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The aim of this work is to understand the retraction phenomenon in the arts and humanities domain through an analysis of the retraction notices—formal documents stating and describing the retraction of a particular publication. The retractions and the corresponding notices are identified using the data provided by Retraction Watch. Our methodology for the analysis combines a metadata analysis and a content analysis (mainly performed using a topic modelling process) of the retraction notices. Considering 343 cases of retraction, we found that many retraction notices are neither identifiable nor findable. In addition, these were not always separated from the original papers, introducing ambiguity in understanding how these notices were perceived by the community (i.e. cited). Also, we noticed that there is no systematic way to write a retraction notice. Indeed, some retraction notices presented a complete discussion of the reasons for retraction, while others tended to be more direct and succinct. We have also reported many notices having similar text while addressing different retractions. We think a further study with a larger collection should be done using the same methodology to confirm and investigate our findings further. [ABSTRACT FROM AUTHOR]

Purpose: 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. Design/methodology/approach: 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. Findings: 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. Originality/value: 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). [ABSTRACT FROM AUTHOR]

Citation indexes are by now part of the research infrastructure in use by most scientists: a necessary tool in order to cope with the increasing amounts of scientific literature being published. Commercial citation indexes are designed for the sciences and have uneven coverage and unsatisfactory characteristics for humanities scholars, while no comprehensive citation index is published by a public organisation. We argue that an open citation index for the humanities is desirable, for four reasons: it would greatly improve and accelerate the retrieval of sources, it would offer a way to interlink collections across repositories (such as archives and libraries), it would foster the adoption of metadata standards and best practices by all stakeholders (including publishers) and it would contribute research data to fields such as bibliometrics and science studies. We also suggest that the citation index should be informed by a set of requirements relevant to the humanities. We discuss four such requirements: source coverage must be comprehensive, including books and citations to primary sources; there needs to be chronological depth, as scholarship in the humanities remains relevant over time; the index should be collection driven, leveraging the accumulated thematic collections of specialised research libraries; and it should be rich in context in order to allow for the qualification of each citation, for example, by providing citation excerpts. We detail the fit-for-purpose research infrastructure which can make the Humanities Citation Index a reality. Ultimately, we argue that a citation index for the humanities can be created by humanists, via a collaborative, distributed and open effort. [ABSTRACT FROM AUTHOR]

In this article, we present a methodology which takes as input a collection of retracted articles, gathers the entities citing them, characterizes such entities according to multiple dimensions (disciplines, year of publication, sentiment, etc.), and applies a quantitative and qualitative analysis on the collected values. The methodology is composed of four phases: (1) identifying, retrieving, and extracting basic metadata of the entities which have cited a retracted article, (2) extracting and labeling additional features based on the textual content of the citing entities, (3) building a descriptive statistical summary based on the collected data, and finally (4) running a topic modeling analysis. The goal of the methodology is to generate data and visualizations that help understanding possible behaviors related to retraction cases. We present the methodology in a structured step-by-step form following its four phases, discuss its limits and possible workarounds, and list the planned future improvements. [ABSTRACT FROM AUTHOR]

Purpose: 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. Design/methodology/approach: 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. Findings: 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. Research limitations/implications: 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. Originality/value: 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. [ABSTRACT FROM AUTHOR]

Purpose: 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. Design/methodology/approach: 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. Findings: 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. Originality/value: 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. [ABSTRACT FROM AUTHOR]

In this work, we investigate existing citation practices by analysing a huge set of articles published in journals to measure which metadata are used across the various scholarly disciplines, independently from the particular citation style adopted, for defining bibliographic reference. We selected the most cited journals in each of the 27 subject areas listed in the SCImago Journal Rank in the 2015–2017 triennium according to the SCImago total cites ranking. Each journal in the sample was represented by five articles (in PDF format) published in the most recent issue published in October 2019, for a total of 729 articles. We extracted all 34,140 bibliographic references in the bibliographic references lists of these articles. Finally, we detected the types of cited works in each discipline and the structure of bibliographic references and in-text reference pointers for each type of cited work. By analysing the data gathered, we observed that the bibliographic references in our sample referenced 36 different types of cited works. Such a considerable variety of publications revealed the existence of particular citing behaviours in scientific articles that varied from subject area to subject area. [ABSTRACT FROM AUTHOR]

In this paper we investigate whether it is possible to create a computational approach that allows us to distinguish topical tags (i.e. talking about the topic of a resource) and non-topical tags (i.e. describing aspects of a resource that are not related to its topic) in folksonomies, in a way that correlates with humans. Towards this goal, we collected 21 million tags (1.2 million unique terms) from Delicious and developed an unsupervised statistical algorithm that classifies such tags by applying a word space model adapted to the folksonomy space. Our algorithm analyses the co-occurrence network of tags to a target tag and exploits graph-based metrics for their classification. We validated its outcomes against a reference classification made by humans on a limited number of terms in three separate tests. The analysis of the outcomes of our algorithm shows, in some cases, a consistent disagreement among humans and between humans and our algorithm about what constitutes a topical tag, and suggests the rise of a new category of overly generic tags (i.e. umbrella tags). [ABSTRACT FROM AUTHOR]

Purpose -- 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. Design/methodology/approach -- 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. Findings -- 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. Originality/value -- 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. [ABSTRACT FROM AUTHOR]

This study presents the results of an experiment we performed to measure the coverage of Digital Humanities (DH) publications in mainstream open and proprietary bibliographic data sources, by further highlighting the relations among DH and other disciplines. We created a list of DH journals based on manual curation and bibliometric data. We used that list to identify DH publications in the bibliographic data sources under consideration. We used the ERIH-PLUS list of journals to identify Social Sciences and Humanities (SSH) publications. We analysed the citation links they included to understand the relationship between DH publications and SSH and non-SSH fields. Crossref emerges as the database containing the highest number of DH publications. Citations from and to DH publications show strong connections between DH and research in Computer Science, Linguistics, Psychology, and Pedagogical & Educational Research. Computer Science is responsible for a large part of incoming and outgoing citations to and from DH research, which suggests a reciprocal interest between the two disciplines. This is the first bibliometric study of DH research involving several bibliographic data sources, including open and proprietary databases. The list of DH journals we created might be only partially representative of broader DH research. In addition, some DH publications could have been cut off from the study since we did not consider books and other publications published in proceedings of DH conferences and workshops. Finally, we used a specific time coverage (2000–2018) that could have prevented the inclusion of additional DH publications. [ABSTRACT FROM AUTHOR]

Overlapping structures in XML are not symptoms of a misunderstanding of the intrinsic characteristics of a text document nor evidence of extreme scholarly requirements far beyond those needed by the most common XML-based applications. On the contrary, overlaps have started to appear in a large number of incredibly popular applications hidden under the guise of syntactical tricks to the basic hierarchy of the XML data format. Unfortunately, syntactical tricks have the drawback that the affected structures require complicated workarounds to support even the simplest query or usage. In this article, we present Extremely Annotational Resource Description Framework (RDF) Markup (EARMARK), an approach to overlapping markup that simplifies and streamlines the management of multiple hierarchies on the same content, and provides an approach to sophisticated queries and usages over such structures without the need of ad-hoc applications, simply by using Semantic Web tools and languages. We compare how relevant tasks (e.g., the identification of the contribution of an author in a word processor document) are of some substantial complexity when using the original data format and become more or less trivial when using EARMARK. We finally evaluate positively the memory and disk requirements of EARMARK documents in comparison to Open Office and Microsoft Word XML-based formats. [ABSTRACT FROM AUTHOR]

The planetary success of Wikipedia has opened the road to using wikis as shared resources for communities to collect and organize facts, concepts, and structures that constitute both the shared knowledge of the community and, more often than not, the very reason for the community to exist. The ease of creating, editing, and debating one's own and each other's contributions to the wiki knowledge-based are key aspects of the success and livelihood of the community itself. The need for semantic wiki data cannot be separated from the need of friendly authoring environments for those data. This paper introduces a framework that allows users to easily create semantic wiki content by exploiting ontology-driven forms and templates. The system, called OWiki, is an instantiation of a more general model, named GAFFE, that exploits ontologies to generate metadata editors. Both GAFFE and OWiki are presented in this paper, with particular attention to the way they exploit ontologies to model the community shared knowledge, the interfaces used to create that knowledge, and the way it evolves. [ABSTRACT FROM AUTHOR]