This topic is about creating templates for nanopublications for Human Genetics research. We are developing guidelines for Nanopublication that encompass RDF guidelines for how to model and format nanopublications, and how to store and query nanopublication spaces. The guidelines however, are highly technical and a current bottleneck is tooling for creating nanopublications by geneticists without deep knowledge of RDF and semantic web technologies in general. In this project, you will be working with, and adapting, existing tools that may be used for creating nanopublications, in particular these tools allow the creation of a template for a particular data type to be transformed into nanopublication format, such as gentopype-phenotype associations, pathway data, Post translational modicfications and other genetic associations. The tools are Righfield that is based on MS Excel, and OntoMaton, a tool based on Google spreadsheets. These tools accept terms in the cells and map them automaitcally to the correct URL to be used in the RDF schema, and the addition of provenance information (study, authors, time dat stamps, conditional info etc.) can be treated in the same way. Upon ‘save’ the tool will generate correctly formatted, computer readable nanopublication graphs automatically.

Genomics Nanopublication template

The starting point for genomics nanopublication template is previous work on modelling nanopublications for genomics data, in particular nanopublications of the Fantom 5 transcriptional start site data from RIKEN and epigenetic markers developed by Eleni Mina in our laboratory. It is also anticipated that students can bring ‘challenges’ from other genetics and other -omics fields, as we wish to develop templates for as many different data types in biology as possible. We also define an application for these nanopublications. Once we have them, what queries or analyses could we perform across these nanopublications to help with forming new biological hypotheses?
Reviewed and approved templates will be actually placed on the www.nanopub.org website to assist reaearchers in testing the ‘nanopublicability’ of their data sets.

Learning goals: Nanopublication, Semantic Web modelling, knowledge discovery / data integration.