Novel Perspectives for the Management of Multilingual and Multialphabetic Heritages through Automatic Knowledge Extraction: The DigitalMaktaba Approach.

The linguistic and social impact of multiculturalism can no longer be neglected in any sector, creating the urgent need of creating systems and procedures for managing and sharing cultural heritages in both supranational and multi-literate contexts. In order to achieve this goal, text sensing appears to be one of the most crucial research areas. The long-term objective of the project, born from interdisciplinary collaboration between computer scientists, historians, librarians, engineers and linguists, is to establish procedures for the creation, management and cataloguing of archival heritage in non-Latin alphabets.

The Italian National Registry for FSHD: an enhanced data integration and an analytics framework towards Smart Health Care and Precision Medicine for a rare disease.

Background: The Italian Clinical network for FSHD (ICNF) has established the Italian National Registry for FSHD (INRF), collecting data from patients affected by Facioscapulohumeral dystrophy (FSHD) and their relatives. The INRF has gathered data from molecular analysis, clinical evaluation, anamnestic information, and family history from more than 3500 participants.

Methods: A data management framework, called Mediator Environment for Multiple Information Sources (MOMIS) FSHD Web Platform, has been developed to provide charts, maps and search tools customized for specific needs.

A genotypic and phenotypic information source for marker-assisted selection of cereals: the CEREALAB database.

The CEREALAB database aims to store genotypic and phenotypic data obtained by the CEREALAB project and to integrate them with already existing data sources in order to create a tool for plant breeders and geneticists. The database can help them in unravelling the genetics of economically important phenotypic traits; in identifying and choosing molecular markers associated to key traits; and in choosing the desired parentals for breeding programs. The database is divided into three sub-schemas corresponding to the species of interest: wheat, barley and rice; each sub-schema is then divided into two sub-ontologies, regarding genotypic and phenotypic data, respectively.