Abstract"Enhanced publications" are commonly intended as digital publications that consist of a mandatory narrative part (the description of the research conducted) plus related "parts", such as datasets, other publications, images, tables, workflows, devices. The state-of-the-art on information systems for enhanced publica tions has today reached the point where some kind of common understanding is required, in order to provide the methodology and language for scientists to com pare, analyse, or simply discuss the multitude of solutions in the field. In this paper, we thoroughly examined the literature with a two-fold aim: firstly, introducing the terminology required to describe and compare structural and semantic features of existing enhanced publication data models; secondly, proposing a classification of enhanced publication information systems based on their main functional goals.

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Since 2012, the "Open Researcher and Contributor ID" organisation (ORCID) has been successfully running a worldwide registry, with the aim of "providing a unique, persistent identifier for individuals to use as they engage in research, scholarship, and innovation activities". Any service in the scholarly communication ecosystem (e.g., publishers, repositories, CRIS systems, etc.) can contribute to a non-ambiguous scholarly record by including, during metadata deposition, referrals to iDs in the ORCID registry.2 Baglioni et al.

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Today, several online services offer functionalities to access information from big scholarly communication graphs, which interlink entities such as publications, authors, datasets, organizations, etc. Such graphs are often populated over time as aggregations of multiple sources and therefore suffer from entity duplication problems. Although deduplication of graphs is a known and actual problem, solutions tend to be dedicated and address a few of the underlying challenges. In this paper, we propose the GDup system, an integrated, scalable, generalpurpose system for entity deduplication over big information graphs. GDup supports practitioners with the functionalities needed to realize a fully-fledged entity deduplication workflow over a generic input graph, inclusive of Ground Truth support, end-user feedback, and strategies for identifying and merging duplicates to obtain an output disambiguated graph. GDup is today one of the core components of the OpenAIRE infrastructure production system, monitoring Open Science trends on behalf of the European Commission.