Semantic Representation of Biomedical Data

Description.

How we can identify and represent knowledge? How we can semantify biomedical data in a way that they are meaningful and interoperable for machines and different sources? What is the relation between semantics/ontologies and biomedical data? How can I use or create an ontology (ontology engineering)? How I can share or link semantic data in the research community? These are some of the questions that need addressing when dealing with semantics in biomedical data and sources. We aim to resolve these issues in both theoretical and practical level, as well as to identify the necessary protocols and technologies towards the semantification and integration of data. Moreover, we will discuss:  The influence existing cases (e.g. the «Semantic Web» paradigm).  Analysis of the semantic stack protocols:  eXtensible Markup Language (XML),  Resource Description Framework and Schema (RDF/RDFS),  Ontology Languages (e.g. OWL).  Semantic data warehouses and NoSQL: Triplestores (e.g. Virtuoso, CouchDB), SPARQL.  Definition between explicit vs. inferred knowledge.  Data reuse and knowledge extension in current semantic repositories and ontologies (e.g. the Gene Ontology).  Ontology Engineering tools in Bioinformatics.

Bibliography:
Journal of Biomedical Semantics, http://www.jbiomedsem.com,BMC Bioinformatics Biomedical Ontologies,http://www.biomedcentral.com/bmcbioinformatics/series/BIOONT, The Gene OntologyConsortium, http://geneontology.org/, http://www.w3.org/wiki/Semantic_Bioinformatics, http://www.w3.org/wiki/SemanticWebTools