# Can Semantics Uncover Hidden Relations between Neurodegenerative Diseases and Artistic Behaviors?
## 4 State-of-the-Art
### Ontologies Related to NDs
The authors found that some of the ontologies had high reusability, class hierarchy, and metadata, whereas others were lacking in these areas. Additionally, some of the ontologies focused on term standardization, whereas others were part of an expert system. [PERSON] et al. [77] presented the NeuroLOG ref middleware data management layer in their paper, which provides a platform for sharing heterogeneous neuroimaging data using a federated approach. The data management system captures the semantics of shared information through a multi-layer application ontology and a federated schema, which aligns the heterogeneous database schemas from different legacy repositories. The NeuroLOG system ref can translate the relational data into a semantic representation and support semantic search using a semantic search engine. The authors highlight the importance of the distributed approach for neuroscience data management. The NeuroLOG repository [77] integrates data from multiple federated sites and encompasses images stored as regular files as well as metadata stored in relational databases. This metadata could include information on the content of images, image acquisition conditions, subjects involved, context of image acquisitions, and scores obtained from neurological and cognitive assessments. The OntoNeuroLOG ontology, which was built as a modular multi-layer application ontology, was based on the preliminary work done in the NeuroBase project [78] and reuses the OntoNeuroBase ontology. The Biomedical Informatics Research Network (BIRN) [79; 80] program was a pioneering effort in the field of data integration, utilizing a federated method that incorporated ontology-based mediation in the realm of neuroscience research. Launched in 2001, BIRN aimed to build an infrastructure that could facilitate data exchange and computation resources, with the ultimate goal of advancing our understanding of brain anatomy and function, from the cellular level to behavior. During its first phase (2001-2008), BIRN placed significant emphasis on the creation of ontologies, which resulted in the development of the BIRNLex ontology [79; 80; 81; 82]. This resource, more of a lexicon than a full-fledged ontology, is now widely accessible through the NCBO BioPortal [71]. In parallel with the development of the ontologies, BIRN also introduced a technologically advanced architecture built around the storage resource broker (SRB), a mechanism that enables the virtualization of files in large federated systems [81]. The BIRN federated system currently comprises 11 HIDs. This PoC demonstrated by BIRN showed that ontology-based mediation could be an effective way of integrating data in the field of neuroscience and has had a lasting impact on the field. The BIRN program serves as a shining example of the power of collaboration and the potential for progress that can be achieved through collective efforts. [PERSON] et al. presented a comprehensive work in their paper [83], outlining the development of the Neurocognitive Integrated Ontology (NIO), which is available through NCBO BioPortal [71]. The NIO ontology represents a significant contribution to the field of neuroscience research by integrating the main domains of NDs, diagnostic tests, cognitive functions, and brain areas. The authors aimed to address common limitations in existing ontologies by developing an ontology that is capable of being adapted to new projects and expanding to incorporate new knowledge domains. To evaluate the stability and usefulness of the NIO ontology, the authors performed two case studies: adapting the ontology to a new project and updating the ontology using a new ontology. The inner reasoner of Protege [19] was used to assess the stability of the ontology. The results showed that the NIO ontology was successful in overcoming the difficulties of adapting and expanding existing ontologies, making it a valuable tool for researchers.