A collaborative methodology for developing a semantic model for interlinking Cancer Chemoprevention linked-data sources

摘要

This paper proposes a collaborative methodology for developing semantic data models. The proposed methodology for the semantic model development follows a "meet-in-the-middle" approach. On the one hand, the concepts emerged in a bottom-up fashion from analyzing the domain and interviewing the domain experts regarding their data needs. On the other hand, it followed a top-down approach whereby existing ontologies, vocabularies and data models were analyzed and inte-grated with the model. The identified elements were then fed to a multiphase abstraction exercise in order to get the concepts of the model. The derived model is also evaluated and validated by domain experts. The methodology is applied on the crea-tion of the Cancer Chemoprevention semantic model that formally defines the fundamental entities used for annotating and describing inter-connected cancer chemoprevention related data and knowledge resources on the Web. This model is meant to offer a single point of reference for biomedical researchers to search, retrieve and annotate linked cancer chemoprevention related data and web resources. The model covers four areas related to Cancer Chemoprevention: i) concepts from the litera-ture that refer to cancer chemoprevention, ii) facts and resources relevant for cancer prevention, iii) collections of experi-mental data, procedures and protocols and iv) concepts to facilitate the representation of results related to virtual screening of chemopreventive agents.