A brief overview is presented of the main findings related to the role of Industry 4.0 (in terms of smart computing and sensing technologies) for the Precision Grazing, as strictly connected to the principles of both Precision Agriculture and Precision Livestock Farming.

The present work describes the analysis conducted on the diagnoses made during the general physical examinations in the decade 2010–2020, starting from the DB of the EMR previously implemented in the University Veterinary Teaching Hospital at Federico II University of Naples. A decision tree algorithm was implemented to work out a predictive model for an effective recognition of neoplastic diseases and zoonoses for cats and dogs from Campania Region. The results achievable by data mining techniques for what concerns computer aided disease diagnosis and exploration of risk factors and their relations to diseases, show the increasing importance of Veterinary Informatics within the wider field of Biomedical and Health Informatics, and in particular its capacity to point out the existing connections between humans, animals, and surrounding environment, according to the One (Digital) Health perspective specifics.

During the practice of a public administration or a company, a large volume of documents are typically produced. The recent dematerialization efforts have been pushing the way for a digital form of these documents, so as to make their management more efficient and cost-saving. But, traditional document management systems entail many non-value adding activities, such as printing, transport and archiving these documents, making the retrieval of information extremely cumbersome, especially by users without a computer science degree. The research community is putting a lot of attention to realize effective and easy-to-use search capabilities over these large number of digital/digitalized documents. This paper investigates such a problem within the context of a document management system for past civil engineering projects, and proposes an applied solution to offer advanced document retrieval capabilities without demanding a strong background in computer science by presenting a proof-of.concept implemented within the context of the PROBIM project.