Intuitive and machine-understandable organization of the bioinformatics domain and related resources with Resourceomes

Bioinformatics has grown tremendously and the full set of bioinformatics resources (e.g. databases, programs, articles) has reached an “ome” status. Consequently, it has also greatly increased the difficulty for the scientists in finding the proper resources and maintaining an updated, organic and comprehensive overview of the whole domain. Approaching an unknown research area, for scientists coming from other disciplines, is frightening. Moreover, a common classification schema for resources is missing and life sciences themselves lack a taxonomic organization of their knowledge domains. To help individual scientists, research groups and communities to intuitively organize the perceived knowledge and resources belonging to a domain, we propose to organize scientific domains and resources metadata into Resourceomes. In such frameworks, resources, classified according to a resource ontology, are thus linked in a machine-understandable way to the concepts of the domain they refer to. Navigation and reasoning over the semantic networks connecting resources and concepts of the domain is then permitted, being the latter also formalized into a domain ontology. We present the prototype of a web accessible semantic browser for Resourceomes. An example, showing how main areas of bioinformatics could be hierarchically arranged in an intuitive visual representation with the related resources, is provided. In our vision, Resourceomes should facilitate the life of scientists, significantly reducing the time lost in Internet searches for bioinformatics resources of every kind.