This paper explores the evolving landscape of training for archival professionals in the context of big data and emerging technologies. By comparing two educational frameworks—the CAS framework, developed from computational thinking research and CAS research papers, and the InterPARES framework, based on empirical studies with archivists working with AI/ML, we identify areas of alignment and divergence. While both frameworks share significant concordance, suggesting a growing consensus on integrating computing into archival work, key differences in their approaches (learning outcomes vs. competencies) and focus areas (such as work practices, systems thinking, and cybersecurity) highlight the need for further discourse among archival scholars, educators, and practitioners. These distinctions must be addressed before formalizing CAS educational frameworks. This paper also initiates efforts to integrate emerging technological competencies by bridging the CAS and InterPARES frameworks, emphasizing the value of complementary perspectives from both professional practice and academic research. We argue that such integration is essential for developing robust competency frameworks in archival education, particularly within higher education's professional programs.

This paper discusses the problem of double-ending fraud in real estate transactions – a type of transactional fraud wherein agents handling real estate transactions unfairly benefit (e.g., by simultaneously representing both the buy and sell side of a real estate transaction in a manner that unfairly boosts the commission they receive, or colluding to increase their commission in a real estate transaction at the expense of the buyer and/or seller of the real property). The paper proposes a unique blockchain solution design that leverages blockchain's properties of transparency and ability to create tamper-resistant audit trails to reduce opportunities for double-ending fraud and increase real estate market participants' trust in the handling of their transactions. The paper discusses the implementation of a prototype of the solution based on hyperledger fabric and sails; it presents the results of an agent-based modelling simulation validating that the inherent transparency of the proposed design offers optimal allocation for both sellers and buyers.

Thousands of videos are posted online every day. The affordability of video editing tools and social networks has facilitated the creation and spread of videos carrying disinformation, i.e. fake videos. Previous attempts to categorize disinformation have focused on content analysis and ascertaining the intention of creators. To extend these approaches, it is beneficial to incorporate the perspective of other fields that study the trustworthiness of records, such as archival science, to help detect and categorize fake videos. This paper proposes to leverage archival science in combination with computer engineering to devise a new framework for detecting and categorizing fake videos. In doing so, the paper offers a case study of the way in which Computational Archival Science, which blends archival and computational thinking, can be used to contribute to a novel approach towards solving the problem of fake videos.

One of the principal difficulties in classifying and interpreting online disinformation is that the data arrive rapidly and evolve dramatically. The core challenges of classification and interpretation are not unique to contemporary disinformation; the problem of classifying documented information as authentic or inauthentic has been the focus of archivists for centuries. However, the rate of information creation and dissemination enabled by the Internet requires a new approach to categorization and archival examination of disinformation of documented information. This paper provides a survey of the archival problems facing disinformation researchers and proposes a taxonomy of disinformation that will aid future discussion and classification of disinformation.

This paper presents a synthesis of original research documenting several cases of the application of blockchain technology to land transaction, medical, and financial record keeping. Using a thematic synthesis of the cases, the paper describes a typology of blockchain solutions for managing current records representing three distinct design patterns. It then considers the different types of solutions in relation to implications for recordkeeping and long-term preservation of authentic records.

This paper discusses a project that studied the relationship between citizen trust and social protest using visual analysis of approximately 11 million sentiment classified Tweets from the period of the 2014 Brazilian World Cup. The results of the study reveal that the 2014 World Cup protests in Brazil sprang from a wide range of grievances coupled with a relative sense of deprivation compared with emergent comparative `standards'. This sense of grievance gave rise to sentiments that activated online protest that may have led to other forms of social protest, such as demonstrations. The paper describes an innovative approach to big data analytics-mixed initiative social media analytics - and discusses the potential of using big data in social science research of this kind, as well as some of the open methodological, technical and ethical issues still to be addressed.

In the wake of the global financial crisis, the U.S. Dodd‐ Frank Wall Street Reform and Consumer Protection Act (Dodd‐Frank) was enacted to provide increased transparency in financial markets. In response to Dodd‐Frank, a series of rules relating to swaps record keeping have been issued, and one such rule calls for the creation of a financial products classification system. The manner in which financial products are classified will have a profound effect on data integration and analysis in the financial industry. This article considers various approaches that can be taken when classifying financial products and recommends the use of facet analysis. The article argues that this type of analysis is flexible enough to accommodate multiple viewpoints and rigorous enough to facilitate inferences that are based on the hierarchical structure. Various use cases are examined that pertain to the organization of financial products. The use cases confirm the practical utility of taxonomies that are designed according to faceted principles.