The integration and reuse of digital research products can be only ensured through the adoption of machine-actionable (meta)data standards enriched with semantic artefacts. This study compiles 540 semantic artefacts in environmental sciences to: i. examine their coverage in scientific domains and topics; ii. assess key aspects of their FAIRness; and iii. evaluate management and governance concerns. The analyses showed that the majority of semantic artefacts concern the terrestrial biosphere domain, and that a small portion of the total failed to meet the FAIR principles. For example, 5.5% of semantic artefacts were not available in semantic catalogues, 8% were not built with standard model languages and formats, 24.6% were published without usage licences and 22.4% without version information or with divergent versions across catalogues in which they were available. This investigation discusses common semantic practices, outlines existing gaps and suggests potential solutions to address semantic interoperability challenges in some of the resources originally designed to guarantee it.

The study of hypogean fauna is critical for preserving subterranean biodiversity and ecosystem functions despite climate change. However, underground habitats, often hosting unique and endemic species, present significant challenges for traditional biodiversity assessments owing to their inaccessibility and the specialised nature of their inhabitants, resulting in a paucity of academic studies. Furthermore, even when these studies exist, data are often held in personal notes and databases that are not interoperable according to current standards, making them less usable for research purposes. Reawakening this dormant data, standardising, and sharing it according to modern criteria offers enormous opportunities to expand existing knowledge and provide support for future studies. In the Apulian region of Southern Italy, a biodiversity hotspot for subterranean life, the paucity of recent systematic surveys and reliance on expert knowledge poses both opportunities and challenges for ecological research. By integrating data from various sources, this study provides an overview of the subterranean faunal assemblages documented in this region. Overall, the dataset is comprehensive, comprising 109 species (29 of which are considered endemic to Apulia) and 224 sites, totalling 622 presence-only records. As our records have expanded over 93 years, this dataset represents a unique resource for elucidating the characteristics of Apulian subterranean ecosystems and potentially their changes over time. Integrating observations already published in previous studies with unpublished records, this is the first complete data collection on Apulian subterranean fauna organised according to modern standards of data sharing.

Over the past decade, trait data collection and mobilisation have expanded significantly, yet much of this data remains only partially compliant with FAIR principles. A major challenge lies in the inconsistent use of standards for harmonising heterogeneous trait data, along with the diversity, redundancy, and poor alignment of semantic artefacts developed to address this challenge. This study presents an approach to enhance the interoperability of the Trait Thesauri developed within the LifeWatch Italy research infrastructure for annotating and standardising trait data and metadata of aquatic organisms. This approach combines manual and automated alignment techniques, tested within the 2023 Ontology Alignment Evaluation Initiative. Domain experts manually aligned the Phytoplankton, Zooplankton, Macroalgae, Macrozoobenthos, and Fish trait thesauri, while five matching tools, LogMap, LogMapKG, LogMapLt, Matcha, and OLaLa, were tested for automated mappings. Both approaches revealed significant overlap among thesauri: Manual mapping identified 160 cross-thesauri correspondences and served as a benchmark for evaluating automated matching systems. Automated tools showed variable performance, with OLaLa achieving the best automated alignment results, with an F-measure of 0.93. Challenges in alignment included varying linguistic expressions and differing levels of concept specificity. The results highlight the importance of combining automation with expert validation to ensure mapping quality and allowed the development of a unified Trait Thesaurus, which integrates approximately 500 harmonised concepts, reducing redundancy and enhancing FAIR compliance in ecological and trait-based research.

Species distribution data are essential for understanding biodiversity patterns, supporting conservation planning and assessing the impacts of environmental change. Amphipods represent one of the most abundant and diverse groups of marine macroinvertebrates, encompassing over 10,900 species worldwide and exhibiting a wide range of trophic and ecological roles. Owing to their sensitivity to environmental changes, amphipods are widely used as bioindicators and are of considerable interest in both basic and applied research. However, incomplete or outdated information on species distributions has often led to misidentifications and inconsistencies in literature, highlighting the need for updated and reliable checklists. This study presents an inventory of unpublished records comprising more than 300 species collected from the Italian maritime zones of the Adriatic, Tyrrhenian and Ionian areas. The Tyrrhenian Sea exhibited the highest taxonomic richness, whereas the Adriatic Sea accounted for the greatest number of records, likely reflecting differences in sampling effort. Eleven non-indigenous species (NIS), representing 3.6% of the total, were recorded, primarily in ports, lagoons and aquaculture facilities, while 6.6% of the species were classified as cryptogenic or of uncertain origin. Sandy and mixed substrates supported the highest species richness, consistent with their greater sampling effort. Overall, this study provides an updated overview of amphipod biodiversity and distribution in Italian seas and underscores the need for systematic and continuous monitoring. According to the FAIR (Findable, Accessible, Interoperable, Reusable) principles, the dataset was published on the GBIF (Global Biodiversity Information Facility) platform.