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This article explores citing and referencing systems in social sciences and medicine articles from different theoretical and practical perspectives, considering bibliographic references as a facet of descriptive representation.

The analysis of citing and referencing elements (i.e. bibliographic references, mentions, quotations and respective in-text reference pointers) identified citing and referencing habits within disciplines under consideration and errors occurring over the long term as stated by previous studies now expanded. Future expected trends of information retrieval from bibliographic metadata was gathered by approaching these referencing elements from the Functional Requirements for Bibliographic Records (FRBR) entities concepts.

Reference styles do not fully accomplish with their role of guiding authors and publishers on providing concise and well-structured bibliographic metadata within bibliographic references. Trends on representative description revision suggest a predicted distancing on the ways information is approached by bibliographic references and bibliographic catalogs adopting FRBR concepts, including the description levels adopted by each of them under the perspective of the FRBR entities concept.

This study was based on a subset of medicine and social sciences articles published in 2019 and, therefore, it may not be taken as a final and broad coverage. Future studies expanding these approaches to other disciplines and chronological periods are encouraged.

By approaching citing and referencing issues as descriptive representation's facets, findings on this study may encourage further studies that will support information science and computer science on providing tools to become bibliographic metadata description simpler, better structured and more efficient facing the revision of descriptive representation actually in progress.

In this study, the authors want to identify current possible causes for citing and referencing errors in scholarly literature to compare if something changed from the snapshot provided by Sweetland in his 1989 paper.

The authors analysed reference elements, i.e. bibliographic references, mentions, quotations and respective in-text reference pointers, from 729 articles published in 147 journals across the 27 subject areas.

The outcomes of the analysis pointed out that bibliographic errors have been perpetuated for decades and that their possible causes have increased, despite the encouraged use of technological facilities, i.e. the reference managers.

As far as the authors know, the study is the best recent available analysis of errors in referencing and citing practices in the literature since Sweetland (1989).

This article describes the interviews the authors conducted in late 2021 with 19 researchers at the Department of Classical Philology and Italian Studies at the University of Bologna. The main purpose was to shed light on the definition of the word “data” in the humanities domain, as far as FAIR data management practices are concerned, and on what researchers think of the term.

The authors invited one researcher for each of the official disciplinary areas represented within the department and all 19 accepted to participate in the study. Participants were then divided into five main research areas: philology and literary criticism, language and linguistics, history of art, computer science and archival studies. The interviews were transcribed and analysed using a grounded theory approach.

A list of 13 research data types has been compiled thanks to the information collected from participants. The term “data” does not emerge as especially problematic, although a good deal of confusion remains. Looking at current research management practices, methodologies and teamwork appear more central than previously reported.

Our findings confirm that “data” within the FAIR framework should include all types of inputs and outputs humanities research work with, including publications. Also, the participants of this study appear ready for a discussion around making their research data FAIR: they do not find the terminology particularly problematic, while they rely on precise and recognised methodologies, as well as on sharing and collaboration with colleagues.

Citation data needs to be recognised as a part of the Commons – those works that are freely and legally available for sharing – and placed in an open repository. The paper aims to discuss this issue.

The Open Citation Corpus is a new open repository of scholarly citation data, made available under a Creative Commons CC0 1.0 public domain dedication and encoded as Open Linked Data using the SPAR Ontologies.

The Open Citation Corpus presently provides open access (OA) to reference lists from 204,637 articles from the OA Subset of PubMed Central, containing 6,325,178 individual references to 3,373,961 unique papers.

Scholars, publishers and institutions may freely build upon, enhance and reuse the open citation data for any purpose, without restriction under copyright or database law.

The purpose of this paper is to introduce blockchains and distributed ledgers and describe their potential applications to money and banking.

The analysis compares public and private ledgers and outlines the suitability of various types of ledgers for different purposes. Furthermore, a few historical prototypes of blockchains and distributed ledgers are presented, and results of their hard forking are illustrated. Next, some potential applications of distributed ledgers to trading, clearing and settlement, payments, trade finance, etc. are outlined.

Monetary circuits are argued to be natural applications for blockchains. Finally, the role of digital currencies in modern society is articulated and various forms of digital cash, such as central bank issued electronic cash, bank money, Bitcoin and P2P money, are compared and contrasted.