OpenCitations Meta is a new database for open bibliographic metadata of scholarly publications involved in the citations indexed by the OpenCitations infrastructure, adhering to Open Science principles and published under a CC0 license to promote maximum reuse. It presently incorporates bibliographic metadata for publications recorded in Crossref, DataCite, and PubMed, making it the largest bibliographic metadata source using Semantic Web technologies. It assigns new globally persistent identifiers (PIDs), known as OpenCitations Meta Identifiers (OMIDs) to all bibliographic resources, enabling it both to disambiguate publications described using different external PIDS (e.g., a DOI in Crossref and a PMID in PubMed) and to handle citations involving publications lacking external PIDs. By hosting bibliographic metadata internally, OpenCitations Meta eliminates its former reliance on API calls to external resources and thus enhances performance in response to user queries. Its automated data curation, following the OpenCitations Data Model, includes deduplication, error correction, metadata enrichment, and full provenance tracking, ensuring transparency and traceability of data and bolstering confidence in data integrity, a feature unparalleled in other bibliographic databases. Its commitment to Semantic Web standards ensures superior interoperability compared to other machine-readable formats, with availability via a SPARQL endpoint, REST APIs, and data dumps.

In this article, we show and discuss the results of a quantitative and qualitative analysis of open citations of retracted publications in the humanities domain. Our study was conducted by selecting retracted papers in the humanities domain and marking their main characteristics (e.g., retraction reason). Then, we gathered the citing entities and annotated their basic metadata (e.g., title, venue, subject) and the characteristics of their in-text citations (e.g., intent, sentiment). Using these data, we performed a quantitative and qualitative study of retractions in the humanities, presenting descriptive statistics and a topic modeling analysis of the citing entities’ abstracts and the in-text citation contexts. As part of our main findings, we noticed that there was no drop in the overall number of citations after the year of retraction, with few entities that have either mentioned the retraction or expressed a negative sentiment toward the cited publication. In addition, on several occasions, we noticed a higher concern/awareness by citing entities belonging to the health sciences domain about citing a retracted publication, compared with the humanities and social science domains. Philosophy, arts, and history are the humanities areas that showed higher concern toward the retraction.

The importance of open bibliographic repositories is widely accepted by the scientific community. For evaluation processes, however, there is still some skepticism: Even if large repositories of open access articles and free publication indexes exist and are continuously growing, assessment procedures still rely on proprietary databases, mainly due to the richness of the data available in these proprietary databases and the services provided by the companies they are offered by. This paper investigates the status of open bibliographic data of three of the most used open resources, namely Microsoft Academic Graph, Crossref, and OpenAIRE, evaluating their potentialities as substitutes of proprietary databases for academic evaluation processes. We focused on the Italian National Scientific Qualification (NSQ), the Italian process for university professor qualification, which uses data from commercial indexes, and investigated similarities and differences between research areas, disciplines, and application roles. The main conclusion is that open data sets are ready to be used for some disciplines, among them mathematics, natural sciences, economics, and statistics, even if there is still room for improvement; but there is still a large gap to fill in others—such as history, philosophy, pedagogy, and psychology—and greater effort is required from researchers and institutions.

OpenCitations is an infrastructure organization for open scholarship dedicated to the publication of open citation data as Linked Open Data using Semantic Web technologies, thereby providing a disruptive alternative to traditional proprietary citation indexes. Open citation data are valuable for bibliometric analysis, increasing the reproducibility of large-scale analyses by enabling publication of the source data. Following brief introductions to the development and benefits of open scholarship and to Semantic Web technologies, this paper describes OpenCitations and its data sets, tools, services, and activities. These include the OpenCitations Data Model; the SPAR (Semantic Publishing and Referencing) Ontologies; OpenCitations’ open software of generic applicability for searching, browsing, and providing REST APIs over resource description framework (RDF) triplestores; Open Citation Identifiers (OCIs) and the OpenCitations OCI Resolution Service; the OpenCitations Corpus (OCC), a database of open downloadable bibliographic and citation data made available in RDF under a Creative Commons public domain dedication; and the OpenCitations Indexes of open citation data, of which the first and largest is COCI, the OpenCitations Index of Crossref Open DOI-to-DOI Citations, which currently contains over 624 million bibliographic citations and is receiving considerable usage by the scholarly community.