Abstract
Over the past two decades, Digital Transformation (DT) has been focused on improving businesses, industries, and the general public through significant breakthroughs. This paper examines the significant developments brought forth by DT and how they impact organizations. This analysis explores the impact of Virtual Reality (VR) and the Metaverse on global businesses, taking inspiration from successful case studies such as Netflix, Amazon, and Meta. This study emphasizes the potential of virtual reality and the Metaverse in facilitating remote meetings, training employees, engaging with consumers, and gathering data. Case studies and strategic recommendations are offered for overcoming barriers to the adoption of these digital technologies. The study finishes by addressing the future trajectory of DT and emphasizing the significance of devoting time, commitment, and resources to effectively utilize the range of potential offered by VR and the Metaverse. It highlights the importance for organizations to comprehend and handle this ever-changing environment to remain at the forefront of the digital frontier. © 2024 IEEE.

Abstract
Identifying the influential spreaders in complex networks has emerged as an important research challenge to control the spread of (mis)information or infectious diseases. Researchers have proposed many centrality measures to identify the influential nodes (spreaders) in the past few years. Still, most of them have not considered the importance of the edges in unweighted networks. To address this issue, we propose a novel centrality measure to identify the spreading ability of the Influential Spreaders using the Potential Edge Weight method (IS-PEW). Considering the connectivity structure, the ability of information exchange, and the importance of neighbouring nodes, we measure the potential edge weight. The ranking similarity of spreaders identified by IS-PEW and the baseline centrality methods are compared with the Susceptible-Infectious-Recovered (SIR) epidemic simulator using Kendall's rank correlation. The spreading ability of the top-ranking spreaders is also compared for five different percentages of top-ranking node sets using six different real networks.

Abstract
Archaeological discoveries can benefit enormously from linked open data (LOD) technologies since, as new objects are discovered, data about them can be placed in the LOD cloud and instantly accessible to third parties. This article presents a framework developed to publish LOD on arrowheads from the Chalcolithic and Early/Middle Bronze Age chronologies (2800/2900 BC to 1500 BC) found in the last 25 years of excavations on an archaeological site in Portugal. These arrowheads were kept in boxes, hidden from the possibility of being studied and viewed by interested parties. The framework encompasses a metadata application profile (MAP) and tools to be used with this MAP, such as a namespace, two metadata schemas and eight vocabulary coding schemes. The MAP domain model was developed with the support of the scientific literature about this type of arrowheads, and the team integrated two archaeologists. This framework was created with the design philosophy of maximising data interoperability, so terms from the CIDOC CRM conceptual models and other vocabularies widely used in the LOD cloud were used. The MAP was tested using a set of seven arrowheads, which proved, in the first instance, the viability of the developed MAP. The team plans to test the model in future work with arrowheads of other excavations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

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Abstract
To address metadata with researchers it is important to use models that include familiar domain concepts. In the Social Sciences, the DDI is a well-accepted source of such domain concepts. To create FAIR data and metadata, we need to establish a compact set of DDI elements that fit the requirements in projects and are likely to be adopted by researchers inexperienced with metadata creation. Over time, we have engaged in interviews and data description sessions with research groups in the Social Sciences, identifying a manageable DDI subset. A recent Clinical Psychology project, TOGETHER, dealing with risk assessment for hereditary cancer, considered the inclusion of a DDI subset for the production of metadata that are timely and interoperable with data publication initiatives in the same domain. Taking a DDI subset identified by the data curators, we make a preliminary assessment of its use as a realistic effort on the part of researchers, taking into consideration the metadata created in two data description sessions, the effort involved, and overall metadata quality. A follow-up questionnaire was used to assess the perspectives of researchers regarding data description.