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Silvio Peroni

Publications and source records attributed to Silvio Peroni.

At least 19 recordsLinked to original sources

Towards a Definition of the Computational Architecture of Open Scholarly Infrastructures

This paper proposes a layered framework for defining the architecture of the computational unit of an Open Scholarly Infrastructure (OSI) and presents a concrete implementation possibility through the introduction of OpenCitations, an OSI dedicated to publishing citation data and bibliographic metadata. Grounded in the Principles of Open Scholarly Infrastructure (POSI), the study focuses on the technical dimensions of openness, sustainability, interoperability, and reproducibility that are required for a robust OSI. The proposed approach first identifies the core principles and technical features that a computational block in an OSI should guarantee, including separation of operational domains, orchestration, scalability, observability, automation, and workflow portability. It then maps these requirements onto a layered architectural model composed of Hardware, Virtualization, Orchestration, and Application layers, complemented by a transversal Meta layer. The OpenCitations case study shows how this framework can be instantiated in practice through an on-premises infrastructure. The case is presented with details regarding the technicalities and actual implementations of the proposed methodology. By combining a conceptual definition with a real-world implementation, this work offers both a practical reference and a methodological basis for designing the computational block of an OSI.

cs.DL

Supporting the understanding of ontologies for scientific knowledge graphs with the new version of LODE

Scientific Knowledge Graphs (SKGs) rely on increasingly complex and heterogeneous semantic models, whose reuse and interoperability require ontologies and other semantic artefacts to be understandable by both machines and humans. However, existing ontology documentation tools provide limited support for modern reuse-oriented modelling practices, where entities are distributed across imported modules and enriched through cross-module annotations. This paper presents the new version of LODE, a re-engineered and extensible framework for generating human-readable documentation of semantic artefacts. LODE preserves the established single-page, W3C Recommendation-style documentation paradigm of its legacy predecessor, and introduces a modular architecture that separates artefact interpretation (Reader), internal representation (Model), and rendering (Viewer). Served as a web service, LODE supports the documentation of OWL ontologies and enables additional documentation features (e.g., entity stand-alone documentation, RDF entity provenance, Markdown rendering). We demonstrate the applicability of LODE through the documentation of the Scientific Knowledge Graph Interoperability Framework ontology (SKG-O), showing how it improves the accessibility and reuse of modular scientific knowledge graph models.

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Ask the Curator: Demonstrating Expert-Driven RDF Data Curation with HERITRACE

HERITRACE is an open-source Web application for curating RDF data held in triplestores, with provenance and change tracking recorded in RDF as well. It is agnostic to the data model: a technician configures it for a collection by writing SHACL shapes and YAML display rules, after which domain experts edit the data through generated forms, and every change becomes a provenance snapshot that can be inspected and restored. This paper traces the path from configuration to curation on a documented case of bibliographic ambiguity: two unrelated articles that PubMed records under the same DOI. We show how a technician prepares a small OpenCitations Meta subset for curation and how a curator acts on duplicate suggestions to merge two articles, inadvertently confirms a further merge despite conflicting metadata, reverts the mistake through the Time Machine, and corrects the DOI after verification against Crossref.

cs.DL

Enhancing RAMOSE, a framework for implementing REST APIs and semantic-actionable outputs over data sources

Scholarly infrastructures increasingly expose their data through REST APIs that follow shared specifications, such as the Scientific Knowledge Graph - Interoperability Framework (SKG-IF), which defines a common data model, exchange format, and REST API for research information. Implementing such specifications over existing data sources, however, requires a development effort that many open infrastructures cannot afford. RAMOSE, the RESTful API Manager Over SPARQL Endpoints, is an open-source Python framework that reduces this effort by turning a declarative configuration file into a documented REST API over RDF triplestores. This article presents its second major version, which extends the tool with nine new requirements. The new features include query orchestration across multiple SPARQL endpoints and non-RDF sources, with joins across their results; pluggable output formats and request parameters; pagination and caching; OpenAPI export; and write operations, with authentication both of API consumers and towards protected endpoints. A built-in module packages the format and filters that SKG-IF prescribes, letting a provider expose a compliant endpoint only through configuration. A functional comparison with nine similar tools, grounded in reproducible tests, shows that only RAMOSE joins RDF and non-RDF results on arbitrary keys within one API operation. RAMOSE serves the OpenCitations REST APIs, which peaked at almost 38 million monthly requests between May 2025 and May 2026, and has been adopted by the GRAPHIA project to onboard data sources into its SKG-IF-based federation.

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HERITRACE: a domain-agnostic framework for SHACL-driven RDF curation with provenance and change tracking

HERITRACE is an open-source web application that enables users without Semantic Web expertise to curate RDF data through form-based interfaces with automatic provenance documentation and change tracking in RDF. It uses SHACL for data model definition and form generation, connects to existing SPARQL-accessible stores without data migration, and records every modification as a provenance snapshot that can be browsed and restored. HERITRACE is domain-agnostic and its configuration is layered: a minimal deployment only connects to a SPARQL store, while SHACL shapes and YAML display rules refine the data model and presentation, and IRIs are minted automatically by default or through a Python class for institution-specific schemes. This paper describes the software architecture and provides the first empirical evaluation. HERITRACE is deployed in production for the ParaText project, where classical philologists curate bibliographic data about ancient Greek exegetical traditions, and is planned as the editing interface for OpenCitations and as the curation layer for the Social Sciences and Humanities Citation Index within the GRAPHIA Horizon Europe project. Since it operates on any SPARQL-accessible store without data migration, its adoption potential extends to any domain maintaining RDF data. HERITRACE is publicly available on GitHub under the ISC license, archived on Zenodo and Software Heritage Archive, and documented for deployment with a pre-built Docker image.

cs.DL

Are Digital Humanities really committed to open? An exploratory study on the availability of methodological workflows and open peer review practices

Open Science has become a central framework for promoting transparency, accessibility, and inclusiveness in scholarly research. While the Digital Humanities (DH) community has long embraced openness in terms of research outputs, less attention seems to have been paid to the openness of the methodological and evaluative processes underlying knowledge production. This paper presents an exploratory study that investigates the current state of openness in DH research practices, focusing specifically on research data management documentation and peer review processes. In particular, this study addresses two research questions: (1) to what extent DH publications that describe data explicitly reference external documentation detailing data creation and management processes; and (2) how widely open peer review practices are adopted across DH conferences and journals. The results revealed a limited adoption of open methodological practices. Only a small fraction of the analysed articles provided explicit, reusable documentation of data creation workflows, and no references to data management plans or formal research data management documentation were found. An even more critical picture emerges from the analysis of peer review practices: the vast majority of DH venues continue to rely on traditional single- or double-blind review models, with open peer review adopted in only a few isolated cases.

cs.DL

Assessing and Comparing the Coverage of Italian Publications in OpenCitations: a Study within Six Italian Universities

Recent initiatives advocating responsible, transparent research assessment have intensified the call to use open research information rather than proprietary databases. This study evaluates the coverage and citation representation of publications recorded in the Current Research Information Systems (CRIS), all instances of the IRIS software platform, of six Italian universities within OpenCitations, a community-owned open infrastructure. Using persistent identifiers (DOIs, PMIDs, and ISBNs) specified in the IRIS installations involved, we matched the publications recorded in OpenCitations Meta and extracted the related citation links from the OpenCitations Index. Results show that OpenCitations covers, on average, over 40% of IRIS publications, which is quantitatively comparable to those reported by Scopus and Web of Science in another study. However, gaps persist, particularly for publication types prevalent in the Social Sciences and Humanities, such as monographs and critical editions. Overall, the findings demonstrate the growing maturity of OpenCitations and, more broadly, of Open Science infrastructures as viable alternatives as sources of research information, while highlighting areas where further metadata enrichment and interoperability efforts are needed.

cs.DL

A pipeline for matching bibliographic references with incomplete metadata: experiments with Crossref and OpenCitations

While Crossref makes available more than 1.8 billion bibliographic references from publications for which it provides a DOI, more than 698 million of these references do not specify a DOI, making the creation of a formal citation link from the citing entity and the cited entity problematic. In this article, we propose an analysis of Crossref bibliographic references to show how we can use the unstructured text defining such references and the available (and partial) metadata specified in them to (a) map them to existing entities included in OpenCitations Meta and, then, (b) to enable the potential inclusion of additional and valid citations link among these entities. We have defined a precise methodology to address the analysis and run it against a manually defined Gold Standard and a subset of Crossref. While the heuristic-based tool developed has demonstrated strong matching precision and effective metadata integration, its recall limitations highlight the necessity of further enhancements to address metadata inconsistencies and leverage additional sources of citation data.

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HERITRACE in action: the ParaText project as a case study for semantic data management in Classical Philology

HERITRACE is a semantic data editor designed for cultural heritage institutions, addressing the gap between complex Semantic Web technologies and domain expert needs. ParaText Bibliographical Database, a specialized bibliographical database for ancient Greek exegesis, demonstrates HERITRACE's capabilities in Classical Philology. This paper examines how HERITRACE enables non-technical scholars to manage complex semantic data through SHACL-based form generation and validation, while ensuring comprehensive provenance tracking and change management via an OpenCitations Data Model adaptation.

cs.DL

CHAD-KG: A Knowledge Graph for Representing Cultural Heritage Objects and Digitisation Paradata

This paper presents CHAD-KG, a knowledge graph designed to describe bibliographic metadata and digitisation paradata of cultural heritage objects in exhibitions, museums, and collections. It also documents the related data model and materialisation engine. Originally based on two tabular datasets, the data was converted into RDF according to CHAD-AP, an OWL application profile built on standards like CIDOC-CRM, LRMoo, CRMdig, and Getty AAT. A reproducible pipeline, developed with a Morph-KGC extension, was used to generate the graph. CHAD-KG now serves as the main metadata source for the Digital Twin of the temporary exhibition titled \emph{The Other Renaissance - Ulisse Aldrovandi and The Wonders Of The World}, and other collections related to the digitisation work under development in a nationwide funded project, i.e. Project CHANGES (https://fondazionechanges.org). To ensure accessibility and reuse, it offers a SPARQL endpoint, a user interface, open documentation, and is published on Zenodo under a CC0 license. The project improves the semantic interoperability of cultural heritage data, with future work aiming to extend the data model and materialisation pipeline to better capture the complexities of acquisition and digitisation, further enrich the dataset and broaden its relevance to similar initiatives.

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Validating and monitoring bibliographic and citation data in OpenCitations collections

Purpose. The increasing emphasis on data quantity in research infrastructures has highlighted the need for equally robust mechanisms ensuring data quality, particularly in bibliographic and citation datasets. This paper addresses the challenge of maintaining high-quality open research information within OpenCitations, a community-guided Open Science Infrastructure, by introducing tools for validating and monitoring bibliographic metadata and citation data. Methods. We developed a custom validation tool tailored to the OpenCitations Data Model (OCDM), designed to detect and explain ingestion errors from heterogeneous sources, whether due to upstream data inconsistencies or internal software bugs. Additionally, a quality monitoring tool was created to track known data issues post-publication. These tools were applied in two scenarios: (1) validating metadata and citations from Matilda, a potential future source, and (2) monitoring data quality in the existing OpenCitations Meta dataset. Results. The validation tool successfully identified a variety of structural and semantic issues in the Matilda dataset, demonstrating its precision. The monitoring tool enabled the detection of recurring problems in the OpenCitations Meta collection, as well as their quantification. Together, these tools proved effective in enhancing the reliability of OpenCitations' published data. Conclusion. The presented validation and monitoring tools represent a step toward ensuring high-quality bibliographic data in open research infrastructures, though they are limited to the data model adopted by OpenCitations. Future developments are aimed at expanding to additional data sources, with particular regard to crowdsourced data.

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HERITRACE: A User-Friendly Semantic Data Editor with Change Tracking and Provenance Management for Cultural Heritage Institutions

HERITRACE is a data editor designed for galleries, libraries, archives and museums, aimed at simplifying data curation while enabling non-technical domain experts to manage data intuitively without losing its semantic integrity. While the semantic nature of RDF can pose a barrier to data curation due to its complexity, HERITRACE conceals this intricacy while preserving the advantages of semantic representation. The system natively supports provenance management and change tracking, ensuring transparency and accountability throughout the curation process. Although HERITRACE functions effectively out of the box, it offers a straightforward customization interface for technical staff, enabling adaptation to the specific data model required by a given collection. Current applications include the ParaText project, and its adoption is already planned for OpenCitations. Future developments will focus on integrating the RDF Mapping Language (RML) to enhance compatibility with non-RDF data formats, further expanding its applicability in digital heritage management.

cs.DL

Analysing the coverage of the University of Bologna's bibliographic and citation metadata in OpenCitations collections

This study focuses on analysing the coverage of publications' metadata available in the Current Research Information System (CRIS) infrastructure of the University of Bologna (UNIBO), implemented by the IRIS platform, within an authoritative source of open research information, i.e. OpenCitations. The analysis considers data regarding the publication entities alongside the citation links. We precisely quantify the proportion of UNIBO IRIS publications included in OpenCitations, examine their types, and evaluate the number of citations in OpenCitations that involve IRIS publications. Our methodology filters and transforms data dumps of IRIS and OpenCitations, creating novel datasets used for the analysis. Our findings reveal that only 36% of IRIS is covered in OpenCitations, with journal articles exhibiting the highest coverage. We identified 5,129,406 citation links pointing to UNIBO IRIS publications. From a purely quantitative perspective, comparing our results with broader proprietary services like Scopus and Web of Science reveals a comparable quantitative coverage in the number of IRIS bibliographic resources included in all the systems analysed (OpenCitations, Scopus and Web of Science) as well as in the number of citations received by them.

cs.DL

Recent Developments in Deep Learning-based Author Name Disambiguation

Author Name Disambiguation (AND) is a critical task for digital libraries aiming to link existing authors with their respective publications. Due to the lack of persistent identifiers used by researchers and the presence of intrinsic linguistic challenges, such as homonymy, the development of Deep Learning algorithms to address this issue has become widespread. Many AND deep learning methods have been developed, and surveys exist comparing the approaches in terms of techniques, complexity, performance. However, none explicitly addresses AND methods in the context of deep learning in the latest years (i.e. timeframe 2016-2024). In this paper, we provide a systematic review of state-of-the-art AND techniques based on deep learning, highlighting recent improvements, challenges, and open issues in the field. We find that DL methods have significantly impacted AND by enabling the integration of structured and unstructured data, and hybrid approaches effectively balance supervised and unsupervised learning.

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Leveraging virtual technologies to enhance museums and art collections: insights from project CHANGES

We investigated the use of virtual technologies to digitise and enhance cultural heritage (CH), aligning with Open Science and FAIR principles. Through case studies in museums, we developed reproducible workflows, 3D models, and tools fostering accessibility, inclusivity, and sustainability of CH. Applications include interdisciplinary research, educational innovation, and CH preservation.

cs.GR

The OpenCitations Index

This article presents the OpenCitations Index, a collection of open citation data maintained by OpenCitations, an independent, not-for-profit infrastructure organisation for open scholarship dedicated to publishing open bibliographic and citation data using Semantic Web and Linked Open Data technologies. The collection involves citation data harvested from multiple sources. To address the possibility of different sources providing citation data for bibliographic entities represented with different identifiers, therefore potentially representing same citation, a deduplication mechanism has been implemented. This ensures that citations integrated into OpenCitations Index are accurately identified uniquely, even when different identifiers are used. This mechanism follows a specific workflow, which encompasses a preprocessing of the original source data, a management of the provided bibliographic metadata, and the generation of new citation data to be integrated into the OpenCitations Index. The process relies on another data collection: OpenCitations Meta, and on the use of a new globally persistent identifier, namely OMID (OpenCitations Meta Identifier). As of July 2024, OpenCitations Index stores over 2 billion unique citation links, harvest from Crossref, the National Institute of Heath Open Citation Collection (NIH-OCC), DataCite, OpenAIRE, and the Japan Link Center (JaLC). OpenCitations Index can be systematically accessed and queried through several services, including SPARQL endpoint, REST APIs, and web interfaces. Additionally, dataset dumps are available for free download and reuse (under CC0 waiver) in various formats (CSV, N-Triples, and Scholix), including provenance and change tracking information.

cs.DL

CiteFusion: An Ensemble Framework for Citation Intent Classification Harnessing Dual-Model Binary Couples and SHAP Analyses

Understanding the motivations underlying scholarly citations is essential to evaluate research impact and promote transparent scholarly communication. This study introduces CiteFusion, an ensemble framework designed to address the multi-class Citation Intent Classification task on two benchmark datasets: SciCite and ACL-ARC. The framework employs a one-vs-all decomposition of the multi-class task into class-specific binary subtasks, leveraging complementary pairs of SciBERT and XLNet models, independently tuned, for each citation intent. The outputs of these base models are aggregated through a feedforward neural network meta-classifier to reconstruct the original classification task. To enhance interpretability, SHAP (SHapley Additive exPlanations) is employed to analyze token-level contributions, and interactions among base models, providing transparency into the classification dynamics of CiteFusion, and insights about the kind of misclassifications of the ensemble. In addition, this work investigates the semantic role of structural context by incorporating section titles, as framing devices, into input sentences, assessing their positive impact on classification accuracy. CiteFusion ultimately demonstrates robust performance in imbalanced and data-scarce scenarios: experimental results show that CiteFusion achieves state-of-the-art performance, with Macro-F1 scores of 89.60% on SciCite, and 76.24% on ACL-ARC. Furthermore, to ensure interoperability and reusability, citation intents from both datasets schemas are mapped to Citation Typing Ontology (CiTO) object properties, highlighting some overlaps. Finally, we describe and release a web-based application that classifies citation intents leveraging the CiteFusion models developed on SciCite.

cs.CL

A Proposal for a FAIR Management of 3D Data in Cultural Heritage: The Aldrovandi Digital Twin Case

In this article we analyse 3D models of cultural heritage with the aim of answering three main questions: what processes can be put in place to create a FAIR-by-design digital twin of a temporary exhibition? What are the main challenges in applying FAIR principles to 3D data in cultural heritage studies and how are they different from other types of data (e.g. images) from a data management perspective? We begin with a comprehensive literature review touching on: FAIR principles applied to cultural heritage data; representation models; both Object Provenance Information (OPI) and Metadata Record Provenance Information (MRPI), respectively meant as, on the one hand, the detailed history and origin of an object, and - on the other hand - the detailed history and origin of the metadata itself, which describes the primary object (whether physical or digital); 3D models as cultural heritage research data and their creation, selection, publication, archival and preservation. We then describe the process of creating the Aldrovandi Digital Twin, by collecting, storing and modelling data about cultural heritage objects and processes. We detail the many steps from the acquisition of the Digital Cultural Heritage Objects (DCHO), through to the upload of the optimised DCHO onto a web-based framework (ATON), with a focus on open technologies and standards for interoperability and preservation. Using the FAIR Principles for Heritage Library, Archive and Museum Collections [1] as a framework, we look in detail at how the Digital Twin implements FAIR principles at the object and metadata level. We then describe the main challenges we encountered and we summarise what seem to be the peculiarities of 3D cultural heritage data and the possible directions for further research in this field.

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