) is crucial for the archiving (long-term preservation) of intellectual content of undergraduate and postgraduate students in universities. This paper aims to investigate the digitization of TDs in three selected academic libraries in Oyo State, south-west Nigeria.

Descriptive survey research design was used for this study. The instrument for data collection was the questionnaire. The study comprised 78 professionals and paraprofessional librarians in the three selected university libraries in Oyo State.

The study revealed that digital preservation of TDs in university libraries is at the developmental stage. Also, the study revealed that most participants strongly agreed that the main purpose for embarking on the digital preservation of TDs was to influence the web ranking of the institutions. Web archiving was the widely adopted method of digital preservation in university libraries. Poor information and communication technology infrastructure, absence of policy and poor funding were identified as major challenges militating against the effective digital preservation of theses in the libraries. Hence, it was recommended that the management of university libraries should be more committed to providing substantial funds to meet the financial obligation for digital preservation initiatives.

The study provides insight into a case study of digitization of theses and dissertation i academic libraries in three selected universities to serve as a basis for further research.

Community-generated digital content (CGDC) is one of the UK’s prime cultural assets. However, CGDC is currently “critically endangered” (Digital Preservation Coalition, 2021) due to technological and organisational barriers and has proven resistant to traditional methods of linking and integration. The challenge of integrating CGDC into larger archives has effectively silenced diverse community voices within our national collection. Our Heritage, Our Stories (OHOS), funded by the UK’s AHRC programme Towards a National Collection, responds to these urgent challenges by bringing together cutting-edge approaches from cultural heritage, humanities and computer science.

Existing solutions to CGDC integration, involving bespoke interventionist activities, are expensive, time-consuming and unsustainable at scale, while unsophisticated computational integration erases the meaning and purpose of both CGDC and its creators. Using innovative multidisciplinary methods, AI tools and a co-design process, previously unfindable and unlinkable CGDC will be made discoverable in our virtual national collection.

There currently exists a range of disconnected, fragile and under-represented community-generated heritage which is at increasing risk of loss. Therefore, OHOS will work to ensure the survival and preservation of these nationally important resources, for the future and for our shared national collection.

As we dissolve barriers to create meaningful new links across CGDC collections and develop new methods of engagement, OHOS will also make this content accessible to new and diverse audiences. This will facilitate a wealth of fresh research while also embedding new strategies for future management of CGDC into heritage practice and training and fostering newly enriching, robust connections between communities and archival institutions.

This paper focuses on image-to-text manuscript processing through Handwritten Text Recognition (HTR), a Machine Learning (ML) approach enabled by Artificial Intelligence (AI). With HTR now achieving high levels of accuracy, we consider its potential impact on our near-future information environment and knowledge of the past.

In undertaking a more constructivist analysis, we identified gaps in the current literature through a Grounded Theory Method (GTM). This guided an iterative process of concept mapping through writing sprints in workshop settings. We identified, explored and confirmed themes through group discussion and a further interrogation of relevant literature, until reaching saturation.

Catalogued as part of our GTM, 120 published texts underpin this paper. We found that HTR facilitates accurate transcription and dataset cleaning, while facilitating access to a variety of historical material. HTR contributes to a virtuous cycle of dataset production and can inform the development of online cataloguing. However, current limitations include dependency on digitisation pipelines, potential archival history omission and entrenchment of bias. We also cite near-future HTR considerations. These include encouraging open access, integrating advanced AI processes and metadata extraction; legal and moral issues surrounding copyright and data ethics; crediting individuals’ transcription contributions and HTR’s environmental costs.

Our research produces a set of best practice recommendations for researchers, data providers and memory institutions, surrounding HTR use. This forms an initial, though not comprehensive, blueprint for directing future HTR research. In pursuing this, the narrative that HTR’s speed and efficiency will simply transform scholarship in archives is deconstructed.